From a29ecf6eac32bb6651a3a520fb176334d4606ded Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 12:58:28 -0700 Subject: [PATCH 01/58] Add issue-351 Newton independent-seed study script --- .context/issue-351/newton_seeds.py | 291 +++++++++++++++++++++++++++++ 1 file changed, 291 insertions(+) create mode 100644 .context/issue-351/newton_seeds.py diff --git a/.context/issue-351/newton_seeds.py b/.context/issue-351/newton_seeds.py new file mode 100644 index 0000000..13831d6 --- /dev/null +++ b/.context/issue-351/newton_seeds.py @@ -0,0 +1,291 @@ +"""Newton-enabled single-model runs on the full ds002718 sub-002 recording +(issue #351 item 4a, re-running the issue #145 protocol under epic #324). + +The paper's claim: with Newton enabled (``do_newton=1``) and independent seeds, +one pamica seed of three (seed 42) put ten of seventy components in a different +basin, the other two matched the reference at ~0.99, and a matched +initialization (A = I, mu = [-1, 0, 1], sbeta = 1, rho = rho0, alpha = 1/3, +c = 0 on both sides) restored ~0.997. The issue #145 records are +``.context/issue-145/full_data_reproduction.md`` and ``same_init_result.md``; +this script repeats that protocol with the code at the epic head and the +pinned v0.3.3 native binary. + +Protocol, as in #145: + +* data: the full 70-channel x 747,750-frame recording (k ~ 153), rounded to + float32 as the #145 runs read it (``data.fdt``) and as the binary reads it; +* pamica: ``AMICATorchNG`` on CUDA float64, 2000 iterations, the #145 keyword + set (``fit_torch_full.py``: ``lrate=0.05``, ``do_newton=True``, + ``newt_start=50``, ``newt_ramp=10``, ``newtrate=1.0``, ``lratefact=0.5``, + ``rholrate=0.05``, ``rholratefact=0.5``, ``maxdecs=3``, ``block_size=512``; + everything else at the constructor default), seeds 42, 7 and 13; the early + stops are off here so both sides run the full budget, as they did in #145 + (pamica had no ``min_dll`` stop then, and every #145 fit ran 2000 iterations); +* reference: two independent fits of the native binary with the ``input.param`` + settings, ``do_newton=1``, 2000 iterations, early stops off (as the #145 + load-path run had them), here seeded (1 and 2) so the run is reproducible, + where #145 used clock-seeded runs; +* same-init: both sides from the deterministic start above, the binary through + its ``load_*`` path. + +Subcommands (each writes one ``.npz`` under ``--out-dir``):: + + python newton_seeds.py pamica --seed 42 --data DATA.npy --out-dir OUT + python newton_seeds.py pamica --fixinit --data DATA.npy --out-dir OUT + python newton_seeds.py fortran --seed 1 --threads 10 --data DATA.npy --out-dir OUT + python newton_seeds.py fortran --fixinit --threads 10 --data DATA.npy --out-dir OUT + python newton_seeds.py compare --out-dir OUT +""" + +from __future__ import annotations + +import argparse +import itertools +import json +import time +from pathlib import Path + +import numpy as np +from scipy.optimize import linear_sum_assignment + +MAX_ITER = 2000 +NMIX = 3 +PAMICA_KW = dict( + n_mix=NMIX, lrate=0.05, do_mean=True, do_sphere=True, do_approx_sphere=True, + do_newton=True, newt_start=50, newt_ramp=10, newtrate=1.0, lratefact=0.5, + rholrate=0.05, rholratefact=0.5, maxdecs=3, block_size=512, + use_min_dll=False, use_grad_norm=False, +) # fmt: skip +FORTRAN_KW = dict( + num_models=1, num_mix_comps=NMIX, max_iter=MAX_ITER, do_newton=1, + use_min_dll=0, use_grad_norm=0, block_size=512, +) # fmt: skip + + +def load_data(path: Path) -> np.ndarray: + """The recording rounded to float32 (what the binary reads), in float64.""" + return np.load(path).astype(np.float32).astype(np.float64) + + +def fixinit_state(nw: int, rho0: float = 1.5) -> dict[str, np.ndarray]: + """The deterministic start of the #145 same-init test (reference layout: + ``mu``/``sbeta``/``rho``/``alpha`` are ``(num_mix, num_comps)``).""" + return { + "A": np.eye(nw), + "mu": np.tile(np.linspace(-1.0, 1.0, NMIX)[:, None], (1, nw)), + "sbeta": np.ones((NMIX, nw)), + "rho": np.full((NMIX, nw), rho0), + "alpha": np.full((NMIX, nw), 1.0 / NMIX), + "gm": np.ones(1), + "c": np.zeros((nw, 1)), + } + + +def run_pamica( + data: np.ndarray, seed: int | None, fixinit: bool, device: str, max_iter: int +) -> dict: + import torch + + from pamica.torch_impl.core import AMICATorchNG + + nw = data.shape[0] + + class FixInitNG(AMICATorchNG): + """The #145 deterministic start in place of the drawn one.""" + + def _initialize_parameters(self): + super()._initialize_parameters() + st = fixinit_state(self.n_channels, self.rho0) + dev, dt = self.device, self.dtype + self.A = torch.from_numpy(st["A"]).to(dev, dt) # symmetric: rows == cols + self.mu = torch.from_numpy(st["mu"]).to(dev, dt) + self.beta = torch.from_numpy(st["sbeta"]).to(dev, dt) + self.rho = torch.from_numpy(st["rho"]).to(dev, dt) + self.alpha = torch.from_numpy(st["alpha"]).to(dev, dt) + self.c = torch.from_numpy(st["c"]).to(dev, dt) + self._update_unmixing_matrices() + + cls = FixInitNG if fixinit else AMICATorchNG + m = cls( + n_channels=nw, n_models=1, seed=0 if fixinit else seed, device=device, + dtype=torch.float64, **PAMICA_KW, + ) # fmt: skip + t0 = time.time() + m.fit(data, max_iter=max_iter, verbose=False) + dt = time.time() - t0 + return { + "W": np.asarray(m.get_unmixing_matrix(0)), + "S": np.asarray(m.get_sphere()), + "ll_history": np.asarray(m.ll_history), + "final_ll": float(m.final_ll_), + "stop_reason": str(m.stop_reason), + "n_newton_fallbacks": int(m.n_newton_fallbacks), + "end_newtrate": float(m.newtrate), + "seconds": dt, + } + + +def run_fortran( + data: np.ndarray, + seed: int | None, + fixinit: bool, + threads: int, + work: Path, + max_iter: int, +) -> dict: + from pamica.native import resolver + from pamica.native.engine import AMICANative + + binary = resolver.resolve("v0.3.3") + t0 = time.time() + if not fixinit: + eng = AMICANative( + binary=binary, threads=threads, max_threads=threads, timeout=6 * 3600, + seed=seed, **{**FORTRAN_KW, "max_iter": max_iter}, + ) # fmt: skip + eng.fit(data) + out = eng.output_ + assert out is not None + W = out.W[:, :, 0] + S = out.S + ll = np.asarray(out.LL) + else: + from pamica.tests.native_oracle import SeedState, run_seeded_reference + + nw, n_samples = data.shape + fdt = work / "data_f32.fdt" + if not fdt.exists(): + np.ascontiguousarray(data.T).astype(" np.ndarray: + """Hungarian-matched |corr| per component (rows of the unmixing matrices), + as in the #145 ``compare_local.py``.""" + a = Wa / (np.linalg.norm(Wa, axis=1, keepdims=True) + 1e-12) + b = Wb / (np.linalg.norm(Wb, axis=1, keepdims=True) + 1e-12) + c = np.abs(a @ b.T) + r, cc = linear_sum_assignment(1 - c) + return c[r, cc] + + +def summ(m: np.ndarray) -> dict: + return { + "mean": float(m.mean()), + "min": float(m.min()), + "n_below_0.9": int((m < 0.9).sum()), + "worst5": [round(float(x), 3) for x in np.sort(m)[:5]], + } + + +def compare(out_dir: Path) -> dict: + runs = { + p.stem: dict(np.load(p, allow_pickle=True)) + for p in sorted(out_dir.glob("*.npz")) + } + # Sphered-space unmixing rows, as #145 compared them: both sides compute + # the same symmetric ZCA sphere from the same float32-rounded data. + Wt = {k: v["W"] for k, v in runs.items()} + report: dict = { + "runs": {k: {"final_ll": float(v["final_ll"])} for k, v in runs.items()} + } + fort = sorted(k for k in Wt if k.startswith("fortran_seed")) + pam = sorted(k for k in Wt if k.startswith("pamica_seed")) + pairs = {} + for a, b in itertools.combinations(fort, 2): + pairs[f"{a} vs {b}"] = summ(matched(Wt[a], Wt[b])) + for a in pam: + for b in fort: + pairs[f"{a} vs {b}"] = summ(matched(Wt[a], Wt[b])) + for a, b in itertools.combinations(pam, 2): + pairs[f"{a} vs {b}"] = summ(matched(Wt[a], Wt[b])) + if "pamica_fixinit" in Wt and "fortran_fixinit" in Wt: + pairs["pamica_fixinit vs fortran_fixinit"] = summ( + matched(Wt["pamica_fixinit"], Wt["fortran_fixinit"]) + ) + for b in fort: + pairs[f"fortran_fixinit vs {b}"] = summ( + matched(Wt["fortran_fixinit"], Wt[b]) + ) + for a in pam: + pairs[f"pamica_fixinit vs {a}"] = summ(matched(Wt["pamica_fixinit"], Wt[a])) + report["pairs"] = pairs + for k, v in runs.items(): + extra = { + x: v[x].item() + for x in ("stop_reason", "n_newton_fallbacks", "end_newtrate", "seconds") + if x in v + } + report["runs"][k].update( + { + x: (y if not isinstance(y, bytes) else y.decode()) + for x, y in extra.items() + } + ) + return report + + +def main() -> None: + p = argparse.ArgumentParser() + p.add_argument("cmd", choices=["pamica", "fortran", "compare"]) + p.add_argument("--seed", type=int) + p.add_argument("--fixinit", action="store_true") + p.add_argument("--data", type=Path) + p.add_argument("--out-dir", type=Path, required=True) + p.add_argument("--threads", type=int, default=10) + p.add_argument("--device", default="cuda") + # Smoke-test knobs only; the protocol is the full recording at 2000 iterations. + p.add_argument("--max-iter", type=int, default=MAX_ITER) + p.add_argument("--frames", type=int, default=None) + a = p.parse_args() + a.out_dir.mkdir(parents=True, exist_ok=True) + if a.cmd == "compare": + rep = compare(a.out_dir) + (a.out_dir / "newton_seeds_report.json").write_text(json.dumps(rep, indent=2)) + print(json.dumps(rep, indent=2)) + return + data = load_data(a.data) + if a.frames: + data = data[:, : a.frames] + tag = "fixinit" if a.fixinit else f"seed{a.seed}" + if a.cmd == "pamica": + res = run_pamica(data, a.seed, a.fixinit, a.device, a.max_iter) + else: + res = run_fortran(data, a.seed, a.fixinit, a.threads, a.out_dir, a.max_iter) + np.savez(a.out_dir / f"{a.cmd}_{tag}.npz", **res) + print( + f"{a.cmd} {tag}: final_ll={res['final_ll']:.6f} iters={len(res['ll_history'])} " + + " ".join( + f"{k}={res[k]}" + for k in ("stop_reason", "n_newton_fallbacks", "end_newtrate") + if k in res + ) + + f" time={res['seconds']:.0f}s", + flush=True, + ) + + +if __name__ == "__main__": + main() From 3021d164fbe57cb4720704886797d3b1773716c5 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 13:52:02 -0700 Subject: [PATCH 02/58] Add hallu driver for the Newton seed study --- .context/issue-351/run_newton_hallu.sh | 34 ++++++++++++++++++++++++++ 1 file changed, 34 insertions(+) create mode 100644 .context/issue-351/run_newton_hallu.sh diff --git a/.context/issue-351/run_newton_hallu.sh b/.context/issue-351/run_newton_hallu.sh new file mode 100644 index 0000000..fbc3ddf --- /dev/null +++ b/.context/issue-351/run_newton_hallu.sh @@ -0,0 +1,34 @@ +#!/usr/bin/env bash +# Driver for newton_seeds.py on the CUDA workstation (issue #351 item 4a). +# Two queues run side by side: the pamica fits on the GPU, the reference fits +# on FORTRAN_THREADS CPU threads. Launch detached: +# nohup bash .context/issue-351/run_newton_hallu.sh OUT_DIR > OUT_DIR.log 2>&1 < /dev/null & +set -u +OUT=${1:?usage: run_newton_hallu.sh OUT_DIR} +DATA=${DATA:-benchmarks/data/ds002718_sub-002_eeg70_full.npy} +FORTRAN_THREADS=${FORTRAN_THREADS:-10} +UV=${UV:-uv} +SCRIPT=.context/issue-351/newton_seeds.py +mkdir -p "$OUT" + +gpu_queue() { + for s in 42 7 13; do + [ -f "$OUT/pamica_seed$s.npz" ] || "$UV" run python "$SCRIPT" pamica --seed "$s" --data "$DATA" --out-dir "$OUT" + done + [ -f "$OUT/pamica_fixinit.npz" ] || "$UV" run python "$SCRIPT" pamica --fixinit --data "$DATA" --out-dir "$OUT" +} + +cpu_queue() { + for s in 1 2; do + [ -f "$OUT/fortran_seed$s.npz" ] || "$UV" run python "$SCRIPT" fortran --seed "$s" --threads "$FORTRAN_THREADS" --data "$DATA" --out-dir "$OUT" + done + [ -f "$OUT/fortran_fixinit.npz" ] || "$UV" run python "$SCRIPT" fortran --fixinit --threads "$FORTRAN_THREADS" --data "$DATA" --out-dir "$OUT" +} + +date +gpu_queue > "$OUT/gpu_queue.log" 2>&1 & +cpu_queue > "$OUT/cpu_queue.log" 2>&1 & +wait +date +"$UV" run python "$SCRIPT" compare --out-dir "$OUT" +echo DONE From 2df2cc6c6b26c2c4b7ef407b2c7cfee2e7aaa081 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:09:31 -0700 Subject: [PATCH 03/58] Record harness, same-start and fixture parity runs --- .context/issue-351/fixture_parity.py | 82 ++++++ .context/issue-351/harness_gap.py | 194 ++++++++++++++ .context/issue-351/orientation_check.py | 82 ++++++ .../issue-351/raw/fixture_parity_head.txt | 3 + .context/issue-351/raw/harness_gap_head.json | 65 +++++ .context/issue-351/raw/harness_gap_head.log | 131 ++++++++++ .../raw/harness_gap_pre_epic_e38aa11.json | 21 ++ .../raw/harness_gap_pre_epic_e38aa11.log | 30 +++ .../fortran_run/fortran_output/out.txt | 108 ++++++++ .../fortran_run/input.param | 82 ++++++ .../parity_summary.md | 6 + .../raw/harness_pre_epic_e38aa11/stdout.log | 240 ++++++++++++++++++ .../validation_report.txt | 33 +++ .../validation_report_mlx.txt | 33 +++ .../validation_report_numpy.txt | 33 +++ .../fortran_run/fortran_output/out.txt | 108 ++++++++ .../raw/harness_run1/fortran_run/input.param | 82 ++++++ .../raw/harness_run1/parity_summary.md | 6 + .../issue-351/raw/harness_run1/stdout.log | 240 ++++++++++++++++++ .../raw/harness_run1/validation_report.txt | 33 +++ .../harness_run1/validation_report_mlx.txt | 33 +++ .../harness_run1/validation_report_numpy.txt | 33 +++ .../fortran_run/fortran_output/out.txt | 108 ++++++++ .../raw/harness_run2/fortran_run/input.param | 82 ++++++ .../raw/harness_run2/parity_summary.md | 6 + .../issue-351/raw/harness_run2/stdout.log | 240 ++++++++++++++++++ .../raw/harness_run2/validation_report.txt | 33 +++ .../harness_run2/validation_report_mlx.txt | 33 +++ .../harness_run2/validation_report_numpy.txt | 33 +++ .context/issue-351/raw/orientation_check.txt | 10 + 30 files changed, 2223 insertions(+) create mode 100644 .context/issue-351/fixture_parity.py create mode 100644 .context/issue-351/harness_gap.py create mode 100644 .context/issue-351/orientation_check.py create mode 100644 .context/issue-351/raw/fixture_parity_head.txt create mode 100644 .context/issue-351/raw/harness_gap_head.json create mode 100644 .context/issue-351/raw/harness_gap_head.log create mode 100644 .context/issue-351/raw/harness_gap_pre_epic_e38aa11.json create mode 100644 .context/issue-351/raw/harness_gap_pre_epic_e38aa11.log create mode 100644 .context/issue-351/raw/harness_pre_epic_e38aa11/fortran_run/fortran_output/out.txt create mode 100644 .context/issue-351/raw/harness_pre_epic_e38aa11/fortran_run/input.param create mode 100644 .context/issue-351/raw/harness_pre_epic_e38aa11/parity_summary.md create mode 100644 .context/issue-351/raw/harness_pre_epic_e38aa11/stdout.log create mode 100644 .context/issue-351/raw/harness_pre_epic_e38aa11/validation_report.txt create mode 100644 .context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_mlx.txt create mode 100644 .context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_numpy.txt create mode 100644 .context/issue-351/raw/harness_run1/fortran_run/fortran_output/out.txt create mode 100644 .context/issue-351/raw/harness_run1/fortran_run/input.param create mode 100644 .context/issue-351/raw/harness_run1/parity_summary.md create mode 100644 .context/issue-351/raw/harness_run1/stdout.log create mode 100644 .context/issue-351/raw/harness_run1/validation_report.txt create mode 100644 .context/issue-351/raw/harness_run1/validation_report_mlx.txt create mode 100644 .context/issue-351/raw/harness_run1/validation_report_numpy.txt create mode 100644 .context/issue-351/raw/harness_run2/fortran_run/fortran_output/out.txt create mode 100644 .context/issue-351/raw/harness_run2/fortran_run/input.param create mode 100644 .context/issue-351/raw/harness_run2/parity_summary.md create mode 100644 .context/issue-351/raw/harness_run2/stdout.log create mode 100644 .context/issue-351/raw/harness_run2/validation_report.txt create mode 100644 .context/issue-351/raw/harness_run2/validation_report_mlx.txt create mode 100644 .context/issue-351/raw/harness_run2/validation_report_numpy.txt create mode 100644 .context/issue-351/raw/orientation_check.txt diff --git a/.context/issue-351/fixture_parity.py b/.context/issue-351/fixture_parity.py new file mode 100644 index 0000000..d18bff9 --- /dev/null +++ b/.context/issue-351/fixture_parity.py @@ -0,0 +1,82 @@ +"""Parity against the bundled ``amicaout`` fixture (200 reference iterations of +the bundled macOS binary, ``input.param`` settings, unseeded), for every +backend. The protocol of the epic #324 Phase 7 and Phase 11 before/after +figures (PR 340 and PR 348), kept here as the issue #351 run record: +each backend fits the sample through ``input.param`` for K iterations, seed 42, +and is compared with the fixture's W @ S and its LL at iteration K. + + uv run python .context/issue-351/fixture_parity.py ROOT BACKEND [K] + +ROOT is a pamica source tree (the worktree, or an older checkout).""" + +import sys +import tempfile +import time + +root = sys.argv[1] +sys.path.insert(0, root) +import importlib.util # noqa: E402 + +import numpy as np # noqa: E402 +from scipy.optimize import linear_sum_assignment # noqa: E402 + +import pamica # noqa: E402 + +assert pamica.__file__.startswith(root), pamica.__file__ +from pamica.torch_impl.utils import load_eeglab_data # noqa: E402 + +backend = sys.argv[2] +K = int(sys.argv[3]) if len(sys.argv) > 3 else 200 +SD = root + "/pamica/sample_data/" +vspec = importlib.util.spec_from_file_location( + "vi", root + "/validate_implementations.py" +) +vi = importlib.util.module_from_spec(vspec) +vspec.loader.exec_module(vi) +X = load_eeglab_data(SD + "eeglab_data.fdt", data_dim=32, field_dim=30504).astype( + np.float64 +) +AO = SD + "amicaout/" +W_ref = np.fromfile(AO + "W", np.float64).reshape(32, 32, order="F") +S_ref = np.fromfile(AO + "S", np.float64).reshape(32, 32, order="F") +LL_ref = np.fromfile(AO + "LL", np.float64) +LL_ref = LL_ref[LL_ref != 0] + +t0 = time.time() +if backend == "numpy": + from pamica.numpy_impl.core import AMICA as AMICA_NumPy + + with tempfile.TemporaryDirectory() as td: + m = AMICA_NumPy( + params_file=SD + "input.param", + max_iter=K, + seed=42, + use_tqdm=False, + outdir=td, + writestep=10**6, + ) + m.fit(X) + Wp = m.get_weights() @ m.sphere + ll = float(m.ll[-1]) + n_it = len(m.ll) + stop = m.stop_reason +else: + from pamica import AMICA + + a = AMICA.from_params_file(SD + "input.param", backend=backend) + a.fit(X, max_iter=K, seed=42) + mm = a.model_ + Wp = np.asarray(mm.get_unmixing_matrix(0)) @ np.asarray(mm.get_sphere()) + ll = float(mm.final_ll_) + n_it = len(mm.ll_history) + stop = mm.stop_reason +Wr = W_ref @ S_ref +an = Wp / np.linalg.norm(Wp, axis=1, keepdims=True) +bn = Wr / np.linalg.norm(Wr, axis=1, keepdims=True) +c = np.abs(an @ bn.T) +ri, ci = linear_sum_assignment(1 - c) +print( + f"{backend} K={K}: LL {ll:.6f} fixture {LL_ref[K - 1]:.6f} |dLL|={abs(ll - LL_ref[K - 1]):.2e} " + f"corr={c[ri, ci].mean():.6f} min={c[ri, ci].min():.4f} amari={vi.amari_distance(Wp, Wr):.3e} " + f"stop={stop} iters={n_it} ({time.time() - t0:.0f}s)" +) diff --git a/.context/issue-351/harness_gap.py b/.context/issue-351/harness_gap.py new file mode 100644 index 0000000..8b275f4 --- /dev/null +++ b/.context/issue-351/harness_gap.py @@ -0,0 +1,194 @@ +"""Why the harness's 100-iteration log-likelihood gap moved (issue #351). + +``validate_implementations.py --backend all`` runs each pamica backend and the +reference binary from their OWN initializations with the same seed number +(numpy's ``RandomState(42)`` for pamica, gfortran's ``random_number`` seeded +with 42 for the binary), so the two start from different points. Its +log-likelihood difference after 100 iterations mixes two things: how far apart +the two starting points leave the fits at iteration 100, and any difference in +the update rule. This script separates them on the harness's own settings. + +1. Same start: pamica's seed-42 initialization is written into the binary's + ``load_*`` files (``pamica/tests/native_oracle.py``) and both sides run the + harness's 100 iterations from it, single-threaded. What remains is the + update rule's difference. +2. Start-to-start spread: the binary and pamica each run from several seeds. + The spread of their final log-likelihoods is what the harness's + independent-start difference is drawn from. + +``ROOT`` is a pamica source tree: the worktree, or a checkout of an older +commit (run it from the worktree's environment; the tree at ``ROOT`` is +imported in place of the installed package, and ``native_oracle`` is read from +this worktree so an old tree without it still works):: + + uv run python .context/issue-351/harness_gap.py ROOT OUT.json [--spread 1,2,3] +""" + +from __future__ import annotations + +import argparse +import importlib.util +import json +import sys +import tempfile +import time +from pathlib import Path + +HERE = Path(__file__).resolve().parent +WORKTREE = HERE.parents[1] + + +def _load(path: Path, name: str): + spec = importlib.util.spec_from_file_location(name, path) + assert spec is not None and spec.loader is not None + mod = importlib.util.module_from_spec(spec) + sys.modules[name] = mod + spec.loader.exec_module(mod) + return mod + + +def main() -> None: + p = argparse.ArgumentParser() + p.add_argument("root", type=Path) + p.add_argument("out", type=Path) + p.add_argument("--seed", type=int, default=42) + p.add_argument("--spread", default="", help="comma-separated extra seeds") + p.add_argument( + "--binary", + type=Path, + default=Path.home() / ".cache/pamica/bin/v0.3.3/amica15-macos-arm64", + ) + a = p.parse_args() + root = a.root.resolve() + sys.path.insert(0, str(root)) + + import numpy as np # noqa: E402 + + import pamica # noqa: E402 + + assert pamica.__file__.startswith(str(root)), pamica.__file__ + from pamica.torch_impl import AMICATorchNG # noqa: E402 + + vi = _load(root / "validate_implementations.py", "vi_under_test") + oracle = _load(WORKTREE / "pamica/tests/native_oracle.py", "native_oracle_351") + + data, params = vi.load_sample_data() + params = dict(params) + params["max_iter"] = 100 + X = data.astype(np.float64) + nw, n = X.shape + fdt = root / "pamica/sample_data/eeglab_data.fdt" + report: dict = {"root": str(root), "binary": str(a.binary), "seed": a.seed} + + # --- 1. same start -------------------------------------------------------- + t0 = time.time() + fit = vi.run_pytorch_amica(data, params, Path(tempfile.mkdtemp()), a.seed) + torch_dt = time.time() - t0 + init = AMICATorchNG( + n_channels=nw, + n_models=1, + n_mix=params.get("num_mix", 3), + rho0=params["rho0"], + seed=a.seed, + device="cpu", + ) + init._preprocess(X) + init._initialize_parameters() + state = oracle.seed_from_torch(init) + # The harness's reference settings: the input.param it writes, minus the + # keys the seeded runner sets itself. + with tempfile.TemporaryDirectory() as td: + ref_free = vi.run_fortran_amica(data, params, Path(td), a.seed, a.binary) + written = (Path(td) / "fortran_run" / "input.param").read_text().splitlines() + skip = { + "files", "outdir", "indir", "seed", "max_threads", "data_dim", + "field_dim", "pcakeep", "max_iter", "num_models", "num_mix_comps", + "writestep", "write_LLt", "num_comps", "load_W", "doPCA", + "field_blocksize", + } # fmt: skip + ref_params = {} + for line in written: + parts = line.split() + if ( + len(parts) >= 2 + and parts[0] not in skip + and not parts[0].startswith("load_") + ): + ref_params[parts[0]] = parts[1] + with tempfile.TemporaryDirectory() as td: + ref = oracle.run_seeded_reference( + state, fdt, Path(td), n_samples=n, max_iter=100, threads=1, + binary=a.binary, **ref_params, + ) # fmt: skip + W_ref = np.linalg.inv(ref.A) # reference A: component k in column k + ref_ll = ref.LL[ref.LL != 0] + same = { + "pamica_final_ll": float(fit["final_ll"]), + "reference_from_pamica_init_final_ll": float(ref_ll[-1]), + "abs_ll_difference": abs(float(fit["final_ll"]) - float(ref_ll[-1])), + "mean_matched_corr": None, + "min_matched_corr": None, + "amari": float(vi.amari_distance(W_ref, fit["W"])), + "pamica_runtime_s": torch_dt, + } + cmp = vi.compare_results( + {"final_ll": ref_ll[-1], "W": W_ref, "final_iter": 100}, fit + ) + same["mean_matched_corr"] = float(cmp["mean_correlation"]) + same["min_matched_corr"] = float(cmp.get("min_correlation", np.nan)) + free = vi.compare_results(ref_free, fit) + report["independent_start"] = { + "reference_final_ll": float(ref_free["final_ll"]), + "pamica_final_ll": float(fit["final_ll"]), + "abs_ll_difference": float(free["ll_difference"]), + "mean_matched_corr": float(free["mean_correlation"]), + "amari": float(vi.amari_distance(ref_free["W"], fit["W"])), + } + report["same_start"] = same + + # --- 2. start-to-start spread ---------------------------------------------- + seeds = [a.seed] + [int(s) for s in a.spread.split(",") if s] + if len(seeds) > 1: + F, G = {}, {} + for s in seeds: + with tempfile.TemporaryDirectory() as td: + F[s] = vi.run_fortran_amica(data, params, Path(td), s, a.binary) + G[s] = ( + fit + if s == a.seed + else vi.run_pytorch_amica(data, params, Path(tempfile.mkdtemp()), s) + ) + f_ll = np.array([F[s]["final_ll"] for s in seeds]) + g_ll = np.array([G[s]["final_ll"] for s in seeds]) + gaps = np.array([abs(g - f) for g in g_ll for f in f_ll]) + corr_fg = [ + vi.compare_results(F[fs], G[gs])["mean_correlation"] + for fs in seeds + for gs in seeds + ] + corr_ff = [ + vi.compare_results(F[x], F[y])["mean_correlation"] + for i, x in enumerate(seeds) + for y in seeds[i + 1 :] + ] + report["spread"] = { + "seeds": seeds, + "reference_final_ll": f_ll.tolist(), + "pamica_final_ll": g_ll.tolist(), + "reference_ll_sd": float(f_ll.std()), + "pamica_ll_sd": float(g_ll.std()), + "reference_ll_range": float(np.ptp(f_ll)), + "pamica_ll_range": float(np.ptp(g_ll)), + "mean_ll_difference_of_means": float(abs(g_ll.mean() - f_ll.mean())), + "all_pairs_abs_gap_median": float(np.median(gaps)), + "all_pairs_abs_gap_min_max": [float(gaps.min()), float(gaps.max())], + "corr_pamica_vs_reference_mean": float(np.mean(corr_fg)), + "corr_reference_vs_reference_mean": float(np.mean(corr_ff)), + } + a.out.parent.mkdir(parents=True, exist_ok=True) + a.out.write_text(json.dumps(report, indent=2)) + print(json.dumps(report, indent=2)) + + +if __name__ == "__main__": + main() diff --git a/.context/issue-351/orientation_check.py b/.context/issue-351/orientation_check.py new file mode 100644 index 0000000..2a78add --- /dev/null +++ b/.context/issue-351/orientation_check.py @@ -0,0 +1,82 @@ +"""Check that ``native_oracle.seed_from_torch`` writes a tree's initialization in +the orientation the binary reads (issue #351, for ``harness_gap.py``). + +For the tree at ``ROOT``, pamica's seed-42 initialization is written into the +binary's ``load_*`` files twice: as ``seed_from_torch`` writes it (the stored +``A`` transposed) and with the stored ``A`` itself. The binary runs ONE +iteration from each; its iteration-1 log-likelihood is the E-step at the loaded +state, before any update, so the right orientation reproduces pamica's own +iteration-1 log-likelihood to round-off and the wrong one does not. + + uv run python .context/issue-351/orientation_check.py ROOT +""" + +from __future__ import annotations + +import dataclasses +import importlib.util +import sys +import tempfile +from pathlib import Path + +HERE = Path(__file__).resolve().parent +WORKTREE = HERE.parents[1] +BINARY = Path.home() / ".cache/pamica/bin/v0.3.3/amica15-macos-arm64" + + +def main() -> None: + root = Path(sys.argv[1]).resolve() + sys.path.insert(0, str(root)) + import numpy as np + + import pamica + + assert pamica.__file__.startswith(str(root)), pamica.__file__ + from pamica.torch_impl import AMICATorchNG + + spec = importlib.util.spec_from_file_location( + "native_oracle_351", WORKTREE / "pamica/tests/native_oracle.py" + ) + assert spec is not None and spec.loader is not None + oracle = importlib.util.module_from_spec(spec) + sys.modules["native_oracle_351"] = oracle # dataclasses need the module + spec.loader.exec_module(oracle) + vspec = importlib.util.spec_from_file_location( + "vi_351", root / "validate_implementations.py" + ) + assert vspec is not None and vspec.loader is not None + vi = importlib.util.module_from_spec(vspec) + vspec.loader.exec_module(vi) + + data, params = vi.load_sample_data() + X = data.astype(np.float64) + nw, n = X.shape + kw = dict(n_channels=nw, n_models=1, n_mix=3, rho0=params["rho0"], seed=42) + fit = AMICATorchNG(block_size=512, lrate=0.05, device="cpu", **kw) + fit.fit(X, max_iter=1, verbose=False) + pamica_ll1 = float(fit.ll_history[0]) + + init = AMICATorchNG(device="cpu", **kw) + init._preprocess(X) + init._initialize_parameters() + state = oracle.seed_from_torch(init) + stored = dataclasses.replace(state, A=np.ascontiguousarray(state.A.T)) + fdt = root / "pamica/sample_data/eeglab_data.fdt" + out = {} + for name, st in (("seed_from_torch", state), ("stored A untransposed", stored)): + with tempfile.TemporaryDirectory() as td: + ref = oracle.run_seeded_reference( + st, fdt, Path(td), n_samples=n, max_iter=1, threads=1, binary=BINARY, + block_size=512, do_newton=1, use_min_dll=0, use_grad_norm=0, + ) # fmt: skip + out[name] = float(ref.LL[0]) + asym = float(np.abs(state.A - state.A.T).max()) + print(f"root {root}") + print(f"max |A - A.T| of the initial A: {asym:.3e}") + print(f"pamica iteration-1 LL: {pamica_ll1:.15f}") + for name, ll in out.items(): + print(f"binary iteration-1 LL, {name}: {ll:.15f} (diff {ll - pamica_ll1:+.3e})") + + +if __name__ == "__main__": + main() diff --git a/.context/issue-351/raw/fixture_parity_head.txt b/.context/issue-351/raw/fixture_parity_head.txt new file mode 100644 index 0000000..34d6118 --- /dev/null +++ b/.context/issue-351/raw/fixture_parity_head.txt @@ -0,0 +1,3 @@ +torch K=200: LL -3.401731 fixture -3.401873 |dLL|=1.42e-04 corr=0.998321 min=0.9827 amari=4.757e-03 stop=max_iter iters=200 (36s) +numpy K=200: LL -3.401741 fixture -3.401873 |dLL|=1.32e-04 corr=0.998317 min=0.9826 amari=4.753e-03 stop=None iters=200 (65s) +mlx K=200: LL -3.401729 fixture -3.401873 |dLL|=1.44e-04 corr=0.998291 min=0.9823 amari=4.787e-03 stop=max_iter iters=200 (6s) diff --git a/.context/issue-351/raw/harness_gap_head.json b/.context/issue-351/raw/harness_gap_head.json new file mode 100644 index 0000000..7d167cb --- /dev/null +++ b/.context/issue-351/raw/harness_gap_head.json @@ -0,0 +1,65 @@ +{ + "root": "/Users/yahya/Documents/git/mlx-fc-phase15-final-parity", + "binary": "/Users/yahya/.cache/pamica/bin/v0.3.3/amica15-macos-arm64", + "seed": 42, + "independent_start": { + "reference_final_ll": -3.4112742644, + "pamica_final_ll": -3.4110031143196786, + "abs_ll_difference": 0.0002711500803211919, + "mean_matched_corr": 0.9991066998432325, + "amari": 0.0038402262528516836 + }, + "same_start": { + "pamica_final_ll": -3.4110031143196786, + "reference_from_pamica_init_final_ll": -3.411001549158044, + "abs_ll_difference": 1.5651616345202513e-06, + "mean_matched_corr": 0.9999999298370493, + "min_matched_corr": 0.9999994935065543, + "amari": 3.919041819197437e-05, + "pamica_runtime_s": 18.209407091140747 + }, + "spread": { + "seeds": [ + 42, + 1, + 2, + 3, + 4, + 5, + 6, + 7 + ], + "reference_final_ll": [ + -3.4112742644, + -3.4109011933, + -3.4113405673, + -3.4111396355, + -3.4110592339, + -3.4114007131, + -3.4106012053, + -3.411368154 + ], + "pamica_final_ll": [ + -3.4110031143196786, + -3.410626483863021, + -3.411424789950665, + -3.4107315624727748, + -3.410645033104124, + -3.4112454654530766, + -3.410883961942931, + -3.4109585758636474 + ], + "reference_ll_sd": 0.00025787060418183374, + "pamica_ll_sd": 0.0002656461686797844, + "reference_ll_range": 0.0007995078000000433, + "pamica_ll_range": 0.0007983060876441961, + "mean_ll_difference_of_means": 0.00019574747876038856, + "all_pairs_abs_gap_median": 0.0003508213583620634, + "all_pairs_abs_gap_min_max": [ + 1.723135706876988e-05, + 0.0008235846506652322 + ], + "corr_pamica_vs_reference_mean": 0.9972741592912583, + "corr_reference_vs_reference_mean": 0.9976571097787578 + } +} \ No newline at end of file diff --git a/.context/issue-351/raw/harness_gap_head.log b/.context/issue-351/raw/harness_gap_head.log new file mode 100644 index 0000000..6888ec9 --- /dev/null +++ b/.context/issue-351/raw/harness_gap_head.log @@ -0,0 +1,131 @@ +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Running Fortran AMICA... +Running Fortran AMICA... +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +{ + "root": "/Users/yahya/Documents/git/mlx-fc-phase15-final-parity", + "binary": "/Users/yahya/.cache/pamica/bin/v0.3.3/amica15-macos-arm64", + "seed": 42, + "independent_start": { + "reference_final_ll": -3.4112742644, + "pamica_final_ll": -3.4110031143196786, + "abs_ll_difference": 0.0002711500803211919, + "mean_matched_corr": 0.9991066998432325, + "amari": 0.0038402262528516836 + }, + "same_start": { + "pamica_final_ll": -3.4110031143196786, + "reference_from_pamica_init_final_ll": -3.411001549158044, + "abs_ll_difference": 1.5651616345202513e-06, + "mean_matched_corr": 0.9999999298370493, + "min_matched_corr": 0.9999994935065543, + "amari": 3.919041819197437e-05, + "pamica_runtime_s": 18.209407091140747 + }, + "spread": { + "seeds": [ + 42, + 1, + 2, + 3, + 4, + 5, + 6, + 7 + ], + "reference_final_ll": [ + -3.4112742644, + -3.4109011933, + -3.4113405673, + -3.4111396355, + -3.4110592339, + -3.4114007131, + -3.4106012053, + -3.411368154 + ], + "pamica_final_ll": [ + -3.4110031143196786, + -3.410626483863021, + -3.411424789950665, + -3.4107315624727748, + -3.410645033104124, + -3.4112454654530766, + -3.410883961942931, + -3.4109585758636474 + ], + "reference_ll_sd": 0.00025787060418183374, + "pamica_ll_sd": 0.0002656461686797844, + "reference_ll_range": 0.0007995078000000433, + "pamica_ll_range": 0.0007983060876441961, + "mean_ll_difference_of_means": 0.00019574747876038856, + "all_pairs_abs_gap_median": 0.0003508213583620634, + "all_pairs_abs_gap_min_max": [ + 1.723135706876988e-05, + 0.0008235846506652322 + ], + "corr_pamica_vs_reference_mean": 0.9972741592912583, + "corr_reference_vs_reference_mean": 0.9976571097787578 + } +} +uv run python .context/issue-351/harness_gap.py . --spread 1,2,3,4,5,6,7 277.67s user 219.56s system 202% cpu 4:05.71 total diff --git a/.context/issue-351/raw/harness_gap_pre_epic_e38aa11.json b/.context/issue-351/raw/harness_gap_pre_epic_e38aa11.json new file mode 100644 index 0000000..4593b80 --- /dev/null +++ b/.context/issue-351/raw/harness_gap_pre_epic_e38aa11.json @@ -0,0 +1,21 @@ +{ + "root": "/private/tmp/claude-501/-Users-yahya-Documents-git-pamica/3b0e67f1-eae1-4864-8013-454e2363dda4/scratchpad/p15_pre", + "binary": "/Users/yahya/.cache/pamica/bin/v0.3.3/amica15-macos-arm64", + "seed": 42, + "independent_start": { + "reference_final_ll": -3.4112742644, + "pamica_final_ll": -3.411245246404745, + "abs_ll_difference": 2.901799525467652e-05, + "mean_matched_corr": 0.9992076035220132, + "amari": 0.003728162900584144 + }, + "same_start": { + "pamica_final_ll": -3.411245246404745, + "reference_from_pamica_init_final_ll": -3.41100986299553, + "abs_ll_difference": 0.00023538340921502865, + "mean_matched_corr": 0.9999857141680409, + "min_matched_corr": 0.9998973352640502, + "amari": 0.000575904415394627, + "pamica_runtime_s": 17.72438097000122 + } +} \ No newline at end of file diff --git a/.context/issue-351/raw/harness_gap_pre_epic_e38aa11.log b/.context/issue-351/raw/harness_gap_pre_epic_e38aa11.log new file mode 100644 index 0000000..3c64bec --- /dev/null +++ b/.context/issue-351/raw/harness_gap_pre_epic_e38aa11.log @@ -0,0 +1,30 @@ +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +Running Fortran AMICA... +{ + "root": "/private/tmp/claude-501/-Users-yahya-Documents-git-pamica/3b0e67f1-eae1-4864-8013-454e2363dda4/scratchpad/p15_pre", + "binary": "/Users/yahya/.cache/pamica/bin/v0.3.3/amica15-macos-arm64", + "seed": 42, + "independent_start": { + "reference_final_ll": -3.4112742644, + "pamica_final_ll": -3.411245246404745, + "abs_ll_difference": 2.901799525467652e-05, + "mean_matched_corr": 0.9992076035220132, + "amari": 0.003728162900584144 + }, + "same_start": { + "pamica_final_ll": -3.411245246404745, + "reference_from_pamica_init_final_ll": -3.41100986299553, + "abs_ll_difference": 0.00023538340921502865, + "mean_matched_corr": 0.9999857141680409, + "min_matched_corr": 0.9998973352640502, + "amari": 0.000575904415394627, + "pamica_runtime_s": 17.72438097000122 + } +} +uv run --project /Users/yahya/Documents/git/mlx-fc-phase15-final-parity pytho 42.87s user 26.96s system 180% cpu 38.723 total diff --git a/.context/issue-351/raw/harness_pre_epic_e38aa11/fortran_run/fortran_output/out.txt b/.context/issue-351/raw/harness_pre_epic_e38aa11/fortran_run/fortran_output/out.txt new file mode 100644 index 0000000..afc2886 --- /dev/null +++ b/.context/issue-351/raw/harness_pre_epic_e38aa11/fortran_run/fortran_output/out.txt @@ -0,0 +1,108 @@ + minimum eigenvalues = 4.8799005132501518 6.9201197127079643 7.6562147928880719 + maximum eigenvalues = 9711.1430838537053 3039.6850435125002 1244.4129447052055 + num eigs kept = 32 + minimum eigenvalues = 4.8799005132501518 6.9201197127079643 7.6562147928880719 + maximum eigenvalues = 9711.1430838537053 3039.6850435125002 1244.4129447052055 + num eigs kept = 32 + iter 1 lrate = 0.0500000000 LL = -3.5138404119 nd = 0.0582472378, D = 0.42970E-02 0.42970E-02 ( 0.10 s, 0.0 h) + iter 2 lrate = 0.0500000000 LL = -3.4686647974 nd = 0.0257873373, D = 0.37613E-02 0.37613E-02 ( 0.10 s, 0.0 h) + iter 3 lrate = 0.0500000000 LL = -3.4616920323 nd = 0.0243745621, D = 0.37866E-02 0.37866E-02 ( 0.10 s, 0.0 h) + iter 4 lrate = 0.0500000000 LL = -3.4590483434 nd = 0.0268337143, D = 0.57743E-02 0.57743E-02 ( 0.10 s, 0.0 h) + iter 5 lrate = 0.0500000000 LL = -3.4570950991 nd = 0.0275204167, D = 0.10300E-01 0.10300E-01 ( 0.10 s, 0.0 h) + iter 6 lrate = 0.0500000000 LL = -3.4554259776 nd = 0.0271554390, D = 0.17193E-01 0.17193E-01 ( 0.10 s, 0.0 h) + iter 7 lrate = 0.0500000000 LL = -3.4539448816 nd = 0.0263078732, D = 0.25963E-01 0.25963E-01 ( 0.10 s, 0.0 h) + iter 8 lrate = 0.0500000000 LL = -3.4526061773 nd = 0.0252305695, D = 0.36058E-01 0.36058E-01 ( 0.10 s, 0.0 h) + iter 9 lrate = 0.0500000000 LL = -3.4514049324 nd = 0.0239589135, D = 0.46948E-01 0.46948E-01 ( 0.10 s, 0.0 h) + iter 10 lrate = 0.0500000000 LL = -3.4503446967 nd = 0.0224833972, D = 0.58114E-01 0.58114E-01 ( 0.10 s, 0.0 h) + iter 11 lrate = 0.0500000000 LL = -3.4494273388 nd = 0.0208405539, D = 0.69043E-01 0.69043E-01 ( 0.10 s, 0.0 h) + iter 12 lrate = 0.0500000000 LL = -3.4486503827 nd = 0.0191031940, D = 0.79272E-01 0.79272E-01 ( 0.10 s, 0.0 h) + iter 13 lrate = 0.0500000000 LL = -3.4480028416 nd = 0.0173800933, D = 0.88429E-01 0.88429E-01 ( 0.10 s, 0.0 h) + iter 14 lrate = 0.0500000000 LL = -3.4474749603 nd = 0.0156968335, D = 0.96270E-01 0.96270E-01 ( 0.10 s, 0.0 h) + iter 15 lrate = 0.0500000000 LL = -3.4470391911 nd = 0.0143341558, D = 0.10260E+00 0.10260E+00 ( 0.10 s, 0.0 h) + iter 16 lrate = 0.0500000000 LL = -3.4466732866 nd = 0.0132110732, D = 0.10754E+00 0.10754E+00 ( 0.10 s, 0.0 h) + iter 17 lrate = 0.0500000000 LL = -3.4463623229 nd = 0.0123285260, D = 0.11120E+00 0.11120E+00 ( 0.10 s, 0.0 h) + iter 18 lrate = 0.0500000000 LL = -3.4460914899 nd = 0.0116493533, D = 0.11371E+00 0.11371E+00 ( 0.10 s, 0.0 h) + iter 19 lrate = 0.0500000000 LL = -3.4458502064 nd = 0.0111482807, D = 0.11524E+00 0.11524E+00 ( 0.10 s, 0.0 h) + iter 20 lrate = 0.0500000000 LL = -3.4456268009 nd = 0.0107728174, D = 0.11596E+00 0.11596E+00 ( 0.10 s, 0.0 h) + iter 21 lrate = 0.0500000000 LL = -3.4454181035 nd = 0.0104894729, D = 0.11604E+00 0.11604E+00 ( 0.10 s, 0.0 h) + iter 22 lrate = 0.0500000000 LL = -3.4452217620 nd = 0.0102683247, D = 0.11562E+00 0.11562E+00 ( 0.10 s, 0.0 h) + iter 23 lrate = 0.0500000000 LL = -3.4450342435 nd = 0.0100942550, D = 0.11481E+00 0.11481E+00 ( 0.10 s, 0.0 h) + iter 24 lrate = 0.0500000000 LL = -3.4448536484 nd = 0.0099474996, D = 0.11371E+00 0.11371E+00 ( 0.10 s, 0.0 h) + iter 25 lrate = 0.0500000000 LL = -3.4446793315 nd = 0.0098193230, D = 0.11240E+00 0.11240E+00 ( 0.10 s, 0.0 h) + iter 26 lrate = 0.0500000000 LL = -3.4445112148 nd = 0.0097106364, D = 0.11093E+00 0.11093E+00 ( 0.10 s, 0.0 h) + iter 27 lrate = 0.0500000000 LL = -3.4443458120 nd = 0.0096101155, D = 0.10935E+00 0.10935E+00 ( 0.10 s, 0.0 h) + iter 28 lrate = 0.0500000000 LL = -3.4441841429 nd = 0.0095174602, D = 0.10770E+00 0.10770E+00 ( 0.10 s, 0.0 h) + iter 29 lrate = 0.0500000000 LL = -3.4440258521 nd = 0.0094318094, D = 0.10601E+00 0.10601E+00 ( 0.10 s, 0.0 h) + iter 30 lrate = 0.0500000000 LL = -3.4438715045 nd = 0.0093537182, D = 0.10429E+00 0.10429E+00 ( 0.10 s, 0.0 h) + iter 31 lrate = 0.0500000000 LL = -3.4437197766 nd = 0.0092762513, D = 0.10256E+00 0.10256E+00 ( 0.10 s, 0.0 h) + iter 32 lrate = 0.0500000000 LL = -3.4435705718 nd = 0.0092096201, D = 0.10084E+00 0.10084E+00 ( 0.10 s, 0.0 h) + iter 33 lrate = 0.0500000000 LL = -3.4434240077 nd = 0.0091470859, D = 0.99122E-01 0.99122E-01 ( 0.10 s, 0.0 h) + iter 34 lrate = 0.0500000000 LL = -3.4432801434 nd = 0.0090904652, D = 0.97425E-01 0.97425E-01 ( 0.10 s, 0.0 h) + iter 35 lrate = 0.0500000000 LL = -3.4431381670 nd = 0.0090375639, D = 0.95754E-01 0.95754E-01 ( 0.10 s, 0.0 h) + iter 36 lrate = 0.0500000000 LL = -3.4429990901 nd = 0.0089824829, D = 0.94111E-01 0.94111E-01 ( 0.10 s, 0.0 h) + iter 37 lrate = 0.0500000000 LL = -3.4428609571 nd = 0.0089354414, D = 0.92496E-01 0.92496E-01 ( 0.10 s, 0.0 h) + iter 38 lrate = 0.0500000000 LL = -3.4427244769 nd = 0.0088906811, D = 0.90910E-01 0.90910E-01 ( 0.10 s, 0.0 h) + iter 39 lrate = 0.0500000000 LL = -3.4425891313 nd = 0.0088492082, D = 0.89359E-01 0.89359E-01 ( 0.10 s, 0.0 h) + iter 40 lrate = 0.0500000000 LL = -3.4424553915 nd = 0.0088070259, D = 0.87837E-01 0.87837E-01 ( 0.10 s, 0.0 h) + iter 41 lrate = 0.0500000000 LL = -3.4423226720 nd = 0.0087682129, D = 0.86349E-01 0.86349E-01 ( 0.10 s, 0.0 h) + iter 42 lrate = 0.0500000000 LL = -3.4421911989 nd = 0.0087309078, D = 0.84898E-01 0.84898E-01 ( 0.10 s, 0.0 h) + iter 43 lrate = 0.0500000000 LL = -3.4420611786 nd = 0.0086945363, D = 0.83480E-01 0.83480E-01 ( 0.10 s, 0.0 h) + iter 44 lrate = 0.0500000000 LL = -3.4419321185 nd = 0.0086603649, D = 0.82095E-01 0.82095E-01 ( 0.10 s, 0.0 h) + iter 45 lrate = 0.0500000000 LL = -3.4418042727 nd = 0.0086283889, D = 0.80742E-01 0.80742E-01 ( 0.10 s, 0.0 h) + iter 46 lrate = 0.0500000000 LL = -3.4416768672 nd = 0.0085974373, D = 0.79422E-01 0.79422E-01 ( 0.10 s, 0.0 h) + iter 47 lrate = 0.0500000000 LL = -3.4415505599 nd = 0.0085658375, D = 0.78132E-01 0.78132E-01 ( 0.10 s, 0.0 h) + iter 48 lrate = 0.0500000000 LL = -3.4414252826 nd = 0.0085355070, D = 0.76874E-01 0.76874E-01 ( 0.10 s, 0.0 h) + iter 49 lrate = 0.0500000000 LL = -3.4413008778 nd = 0.0085045367, D = 0.75648E-01 0.75648E-01 ( 0.10 s, 0.0 h) + iter 50 lrate = 0.0500000000 LL = -3.4411775002 nd = 0.0073499988, D = 0.74448E-01 0.74448E-01 ( 0.10 s, 0.0 h) + iter 51 lrate = 0.1000000000 LL = -3.4409782229 nd = 0.0073279306, D = 0.73141E-01 0.73141E-01 ( 0.10 s, 0.0 h) + iter 52 lrate = 0.2000000000 LL = -3.4405919551 nd = 0.0072717685, D = 0.70617E-01 0.70617E-01 ( 0.10 s, 0.0 h) + iter 53 lrate = 0.3000000000 LL = -3.4400260592 nd = 0.0071975653, D = 0.67051E-01 0.67051E-01 ( 0.10 s, 0.0 h) + iter 54 lrate = 0.4000000000 LL = -3.4392902421 nd = 0.0071025916, D = 0.62693E-01 0.62693E-01 ( 0.10 s, 0.0 h) + iter 55 lrate = 0.5000000000 LL = -3.4383944792 nd = 0.0069838003, D = 0.57833E-01 0.57833E-01 ( 0.10 s, 0.0 h) + iter 56 lrate = 0.6000000000 LL = -3.4373514586 nd = 0.0068564048, D = 0.52779E-01 0.52779E-01 ( 0.10 s, 0.0 h) + iter 57 lrate = 0.7000000000 LL = -3.4361733721 nd = 0.0067176434, D = 0.47812E-01 0.47812E-01 ( 0.10 s, 0.0 h) + iter 58 lrate = 0.8000000000 LL = -3.4348773500 nd = 0.0065306037, D = 0.43152E-01 0.43152E-01 ( 0.10 s, 0.0 h) + iter 59 lrate = 0.9000000000 LL = -3.4334862033 nd = 0.0063144473, D = 0.38858E-01 0.38858E-01 ( 0.10 s, 0.0 h) + iter 60 lrate = 1.0000000000 LL = -3.4320290718 nd = 0.0060694050, D = 0.35007E-01 0.35007E-01 ( 0.10 s, 0.0 h) + iter 61 lrate = 1.0000000000 LL = -3.4306539336 nd = 0.0058165467, D = 0.31848E-01 0.31848E-01 ( 0.10 s, 0.0 h) + iter 62 lrate = 1.0000000000 LL = -3.4293727997 nd = 0.0055406777, D = 0.29288E-01 0.29288E-01 ( 0.10 s, 0.0 h) + iter 63 lrate = 1.0000000000 LL = -3.4281948781 nd = 0.0052692527, D = 0.27250E-01 0.27250E-01 ( 0.10 s, 0.0 h) + iter 64 lrate = 1.0000000000 LL = -3.4271211832 nd = 0.0050272799, D = 0.25745E-01 0.25745E-01 ( 0.10 s, 0.0 h) + iter 65 lrate = 1.0000000000 LL = -3.4261411718 nd = 0.0048073579, D = 0.24812E-01 0.24812E-01 ( 0.10 s, 0.0 h) + iter 66 lrate = 1.0000000000 LL = -3.4252466155 nd = 0.0046179247, D = 0.24345E-01 0.24345E-01 ( 0.10 s, 0.0 h) + iter 67 lrate = 1.0000000000 LL = -3.4244237228 nd = 0.0044367521, D = 0.24187E-01 0.24187E-01 ( 0.10 s, 0.0 h) + iter 68 lrate = 1.0000000000 LL = -3.4236656099 nd = 0.0042766153, D = 0.24212E-01 0.24212E-01 ( 0.10 s, 0.0 h) + iter 69 lrate = 1.0000000000 LL = -3.4229613447 nd = 0.0041429572, D = 0.24322E-01 0.24322E-01 ( 0.10 s, 0.0 h) + iter 70 lrate = 1.0000000000 LL = -3.4223013447 nd = 0.0040280167, D = 0.24478E-01 0.24478E-01 ( 0.10 s, 0.0 h) + iter 71 lrate = 1.0000000000 LL = -3.4216799403 nd = 0.0039220625, D = 0.24654E-01 0.24654E-01 ( 0.10 s, 0.0 h) + iter 72 lrate = 1.0000000000 LL = -3.4210881340 nd = 0.0038434466, D = 0.24854E-01 0.24854E-01 ( 0.10 s, 0.0 h) + iter 73 lrate = 1.0000000000 LL = -3.4205200068 nd = 0.0037706961, D = 0.25099E-01 0.25099E-01 ( 0.10 s, 0.0 h) + iter 74 lrate = 1.0000000000 LL = -3.4199694700 nd = 0.0037100029, D = 0.25387E-01 0.25387E-01 ( 0.10 s, 0.0 h) + iter 75 lrate = 1.0000000000 LL = -3.4194343331 nd = 0.0036479584, D = 0.25686E-01 0.25686E-01 ( 0.10 s, 0.0 h) + iter 76 lrate = 1.0000000000 LL = -3.4189134918 nd = 0.0035920222, D = 0.26006E-01 0.26006E-01 ( 0.10 s, 0.0 h) + iter 77 lrate = 1.0000000000 LL = -3.4184066190 nd = 0.0035339680, D = 0.26356E-01 0.26356E-01 ( 0.10 s, 0.0 h) + iter 78 lrate = 1.0000000000 LL = -3.4179137938 nd = 0.0034747481, D = 0.26715E-01 0.26715E-01 ( 0.10 s, 0.0 h) + iter 79 lrate = 1.0000000000 LL = -3.4174367980 nd = 0.0034084627, D = 0.27097E-01 0.27097E-01 ( 0.10 s, 0.0 h) + iter 80 lrate = 1.0000000000 LL = -3.4169767547 nd = 0.0033321218, D = 0.27486E-01 0.27486E-01 ( 0.10 s, 0.0 h) + iter 81 lrate = 1.0000000000 LL = -3.4165384642 nd = 0.0032441994, D = 0.27901E-01 0.27901E-01 ( 0.11 s, 0.0 h) + iter 82 lrate = 1.0000000000 LL = -3.4161213948 nd = 0.0031523169, D = 0.28348E-01 0.28348E-01 ( 0.10 s, 0.0 h) + iter 83 lrate = 1.0000000000 LL = -3.4157282834 nd = 0.0030511007, D = 0.28801E-01 0.28801E-01 ( 0.10 s, 0.0 h) + iter 84 lrate = 1.0000000000 LL = -3.4153589168 nd = 0.0029613584, D = 0.29281E-01 0.29281E-01 ( 0.10 s, 0.0 h) + iter 85 lrate = 1.0000000000 LL = -3.4150109305 nd = 0.0028842884, D = 0.29777E-01 0.29777E-01 ( 0.10 s, 0.0 h) + iter 86 lrate = 1.0000000000 LL = -3.4146806129 nd = 0.0028133041, D = 0.30284E-01 0.30284E-01 ( 0.10 s, 0.0 h) + iter 87 lrate = 1.0000000000 LL = -3.4143657476 nd = 0.0027405093, D = 0.30773E-01 0.30773E-01 ( 0.10 s, 0.0 h) + iter 88 lrate = 1.0000000000 LL = -3.4140664829 nd = 0.0026759716, D = 0.31255E-01 0.31255E-01 ( 0.10 s, 0.0 h) + iter 89 lrate = 1.0000000000 LL = -3.4137827396 nd = 0.0026172247, D = 0.31754E-01 0.31754E-01 ( 0.10 s, 0.0 h) + iter 90 lrate = 1.0000000000 LL = -3.4135099614 nd = 0.0025723970, D = 0.32216E-01 0.32216E-01 ( 0.10 s, 0.0 h) + iter 91 lrate = 1.0000000000 LL = -3.4132471327 nd = 0.0025251906, D = 0.32652E-01 0.32652E-01 ( 0.10 s, 0.0 h) + iter 92 lrate = 1.0000000000 LL = -3.4129956272 nd = 0.0024806124, D = 0.33075E-01 0.33075E-01 ( 0.10 s, 0.0 h) + iter 93 lrate = 1.0000000000 LL = -3.4127524864 nd = 0.0024369464, D = 0.33513E-01 0.33513E-01 ( 0.10 s, 0.0 h) + iter 94 lrate = 1.0000000000 LL = -3.4125183782 nd = 0.0023791588, D = 0.33946E-01 0.33946E-01 ( 0.10 s, 0.0 h) + iter 95 lrate = 1.0000000000 LL = -3.4122952276 nd = 0.0023308726, D = 0.34370E-01 0.34370E-01 ( 0.10 s, 0.0 h) + iter 96 lrate = 1.0000000000 LL = -3.4120794495 nd = 0.0022935368, D = 0.34803E-01 0.34803E-01 ( 0.10 s, 0.0 h) + iter 97 lrate = 1.0000000000 LL = -3.4118716676 nd = 0.0022663411, D = 0.35211E-01 0.35211E-01 ( 0.10 s, 0.0 h) + iter 98 lrate = 1.0000000000 LL = -3.4116682686 nd = 0.0022430245, D = 0.35585E-01 0.35585E-01 ( 0.10 s, 0.0 h) + iter 99 lrate = 1.0000000000 LL = -3.4114690851 nd = 0.0022236502, D = 0.35953E-01 0.35953E-01 ( 0.10 s, 0.0 h) + iter 100 lrate = 1.0000000000 LL = -3.4112742644 nd = 0.0022054248, D = 0.36296E-01 0.36296E-01 ( 0.10 s, 0.0 h) +... done. Execution time: 0.00 h +output directory = ./fortran_output/ diff --git a/.context/issue-351/raw/harness_pre_epic_e38aa11/fortran_run/input.param b/.context/issue-351/raw/harness_pre_epic_e38aa11/fortran_run/input.param new file mode 100644 index 0000000..c8f97ce --- /dev/null +++ b/.context/issue-351/raw/harness_pre_epic_e38aa11/fortran_run/input.param @@ -0,0 +1,82 @@ +files ./eeglab_data.fdt +outdir ./fortran_output/ +block_size 512 +do_opt_block 0 +blk_min 256 +blk_step 256 +blk_max 1024 +num_models 1 +max_threads 1 +use_min_dll 1 +min_dll 1e-09 +use_grad_norm 1 +min_grad_norm 1e-07 +num_mix_comps 3 +pdftype 0 +max_iter 100 +num_samples 1 +data_dim 32 +field_dim 30504 +field_blocksize 1 +do_history 0 +histstep 10 +share_comps 0 +share_start 100 +comp_thresh 0.99 +share_iter 100 +lrate 0.05 +minlrate 1e-08 +mineig 1.000000e-12 +lratefact 0.5 +rholrate 0.05 +rho0 1.5 +minrho 1.0 +maxrho 2.0 +rholratefact 0.5 +kurt_start 3 +num_kurt 5 +kurt_int 1 +do_newton 1 +newt_start 50 +newt_ramp 10 +newtrate 1.0 +do_reject 0 +numrej 3 +rejsig 3.0 +rejstart 2 +rejint 3 +writestep 20 +write_nd 0 +write_LLt 1 +decwindow 1 +max_decs 3 +fix_init 0 +update_A 1 +update_c 1 +update_gm 1 +update_alpha 1 +update_mu 1 +update_beta 1 +invsigmax 100.0 +invsigmin 0.0 +do_rho 1 +load_rej 0 +load_W 0 +load_c 0 +load_gm 0 +load_alpha 0 +load_mu 0 +load_beta 0 +load_rho 0 +load_comp_list 0 +do_mean 1 +do_sphere 1 +doPCA 1 +pcakeep 32 +pcadb 30.0 +byte_size 4 +doscaling 1 +scalestep 1 +num_comps 32 +do_approx_sphere 1 +seed 42 diff --git a/.context/issue-351/raw/harness_pre_epic_e38aa11/parity_summary.md b/.context/issue-351/raw/harness_pre_epic_e38aa11/parity_summary.md new file mode 100644 index 0000000..3a98345 --- /dev/null +++ b/.context/issue-351/raw/harness_pre_epic_e38aa11/parity_summary.md @@ -0,0 +1,6 @@ +| backend | precision | iterations | final LL | abs. LL difference | mean matched corr | min matched corr | Amari distance | runtime (s) | +|---|---|---:|---:|---:|---:|---:|---:|---:| +| Fortran (reference) | float64 | 100 | -3.411274 | | | | | 10.1 | +| PyTorch | float64 | 100 | -3.411245 | 0.000029 | 0.9992 | 0.9935 | 0.0037 | 17.9 | +| NumPy | float64 | 100 | -3.411246 | 0.000029 | 0.9992 | 0.9934 | 0.0037 | 32.5 | +| MLX | float32 | 100 | -3.411242 | 0.000032 | 0.9992 | 0.9935 | 0.0037 | 3.2 | diff --git a/.context/issue-351/raw/harness_pre_epic_e38aa11/stdout.log b/.context/issue-351/raw/harness_pre_epic_e38aa11/stdout.log new file mode 100644 index 0000000..6041ac6 --- /dev/null +++ b/.context/issue-351/raw/harness_pre_epic_e38aa11/stdout.log @@ -0,0 +1,240 @@ +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Validation with seed=42, max_iter=100 +Output directory: /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.context/issue-351/raw/harness_pre_epic_e38aa11 +Loaded data: (32, 30504) +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +Starting AMICA fitting... +Starting optimization... + +====================================================================== +VALIDATION REPORT: Fortran vs PyTorch AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + PyTorch Final LL: -3.411245 + LL Ratio (PyTorch/Fortran): 1.0000 + LL Absolute Difference: 0.000029 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + PyTorch Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9992 + Min Correlation: 0.9935 + Max Correlation: 1.0000 + Std Correlation: 0.0014 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0475 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== + +Report saved to: /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report.txt +Running NumPy AMICA (legacy reference backend)... + +AMICA: 0%| | 0/100 [00:000.9) + + Mixing Matrix Relative Error: 0.0476 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== + +Report saved to: /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_numpy.txt +Running MLX AMICA (Apple-GPU float32 backend)... +WARNING: params.json settings with no AMICAMLXNG equivalent are ignored (MLX uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 + + +====================================================================== +VALIDATION REPORT: Fortran vs MLX AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + MLX Final LL: -3.411242 + LL Ratio (MLX/Fortran): 1.0000 + LL Absolute Difference: 0.000032 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + MLX Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9992 + Min Correlation: 0.9935 + Max Correlation: 1.0000 + Std Correlation: 0.0014 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0474 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== + +Report saved to: /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_mlx.txt + +PARITY SUMMARY (seed=42, max_iter=100): +| backend | precision | iterations | final LL | abs. LL difference | mean matched corr | min matched corr | Amari distance | runtime (s) | +|---|---|---:|---:|---:|---:|---:|---:|---:| +| Fortran (reference) | float64 | 100 | -3.411274 | | | | | 10.1 | +| PyTorch | float64 | 100 | -3.411245 | 0.000029 | 0.9992 | 0.9935 | 0.0037 | 17.9 | +| NumPy | float64 | 100 | -3.411246 | 0.000029 | 0.9992 | 0.9934 | 0.0037 | 32.5 | +| MLX | float32 | 100 | -3.411242 | 0.000032 | 0.9992 | 0.9935 | 0.0037 | 3.2 | + +Summary saved to: /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.context/issue-351/raw/harness_pre_epic_e38aa11/parity_summary.md +uv run --project $W python validate_implementations.py --backend all $R 68.02s user 27.79s system 147% cpu 1:04.93 total diff --git a/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report.txt b/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report.txt new file mode 100644 index 0000000..cad7189 --- /dev/null +++ b/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report.txt @@ -0,0 +1,33 @@ + +====================================================================== +VALIDATION REPORT: Fortran vs PyTorch AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + PyTorch Final LL: -3.411245 + LL Ratio (PyTorch/Fortran): 1.0000 + LL Absolute Difference: 0.000029 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + PyTorch Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9992 + Min Correlation: 0.9935 + Max Correlation: 1.0000 + Std Correlation: 0.0014 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0475 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== diff --git a/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_mlx.txt b/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_mlx.txt new file mode 100644 index 0000000..4c24409 --- /dev/null +++ b/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_mlx.txt @@ -0,0 +1,33 @@ + +====================================================================== +VALIDATION REPORT: Fortran vs MLX AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + MLX Final LL: -3.411242 + LL Ratio (MLX/Fortran): 1.0000 + LL Absolute Difference: 0.000032 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + MLX Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9992 + Min Correlation: 0.9935 + Max Correlation: 1.0000 + Std Correlation: 0.0014 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0474 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== diff --git a/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_numpy.txt b/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_numpy.txt new file mode 100644 index 0000000..1514abb --- /dev/null +++ b/.context/issue-351/raw/harness_pre_epic_e38aa11/validation_report_numpy.txt @@ -0,0 +1,33 @@ + +====================================================================== +VALIDATION REPORT: Fortran vs NumPy AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + NumPy Final LL: -3.411246 + LL Ratio (NumPy/Fortran): 1.0000 + LL Absolute Difference: 0.000029 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + NumPy Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9992 + Min Correlation: 0.9934 + Max Correlation: 1.0000 + Std Correlation: 0.0014 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0476 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== diff --git a/.context/issue-351/raw/harness_run1/fortran_run/fortran_output/out.txt b/.context/issue-351/raw/harness_run1/fortran_run/fortran_output/out.txt new file mode 100644 index 0000000..e3298da --- /dev/null +++ b/.context/issue-351/raw/harness_run1/fortran_run/fortran_output/out.txt @@ -0,0 +1,108 @@ + minimum eigenvalues = 4.8799005132501518 6.9201197127079643 7.6562147928880719 + maximum eigenvalues = 9711.1430838537053 3039.6850435125002 1244.4129447052055 + num eigs kept = 32 + minimum eigenvalues = 4.8799005132501518 6.9201197127079643 7.6562147928880719 + maximum eigenvalues = 9711.1430838537053 3039.6850435125002 1244.4129447052055 + num eigs kept = 32 + iter 1 lrate = 0.0500000000 LL = -3.5138404119 nd = 0.0582472378, D = 0.42970E-02 0.42970E-02 ( 0.10 s, 0.0 h) + iter 2 lrate = 0.0500000000 LL = -3.4686647974 nd = 0.0257873373, D = 0.37613E-02 0.37613E-02 ( 0.10 s, 0.0 h) + iter 3 lrate = 0.0500000000 LL = -3.4616920323 nd = 0.0243745621, D = 0.37866E-02 0.37866E-02 ( 0.10 s, 0.0 h) + iter 4 lrate = 0.0500000000 LL = -3.4590483434 nd = 0.0268337143, D = 0.57743E-02 0.57743E-02 ( 0.10 s, 0.0 h) + iter 5 lrate = 0.0500000000 LL = -3.4570950991 nd = 0.0275204167, D = 0.10300E-01 0.10300E-01 ( 0.10 s, 0.0 h) + iter 6 lrate = 0.0500000000 LL = -3.4554259776 nd = 0.0271554390, D = 0.17193E-01 0.17193E-01 ( 0.10 s, 0.0 h) + iter 7 lrate = 0.0500000000 LL = -3.4539448816 nd = 0.0263078732, D = 0.25963E-01 0.25963E-01 ( 0.10 s, 0.0 h) + iter 8 lrate = 0.0500000000 LL = -3.4526061773 nd = 0.0252305695, D = 0.36058E-01 0.36058E-01 ( 0.10 s, 0.0 h) + iter 9 lrate = 0.0500000000 LL = -3.4514049324 nd = 0.0239589135, D = 0.46948E-01 0.46948E-01 ( 0.10 s, 0.0 h) + iter 10 lrate = 0.0500000000 LL = -3.4503446967 nd = 0.0224833972, D = 0.58114E-01 0.58114E-01 ( 0.10 s, 0.0 h) + iter 11 lrate = 0.0500000000 LL = -3.4494273388 nd = 0.0208405539, D = 0.69043E-01 0.69043E-01 ( 0.10 s, 0.0 h) + iter 12 lrate = 0.0500000000 LL = -3.4486503827 nd = 0.0191031940, D = 0.79272E-01 0.79272E-01 ( 0.10 s, 0.0 h) + iter 13 lrate = 0.0500000000 LL = -3.4480028416 nd = 0.0173800933, D = 0.88429E-01 0.88429E-01 ( 0.10 s, 0.0 h) + iter 14 lrate = 0.0500000000 LL = -3.4474749603 nd = 0.0156968335, D = 0.96270E-01 0.96270E-01 ( 0.10 s, 0.0 h) + iter 15 lrate = 0.0500000000 LL = -3.4470391911 nd = 0.0143341558, D = 0.10260E+00 0.10260E+00 ( 0.10 s, 0.0 h) + iter 16 lrate = 0.0500000000 LL = -3.4466732866 nd = 0.0132110732, D = 0.10754E+00 0.10754E+00 ( 0.10 s, 0.0 h) + iter 17 lrate = 0.0500000000 LL = -3.4463623229 nd = 0.0123285260, D = 0.11120E+00 0.11120E+00 ( 0.10 s, 0.0 h) + iter 18 lrate = 0.0500000000 LL = -3.4460914899 nd = 0.0116493533, D = 0.11371E+00 0.11371E+00 ( 0.10 s, 0.0 h) + iter 19 lrate = 0.0500000000 LL = -3.4458502064 nd = 0.0111482807, D = 0.11524E+00 0.11524E+00 ( 0.10 s, 0.0 h) + iter 20 lrate = 0.0500000000 LL = -3.4456268009 nd = 0.0107728174, D = 0.11596E+00 0.11596E+00 ( 0.10 s, 0.0 h) + iter 21 lrate = 0.0500000000 LL = -3.4454181035 nd = 0.0104894729, D = 0.11604E+00 0.11604E+00 ( 0.10 s, 0.0 h) + iter 22 lrate = 0.0500000000 LL = -3.4452217620 nd = 0.0102683247, D = 0.11562E+00 0.11562E+00 ( 0.10 s, 0.0 h) + iter 23 lrate = 0.0500000000 LL = -3.4450342435 nd = 0.0100942550, D = 0.11481E+00 0.11481E+00 ( 0.10 s, 0.0 h) + iter 24 lrate = 0.0500000000 LL = -3.4448536484 nd = 0.0099474996, D = 0.11371E+00 0.11371E+00 ( 0.10 s, 0.0 h) + iter 25 lrate = 0.0500000000 LL = -3.4446793315 nd = 0.0098193230, D = 0.11240E+00 0.11240E+00 ( 0.10 s, 0.0 h) + iter 26 lrate = 0.0500000000 LL = -3.4445112148 nd = 0.0097106364, D = 0.11093E+00 0.11093E+00 ( 0.10 s, 0.0 h) + iter 27 lrate = 0.0500000000 LL = -3.4443458120 nd = 0.0096101155, D = 0.10935E+00 0.10935E+00 ( 0.10 s, 0.0 h) + iter 28 lrate = 0.0500000000 LL = -3.4441841429 nd = 0.0095174602, D = 0.10770E+00 0.10770E+00 ( 0.10 s, 0.0 h) + iter 29 lrate = 0.0500000000 LL = -3.4440258521 nd = 0.0094318094, D = 0.10601E+00 0.10601E+00 ( 0.10 s, 0.0 h) + iter 30 lrate = 0.0500000000 LL = -3.4438715045 nd = 0.0093537182, D = 0.10429E+00 0.10429E+00 ( 0.10 s, 0.0 h) + iter 31 lrate = 0.0500000000 LL = -3.4437197766 nd = 0.0092762513, D = 0.10256E+00 0.10256E+00 ( 0.10 s, 0.0 h) + iter 32 lrate = 0.0500000000 LL = -3.4435705718 nd = 0.0092096201, D = 0.10084E+00 0.10084E+00 ( 0.10 s, 0.0 h) + iter 33 lrate = 0.0500000000 LL = -3.4434240077 nd = 0.0091470859, D = 0.99122E-01 0.99122E-01 ( 0.10 s, 0.0 h) + iter 34 lrate = 0.0500000000 LL = -3.4432801434 nd = 0.0090904652, D = 0.97425E-01 0.97425E-01 ( 0.10 s, 0.0 h) + iter 35 lrate = 0.0500000000 LL = -3.4431381670 nd = 0.0090375639, D = 0.95754E-01 0.95754E-01 ( 0.10 s, 0.0 h) + iter 36 lrate = 0.0500000000 LL = -3.4429990901 nd = 0.0089824829, D = 0.94111E-01 0.94111E-01 ( 0.10 s, 0.0 h) + iter 37 lrate = 0.0500000000 LL = -3.4428609571 nd = 0.0089354414, D = 0.92496E-01 0.92496E-01 ( 0.10 s, 0.0 h) + iter 38 lrate = 0.0500000000 LL = -3.4427244769 nd = 0.0088906811, D = 0.90910E-01 0.90910E-01 ( 0.10 s, 0.0 h) + iter 39 lrate = 0.0500000000 LL = -3.4425891313 nd = 0.0088492082, D = 0.89359E-01 0.89359E-01 ( 0.10 s, 0.0 h) + iter 40 lrate = 0.0500000000 LL = -3.4424553915 nd = 0.0088070259, D = 0.87837E-01 0.87837E-01 ( 0.10 s, 0.0 h) + iter 41 lrate = 0.0500000000 LL = -3.4423226720 nd = 0.0087682129, D = 0.86349E-01 0.86349E-01 ( 0.10 s, 0.0 h) + iter 42 lrate = 0.0500000000 LL = -3.4421911989 nd = 0.0087309078, D = 0.84898E-01 0.84898E-01 ( 0.10 s, 0.0 h) + iter 43 lrate = 0.0500000000 LL = -3.4420611786 nd = 0.0086945363, D = 0.83480E-01 0.83480E-01 ( 0.10 s, 0.0 h) + iter 44 lrate = 0.0500000000 LL = -3.4419321185 nd = 0.0086603649, D = 0.82095E-01 0.82095E-01 ( 0.10 s, 0.0 h) + iter 45 lrate = 0.0500000000 LL = -3.4418042727 nd = 0.0086283889, D = 0.80742E-01 0.80742E-01 ( 0.10 s, 0.0 h) + iter 46 lrate = 0.0500000000 LL = -3.4416768672 nd = 0.0085974373, D = 0.79422E-01 0.79422E-01 ( 0.10 s, 0.0 h) + iter 47 lrate = 0.0500000000 LL = -3.4415505599 nd = 0.0085658375, D = 0.78132E-01 0.78132E-01 ( 0.10 s, 0.0 h) + iter 48 lrate = 0.0500000000 LL = -3.4414252826 nd = 0.0085355070, D = 0.76874E-01 0.76874E-01 ( 0.10 s, 0.0 h) + iter 49 lrate = 0.0500000000 LL = -3.4413008778 nd = 0.0085045367, D = 0.75648E-01 0.75648E-01 ( 0.10 s, 0.0 h) + iter 50 lrate = 0.0500000000 LL = -3.4411775002 nd = 0.0073499988, D = 0.74448E-01 0.74448E-01 ( 0.10 s, 0.0 h) + iter 51 lrate = 0.1000000000 LL = -3.4409782229 nd = 0.0073279306, D = 0.73141E-01 0.73141E-01 ( 0.10 s, 0.0 h) + iter 52 lrate = 0.2000000000 LL = -3.4405919551 nd = 0.0072717685, D = 0.70617E-01 0.70617E-01 ( 0.10 s, 0.0 h) + iter 53 lrate = 0.3000000000 LL = -3.4400260592 nd = 0.0071975653, D = 0.67051E-01 0.67051E-01 ( 0.10 s, 0.0 h) + iter 54 lrate = 0.4000000000 LL = -3.4392902421 nd = 0.0071025916, D = 0.62693E-01 0.62693E-01 ( 0.10 s, 0.0 h) + iter 55 lrate = 0.5000000000 LL = -3.4383944792 nd = 0.0069838003, D = 0.57833E-01 0.57833E-01 ( 0.10 s, 0.0 h) + iter 56 lrate = 0.6000000000 LL = -3.4373514586 nd = 0.0068564048, D = 0.52779E-01 0.52779E-01 ( 0.10 s, 0.0 h) + iter 57 lrate = 0.7000000000 LL = -3.4361733721 nd = 0.0067176434, D = 0.47812E-01 0.47812E-01 ( 0.10 s, 0.0 h) + iter 58 lrate = 0.8000000000 LL = -3.4348773500 nd = 0.0065306037, D = 0.43152E-01 0.43152E-01 ( 0.10 s, 0.0 h) + iter 59 lrate = 0.9000000000 LL = -3.4334862033 nd = 0.0063144473, D = 0.38858E-01 0.38858E-01 ( 0.10 s, 0.0 h) + iter 60 lrate = 1.0000000000 LL = -3.4320290718 nd = 0.0060694050, D = 0.35007E-01 0.35007E-01 ( 0.10 s, 0.0 h) + iter 61 lrate = 1.0000000000 LL = -3.4306539336 nd = 0.0058165467, D = 0.31848E-01 0.31848E-01 ( 0.10 s, 0.0 h) + iter 62 lrate = 1.0000000000 LL = -3.4293727997 nd = 0.0055406777, D = 0.29288E-01 0.29288E-01 ( 0.10 s, 0.0 h) + iter 63 lrate = 1.0000000000 LL = -3.4281948781 nd = 0.0052692527, D = 0.27250E-01 0.27250E-01 ( 0.10 s, 0.0 h) + iter 64 lrate = 1.0000000000 LL = -3.4271211832 nd = 0.0050272799, D = 0.25745E-01 0.25745E-01 ( 0.10 s, 0.0 h) + iter 65 lrate = 1.0000000000 LL = -3.4261411718 nd = 0.0048073579, D = 0.24812E-01 0.24812E-01 ( 0.10 s, 0.0 h) + iter 66 lrate = 1.0000000000 LL = -3.4252466155 nd = 0.0046179247, D = 0.24345E-01 0.24345E-01 ( 0.10 s, 0.0 h) + iter 67 lrate = 1.0000000000 LL = -3.4244237228 nd = 0.0044367521, D = 0.24187E-01 0.24187E-01 ( 0.10 s, 0.0 h) + iter 68 lrate = 1.0000000000 LL = -3.4236656099 nd = 0.0042766153, D = 0.24212E-01 0.24212E-01 ( 0.10 s, 0.0 h) + iter 69 lrate = 1.0000000000 LL = -3.4229613447 nd = 0.0041429572, D = 0.24322E-01 0.24322E-01 ( 0.10 s, 0.0 h) + iter 70 lrate = 1.0000000000 LL = -3.4223013447 nd = 0.0040280167, D = 0.24478E-01 0.24478E-01 ( 0.10 s, 0.0 h) + iter 71 lrate = 1.0000000000 LL = -3.4216799403 nd = 0.0039220625, D = 0.24654E-01 0.24654E-01 ( 0.10 s, 0.0 h) + iter 72 lrate = 1.0000000000 LL = -3.4210881340 nd = 0.0038434466, D = 0.24854E-01 0.24854E-01 ( 0.10 s, 0.0 h) + iter 73 lrate = 1.0000000000 LL = -3.4205200068 nd = 0.0037706961, D = 0.25099E-01 0.25099E-01 ( 0.10 s, 0.0 h) + iter 74 lrate = 1.0000000000 LL = -3.4199694700 nd = 0.0037100029, D = 0.25387E-01 0.25387E-01 ( 0.10 s, 0.0 h) + iter 75 lrate = 1.0000000000 LL = -3.4194343331 nd = 0.0036479584, D = 0.25686E-01 0.25686E-01 ( 0.10 s, 0.0 h) + iter 76 lrate = 1.0000000000 LL = -3.4189134918 nd = 0.0035920222, D = 0.26006E-01 0.26006E-01 ( 0.10 s, 0.0 h) + iter 77 lrate = 1.0000000000 LL = -3.4184066190 nd = 0.0035339680, D = 0.26356E-01 0.26356E-01 ( 0.10 s, 0.0 h) + iter 78 lrate = 1.0000000000 LL = -3.4179137938 nd = 0.0034747481, D = 0.26715E-01 0.26715E-01 ( 0.10 s, 0.0 h) + iter 79 lrate = 1.0000000000 LL = -3.4174367980 nd = 0.0034084627, D = 0.27097E-01 0.27097E-01 ( 0.10 s, 0.0 h) + iter 80 lrate = 1.0000000000 LL = -3.4169767547 nd = 0.0033321218, D = 0.27486E-01 0.27486E-01 ( 0.10 s, 0.0 h) + iter 81 lrate = 1.0000000000 LL = -3.4165384642 nd = 0.0032441994, D = 0.27901E-01 0.27901E-01 ( 0.10 s, 0.0 h) + iter 82 lrate = 1.0000000000 LL = -3.4161213948 nd = 0.0031523169, D = 0.28348E-01 0.28348E-01 ( 0.10 s, 0.0 h) + iter 83 lrate = 1.0000000000 LL = -3.4157282834 nd = 0.0030511007, D = 0.28801E-01 0.28801E-01 ( 0.10 s, 0.0 h) + iter 84 lrate = 1.0000000000 LL = -3.4153589168 nd = 0.0029613584, D = 0.29281E-01 0.29281E-01 ( 0.10 s, 0.0 h) + iter 85 lrate = 1.0000000000 LL = -3.4150109305 nd = 0.0028842884, D = 0.29777E-01 0.29777E-01 ( 0.10 s, 0.0 h) + iter 86 lrate = 1.0000000000 LL = -3.4146806129 nd = 0.0028133041, D = 0.30284E-01 0.30284E-01 ( 0.10 s, 0.0 h) + iter 87 lrate = 1.0000000000 LL = -3.4143657476 nd = 0.0027405093, D = 0.30773E-01 0.30773E-01 ( 0.10 s, 0.0 h) + iter 88 lrate = 1.0000000000 LL = -3.4140664829 nd = 0.0026759716, D = 0.31255E-01 0.31255E-01 ( 0.10 s, 0.0 h) + iter 89 lrate = 1.0000000000 LL = -3.4137827396 nd = 0.0026172247, D = 0.31754E-01 0.31754E-01 ( 0.10 s, 0.0 h) + iter 90 lrate = 1.0000000000 LL = -3.4135099614 nd = 0.0025723970, D = 0.32216E-01 0.32216E-01 ( 0.10 s, 0.0 h) + iter 91 lrate = 1.0000000000 LL = -3.4132471327 nd = 0.0025251906, D = 0.32652E-01 0.32652E-01 ( 0.10 s, 0.0 h) + iter 92 lrate = 1.0000000000 LL = -3.4129956272 nd = 0.0024806124, D = 0.33075E-01 0.33075E-01 ( 0.10 s, 0.0 h) + iter 93 lrate = 1.0000000000 LL = -3.4127524864 nd = 0.0024369464, D = 0.33513E-01 0.33513E-01 ( 0.10 s, 0.0 h) + iter 94 lrate = 1.0000000000 LL = -3.4125183782 nd = 0.0023791588, D = 0.33946E-01 0.33946E-01 ( 0.10 s, 0.0 h) + iter 95 lrate = 1.0000000000 LL = -3.4122952276 nd = 0.0023308726, D = 0.34370E-01 0.34370E-01 ( 0.10 s, 0.0 h) + iter 96 lrate = 1.0000000000 LL = -3.4120794495 nd = 0.0022935368, D = 0.34803E-01 0.34803E-01 ( 0.10 s, 0.0 h) + iter 97 lrate = 1.0000000000 LL = -3.4118716676 nd = 0.0022663411, D = 0.35211E-01 0.35211E-01 ( 0.10 s, 0.0 h) + iter 98 lrate = 1.0000000000 LL = -3.4116682686 nd = 0.0022430245, D = 0.35585E-01 0.35585E-01 ( 0.10 s, 0.0 h) + iter 99 lrate = 1.0000000000 LL = -3.4114690851 nd = 0.0022236502, D = 0.35953E-01 0.35953E-01 ( 0.10 s, 0.0 h) + iter 100 lrate = 1.0000000000 LL = -3.4112742644 nd = 0.0022054248, D = 0.36296E-01 0.36296E-01 ( 0.10 s, 0.0 h) +... done. Execution time: 0.00 h +output directory = ./fortran_output/ diff --git a/.context/issue-351/raw/harness_run1/fortran_run/input.param b/.context/issue-351/raw/harness_run1/fortran_run/input.param new file mode 100644 index 0000000..c8f97ce --- /dev/null +++ b/.context/issue-351/raw/harness_run1/fortran_run/input.param @@ -0,0 +1,82 @@ +files ./eeglab_data.fdt +outdir ./fortran_output/ +block_size 512 +do_opt_block 0 +blk_min 256 +blk_step 256 +blk_max 1024 +num_models 1 +max_threads 1 +use_min_dll 1 +min_dll 1e-09 +use_grad_norm 1 +min_grad_norm 1e-07 +num_mix_comps 3 +pdftype 0 +max_iter 100 +num_samples 1 +data_dim 32 +field_dim 30504 +field_blocksize 1 +do_history 0 +histstep 10 +share_comps 0 +share_start 100 +comp_thresh 0.99 +share_iter 100 +lrate 0.05 +minlrate 1e-08 +mineig 1.000000e-12 +lratefact 0.5 +rholrate 0.05 +rho0 1.5 +minrho 1.0 +maxrho 2.0 +rholratefact 0.5 +kurt_start 3 +num_kurt 5 +kurt_int 1 +do_newton 1 +newt_start 50 +newt_ramp 10 +newtrate 1.0 +do_reject 0 +numrej 3 +rejsig 3.0 +rejstart 2 +rejint 3 +writestep 20 +write_nd 0 +write_LLt 1 +decwindow 1 +max_decs 3 +fix_init 0 +update_A 1 +update_c 1 +update_gm 1 +update_alpha 1 +update_mu 1 +update_beta 1 +invsigmax 100.0 +invsigmin 0.0 +do_rho 1 +load_rej 0 +load_W 0 +load_c 0 +load_gm 0 +load_alpha 0 +load_mu 0 +load_beta 0 +load_rho 0 +load_comp_list 0 +do_mean 1 +do_sphere 1 +doPCA 1 +pcakeep 32 +pcadb 30.0 +byte_size 4 +doscaling 1 +scalestep 1 +num_comps 32 +do_approx_sphere 1 +seed 42 diff --git a/.context/issue-351/raw/harness_run1/parity_summary.md b/.context/issue-351/raw/harness_run1/parity_summary.md new file mode 100644 index 0000000..f9cb8f0 --- /dev/null +++ b/.context/issue-351/raw/harness_run1/parity_summary.md @@ -0,0 +1,6 @@ +| backend | precision | iterations | final LL | abs. LL difference | mean matched corr | min matched corr | Amari distance | runtime (s) | +|---|---|---:|---:|---:|---:|---:|---:|---:| +| Fortran (reference) | float64 | 100 | -3.411274 | | | | | 10.0 | +| PyTorch | float64 | 100 | -3.411003 | 0.000271 | 0.9991 | 0.9918 | 0.0038 | 18.1 | +| NumPy | float64 | 100 | -3.411003 | 0.000272 | 0.9991 | 0.9917 | 0.0038 | 32.6 | +| MLX | float32 | 100 | -3.410998 | 0.000276 | 0.9991 | 0.9917 | 0.0038 | 3.0 | diff --git a/.context/issue-351/raw/harness_run1/stdout.log b/.context/issue-351/raw/harness_run1/stdout.log new file mode 100644 index 0000000..17e297c --- /dev/null +++ b/.context/issue-351/raw/harness_run1/stdout.log @@ -0,0 +1,240 @@ +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Validation with seed=42, max_iter=100 +Output directory: .context/issue-351/raw/harness_run1 +Loaded data: (32, 30504) +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +Starting AMICA fitting... +Starting optimization... + +====================================================================== +VALIDATION REPORT: Fortran vs PyTorch AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + PyTorch Final LL: -3.411003 + LL Ratio (PyTorch/Fortran): 0.9999 + LL Absolute Difference: 0.000271 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + PyTorch Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9918 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0432 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== + +Report saved to: .context/issue-351/raw/harness_run1/validation_report.txt +Running NumPy AMICA (legacy reference backend)... + +AMICA: 0%| | 0/100 [00:000.9) + + Mixing Matrix Relative Error: 0.0432 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== + +Report saved to: .context/issue-351/raw/harness_run1/validation_report_numpy.txt +Running MLX AMICA (Apple-GPU float32 backend)... +WARNING: params.json settings with no AMICAMLXNG equivalent are ignored (MLX uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 + + +====================================================================== +VALIDATION REPORT: Fortran vs MLX AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + MLX Final LL: -3.410998 + LL Ratio (MLX/Fortran): 0.9999 + LL Absolute Difference: 0.000276 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + MLX Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9917 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0433 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== + +Report saved to: .context/issue-351/raw/harness_run1/validation_report_mlx.txt + +PARITY SUMMARY (seed=42, max_iter=100): +| backend | precision | iterations | final LL | abs. LL difference | mean matched corr | min matched corr | Amari distance | runtime (s) | +|---|---|---:|---:|---:|---:|---:|---:|---:| +| Fortran (reference) | float64 | 100 | -3.411274 | | | | | 10.0 | +| PyTorch | float64 | 100 | -3.411003 | 0.000271 | 0.9991 | 0.9918 | 0.0038 | 18.1 | +| NumPy | float64 | 100 | -3.411003 | 0.000272 | 0.9991 | 0.9917 | 0.0038 | 32.6 | +| MLX | float32 | 100 | -3.410998 | 0.000276 | 0.9991 | 0.9917 | 0.0038 | 3.0 | + +Summary saved to: .context/issue-351/raw/harness_run1/parity_summary.md +uv run python validate_implementations.py --backend all --fortran-binary $R 68.25s user 28.52s system 148% cpu 1:05.38 total diff --git a/.context/issue-351/raw/harness_run1/validation_report.txt b/.context/issue-351/raw/harness_run1/validation_report.txt new file mode 100644 index 0000000..30026a1 --- /dev/null +++ b/.context/issue-351/raw/harness_run1/validation_report.txt @@ -0,0 +1,33 @@ + +====================================================================== +VALIDATION REPORT: Fortran vs PyTorch AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + PyTorch Final LL: -3.411003 + LL Ratio (PyTorch/Fortran): 0.9999 + LL Absolute Difference: 0.000271 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + PyTorch Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9918 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0432 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== diff --git a/.context/issue-351/raw/harness_run1/validation_report_mlx.txt b/.context/issue-351/raw/harness_run1/validation_report_mlx.txt new file mode 100644 index 0000000..4f46450 --- /dev/null +++ b/.context/issue-351/raw/harness_run1/validation_report_mlx.txt @@ -0,0 +1,33 @@ + +====================================================================== +VALIDATION REPORT: Fortran vs MLX AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + MLX Final LL: -3.410998 + LL Ratio (MLX/Fortran): 0.9999 + LL Absolute Difference: 0.000276 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + MLX Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9917 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0433 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== diff --git a/.context/issue-351/raw/harness_run1/validation_report_numpy.txt b/.context/issue-351/raw/harness_run1/validation_report_numpy.txt new file mode 100644 index 0000000..f6d394c --- /dev/null +++ b/.context/issue-351/raw/harness_run1/validation_report_numpy.txt @@ -0,0 +1,33 @@ + +====================================================================== +VALIDATION REPORT: Fortran vs NumPy AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + NumPy Final LL: -3.411003 + LL Ratio (NumPy/Fortran): 0.9999 + LL Absolute Difference: 0.000272 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + NumPy Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9917 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0432 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== diff --git a/.context/issue-351/raw/harness_run2/fortran_run/fortran_output/out.txt b/.context/issue-351/raw/harness_run2/fortran_run/fortran_output/out.txt new file mode 100644 index 0000000..e029b66 --- /dev/null +++ b/.context/issue-351/raw/harness_run2/fortran_run/fortran_output/out.txt @@ -0,0 +1,108 @@ + minimum eigenvalues = 4.8799005132501518 6.9201197127079643 7.6562147928880719 + maximum eigenvalues = 9711.1430838537053 3039.6850435125002 1244.4129447052055 + num eigs kept = 32 + minimum eigenvalues = 4.8799005132501518 6.9201197127079643 7.6562147928880719 + maximum eigenvalues = 9711.1430838537053 3039.6850435125002 1244.4129447052055 + num eigs kept = 32 + iter 1 lrate = 0.0500000000 LL = -3.5138404119 nd = 0.0582472378, D = 0.42970E-02 0.42970E-02 ( 0.10 s, 0.0 h) + iter 2 lrate = 0.0500000000 LL = -3.4686647974 nd = 0.0257873373, D = 0.37613E-02 0.37613E-02 ( 0.10 s, 0.0 h) + iter 3 lrate = 0.0500000000 LL = -3.4616920323 nd = 0.0243745621, D = 0.37866E-02 0.37866E-02 ( 0.10 s, 0.0 h) + iter 4 lrate = 0.0500000000 LL = -3.4590483434 nd = 0.0268337143, D = 0.57743E-02 0.57743E-02 ( 0.10 s, 0.0 h) + iter 5 lrate = 0.0500000000 LL = -3.4570950991 nd = 0.0275204167, D = 0.10300E-01 0.10300E-01 ( 0.10 s, 0.0 h) + iter 6 lrate = 0.0500000000 LL = -3.4554259776 nd = 0.0271554390, D = 0.17193E-01 0.17193E-01 ( 0.10 s, 0.0 h) + iter 7 lrate = 0.0500000000 LL = -3.4539448816 nd = 0.0263078732, D = 0.25963E-01 0.25963E-01 ( 0.10 s, 0.0 h) + iter 8 lrate = 0.0500000000 LL = -3.4526061773 nd = 0.0252305695, D = 0.36058E-01 0.36058E-01 ( 0.10 s, 0.0 h) + iter 9 lrate = 0.0500000000 LL = -3.4514049324 nd = 0.0239589135, D = 0.46948E-01 0.46948E-01 ( 0.10 s, 0.0 h) + iter 10 lrate = 0.0500000000 LL = -3.4503446967 nd = 0.0224833972, D = 0.58114E-01 0.58114E-01 ( 0.10 s, 0.0 h) + iter 11 lrate = 0.0500000000 LL = -3.4494273388 nd = 0.0208405539, D = 0.69043E-01 0.69043E-01 ( 0.10 s, 0.0 h) + iter 12 lrate = 0.0500000000 LL = -3.4486503827 nd = 0.0191031940, D = 0.79272E-01 0.79272E-01 ( 0.10 s, 0.0 h) + iter 13 lrate = 0.0500000000 LL = -3.4480028416 nd = 0.0173800933, D = 0.88429E-01 0.88429E-01 ( 0.10 s, 0.0 h) + iter 14 lrate = 0.0500000000 LL = -3.4474749603 nd = 0.0156968335, D = 0.96270E-01 0.96270E-01 ( 0.10 s, 0.0 h) + iter 15 lrate = 0.0500000000 LL = -3.4470391911 nd = 0.0143341558, D = 0.10260E+00 0.10260E+00 ( 0.10 s, 0.0 h) + iter 16 lrate = 0.0500000000 LL = -3.4466732866 nd = 0.0132110732, D = 0.10754E+00 0.10754E+00 ( 0.10 s, 0.0 h) + iter 17 lrate = 0.0500000000 LL = -3.4463623229 nd = 0.0123285260, D = 0.11120E+00 0.11120E+00 ( 0.10 s, 0.0 h) + iter 18 lrate = 0.0500000000 LL = -3.4460914899 nd = 0.0116493533, D = 0.11371E+00 0.11371E+00 ( 0.10 s, 0.0 h) + iter 19 lrate = 0.0500000000 LL = -3.4458502064 nd = 0.0111482807, D = 0.11524E+00 0.11524E+00 ( 0.10 s, 0.0 h) + iter 20 lrate = 0.0500000000 LL = -3.4456268009 nd = 0.0107728174, D = 0.11596E+00 0.11596E+00 ( 0.10 s, 0.0 h) + iter 21 lrate = 0.0500000000 LL = -3.4454181035 nd = 0.0104894729, D = 0.11604E+00 0.11604E+00 ( 0.10 s, 0.0 h) + iter 22 lrate = 0.0500000000 LL = -3.4452217620 nd = 0.0102683247, D = 0.11562E+00 0.11562E+00 ( 0.10 s, 0.0 h) + iter 23 lrate = 0.0500000000 LL = -3.4450342435 nd = 0.0100942550, D = 0.11481E+00 0.11481E+00 ( 0.10 s, 0.0 h) + iter 24 lrate = 0.0500000000 LL = -3.4448536484 nd = 0.0099474996, D = 0.11371E+00 0.11371E+00 ( 0.10 s, 0.0 h) + iter 25 lrate = 0.0500000000 LL = -3.4446793315 nd = 0.0098193230, D = 0.11240E+00 0.11240E+00 ( 0.10 s, 0.0 h) + iter 26 lrate = 0.0500000000 LL = -3.4445112148 nd = 0.0097106364, D = 0.11093E+00 0.11093E+00 ( 0.10 s, 0.0 h) + iter 27 lrate = 0.0500000000 LL = -3.4443458120 nd = 0.0096101155, D = 0.10935E+00 0.10935E+00 ( 0.10 s, 0.0 h) + iter 28 lrate = 0.0500000000 LL = -3.4441841429 nd = 0.0095174602, D = 0.10770E+00 0.10770E+00 ( 0.10 s, 0.0 h) + iter 29 lrate = 0.0500000000 LL = -3.4440258521 nd = 0.0094318094, D = 0.10601E+00 0.10601E+00 ( 0.10 s, 0.0 h) + iter 30 lrate = 0.0500000000 LL = -3.4438715045 nd = 0.0093537182, D = 0.10429E+00 0.10429E+00 ( 0.10 s, 0.0 h) + iter 31 lrate = 0.0500000000 LL = -3.4437197766 nd = 0.0092762513, D = 0.10256E+00 0.10256E+00 ( 0.10 s, 0.0 h) + iter 32 lrate = 0.0500000000 LL = -3.4435705718 nd = 0.0092096201, D = 0.10084E+00 0.10084E+00 ( 0.10 s, 0.0 h) + iter 33 lrate = 0.0500000000 LL = -3.4434240077 nd = 0.0091470859, D = 0.99122E-01 0.99122E-01 ( 0.10 s, 0.0 h) + iter 34 lrate = 0.0500000000 LL = -3.4432801434 nd = 0.0090904652, D = 0.97425E-01 0.97425E-01 ( 0.10 s, 0.0 h) + iter 35 lrate = 0.0500000000 LL = -3.4431381670 nd = 0.0090375639, D = 0.95754E-01 0.95754E-01 ( 0.10 s, 0.0 h) + iter 36 lrate = 0.0500000000 LL = -3.4429990901 nd = 0.0089824829, D = 0.94111E-01 0.94111E-01 ( 0.10 s, 0.0 h) + iter 37 lrate = 0.0500000000 LL = -3.4428609571 nd = 0.0089354414, D = 0.92496E-01 0.92496E-01 ( 0.10 s, 0.0 h) + iter 38 lrate = 0.0500000000 LL = -3.4427244769 nd = 0.0088906811, D = 0.90910E-01 0.90910E-01 ( 0.10 s, 0.0 h) + iter 39 lrate = 0.0500000000 LL = -3.4425891313 nd = 0.0088492082, D = 0.89359E-01 0.89359E-01 ( 0.10 s, 0.0 h) + iter 40 lrate = 0.0500000000 LL = -3.4424553915 nd = 0.0088070259, D = 0.87837E-01 0.87837E-01 ( 0.10 s, 0.0 h) + iter 41 lrate = 0.0500000000 LL = -3.4423226720 nd = 0.0087682129, D = 0.86349E-01 0.86349E-01 ( 0.10 s, 0.0 h) + iter 42 lrate = 0.0500000000 LL = -3.4421911989 nd = 0.0087309078, D = 0.84898E-01 0.84898E-01 ( 0.10 s, 0.0 h) + iter 43 lrate = 0.0500000000 LL = -3.4420611786 nd = 0.0086945363, D = 0.83480E-01 0.83480E-01 ( 0.10 s, 0.0 h) + iter 44 lrate = 0.0500000000 LL = -3.4419321185 nd = 0.0086603649, D = 0.82095E-01 0.82095E-01 ( 0.10 s, 0.0 h) + iter 45 lrate = 0.0500000000 LL = -3.4418042727 nd = 0.0086283889, D = 0.80742E-01 0.80742E-01 ( 0.10 s, 0.0 h) + iter 46 lrate = 0.0500000000 LL = -3.4416768672 nd = 0.0085974373, D = 0.79422E-01 0.79422E-01 ( 0.10 s, 0.0 h) + iter 47 lrate = 0.0500000000 LL = -3.4415505599 nd = 0.0085658375, D = 0.78132E-01 0.78132E-01 ( 0.10 s, 0.0 h) + iter 48 lrate = 0.0500000000 LL = -3.4414252826 nd = 0.0085355070, D = 0.76874E-01 0.76874E-01 ( 0.10 s, 0.0 h) + iter 49 lrate = 0.0500000000 LL = -3.4413008778 nd = 0.0085045367, D = 0.75648E-01 0.75648E-01 ( 0.10 s, 0.0 h) + iter 50 lrate = 0.0500000000 LL = -3.4411775002 nd = 0.0073499988, D = 0.74448E-01 0.74448E-01 ( 0.10 s, 0.0 h) + iter 51 lrate = 0.1000000000 LL = -3.4409782229 nd = 0.0073279306, D = 0.73141E-01 0.73141E-01 ( 0.10 s, 0.0 h) + iter 52 lrate = 0.2000000000 LL = -3.4405919551 nd = 0.0072717685, D = 0.70617E-01 0.70617E-01 ( 0.10 s, 0.0 h) + iter 53 lrate = 0.3000000000 LL = -3.4400260592 nd = 0.0071975653, D = 0.67051E-01 0.67051E-01 ( 0.10 s, 0.0 h) + iter 54 lrate = 0.4000000000 LL = -3.4392902421 nd = 0.0071025916, D = 0.62693E-01 0.62693E-01 ( 0.10 s, 0.0 h) + iter 55 lrate = 0.5000000000 LL = -3.4383944792 nd = 0.0069838003, D = 0.57833E-01 0.57833E-01 ( 0.10 s, 0.0 h) + iter 56 lrate = 0.6000000000 LL = -3.4373514586 nd = 0.0068564048, D = 0.52779E-01 0.52779E-01 ( 0.10 s, 0.0 h) + iter 57 lrate = 0.7000000000 LL = -3.4361733721 nd = 0.0067176434, D = 0.47812E-01 0.47812E-01 ( 0.11 s, 0.0 h) + iter 58 lrate = 0.8000000000 LL = -3.4348773500 nd = 0.0065306037, D = 0.43152E-01 0.43152E-01 ( 0.10 s, 0.0 h) + iter 59 lrate = 0.9000000000 LL = -3.4334862033 nd = 0.0063144473, D = 0.38858E-01 0.38858E-01 ( 0.10 s, 0.0 h) + iter 60 lrate = 1.0000000000 LL = -3.4320290718 nd = 0.0060694050, D = 0.35007E-01 0.35007E-01 ( 0.10 s, 0.0 h) + iter 61 lrate = 1.0000000000 LL = -3.4306539336 nd = 0.0058165467, D = 0.31848E-01 0.31848E-01 ( 0.11 s, 0.0 h) + iter 62 lrate = 1.0000000000 LL = -3.4293727997 nd = 0.0055406777, D = 0.29288E-01 0.29288E-01 ( 0.10 s, 0.0 h) + iter 63 lrate = 1.0000000000 LL = -3.4281948781 nd = 0.0052692527, D = 0.27250E-01 0.27250E-01 ( 0.10 s, 0.0 h) + iter 64 lrate = 1.0000000000 LL = -3.4271211832 nd = 0.0050272799, D = 0.25745E-01 0.25745E-01 ( 0.10 s, 0.0 h) + iter 65 lrate = 1.0000000000 LL = -3.4261411718 nd = 0.0048073579, D = 0.24812E-01 0.24812E-01 ( 0.10 s, 0.0 h) + iter 66 lrate = 1.0000000000 LL = -3.4252466155 nd = 0.0046179247, D = 0.24345E-01 0.24345E-01 ( 0.10 s, 0.0 h) + iter 67 lrate = 1.0000000000 LL = -3.4244237228 nd = 0.0044367521, D = 0.24187E-01 0.24187E-01 ( 0.10 s, 0.0 h) + iter 68 lrate = 1.0000000000 LL = -3.4236656099 nd = 0.0042766153, D = 0.24212E-01 0.24212E-01 ( 0.10 s, 0.0 h) + iter 69 lrate = 1.0000000000 LL = -3.4229613447 nd = 0.0041429572, D = 0.24322E-01 0.24322E-01 ( 0.10 s, 0.0 h) + iter 70 lrate = 1.0000000000 LL = -3.4223013447 nd = 0.0040280167, D = 0.24478E-01 0.24478E-01 ( 0.10 s, 0.0 h) + iter 71 lrate = 1.0000000000 LL = -3.4216799403 nd = 0.0039220625, D = 0.24654E-01 0.24654E-01 ( 0.10 s, 0.0 h) + iter 72 lrate = 1.0000000000 LL = -3.4210881340 nd = 0.0038434466, D = 0.24854E-01 0.24854E-01 ( 0.10 s, 0.0 h) + iter 73 lrate = 1.0000000000 LL = -3.4205200068 nd = 0.0037706961, D = 0.25099E-01 0.25099E-01 ( 0.10 s, 0.0 h) + iter 74 lrate = 1.0000000000 LL = -3.4199694700 nd = 0.0037100029, D = 0.25387E-01 0.25387E-01 ( 0.10 s, 0.0 h) + iter 75 lrate = 1.0000000000 LL = -3.4194343331 nd = 0.0036479584, D = 0.25686E-01 0.25686E-01 ( 0.10 s, 0.0 h) + iter 76 lrate = 1.0000000000 LL = -3.4189134918 nd = 0.0035920222, D = 0.26006E-01 0.26006E-01 ( 0.10 s, 0.0 h) + iter 77 lrate = 1.0000000000 LL = -3.4184066190 nd = 0.0035339680, D = 0.26356E-01 0.26356E-01 ( 0.10 s, 0.0 h) + iter 78 lrate = 1.0000000000 LL = -3.4179137938 nd = 0.0034747481, D = 0.26715E-01 0.26715E-01 ( 0.10 s, 0.0 h) + iter 79 lrate = 1.0000000000 LL = -3.4174367980 nd = 0.0034084627, D = 0.27097E-01 0.27097E-01 ( 0.10 s, 0.0 h) + iter 80 lrate = 1.0000000000 LL = -3.4169767547 nd = 0.0033321218, D = 0.27486E-01 0.27486E-01 ( 0.10 s, 0.0 h) + iter 81 lrate = 1.0000000000 LL = -3.4165384642 nd = 0.0032441994, D = 0.27901E-01 0.27901E-01 ( 0.11 s, 0.0 h) + iter 82 lrate = 1.0000000000 LL = -3.4161213948 nd = 0.0031523169, D = 0.28348E-01 0.28348E-01 ( 0.10 s, 0.0 h) + iter 83 lrate = 1.0000000000 LL = -3.4157282834 nd = 0.0030511007, D = 0.28801E-01 0.28801E-01 ( 0.10 s, 0.0 h) + iter 84 lrate = 1.0000000000 LL = -3.4153589168 nd = 0.0029613584, D = 0.29281E-01 0.29281E-01 ( 0.10 s, 0.0 h) + iter 85 lrate = 1.0000000000 LL = -3.4150109305 nd = 0.0028842884, D = 0.29777E-01 0.29777E-01 ( 0.10 s, 0.0 h) + iter 86 lrate = 1.0000000000 LL = -3.4146806129 nd = 0.0028133041, D = 0.30284E-01 0.30284E-01 ( 0.10 s, 0.0 h) + iter 87 lrate = 1.0000000000 LL = -3.4143657476 nd = 0.0027405093, D = 0.30773E-01 0.30773E-01 ( 0.10 s, 0.0 h) + iter 88 lrate = 1.0000000000 LL = -3.4140664829 nd = 0.0026759716, D = 0.31255E-01 0.31255E-01 ( 0.10 s, 0.0 h) + iter 89 lrate = 1.0000000000 LL = -3.4137827396 nd = 0.0026172247, D = 0.31754E-01 0.31754E-01 ( 0.10 s, 0.0 h) + iter 90 lrate = 1.0000000000 LL = -3.4135099614 nd = 0.0025723970, D = 0.32216E-01 0.32216E-01 ( 0.10 s, 0.0 h) + iter 91 lrate = 1.0000000000 LL = -3.4132471327 nd = 0.0025251906, D = 0.32652E-01 0.32652E-01 ( 0.10 s, 0.0 h) + iter 92 lrate = 1.0000000000 LL = -3.4129956272 nd = 0.0024806124, D = 0.33075E-01 0.33075E-01 ( 0.10 s, 0.0 h) + iter 93 lrate = 1.0000000000 LL = -3.4127524864 nd = 0.0024369464, D = 0.33513E-01 0.33513E-01 ( 0.10 s, 0.0 h) + iter 94 lrate = 1.0000000000 LL = -3.4125183782 nd = 0.0023791588, D = 0.33946E-01 0.33946E-01 ( 0.10 s, 0.0 h) + iter 95 lrate = 1.0000000000 LL = -3.4122952276 nd = 0.0023308726, D = 0.34370E-01 0.34370E-01 ( 0.10 s, 0.0 h) + iter 96 lrate = 1.0000000000 LL = -3.4120794495 nd = 0.0022935368, D = 0.34803E-01 0.34803E-01 ( 0.10 s, 0.0 h) + iter 97 lrate = 1.0000000000 LL = -3.4118716676 nd = 0.0022663411, D = 0.35211E-01 0.35211E-01 ( 0.10 s, 0.0 h) + iter 98 lrate = 1.0000000000 LL = -3.4116682686 nd = 0.0022430245, D = 0.35585E-01 0.35585E-01 ( 0.10 s, 0.0 h) + iter 99 lrate = 1.0000000000 LL = -3.4114690851 nd = 0.0022236502, D = 0.35953E-01 0.35953E-01 ( 0.10 s, 0.0 h) + iter 100 lrate = 1.0000000000 LL = -3.4112742644 nd = 0.0022054248, D = 0.36296E-01 0.36296E-01 ( 0.10 s, 0.0 h) +... done. Execution time: 0.00 h +output directory = ./fortran_output/ diff --git a/.context/issue-351/raw/harness_run2/fortran_run/input.param b/.context/issue-351/raw/harness_run2/fortran_run/input.param new file mode 100644 index 0000000..c8f97ce --- /dev/null +++ b/.context/issue-351/raw/harness_run2/fortran_run/input.param @@ -0,0 +1,82 @@ +files ./eeglab_data.fdt +outdir ./fortran_output/ +block_size 512 +do_opt_block 0 +blk_min 256 +blk_step 256 +blk_max 1024 +num_models 1 +max_threads 1 +use_min_dll 1 +min_dll 1e-09 +use_grad_norm 1 +min_grad_norm 1e-07 +num_mix_comps 3 +pdftype 0 +max_iter 100 +num_samples 1 +data_dim 32 +field_dim 30504 +field_blocksize 1 +do_history 0 +histstep 10 +share_comps 0 +share_start 100 +comp_thresh 0.99 +share_iter 100 +lrate 0.05 +minlrate 1e-08 +mineig 1.000000e-12 +lratefact 0.5 +rholrate 0.05 +rho0 1.5 +minrho 1.0 +maxrho 2.0 +rholratefact 0.5 +kurt_start 3 +num_kurt 5 +kurt_int 1 +do_newton 1 +newt_start 50 +newt_ramp 10 +newtrate 1.0 +do_reject 0 +numrej 3 +rejsig 3.0 +rejstart 2 +rejint 3 +writestep 20 +write_nd 0 +write_LLt 1 +decwindow 1 +max_decs 3 +fix_init 0 +update_A 1 +update_c 1 +update_gm 1 +update_alpha 1 +update_mu 1 +update_beta 1 +invsigmax 100.0 +invsigmin 0.0 +do_rho 1 +load_rej 0 +load_W 0 +load_c 0 +load_gm 0 +load_alpha 0 +load_mu 0 +load_beta 0 +load_rho 0 +load_comp_list 0 +do_mean 1 +do_sphere 1 +doPCA 1 +pcakeep 32 +pcadb 30.0 +byte_size 4 +doscaling 1 +scalestep 1 +num_comps 32 +do_approx_sphere 1 +seed 42 diff --git a/.context/issue-351/raw/harness_run2/parity_summary.md b/.context/issue-351/raw/harness_run2/parity_summary.md new file mode 100644 index 0000000..2681d7c --- /dev/null +++ b/.context/issue-351/raw/harness_run2/parity_summary.md @@ -0,0 +1,6 @@ +| backend | precision | iterations | final LL | abs. LL difference | mean matched corr | min matched corr | Amari distance | runtime (s) | +|---|---|---:|---:|---:|---:|---:|---:|---:| +| Fortran (reference) | float64 | 100 | -3.411274 | | | | | 10.2 | +| PyTorch | float64 | 100 | -3.411003 | 0.000271 | 0.9991 | 0.9918 | 0.0038 | 18.1 | +| NumPy | float64 | 100 | -3.411003 | 0.000272 | 0.9991 | 0.9917 | 0.0038 | 32.5 | +| MLX | float32 | 100 | -3.410998 | 0.000276 | 0.9991 | 0.9917 | 0.0038 | 3.0 | diff --git a/.context/issue-351/raw/harness_run2/stdout.log b/.context/issue-351/raw/harness_run2/stdout.log new file mode 100644 index 0000000..4f3d853 --- /dev/null +++ b/.context/issue-351/raw/harness_run2/stdout.log @@ -0,0 +1,240 @@ +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. +Validation with seed=42, max_iter=100 +Output directory: .context/issue-351/raw/harness_run2 +Loaded data: (32, 30504) +Running Fortran AMICA... +Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 +AMICA uses float64 for Fortran parity; MPS lacks float64 support, so falling back to CPU. Pass dtype=torch.float32 with device='mps' to run on MPS. + +Starting AMICA fitting... +Starting optimization... + +====================================================================== +VALIDATION REPORT: Fortran vs PyTorch AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + PyTorch Final LL: -3.411003 + LL Ratio (PyTorch/Fortran): 0.9999 + LL Absolute Difference: 0.000271 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + PyTorch Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9918 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0432 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== + +Report saved to: .context/issue-351/raw/harness_run2/validation_report.txt +Running NumPy AMICA (legacy reference backend)... + +AMICA: 0%| | 0/100 [00:000.9) + + Mixing Matrix Relative Error: 0.0432 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== + +Report saved to: .context/issue-351/raw/harness_run2/validation_report_numpy.txt +Running MLX AMICA (Apple-GPU float32 backend)... +WARNING: params.json settings with no AMICAMLXNG equivalent are ignored (MLX uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 30504 samples +Models: 1, Mixture components: 3 + + +====================================================================== +VALIDATION REPORT: Fortran vs MLX AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + MLX Final LL: -3.410998 + LL Ratio (MLX/Fortran): 0.9999 + LL Absolute Difference: 0.000276 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + MLX Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9917 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0433 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== + +Report saved to: .context/issue-351/raw/harness_run2/validation_report_mlx.txt + +PARITY SUMMARY (seed=42, max_iter=100): +| backend | precision | iterations | final LL | abs. LL difference | mean matched corr | min matched corr | Amari distance | runtime (s) | +|---|---|---:|---:|---:|---:|---:|---:|---:| +| Fortran (reference) | float64 | 100 | -3.411274 | | | | | 10.2 | +| PyTorch | float64 | 100 | -3.411003 | 0.000271 | 0.9991 | 0.9918 | 0.0038 | 18.1 | +| NumPy | float64 | 100 | -3.411003 | 0.000272 | 0.9991 | 0.9917 | 0.0038 | 32.5 | +| MLX | float32 | 100 | -3.410998 | 0.000276 | 0.9991 | 0.9917 | 0.0038 | 3.0 | + +Summary saved to: .context/issue-351/raw/harness_run2/parity_summary.md +uv run python validate_implementations.py --backend all --fortran-binary $R 68.21s user 30.74s system 152% cpu 1:05.08 total diff --git a/.context/issue-351/raw/harness_run2/validation_report.txt b/.context/issue-351/raw/harness_run2/validation_report.txt new file mode 100644 index 0000000..30026a1 --- /dev/null +++ b/.context/issue-351/raw/harness_run2/validation_report.txt @@ -0,0 +1,33 @@ + +====================================================================== +VALIDATION REPORT: Fortran vs PyTorch AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + PyTorch Final LL: -3.411003 + LL Ratio (PyTorch/Fortran): 0.9999 + LL Absolute Difference: 0.000271 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + PyTorch Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9918 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0432 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== diff --git a/.context/issue-351/raw/harness_run2/validation_report_mlx.txt b/.context/issue-351/raw/harness_run2/validation_report_mlx.txt new file mode 100644 index 0000000..4f46450 --- /dev/null +++ b/.context/issue-351/raw/harness_run2/validation_report_mlx.txt @@ -0,0 +1,33 @@ + +====================================================================== +VALIDATION REPORT: Fortran vs MLX AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + MLX Final LL: -3.410998 + LL Ratio (MLX/Fortran): 0.9999 + LL Absolute Difference: 0.000276 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + MLX Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9917 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0433 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== diff --git a/.context/issue-351/raw/harness_run2/validation_report_numpy.txt b/.context/issue-351/raw/harness_run2/validation_report_numpy.txt new file mode 100644 index 0000000..f6d394c --- /dev/null +++ b/.context/issue-351/raw/harness_run2/validation_report_numpy.txt @@ -0,0 +1,33 @@ + +====================================================================== +VALIDATION REPORT: Fortran vs NumPy AMICA +====================================================================== + +1. LOG-LIKELIHOOD COMPARISON: +---------------------------------------- + Fortran Final LL: -3.4112742644 + NumPy Final LL: -3.411003 + LL Ratio (NumPy/Fortran): 0.9999 + LL Absolute Difference: 0.000272 + +2. CONVERGENCE COMPARISON: +---------------------------------------- + Fortran Iterations: 100 + NumPy Iterations: 100 + +3. COMPONENT CORRELATION: +---------------------------------------- + Mean Correlation: 0.9991 + Min Correlation: 0.9917 + Max Correlation: 1.0000 + Std Correlation: 0.0017 + ✓ Components are highly correlated (>0.9) + + Mixing Matrix Relative Error: 0.0432 + ✓ Mixing matrices are very similar (<10% error) + +4. OVERALL ASSESSMENT: +---------------------------------------- + ✓ Implementations produce comparable results + +====================================================================== diff --git a/.context/issue-351/raw/orientation_check.txt b/.context/issue-351/raw/orientation_check.txt new file mode 100644 index 0000000..168d9de --- /dev/null +++ b/.context/issue-351/raw/orientation_check.txt @@ -0,0 +1,10 @@ +root /Users/yahya/Documents/git/mlx-fc-phase15-final-parity +max |A - A.T| of the initial A: 9.821e-03 +pamica iteration-1 LL: -3.513155323725571 +binary iteration-1 LL, seed_from_torch: -3.513155323725570 (diff +8.882e-16) +binary iteration-1 LL, stored A untransposed: -3.513168802764010 (diff -1.348e-05) +root /private/tmp/claude-501/-Users-yahya-Documents-git-pamica/3b0e67f1-eae1-4864-8013-454e2363dda4/scratchpad/p15_pre +max |A - A.T| of the initial A: 9.822e-03 +pamica iteration-1 LL: -3.513128081184544 +binary iteration-1 LL, seed_from_torch: -3.513128081184544 (diff +8.882e-16) +binary iteration-1 LL, stored A untransposed: -3.513141342844886 (diff -1.326e-05) From 391885850ac8dcf44218e2de6af7a80389993fe4 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:19:54 -0700 Subject: [PATCH 04/58] Record share_comps counts and float32 agreement runs --- .context/issue-351/precision_agreement.py | 54 +++++ .../issue-351/raw/precision_agreement.json | 20 ++ .../raw/share_comps/share_comps_counts.json | 117 +++++++++ .context/issue-351/raw/share_comps/stdout.log | 140 +++++++++++ .context/issue-351/share_comps_counts.py | 225 ++++++++++++++++++ 5 files changed, 556 insertions(+) create mode 100644 .context/issue-351/precision_agreement.py create mode 100644 .context/issue-351/raw/precision_agreement.json create mode 100644 .context/issue-351/raw/share_comps/share_comps_counts.json create mode 100644 .context/issue-351/raw/share_comps/stdout.log create mode 100644 .context/issue-351/share_comps_counts.py diff --git a/.context/issue-351/precision_agreement.py b/.context/issue-351/precision_agreement.py new file mode 100644 index 0000000..b50ff3c --- /dev/null +++ b/.context/issue-351/precision_agreement.py @@ -0,0 +1,54 @@ +"""Component-level float32 agreement at a matched iteration budget (issue #351 +item 4c): MLX (float32) against PyTorch (float64) from the same start. + +Both backends draw their initialization from numpy's ``RandomState(seed)``, so +with the same seed they start from the same point up to MLX's float32 cast, and +any difference after K iterations is float32 arithmetic. The harness settings +(``sample_params.json`` through ``validate_implementations._run_wrapper_amica``) +at K = 100 (the harness budget) and 200 (the fixture budget), seed 42. + + uv run python .context/issue-351/precision_agreement.py OUT.json +""" + +from __future__ import annotations + +import importlib.util +import json +import sys +from pathlib import Path + +import numpy as np + +HERE = Path(__file__).resolve().parent +REPO = HERE.parents[1] + + +def main() -> None: + spec = importlib.util.spec_from_file_location( + "vi_351p", REPO / "validate_implementations.py" + ) + assert spec is not None and spec.loader is not None + vi = importlib.util.module_from_spec(spec) + spec.loader.exec_module(vi) + data, params = vi.load_sample_data() + out = {} + for k in (100, 200): + p = dict(params, max_iter=k) + t = vi._run_wrapper_amica("torch", data, p, 42) + m = vi._run_wrapper_amica("mlx", data, p, 42) + cmp = vi.compare_results(t, m, label="MLX") + out[str(k)] = { + "torch_final_ll": float(t["final_ll"]), + "mlx_final_ll": float(m["final_ll"]), + "abs_ll_difference": float(abs(t["final_ll"] - m["final_ll"])), + "mean_matched_corr": float(cmp["mean_correlation"]), + "min_matched_corr": float(cmp["min_correlation"]), + "amari": float(vi.amari_distance(t["W"], m["W"])), + "max_abs_W_diff": float(np.abs(t["W"] - m["W"]).max()), + } + Path(sys.argv[1]).write_text(json.dumps(out, indent=2)) + print(json.dumps(out, indent=2)) + + +if __name__ == "__main__": + main() diff --git a/.context/issue-351/raw/precision_agreement.json b/.context/issue-351/raw/precision_agreement.json new file mode 100644 index 0000000..aae206d --- /dev/null +++ b/.context/issue-351/raw/precision_agreement.json @@ -0,0 +1,20 @@ +{ + "100": { + "torch_final_ll": -3.4110031143196786, + "mlx_final_ll": -3.4109981060028076, + "abs_ll_difference": 5.0083168710024495e-06, + "mean_matched_corr": 0.9999999096496164, + "min_matched_corr": 0.9999993779271434, + "amari": 4.975071791940432e-05, + "max_abs_W_diff": 0.00044353275198191766 + }, + "200": { + "torch_final_ll": -3.401731290101124, + "mlx_final_ll": -3.401728868484497, + "abs_ll_difference": 2.4216166267798656e-06, + "mean_matched_corr": 0.9999997770650518, + "min_matched_corr": 0.9999982846224417, + "amari": 6.270096656839582e-05, + "max_abs_W_diff": 0.0006998187339538331 + } +} \ No newline at end of file diff --git a/.context/issue-351/raw/share_comps/share_comps_counts.json b/.context/issue-351/raw/share_comps/share_comps_counts.json new file mode 100644 index 0000000..227cb69 --- /dev/null +++ b/.context/issue-351/raw/share_comps/share_comps_counts.json @@ -0,0 +1,117 @@ +{ + "a": { + "share_off_final_ll": -3.3393496568371823, + "share_off_stop": "max_iter", + "share_off_newton_fallbacks": 0, + "share_on_final_ll": -3.3409951996200453, + "share_on_stop": "max_iter", + "share_on_newton_fallbacks": 0, + "merges": [ + { + "iter": 100, + "model": 0, + "source": 11, + "into_model": 1, + "into_source": 3, + "map_abs_cos": 0.9699489398459946 + } + ], + "unique_components": 63, + "groups": [ + { + "group": [ + [ + 1, + 3 + ], + [ + 0, + 11 + ] + ], + "identical": true + } + ] + }, + "b": { + "scan_at_8_thr_0.9": { + "merged": 31, + "final_ll": -3.453995960732006, + "stop": "max_iter" + }, + "scan_at_8_thr_0.95": { + "merged": 30, + "final_ll": -3.4531792987461793, + "stop": "max_iter" + }, + "scan_at_8_thr_0.99": { + "merged": 17, + "final_ll": -3.4340012191597338, + "stop": "max_iter" + }, + "scan_at_20_thr_0.9": { + "merged": 30, + "final_ll": -3.4702865291798437, + "stop": "max_iter" + }, + "scan_at_20_thr_0.95": { + "merged": 22, + "final_ll": -3.4485215414735295, + "stop": "max_iter" + }, + "scan_at_20_thr_0.99": { + "merged": 5, + "final_ll": -3.4105196773183413, + "stop": "max_iter" + } + }, + "c": { + "state_A_diff_torch_vs_ref": 5.2365930183172205e-06, + "state_LL_diff_torch_vs_ref": 1.550818593543113e-07, + "thr_0.9": { + "reference_state": 32, + "torch_state": 32, + "numpy_state": 32, + "torch_fit_scan": 32, + "same_comp_list_ref_torch_numpy_fit": [ + true, + true, + true + ] + }, + "thr_0.95": { + "reference_state": 32, + "torch_state": 32, + "numpy_state": 32, + "torch_fit_scan": 32, + "same_comp_list_ref_torch_numpy_fit": [ + true, + true, + true + ] + }, + "thr_0.99": { + "reference_state": 29, + "torch_state": 29, + "numpy_state": 29, + "torch_fit_scan": 29, + "same_comp_list_ref_torch_numpy_fit": [ + true, + true, + true + ] + } + }, + "d": { + "first_scan_merges": 28, + "gm2_after_first_scan": 0.5720240822678972, + "gm2_1_after_scan": 0.0021825430273267536, + "gm2_2_after_scan": 0.0009015369020092886, + "second_scan_stop": "max_iter", + "merges_after_second_scan": 28, + "gm2_after_second_scan": 0.000244140625, + "long_fit_stop": "nan_params", + "long_fit_iterations_recorded": 23, + "long_fit_last_iteration_index": 22 + } +} \ No newline at end of file diff --git a/.context/issue-351/raw/share_comps/stdout.log b/.context/issue-351/raw/share_comps/stdout.log new file mode 100644 index 0000000..d70f10d --- /dev/null +++ b/.context/issue-351/raw/share_comps/stdout.log @@ -0,0 +1,140 @@ +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +Starting AMICA fitting... +Starting optimization... + iter 2 lrate = 0.0500000000 LL = -3.4682954058 nd = 0.0278618498, D = 4.41736e-02 4.41736e-02 ( 1.51 s, 0.0 h) + iter 3 lrate = 0.0500000000 LL = -3.4603659507 nd = 0.0301293222, D = 7.92946e-03 7.92946e-03 ( 2.29 s, 0.0 h) + iter 4 lrate = 0.0500000000 LL = -3.4563302679 nd = 0.0361807797, D = 4.03568e-03 4.03568e-03 ( 3.08 s, 0.0 h) + iter 5 lrate = 0.0500000000 LL = -3.4524903836 nd = 0.0403887082, D = 3.83988e-03 3.83988e-03 ( 3.86 s, 0.0 h) + iter 6 lrate = 0.0500000000 LL = -3.4487996014 nd = 0.0425780782, D = 3.69078e-03 3.69078e-03 ( 4.67 s, 0.0 h) + iter 7 lrate = 0.0500000000 LL = -3.4451593881 nd = 0.0432309476, D = 3.64021e-03 3.64021e-03 ( 5.45 s, 0.0 h) + iter 8 lrate = 0.0500000000 LL = -3.4416417346 nd = 0.0430271621, D = 3.51765e-03 3.51765e-03 ( 6.26 s, 0.0 h) +Optimization finished after 8 iterations +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +keep_best is inactive under share_comps: best-iterate selection by LL is not well-defined (a merge changes the parameter count and reverting to an earlier snapshot would undo the merge), so fit() returns the last iterate. +Non-finite mu at iter 22 (a mixture component likely collapsed); stopping. +{ + "a": { + "share_off_final_ll": -3.3393496568371823, + "share_off_stop": "max_iter", + "share_off_newton_fallbacks": 0, + "share_on_final_ll": -3.3409951996200453, + "share_on_stop": "max_iter", + "share_on_newton_fallbacks": 0, + "merges": [ + { + "iter": 100, + "model": 0, + "source": 11, + "into_model": 1, + "into_source": 3, + "map_abs_cos": 0.9699489398459946 + } + ], + "unique_components": 63, + "groups": [ + { + "group": [ + [ + 1, + 3 + ], + [ + 0, + 11 + ] + ], + "identical": true + } + ] + }, + "b": { + "scan_at_8_thr_0.9": { + "merged": 31, + "final_ll": -3.453995960732006, + "stop": "max_iter" + }, + "scan_at_8_thr_0.95": { + "merged": 30, + "final_ll": -3.4531792987461793, + "stop": "max_iter" + }, + "scan_at_8_thr_0.99": { + "merged": 17, + "final_ll": -3.4340012191597338, + "stop": "max_iter" + }, + "scan_at_20_thr_0.9": { + "merged": 30, + "final_ll": -3.4702865291798437, + "stop": "max_iter" + }, + "scan_at_20_thr_0.95": { + "merged": 22, + "final_ll": -3.4485215414735295, + "stop": "max_iter" + }, + "scan_at_20_thr_0.99": { + "merged": 5, + "final_ll": -3.4105196773183413, + "stop": "max_iter" + } + }, + "c": { + "state_A_diff_torch_vs_ref": 5.2365930183172205e-06, + "state_LL_diff_torch_vs_ref": 1.550818593543113e-07, + "thr_0.9": { + "reference_state": 32, + "torch_state": 32, + "numpy_state": 32, + "torch_fit_scan": 32, + "same_comp_list_ref_torch_numpy_fit": [ + true, + true, + true + ] + }, + "thr_0.95": { + "reference_state": 32, + "torch_state": 32, + "numpy_state": 32, + "torch_fit_scan": 32, + "same_comp_list_ref_torch_numpy_fit": [ + true, + true, + true + ] + }, + "thr_0.99": { + "reference_state": 29, + "torch_state": 29, + "numpy_state": 29, + "torch_fit_scan": 29, + "same_comp_list_ref_torch_numpy_fit": [ + true, + true, + true + ] + } + }, + "d": { + "first_scan_merges": 28, + "gm2_after_first_scan": 0.5720240822678972, + "gm2_1_after_scan": 0.0021825430273267536, + "gm2_2_after_scan": 0.0009015369020092886, + "second_scan_stop": "max_iter", + "merges_after_second_scan": 28, + "gm2_after_second_scan": 0.000244140625, + "long_fit_stop": "nan_params", + "long_fit_iterations_recorded": 23, + "long_fit_last_iteration_index": 22 + } +} diff --git a/.context/issue-351/share_comps_counts.py b/.context/issue-351/share_comps_counts.py new file mode 100644 index 0000000..0f1c53f --- /dev/null +++ b/.context/issue-351/share_comps_counts.py @@ -0,0 +1,225 @@ +"""The ``share_comps`` figures of ``docs/guides/amica-differences.md`` +("Component sharing compares and ties components"), re-measured under epic +#324 (issue #351 item 6). Protocols as the page and the Phase 8 run records +(PR 342) describe them, on the bundled sample EEG: + +a. end to end: 2 models, seed 42, Newton on, 300 iterations, ``share_start`` + 100, ``share_iter`` 100, ``comp_thresh`` 0.95, PyTorch defaults otherwise; + every merge with its iteration and the |cos| of the two scalp maps, and the + final log-likelihood with sharing on and off; +b. early scans: 2 models, seed 42, PyTorch defaults, one scan at iteration 8 + or 20 (``share_iter`` 100), fit to ``share_start + 2``; merges per threshold; +c. the reference's similarity on its own early state: the binary runs 8 + iterations from pamica's seed-42 initialization (the test suite's ``_OPT`` + optimizer settings), and the reference's formula (``Spinv2 = Spinv^T Spinv``, + i.e. the scalp maps ``pinv(S) @ A``) on that state is compared with + PyTorch's and NumPy's scans of their own 8-iteration states; +d. the collapse recipe of ``test_component_rows.py`` (4096 samples, seed 23, + ``share_start`` = ``share_iter`` = 11, ``comp_thresh`` 0.9): merges at the + first scan, the second model's ``gm`` over the next iterations, and the + iteration where the fit goes non-finite. + + uv run python .context/issue-351/share_comps_counts.py OUT.json +""" + +from __future__ import annotations + +import dataclasses +import json +import sys +import tempfile +from pathlib import Path + +import numpy as np +import torch + +from pamica import AMICA_NumPy +from pamica.numpy_impl.utils import identify_shared_components +from pamica.tests.native_oracle import run_seeded_reference, seed_from_torch +from pamica.tests.test_component_rows import _COLLAPSE, _OPT, _REF_OPT, DATA_FILE +from pamica.torch_impl.core import AMICATorchNG +from pamica.torch_impl.utils import load_eeglab_data + +NW, FIELD = 32, 30504 +X = load_eeglab_data(str(DATA_FILE), data_dim=NW, field_dim=FIELD).astype(np.float64) + + +def logged(base): + """``base`` with every merge recorded: (1-based iteration, model, source, + merged-into model, source, |cos| of the two scalp maps before the scan).""" + + class Logged(base): + merge_log: list + + def _identify_shared_comps(self): + before = self.comp_list.cpu().numpy().copy() + maps = [self.get_sensor_mixing_matrix(h) for h in range(self.n_models)] + maps = [q / np.linalg.norm(q, axis=0) for q in maps] + super()._identify_shared_comps() + after = self.comp_list.cpu().numpy() + for hh in range(self.n_models): + for ii in range(self.n_channels): + if after[ii, hh] != before[ii, hh]: + tgt = after[ii, hh] + h, i = next( + (h, i) + for h in range(self.n_models) + for i in range(self.n_channels) + if before[i, h] == tgt + ) + cos = float(abs(maps[h][:, i] @ maps[hh][:, ii])) + self.merge_log.append((self.iteration + 1, h, i, hh, ii, cos)) + + return Logged + + +def part_a() -> dict: + kw = dict(n_channels=NW, n_models=2, n_mix=3, device="cpu", seed=42, do_newton=True) + share = dict(share_comps=True, share_start=100, share_iter=100, comp_thresh=0.95) + off = AMICATorchNG(**kw).fit(X, max_iter=300, verbose=False) + m = logged(AMICATorchNG)(**kw, **share) + m.merge_log = [] + m.fit(X, max_iter=300, verbose=False) + groups = [] + for g in m.shared_components(): + v = [m.get_mixing_matrix(h)[:, i] for h, i in g] + groups.append( + {"group": g, "identical": all(np.array_equal(v[0], x) for x in v[1:])} + ) + return { + "share_off_final_ll": float(off.final_ll_), + "share_off_stop": str(off.stop_reason), + "share_off_newton_fallbacks": int(off.n_newton_fallbacks), + "share_on_final_ll": float(m.final_ll_), + "share_on_stop": str(m.stop_reason), + "share_on_newton_fallbacks": int(m.n_newton_fallbacks), + "merges": [ + { + "iter": r[0], + "model": r[1], + "source": r[2], + "into_model": r[3], + "into_source": r[4], + "map_abs_cos": r[5], + } + for r in m.merge_log + ], # fmt: skip + "unique_components": int(m.comp_used.sum()), + "groups": groups, + } + + +def part_b() -> dict: + out = {} + for start in (8, 20): + for thr in (0.9, 0.95, 0.99): + m = AMICATorchNG( + NW, n_models=2, seed=42, share_comps=True, share_start=start, + share_iter=100, comp_thresh=thr, device="cpu", + ) # fmt: skip + m.fit(X, max_iter=start + 2, verbose=False) + merged = 2 * NW - len(np.unique(m.comp_list.cpu().numpy())) + out[f"scan_at_{start}_thr_{thr}"] = { + "merged": int(merged), + "final_ll": float(m.final_ll_), + "stop": str(m.stop_reason), + } + return out + + +def part_c(work: Path) -> dict: + pre = 8 + + def torch_model(**kw): + return AMICATorchNG( + n_channels=NW, n_models=2, n_mix=3, seed=42, device="cpu", + dtype=torch.float64, keep_best=False, **{**_OPT, **kw}, + ) # fmt: skip + + init = torch_model() + init._preprocess(X) + init._initialize_parameters() + default = init.comp_list.numpy().copy() + seed = dataclasses.replace(seed_from_torch(init), comp_list=default) + ref8 = run_seeded_reference( + seed, DATA_FILE, work / "c", n_samples=FIELD, max_iter=pre, num_models=2, + **{**_REF_OPT, "share_start": pre, "share_iter": 100, "share_comps": 0}, + ) # fmt: skip + t8 = torch_model(share_comps=False) + t8.fit(X, max_iter=pre, verbose=False) + with tempfile.TemporaryDirectory() as td: + n8 = AMICA_NumPy( + num_models=2, num_mix=3, max_iter=pre, seed=42, use_tqdm=False, + outdir=str(td), do_opt_block=False, writestep=10**6, **_OPT, + ) # fmt: skip + n8.fit(X) + ref_maps = np.linalg.pinv(ref8.S) @ ref8.A + out = { + "state_A_diff_torch_vs_ref": float(np.abs(t8.A.numpy().T - ref8.A).max()), + "state_LL_diff_torch_vs_ref": float( + np.abs(np.asarray(t8.ll_history) - ref8.LL).max() + ), + } + for thr in (0.9, 0.95, 0.99): + res = {} + lists = {} + for name, maps in ( + ("reference_state", ref_maps), + ("torch_state", t8._component_sensor_maps()), + ("numpy_state", n8._component_sensor_maps()), + ): + new, _ = identify_shared_components(maps, default.copy(), thr) + lists[name] = new + res[name] = int(2 * NW - len(np.unique(new))) + ts = torch_model( + share_comps=True, share_start=pre, share_iter=100, comp_thresh=thr + ) + ts.fit(X, max_iter=pre, verbose=False) + res["torch_fit_scan"] = int(2 * NW - len(np.unique(ts.comp_list.numpy()))) + res["same_comp_list_ref_torch_numpy_fit"] = [ + bool(np.array_equal(lists["reference_state"], lists["torch_state"])), + bool(np.array_equal(lists["reference_state"], lists["numpy_state"])), + bool(np.array_equal(lists["reference_state"], ts.comp_list.numpy())), + ] + out[f"thr_{thr}"] = res + return out + + +def part_d() -> dict: + Xs = X[:, :4096] + out: dict = {} + first = AMICATorchNG(**_COLLAPSE) + first.fit(Xs, max_iter=_COLLAPSE["share_start"], verbose=False) + out["first_scan_merges"] = int(2 * NW - len(np.unique(first.comp_list.numpy()))) + out["gm2_after_first_scan"] = float(first.gm.numpy()[1]) + for k in (1, 2): + m = AMICATorchNG(**_COLLAPSE) + m.fit(Xs, max_iter=_COLLAPSE["share_start"] + k, verbose=False) + out[f"gm2_{k}_after_scan"] = float(m.gm.numpy()[1]) + second = AMICATorchNG(**_COLLAPSE) + second.fit( + Xs, max_iter=_COLLAPSE["share_start"] + _COLLAPSE["share_iter"], verbose=False + ) + out["second_scan_stop"] = str(second.stop_reason) + out["merges_after_second_scan"] = int( + 2 * NW - len(np.unique(second.comp_list.numpy())) + ) + out["gm2_after_second_scan"] = float(second.gm.numpy()[1]) + long = AMICATorchNG(**_COLLAPSE) + long.fit(Xs, max_iter=40, verbose=False) + out["long_fit_stop"] = str(long.stop_reason) + out["long_fit_iterations_recorded"] = len(long.ll_history) + out["long_fit_last_iteration_index"] = int(long.iteration) + return out + + +def main() -> None: + out = Path(sys.argv[1]) + with tempfile.TemporaryDirectory() as td: + rep = {"a": part_a(), "b": part_b(), "c": part_c(Path(td)), "d": part_d()} + out.write_text(json.dumps(rep, indent=2)) + print(json.dumps(rep, indent=2)) + + +if __name__ == "__main__": + main() From df3460410d8f74a55fa2090983f20201c328e116 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:19:55 -0700 Subject: [PATCH 05/58] Update share_comps merge counts in differences guide --- docs/guides/amica-differences.md | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/docs/guides/amica-differences.md b/docs/guides/amica-differences.md index d8f1120..7b15537 100644 --- a/docs/guides/amica-differences.md +++ b/docs/guides/amica-differences.md @@ -456,19 +456,21 @@ and indexed its COLUMNS by component id, but a stored column is one sphered chan Seeded from a merged state through the reference's `load_comp_list`, the PyTorch and NumPy updates match the native binary to float64 round-off after one and three iterations, with `doscaling` on and off (`pamica/tests/test_component_rows.py`, opt-in with `AMICA_RUN_FORTRAN=1`). -On the bundled sample (2 models, 300 iterations, `share_start=100`, `comp_thresh=0.95`) -the scan merges three pairs whose maps agree (|cos| 0.956 to 0.971), -where the old metric merged three whose maps did not (|cos| 0.06, 0.35 and 0.55). +On the bundled sample (2 models, seed 42, Newton on, 300 iterations, `share_start=100`, `share_iter=100`, `comp_thresh=0.95`) +the scan at iteration 100 merges one pair whose maps agree (|cos| 0.970) and the scans at 200 and 300 merge nothing, +so the fit ends with 63 of 64 components at log-likelihood -3.3410 (-3.3394 with sharing off; measured with the finished epic #324, issue #351). +Right after this change, before the reference's iteration order (issue #339) and the later changes of epic #324, the same fit merged three such pairs (|cos| 0.956 to 0.971), +and the old metric three whose maps did not (|cos| 0.06, 0.35 and 0.55). Two consequences to know: - A scan early in a fit merges most components, and the reference's formula does the same. Both models start near the identity, so their components stay near-collinear for the first iterations - (on the sample with 2 models and seed 42, a scan at iteration 8 merges all 32 at `comp_thresh=0.95` and 24 at 0.99; - one at iteration 20 merges 24 and 5). + (on the sample with 2 models, seed 42 and PyTorch's defaults, a scan at iteration 8 merges 30 of 32 at `comp_thresh=0.95` and 17 at 0.99; + one at iteration 20 merges 22 and 5). The reference's own scan cannot show this (it never merges, above), but its similarity with `Spinv2 = Spinv^T Spinv`, applied to the binary's own state after 8 iterations from pamica's initialization, - merges exactly the pairs the PyTorch and NumPy scans merge: 32, 32 and 30 at `comp_thresh` 0.9, 0.95 and 0.99. + merges exactly the pairs the PyTorch and NumPy scans merge: 32, 32 and 29 at `comp_thresh` 0.9, 0.95 and 0.99. - A model left with few components of its own then loses its responsibility, and can end in a non-finite fit. In a short recipe (4096 samples, seed 23, `share_start=11`, `share_iter=11`, `comp_thresh=0.9`), 28 merges at iteration 11 dropped the second model's `gm` from 0.57 to 9.0e-4 within two iterations From 635650b809b9440ca265cd58c4469258bfc7e6b4 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:19:55 -0700 Subject: [PATCH 06/58] Re-state the harness rows with same-start parity --- docs/guides/validation.md | 43 +++++++++++++++++++++++++++++++-------- 1 file changed, 34 insertions(+), 9 deletions(-) diff --git a/docs/guides/validation.md b/docs/guides/validation.md index ecbc627..cdb11a4 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -22,7 +22,7 @@ Throughout, IC abbreviates independent component and LL log-likelihood. | Per-block sufficient statistics and one M-step | vs Fortran | bit-exact ($\sim\!10^{-15}$) | | Single-model solution (`do_newton=0`, $k\approx153$) | log-likelihood, component correlation vs Fortran | LL within ~0.0005 of $-3.6993$; correlation 0.998 | | Single-model solution (`do_newton=0`, bundled, $k\approx30$) | Amari distance vs Fortran | 0.006 | -| Every backend against the reference (harness defaults, bundled) | `validate_implementations.py --backend all`: PyTorch, NumPy and MLX each vs Fortran | LL within 3.2e-5; correlation 0.9992; Amari distance 0.004, for all three (measured before issue #333's `doscaling` change; see [the per-backend rows](#parity-rows-per-backend)) | +| Every backend against the reference (harness defaults, bundled) | `validate_implementations.py --backend all`: PyTorch, NumPy and MLX each vs Fortran | from independent starts: LL within 2.8e-4 (the reference's own seed-to-seed standard deviation is 2.6e-4), correlation 0.9991, Amari distance 0.004, for all three; from a shared start: LL within 1.6e-6, correlation 0.99999993 ([per-backend rows](#parity-rows-per-backend)) | | Multi-model solution | distributional similarity over 20-run ensembles | indistinguishable from Fortran's own run-to-run spread ($p = 0.96$) | | Device and precision invariance | same independent components across CPU/CUDA/MPS/MLX, float32/float64, Linux/macOS | identical (1.000) across all eight torch/MLX combinations | | Cross-backend log-likelihood | converged LL across every backend | agree to ~3 significant digits (max pairwise ~0.003) | @@ -70,11 +70,7 @@ falling back, with a warning, to the bundled macOS x86_64 `amica15mac`, which ca ### Parity rows per backend -These rows predate epic #324 Phase 7 (issue #333), -which changed `doscaling` from normalizing stored columns to normalizing components, as the reference does; -they will be re-measured before the epic merges. - -Measured on 2026-09-22 on an Apple M4 Pro (14 cores, 64 GB, macOS 27; MLX 0.32.0, PyTorch 2.12.1, NumPy 2.5.0) +Measured on 2026-09-23 with the code of epic #324 (issue #351) on an Apple M4 Pro (14 cores, 64 GB, macOS 27; MLX 0.32.0, PyTorch 2.12.1, NumPy 2.5.0) against the v0.3.3 release native engine (`amica15-macos-arm64`, SHA-256 `c8b2ac7f...`), with the harness defaults: ```bash @@ -90,9 +86,9 @@ so on a machine that fetched an earlier release the default can run an older bin | Backend | Precision | Final LL | LL difference from Fortran | Mean matched correlation | Min matched correlation | Amari distance | Runtime (s) | Expected bar | |---|---|---:|---:|---:|---:|---:|---:|---| | Fortran (reference) | float64 | -3.411274 | | | | | 10.0 | the reference | -| PyTorch (`AMICA`) | float64 | -3.411245 | 0.000029 | 0.9992 | 0.9935 | 0.0037 | 17.7 | correlation > 0.95, Amari < 0.05, LL difference < 0.005 | -| NumPy (`AMICA_NumPy`) | float64 | -3.411246 | 0.000029 | 0.9992 | 0.9934 | 0.0037 | 32.8 | the PyTorch bar, and final LL within 1e-5 of PyTorch's | -| MLX (`AMICA(backend="mlx")`) | float32 | -3.411242 | 0.000032 | 0.9992 | 0.9935 | 0.0037 | 3.4 | the PyTorch bar, and final LL within 1e-4 of PyTorch's | +| PyTorch (`AMICA`) | float64 | -3.411003 | 0.000271 | 0.9991 | 0.9918 | 0.0038 | 18.1 | correlation > 0.95, Amari < 0.05, LL difference < 0.005 | +| NumPy (`AMICA_NumPy`) | float64 | -3.411003 | 0.000272 | 0.9991 | 0.9917 | 0.0038 | 32.6 | the PyTorch bar, and final LL within 1e-5 of PyTorch's | +| MLX (`AMICA(backend="mlx")`) | float32 | -3.410998 | 0.000276 | 0.9991 | 0.9917 | 0.0038 | 3.0 | the PyTorch bar, and final LL within 1e-4 of PyTorch's | Every backend meets its bar. All four runs stop at the 100-iteration budget, so the rows compare matched trajectories rather than converged optima; @@ -102,6 +98,35 @@ MLX computes in float32 (about seven significant digits per operation), so its b it lands within about five significant digits of the float64 likelihood, which is float32 consistency, not float64 parity. Runtime is one run's wall-clock time for the fit alone and varies by about a third between runs on the same host; the reference's includes process start-up and is single-threaded. +Epic #324 left the runtimes unchanged: the code before it (e38aa11), run in the same session, took 10.1, 17.9, 32.5 and 3.2 seconds. + +**The log-likelihood difference in these rows is set by the two starting points, not by the update rule.** +The harness starts each side from its own draw: numpy's `RandomState(42)` for pamica, gfortran's generator seeded with 42 for the reference. +After 100 iterations the final log-likelihood still depends on where a fit started. +Over eight seeds, the reference's own final log-likelihood has a standard deviation of 2.6e-4 and a range of 8.0e-4 (pamica's: 2.7e-4 and 8.0e-4), +and over the 64 pairs of a pamica start and a reference start the median difference is 3.5e-4 (range 1.7e-5 to 8.2e-4). +The 2.7e-4 in the table is one draw from that spread. +Before epic #324 the same run showed 2.9e-5, which was a cancellation for this one pair of starts, not tighter parity: +from a shared start, the code before the epic lagged the reference by 2.4e-4 after 100 iterations, and that lag happened to offset the difference between the two starts. + +The update rule itself is compared from a shared start: +pamica's seed-42 initialization is written into the reference's `load_*` files, and both sides run the harness settings for 100 iterations, the reference on one thread +(`.context/issue-351/harness_gap.py`). + +| Code | LL difference | Mean matched correlation | Amari distance | +|---|---:|---:|---:| +| before epic #324 (e38aa11) | 2.4e-4 | 0.99999 | 5.8e-4 | +| epic #324 | 1.6e-6 | 0.99999993 | 3.9e-5 | + +The earlier row starts from that code's own initialization, which predates the component-row layout (issue #334) and the normalized initial mixing matrix (issue #341); +from each code's seeded state, the reference's first-iteration log-likelihood matches pamica's to 9e-16, so the state was written in the orientation the reference reads. +Against the bundled `amicaout` output (200 reference iterations with the `input.param` settings, from its own unseeded start), +the three backends are within 1.3e-4 to 1.4e-4 in log-likelihood, with mean matched correlation 0.9983 (minimum 0.982 to 0.983) and Amari distance 4.8e-3. + +The float32 MLX backend and the float64 PyTorch backend draw their start from the same generator, so they can be compared from the same start directly. +With the harness settings, after 100 iterations they differ by 5.0e-6 in log-likelihood, with mean matched correlation 0.99999991 (minimum 0.9999994) and Amari distance 5.0e-5; +after 200 iterations by 2.4e-6, 0.9999998 and 6.3e-5 (`.context/issue-351/precision_agreement.py`). + The same bars are pinned by `test_backend_meets_its_parity_bar_against_fortran` in `pamica/tests/test_fortran_param_forwarding.py`, which runs when `AMICA_RUN_FORTRAN=1` is set (as the weekly macOS job does). From dd7d846b8126b9373d336e50faed2c7a77a8161e Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:24:25 -0700 Subject: [PATCH 07/58] Add an MLX float32 option to the Newton seed study --- .context/issue-351/newton_seeds.py | 35 ++++++++++++++++++++++++------ 1 file changed, 28 insertions(+), 7 deletions(-) diff --git a/.context/issue-351/newton_seeds.py b/.context/issue-351/newton_seeds.py index 13831d6..a32a8d2 100644 --- a/.context/issue-351/newton_seeds.py +++ b/.context/issue-351/newton_seeds.py @@ -105,11 +105,21 @@ def _initialize_parameters(self): self.c = torch.from_numpy(st["c"]).to(dev, dt) self._update_unmixing_matrices() - cls = FixInitNG if fixinit else AMICATorchNG - m = cls( - n_channels=nw, n_models=1, seed=0 if fixinit else seed, device=device, - dtype=torch.float64, **PAMICA_KW, - ) # fmt: skip + if device == "mlx": + # Supplementary float32 run (not part of the #145 protocol): the MLX + # backend with the same keywords and the same drawn start as the + # float64 PyTorch fit of this seed. + if fixinit: + raise SystemExit("--fixinit is PyTorch-only") + from pamica.mlx_impl import AMICAMLXNG + + m = AMICAMLXNG(n_channels=nw, n_models=1, seed=seed, **PAMICA_KW) + else: + cls = FixInitNG if fixinit else AMICATorchNG + m = cls( + n_channels=nw, n_models=1, seed=0 if fixinit else seed, device=device, + dtype=torch.float64, **PAMICA_KW, + ) # fmt: skip t0 = time.time() m.fit(data, max_iter=max_iter, verbose=False) dt = time.time() - t0 @@ -212,7 +222,9 @@ def compare(out_dir: Path) -> dict: "runs": {k: {"final_ll": float(v["final_ll"])} for k, v in runs.items()} } fort = sorted(k for k in Wt if k.startswith("fortran_seed")) - pam = sorted(k for k in Wt if k.startswith("pamica_seed")) + pam = sorted( + k for k in Wt if k.startswith("pamica_seed") and not k.endswith("_mlx") + ) pairs = {} for a, b in itertools.combinations(fort, 2): pairs[f"{a} vs {b}"] = summ(matched(Wt[a], Wt[b])) @@ -231,6 +243,13 @@ def compare(out_dir: Path) -> dict: ) for a in pam: pairs[f"pamica_fixinit vs {a}"] = summ(matched(Wt["pamica_fixinit"], Wt[a])) + for k in sorted(Wt): + if k.endswith("_mlx") and k[: -len("_mlx")] in Wt: + pairs[f"{k} vs {k[: -len('_mlx')]}"] = summ( + matched(Wt[k], Wt[k[: -len("_mlx")]]) + ) + for b in fort: + pairs[f"{k} vs {b}"] = summ(matched(Wt[k], Wt[b])) report["pairs"] = pairs for k, v in runs.items(): extra = { @@ -255,7 +274,7 @@ def main() -> None: p.add_argument("--data", type=Path) p.add_argument("--out-dir", type=Path, required=True) p.add_argument("--threads", type=int, default=10) - p.add_argument("--device", default="cuda") + p.add_argument("--device", default="cuda", help="cuda, cpu, or mlx (float32)") # Smoke-test knobs only; the protocol is the full recording at 2000 iterations. p.add_argument("--max-iter", type=int, default=MAX_ITER) p.add_argument("--frames", type=int, default=None) @@ -270,6 +289,8 @@ def main() -> None: if a.frames: data = data[:, : a.frames] tag = "fixinit" if a.fixinit else f"seed{a.seed}" + if a.device == "mlx": + tag += "_mlx" if a.cmd == "pamica": res = run_pamica(data, a.seed, a.fixinit, a.device, a.max_iter) else: From 8f528be212ea5e206d3f651fd9f7610c3a420185 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:24:26 -0700 Subject: [PATCH 08/58] Mark the issue-27 and issue-51 records as pre-epic --- .context/issue-27/multimodel_distributional_equivalence.md | 7 +++++++ .context/issue-51/best_iterate_safeguard.md | 6 ++++++ 2 files changed, 13 insertions(+) diff --git a/.context/issue-27/multimodel_distributional_equivalence.md b/.context/issue-27/multimodel_distributional_equivalence.md index 01ef0b3..4f9f222 100644 --- a/.context/issue-27/multimodel_distributional_equivalence.md +++ b/.context/issue-27/multimodel_distributional_equivalence.md @@ -1,5 +1,12 @@ # Multi-model AMICA parity: distributional equivalence to Fortran (issue #27) +> **Historical record.** These ensembles predate epic #324, which changed every +> backend's default trajectory (issues #333, #335, #339, #341, #344, #345). +> The re-measured study under the finished epic, with the same protocol against +> the pinned v0.3.3 native binary, is in `.context/issue-351/findings.md` +> (script `.context/issue-351/multimodel_ensemble.py`, which reuses this +> directory's analysis and figure code). + **Bottom line.** For multi-model AMICA (`n_models > 1`), the natural-gradient PyTorch backend (`AMICATorchNG`) is validated against the Fortran reference at the level that is actually well-posed: its **ensemble of solutions is diff --git a/.context/issue-51/best_iterate_safeguard.md b/.context/issue-51/best_iterate_safeguard.md index f2a3fef..906b599 100644 --- a/.context/issue-51/best_iterate_safeguard.md +++ b/.context/issue-51/best_iterate_safeguard.md @@ -1,5 +1,11 @@ # Multi-model NG log-likelihood: best-iterate safeguard (issue #51) +> **Historical record.** These figures predate epic #324, which changed every +> backend's default trajectory. The re-measured `keep_best` ensemble (seeded, +> against the pinned v0.3.3 native binary) is in `.context/issue-351/findings.md` +> (script `.context/issue-351/keep_best_ensemble.py`) and in ADR 0003's +> "Re-measured after epic #324" section. + **Bottom line.** The multi-model NG log-likelihood was ~0.02 lower and ~13x more variable than Fortran because `AMICATorchNG.fit` returned the *last* EM iterate under a deliberately non-monotone learning-rate schedule. Returning the *best* From 3d54d7eee5c7eea564f9ad1df071167033337a56 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:24:27 -0700 Subject: [PATCH 09/58] Update the harness figures in AGENTS and progress summary --- .context/progress_summary.md | 6 ++++-- AGENTS.md | 7 ++++--- 2 files changed, 8 insertions(+), 5 deletions(-) diff --git a/.context/progress_summary.md b/.context/progress_summary.md index 7e6a5ee..77afab5 100644 --- a/.context/progress_summary.md +++ b/.context/progress_summary.md @@ -74,8 +74,10 @@ what remains as of the v0.1.0 preparation. - Validation harness (`validate_implementations.py --backend {torch,numpy,mlx}`, a comma-separated list, or `all`; default `torch`, whose report is unchanged) runs each backend against one Fortran reference run with the same settings and matches components via the Hungarian algorithm, on real - sample EEG (#315). All three meet the Fortran bar on the bundled sample (LL within 3.2e-5, - correlation 0.9992, Amari 0.004; rows and bars in `docs/guides/validation.md`), pinned by the + sample EEG (#315). All three meet the Fortran bar on the bundled sample (re-measured under epic + #324 in #351: LL within 2.8e-4, correlation 0.9991, Amari 0.004 from independent starts, inside the + reference's own seed-to-seed LL sd of 2.6e-4; from a shared start LL within 1.6e-6; rows and bars + in `docs/guides/validation.md`, run records in `.context/issue-351/`), pinned by the `AMICA_RUN_FORTRAN`-gated test in `test_fortran_param_forwarding.py`. ## Remaining before / around v0.1.0 diff --git a/AGENTS.md b/AGENTS.md index 5650fb7..ef790a6 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -115,9 +115,10 @@ have no float64). - `validate_implementations.py --backend {torch,numpy,mlx}` (a comma-separated list, or `all`; default `torch`, whose report is unchanged) runs each backend against one Fortran reference run with the same settings and matches components via the Hungarian algorithm (#315). All three meet the Fortran bar on - the bundled sample (LL within 3.2e-5, correlation 0.9992, Amari 0.004; rows and bars in - `docs/guides/validation.md`), pinned by the `AMICA_RUN_FORTRAN`-gated test in - `test_fortran_param_forwarding.py`. + the bundled sample (re-measured under epic #324 in #351: LL within 2.8e-4, correlation 0.9991, Amari + 0.004 from independent starts, where the reference's own seed-to-seed LL sd is 2.6e-4; from a shared + start LL within 1.6e-6, correlation 0.99999993; rows and bars in `docs/guides/validation.md`), pinned + by the `AMICA_RUN_FORTRAN`-gated test in `test_fortran_param_forwarding.py`. - Newton and exact-EM updates are implemented in `AMICATorchNG` and the legacy NumPy `numpy_impl/core.py` (both Fortran-faithful). Adaptive PDF (#26) is DONE (all five `pdftype` families + ext-Infomax switcher); full multi-model matching (#27) is validated by distributional equivalence. From e4d0563b8acfd021c1c8026dd1ae1a4d4b37ab46 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:24:27 -0700 Subject: [PATCH 10/58] Add ensemble scripts and dimsweep LL records --- .context/issue-351/keep_best_ensemble.py | 226 ++++++++++++++++++ .context/issue-351/multimodel_ensemble.py | 147 ++++++++++++ .../raw/dimsweep/dimsweep_mac_ll.json | 127 ++++++++++ .../raw/dimsweep/dimsweep_mac_ll.log | 15 ++ 4 files changed, 515 insertions(+) create mode 100644 .context/issue-351/keep_best_ensemble.py create mode 100644 .context/issue-351/multimodel_ensemble.py create mode 100644 .context/issue-351/raw/dimsweep/dimsweep_mac_ll.json create mode 100644 .context/issue-351/raw/dimsweep/dimsweep_mac_ll.log diff --git a/.context/issue-351/keep_best_ensemble.py b/.context/issue-351/keep_best_ensemble.py new file mode 100644 index 0000000..5246ab5 --- /dev/null +++ b/.context/issue-351/keep_best_ensemble.py @@ -0,0 +1,226 @@ +"""Seeded multi-model log-likelihood ensemble against the pinned binary +(issue #351 items 3 and 5): ADR 0003's ``keep_best`` figures and the paper's +"convergence speed" explanation, re-measured under epic #324. + +Protocol of ``.context/issue-51/ensemble_ll.py`` (ADR 0003): the bundled +sample EEG, ``n_models=2``, three mixtures, the reference's ``input.param`` +schedule (``lrate`` 0.05, Newton from iteration 50, ``newtrate`` 1.0, block +size 512), N = 20 fits per implementation, pamica seeds 0-19 on +``AMICATorchNG`` with the #51 keyword set. Changes, each recorded in +``findings.md``: + +* the reference is the pinned v0.3.3 native binary through ``AMICANative``, + seeded 0-19 and single-threaded, so every run is reproducible (#51 used the + clock-seeded bundled ``amica15mac``); +* each fit runs the longest budget (300 iterations) once, and the 100- and + 200-iteration figures are read from the prefix of its trajectory: a fit's + iterations do not depend on ``max_iter``, and ``verify`` checks that on the + first seeds (separate 100-iteration fits with ``keep_best`` on and off give + exactly the prefix's values, on both sides). + +At a budget of K iterations, "return-last" is ``ll_history[K-1]`` (the +likelihood ``keep_best=False`` reports) and ``keep_best`` is the best of the +first K (restored when it beats the last by more than ``_KEEP_BEST_TOL``). + + uv run python .context/issue-351/keep_best_ensemble.py run OUT.npz [N] + uv run python .context/issue-351/keep_best_ensemble.py verify OUT.json [n] + uv run python .context/issue-351/keep_best_ensemble.py report OUT.npz +""" + +from __future__ import annotations + +import json +import sys +import time +from pathlib import Path + +import numpy as np +from scipy import stats + +HERE = Path(__file__).resolve().parent +REPO = HERE.parents[1] +FDT = REPO / "pamica/sample_data/eeglab_data.fdt" +NW, FIELD = 32, 30504 +BUDGETS = (100, 200, 300) +DELTA_LL = 0.01 # the #51 TOST margin on the mean LL + + +def load_data() -> np.ndarray: + from pamica.torch_impl.utils import load_eeglab_data + + return load_eeglab_data(str(FDT), data_dim=NW, field_dim=FIELD).astype(np.float64) + + +def run_fortran(data: np.ndarray, seed: int, max_iter: int) -> np.ndarray: + from pamica import AMICANative + from pamica.native import resolver + + eng = AMICANative( + binary=resolver.resolve("v0.3.3"), threads=1, max_threads=1, + timeout=3600, n_models=2, n_mix=3, max_iter=max_iter, seed=seed, + ) # fmt: skip + eng.fit(data) + assert eng.output_ is not None + ll = np.asarray(eng.output_.LL, dtype=np.float64) + return ll[ll != 0] + + +def run_ng(data: np.ndarray, seed: int, max_iter: int, keep_best: bool = True): + from pamica.torch_impl import AMICATorchNG + + ng = AMICATorchNG( + n_channels=NW, n_models=2, n_mix=3, block_size=512, lrate=0.05, minlrate=1e-8, + lratefact=0.5, maxdecs=3, do_newton=True, newt_start=50, newt_ramp=10, + newtrate=1.0, rho0=1.5, minrho=1.0, maxrho=2.0, rholrate=0.05, + rholratefact=0.5, invsigmin=1e-8, invsigmax=100.0, doscaling=True, + scalestep=1, seed=seed, device="cpu", keep_best=keep_best, + ) # fmt: skip + ng.fit(data, max_iter=max_iter, verbose=False) + return ng + + +def at_budget(hist: np.ndarray, k: int, tol: float) -> tuple[float, float, bool]: + """(return-last, keep_best, restored) at a budget of ``k`` iterations.""" + h = hist[:k] + last, best = float(h[-1]), float(h.max()) + restored = best - last > tol + return last, (best if restored else last), restored + + +def cmd_run(out: Path, n: int) -> None: + from pamica.torch_impl.core import _KEEP_BEST_TOL + + data = load_data() + kmax = max(BUDGETS) + F_hist = np.full((n, kmax), np.nan) + G_hist = np.full((n, kmax), np.nan) + G_final = np.full(n, np.nan) + G_stop, G_fallbacks = [], [] + t0 = time.time() + for k in range(n): + f = run_fortran(data, k, kmax) + F_hist[k, : f.size] = f + ng = run_ng(data, k, kmax) + h = np.asarray(ng.ll_history, dtype=np.float64) + G_hist[k, : h.size] = h + G_final[k] = ng.final_ll_ + G_stop.append(str(ng.stop_reason)) + G_fallbacks.append(int(ng.n_newton_fallbacks)) + print( + f"seed {k}: Fortran LL[{f.size}]={f[-1]:.4f} NG iters={h.size} " + f"last={h[-1]:.4f} final={ng.final_ll_:.4f} stop={ng.stop_reason} " + f"fallbacks={ng.n_newton_fallbacks} ({time.time() - t0:.0f}s)", + flush=True, + ) + np.savez( + out, F_hist=F_hist, G_hist=G_hist, G_final=G_final, + G_stop=np.array(G_stop), G_fallbacks=np.array(G_fallbacks), + keep_best_tol=_KEEP_BEST_TOL, budgets=np.array(BUDGETS), + ) # fmt: skip + cmd_report(out) + + +def cmd_verify(out: Path, n: int) -> None: + """Separate 100-iteration fits equal the prefix of a 300-iteration fit.""" + from pamica.torch_impl.core import _KEEP_BEST_TOL + + data = load_data() + rows = [] + for k in range(n): + f300 = run_fortran(data, k, 300) + f100 = run_fortran(data, k, 100) + g300 = np.asarray(run_ng(data, k, 300).ll_history) + g100_on = run_ng(data, k, 100, keep_best=True) + g100_off = run_ng(data, k, 100, keep_best=False) + last, kb, restored = at_budget(g300, 100, _KEEP_BEST_TOL) + rows.append( + { + "seed": k, + "fortran_ll100_separate_minus_prefix": float(f100[-1] - f300[99]), + "ng_history_prefix_max_abs_diff": float( + np.abs(np.asarray(g100_on.ll_history) - g300[:100]).max() + ), + "ng_keep_best_off_final_minus_prefix_last": float( + g100_off.final_ll_ - last + ), + "ng_keep_best_on_final_minus_prefix_best": float( + g100_on.final_ll_ - kb + ), + "restored_at_100": bool(restored), + } + ) + print(rows[-1], flush=True) + out.write_text(json.dumps(rows, indent=2)) + + +def _tost(F: np.ndarray, G: np.ndarray) -> float: + diff = G.mean() - F.mean() + se = np.sqrt(G.var(ddof=1) / G.size + F.var(ddof=1) / F.size) + return float( + max( + stats.norm.sf((diff + DELTA_LL) / se), + stats.norm.cdf((diff - DELTA_LL) / se), + ) + ) + + +def cmd_report(out: Path) -> dict: + d = np.load(out) + F_hist, G_hist, tol = d["F_hist"], d["G_hist"], float(d["keep_best_tol"]) + n = F_hist.shape[0] + rep: dict = {"n": n, "keep_best_tol": tol, "budgets": {}} + for K in BUDGETS: + F = np.array([F_hist[i, :K][~np.isnan(F_hist[i, :K])][-1] for i in range(n)]) + last, best, restored = [], [], [] + for i in range(n): + h = G_hist[i][~np.isnan(G_hist[i])] + a, b, r = at_budget(h, min(K, h.size), tol) + last.append(a) + best.append(b) + restored.append(r) + G_last, G_best = np.array(last), np.array(best) + entry = { + "fortran_mean": float(F.mean()), + "fortran_sd": float(F.std()), + "return_last_mean": float(G_last.mean()), + "return_last_sd": float(G_last.std()), + "keep_best_mean": float(G_best.mean()), + "keep_best_sd": float(G_best.std()), + "sd_ratio_return_last": float(G_last.std() / F.std()), + "sd_ratio_keep_best": float(G_best.std() / F.std()), + "gap_return_last": float(G_last.mean() - F.mean()), + "gap_keep_best": float(G_best.mean() - F.mean()), + "ks_p_keep_best": float(stats.ks_2samp(G_best, F).pvalue), + "ks_p_return_last": float(stats.ks_2samp(G_last, F).pvalue), + "tost_p_keep_best": _tost(F, G_best), + "n_restored": int(np.sum(restored)), + "restored_seeds": [int(i) for i in np.flatnonzero(restored)], + "max_restore_gain": float((G_best - G_last).max()), + } + rep["budgets"][str(K)] = entry + F100 = np.array([F_hist[i, 99] for i in range(n)]) + rep["keep_best_gap_to_fortran_at_100"] = { + str(K): rep["budgets"][str(K)]["keep_best_mean"] - float(F100.mean()) + for K in BUDGETS + } + rep["ng_stop_reasons"] = sorted(set(d["G_stop"].tolist())) + rep["ng_newton_fallbacks_total"] = int(d["G_fallbacks"].sum()) + out.with_suffix(".json").write_text(json.dumps(rep, indent=2)) + print(json.dumps(rep, indent=2)) + return rep + + +def main() -> None: + cmd, out = sys.argv[1], Path(sys.argv[2]) + if cmd == "run": + cmd_run(out, int(sys.argv[3]) if len(sys.argv) > 3 else 20) + elif cmd == "verify": + cmd_verify(out, int(sys.argv[3]) if len(sys.argv) > 3 else 2) + elif cmd == "report": + cmd_report(out) + else: + raise SystemExit(f"unknown command {cmd!r}") + + +if __name__ == "__main__": + main() diff --git a/.context/issue-351/multimodel_ensemble.py b/.context/issue-351/multimodel_ensemble.py new file mode 100644 index 0000000..85c273f --- /dev/null +++ b/.context/issue-351/multimodel_ensemble.py @@ -0,0 +1,147 @@ +"""Multi-model distributional-equivalence study (issue #27), re-run under epic +#324 (issue #351 item 3). Same shape as ``.context/issue-27/multimodel_ensemble.py`` +and ``amari_distance.py``, whose analysis functions and figure it reuses: +N = 20 reference and N = 20 pamica fits of the bundled sample EEG +(``n_models=2``, three mixtures, 100 iterations, Newton from iteration 50), +compared by the within-Fortran, within-pamica and between distributions of the +Hungarian-matched correlation and the Amari distance, with the run-level +permutation test and a Kolmogorov-Smirnov test on the final log-likelihoods. + +The fits are ``benchmarks/reproduce_table1.py``'s bundled-tier ensemble (so the +paper's Table 1 rows and the figure come from the same 40 fits): the pinned +v0.3.3 native binary through ``AMICANative`` (clock-seeded, as the #27 +reference runs were) and ``AMICA`` seeds 1-20 with the #27 keyword set. + + # analyze an existing ensemble (the bundled tier's .npz) + uv run python .context/issue-351/multimodel_ensemble.py --from-npz PATH + # or fit a new one first (writes ensemble.npz next to this script) + uv run python .context/issue-351/multimodel_ensemble.py [N] [--threads T] + +Writes ``multimodel_summary.json`` and ``per_run_detail.csv`` next to this +script and the figure to ``docs/assets/figures/multimodel-ensemble.png``. +""" + +from __future__ import annotations + +import argparse +import csv +import importlib.util +import json +import shutil +import sys +from pathlib import Path + +import numpy as np +from scipy import stats + +HERE = Path(__file__).resolve().parent +REPO = HERE.parents[1] +FIGURE = REPO / "docs/assets/figures/multimodel-ensemble.png" +NW = 32 + + +def _load(path: Path, name: str): + spec = importlib.util.spec_from_file_location(name, path) + assert spec is not None and spec.loader is not None + mod = importlib.util.module_from_spec(spec) + sys.modules[name] = mod + spec.loader.exec_module(mod) + return mod + + +def fit_ensemble(n: int, threads: int) -> dict[str, np.ndarray]: + table1 = _load(REPO / "benchmarks/reproduce_table1.py", "reproduce_table1_351") + device = table1.resolve_device("cpu") + binary = table1.resolve_binary(None, "v0.3.3") + data, _ = table1.load_bundled_data() + _, raw = table1.run_multimodel_ensemble(data, n, 100, threads, device, binary) + np.savez(HERE / "ensemble.npz", **raw) + return raw + + +def main() -> None: + p = argparse.ArgumentParser() + p.add_argument("n", nargs="?", type=int, default=20) + p.add_argument("--from-npz", type=Path) + p.add_argument("--threads", type=int, default=4) + a = p.parse_args() + ens27 = _load(REPO / ".context/issue-27/multimodel_ensemble.py", "ens27") + ama27 = _load(REPO / ".context/issue-27/amari_distance.py", "ama27") + + d = dict(np.load(a.from_npz)) if a.from_npz else fit_ensemble(a.n, a.threads) + Fs, Gs, F_ll, G_ll = d["Fs"], d["Gs"], d["F_ll"], d["G_ll"] + n = len(Fs) + + within_F = ens27.pairwise(Fs, Fs, True) + within_G = ens27.pairwise(Gs, Gs, True) + between = ens27.pairwise(Gs, Fs, False) + diff, p_perm = ens27.perm_test_not_worse(Fs, Gs) + ks = float(stats.ks_2samp(G_ll, F_ll).pvalue) + + summary: dict = { + "source": str(a.from_npz) if a.from_npz else "fit here", + "n_fortran": int(len(Fs)), + "n_pamica": int(len(Gs)), + "ll": { + "fortran_mean": float(F_ll.mean()), + "fortran_sd": float(F_ll.std()), + "pamica_mean": float(G_ll.mean()), + "pamica_sd": float(G_ll.std()), + "pamica_minus_fortran": float(G_ll.mean() - F_ll.mean()), + "ks_p": ks, + "mann_whitney_p": float(stats.mannwhitneyu(G_ll, F_ll).pvalue), + }, + } + for name, metric, higher_is_worse in ( + ("corr", ama27.xcorr, False), + ("amari", ama27.model_amari, True), + ): + wF = ama27.pairwise(Fs, Fs, True, metric) + wG = ama27.pairwise(Gs, Gs, True, metric) + bt = ama27.pairwise(Gs, Fs, False, metric) + summary[name] = { + "within_Fortran": {"mean": float(wF.mean()), "sd": float(wF.std())}, + "within_pamica": {"mean": float(wG.mean()), "sd": float(wG.std())}, + "between": {"mean": float(bt.mean()), "sd": float(bt.std())}, + "between_minus_within_Fortran": float(bt.mean() - wF.mean()), + "perm_p_not_worse": float( + ama27.perm_test_not_worse(Fs, Gs, metric, higher_is_worse) + ), + "range_within_Fortran": [float(wF.min()), float(wF.max())], + "range_within_pamica": [float(wG.min()), float(wG.max())], + "range_between": [float(bt.min()), float(bt.max())], + } + (HERE / "multimodel_summary.json").write_text(json.dumps(summary, indent=2)) + print(json.dumps(summary, indent=2)) + + corr_detail = { + (r["implementation"], r["run"]): r + for r in ama27.per_run_detail(Fs, Gs, ama27.xcorr) + } + with open(HERE / "per_run_detail.csv", "w", newline="") as f: + w = csv.writer(f) + w.writerow( + [ + "implementation", "run", "final_ll", "corr_within", "corr_between", + "amari_within", "amari_between", + ] + ) # fmt: skip + for row in ama27.per_run_detail(Fs, Gs, ama27.model_amari): + key = (row["implementation"], row["run"]) + c = corr_detail[key] + ll = (F_ll if row["implementation"] == "Fortran" else G_ll)[row["run"]] + w.writerow( + [ + row["implementation"], row["run"], f"{ll:.4f}", + f"{c['within']:.4f}", f"{c['between']:.4f}", + f"{row['within']:.4f}", f"{row['between']:.4f}", + ] + ) # fmt: skip + + ens27.figure(within_F, within_G, between, F_ll, G_ll, diff, p_perm, ks, HERE) + shutil.copyfile(HERE / "multimodel_ensemble_distributions.png", FIGURE) + print(f"figure -> {FIGURE} (n={n} each)") + + +if __name__ == "__main__": + main() diff --git a/.context/issue-351/raw/dimsweep/dimsweep_mac_ll.json b/.context/issue-351/raw/dimsweep/dimsweep_mac_ll.json new file mode 100644 index 0000000..bf12820 --- /dev/null +++ b/.context/issue-351/raw/dimsweep/dimsweep_mac_ll.json @@ -0,0 +1,127 @@ +{ + "platform": { + "machine": "arm64", + "system": "Darwin", + "nproc": 14, + "torch": "2.12.1", + "loadavg": [ + 10.3, + 15.3, + 12.1 + ] + }, + "config": { + "data": "benchmarks/data/ds002718_sub-002_eeg70.npy", + "channels": "32,48,70", + "montage": null, + "samples": 30000, + "iters": 25, + "repeats": 1, + "backends": 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"m1", + "channels": 48, + "backend": "mlx-f32", + "threads": null, + "ms_per_iter": 35.69712499855086, + "final_ll": -3.208386182785034 + }, + { + "config": "m1", + "channels": 48, + "backend": "torch-cpu-f64", + "threads": null, + "ms_per_iter": 148.65664332173765, + "final_ll": -3.2083835269014345 + }, + { + "config": "m1", + "channels": 48, + "backend": "torch-mps-f32", + "threads": null, + "ms_per_iter": 375.34432664047927, + "final_ll": -3.208386182785034 + }, + { + "config": "m1", + "channels": 48, + "backend": "numpy-cpu-f64", + "threads": null, + "ms_per_iter": 499.61313331965357, + "final_ll": -3.2089337357203798 + }, + { + "config": "m1", + "channels": 70, + "backend": "mlx-f32", + "threads": null, + "ms_per_iter": 38.29424163792282, + "final_ll": -3.216428518295288 + }, + { + "config": "m1", + "channels": 70, + "backend": "torch-cpu-f64", + "threads": null, + "ms_per_iter": 195.01211500028148, + "final_ll": -3.217461695658916 + }, + { + "config": "m1", + "channels": 70, + "backend": "torch-mps-f32", + "threads": null, + "ms_per_iter": 404.7074583196081, + "final_ll": -3.2163822650909424 + }, + { + "config": "m1", + "channels": 70, + "backend": "numpy-cpu-f64", + "threads": null, + "ms_per_iter": 743.3544716797769, + "final_ll": -3.220537041706068 + } + ] +} \ No newline at end of file diff --git a/.context/issue-351/raw/dimsweep/dimsweep_mac_ll.log b/.context/issue-351/raw/dimsweep/dimsweep_mac_ll.log new file mode 100644 index 0000000..1e34178 --- /dev/null +++ b/.context/issue-351/raw/dimsweep/dimsweep_mac_ll.log @@ -0,0 +1,15 @@ +platform: {'machine': 'arm64', 'system': 'Darwin', 'nproc': 14, 'torch': '2.12.1', 'loadavg': [10.3, 15.3, 12.1]} +data (70, 60000) | config m1 | channels [32, 48, 70] | samples 30000 | iters 25 x 1 | ['mlx-f32', 'torch-cpu-f64', 'torch-mps-f32', 'numpy-cpu-f64'] + [m1] 32ch mlx-f32 35.30 ms/it LL=-3.28488 + [m1] 32ch torch-cpu-f64 141.09 ms/it LL=-3.28489 + [m1] 32ch torch-mps-f32 302.25 ms/it LL=-3.28488 + [m1] 32ch numpy-cpu-f64 337.44 ms/it LL=-3.28478 + [m1] 48ch mlx-f32 35.70 ms/it LL=-3.20839 + [m1] 48ch torch-cpu-f64 148.66 ms/it LL=-3.20838 + [m1] 48ch torch-mps-f32 375.34 ms/it LL=-3.20839 + [m1] 48ch numpy-cpu-f64 499.61 ms/it LL=-3.20893 + [m1] 70ch mlx-f32 38.29 ms/it LL=-3.21643 + [m1] 70ch torch-cpu-f64 195.01 ms/it LL=-3.21746 + [m1] 70ch torch-mps-f32 404.71 ms/it LL=-3.21638 + [m1] 70ch numpy-cpu-f64 743.35 ms/it LL=-3.22054 +wrote .context/issue-351/raw/dimsweep/dimsweep_mac_ll.json From 65e1c6404202787306d18738e32fa75a1a2be005 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:24:37 -0700 Subject: [PATCH 11/58] Add the hallu CUDA dimsweep LL record --- .../issue-351/raw/dimsweep/dimsweep_cuda.json | 80 +++++++++++++++++++ .../issue-351/raw/dimsweep/dimsweep_cuda.log | 9 +++ 2 files changed, 89 insertions(+) create mode 100644 .context/issue-351/raw/dimsweep/dimsweep_cuda.json create mode 100644 .context/issue-351/raw/dimsweep/dimsweep_cuda.log diff --git a/.context/issue-351/raw/dimsweep/dimsweep_cuda.json b/.context/issue-351/raw/dimsweep/dimsweep_cuda.json new file mode 100644 index 0000000..ca7e49d --- /dev/null +++ b/.context/issue-351/raw/dimsweep/dimsweep_cuda.json @@ -0,0 +1,80 @@ +{ + "platform": { + "machine": "x86_64", + "system": "Linux", + "nproc": 32, + "torch": "2.12.1+cu130", + "cuda_device": "NVIDIA GeForce RTX 4090", + "loadavg": [ + 33.0, + 36.2, + 32.2 + ] + }, + "config": { + "data": "/home/yahya/epic324-runs/p15/ds002718_sub-002_eeg70.npy", + "channels": "32,48,70", + "montage": null, + "samples": 30000, + "iters": 25, + "repeats": 3, + "backends": "torch-cuda-f64,torch-cuda-f32", + "out": "/home/yahya/epic324-runs/p15/dimsweep_cuda.json", + "report": null, + "n_models": 1, + "share": false, + "fortran_bin": "/home/yahya/pamica-p15/benchmarks/fortran/amica15", + "fortran_threads": null, + "threads": null + }, + "rows": [ + { + "config": "m1", + "channels": 32, + "backend": "torch-cuda-f64", + "threads": null, + "ms_per_iter": 125.49756260123104, + "final_ll": -3.2848901731348024 + }, + { + "config": "m1", + "channels": 32, + "backend": "torch-cuda-f32", + "threads": null, + "ms_per_iter": 145.12465924024582, + "final_ll": -3.2848782539367676 + }, + { + "config": "m1", + "channels": 48, + "backend": "torch-cuda-f64", + "threads": null, + "ms_per_iter": 90.71042256429791, + "final_ll": -3.2083838687794355 + }, + { + "config": "m1", + "channels": 48, + "backend": "torch-cuda-f32", + "threads": null, + "ms_per_iter": 105.01488755922765, + "final_ll": -3.208394765853882 + }, + { + "config": "m1", + "channels": 70, + "backend": "torch-cuda-f64", + "threads": null, + "ms_per_iter": 123.88060091994703, + "final_ll": -3.217233763497051 + }, + { + "config": "m1", + "channels": 70, + "backend": "torch-cuda-f32", + "threads": null, + "ms_per_iter": 137.2088565211743, + "final_ll": -3.2168900966644287 + } + ] +} \ No newline at end of file diff --git a/.context/issue-351/raw/dimsweep/dimsweep_cuda.log b/.context/issue-351/raw/dimsweep/dimsweep_cuda.log new file mode 100644 index 0000000..4418063 --- /dev/null +++ b/.context/issue-351/raw/dimsweep/dimsweep_cuda.log @@ -0,0 +1,9 @@ +platform: {'machine': 'x86_64', 'system': 'Linux', 'nproc': 32, 'torch': '2.12.1+cu130', 'cuda_device': 'NVIDIA GeForce RTX 4090', 'loadavg': [33.0, 36.2, 32.2]} +data (70, 60000) | config m1 | channels [32, 48, 70] | samples 30000 | iters 25 x 3 | ['torch-cuda-f64', 'torch-cuda-f32'] + [m1] 32ch torch-cuda-f64 125.50 ms/it LL=-3.28489 + [m1] 32ch torch-cuda-f32 145.12 ms/it LL=-3.28488 + [m1] 48ch torch-cuda-f64 90.71 ms/it LL=-3.20838 + [m1] 48ch torch-cuda-f32 105.01 ms/it LL=-3.20839 + [m1] 70ch torch-cuda-f64 123.88 ms/it LL=-3.21723 + [m1] 70ch torch-cuda-f32 137.21 ms/it LL=-3.21689 +wrote /home/yahya/epic324-runs/p15/dimsweep_cuda.json From 02e35792c13c0c3a599ff3d2c413112baa2a7435 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:25:50 -0700 Subject: [PATCH 12/58] Re-state the cross-backend LL table with the chaos caveat --- docs/guides/validation.md | 31 ++++++++++++++++++++++--------- 1 file changed, 22 insertions(+), 9 deletions(-) diff --git a/docs/guides/validation.md b/docs/guides/validation.md index cdb11a4..4d3dc8e 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -25,7 +25,7 @@ Throughout, IC abbreviates independent component and LL log-likelihood. | Every backend against the reference (harness defaults, bundled) | `validate_implementations.py --backend all`: PyTorch, NumPy and MLX each vs Fortran | from independent starts: LL within 2.8e-4 (the reference's own seed-to-seed standard deviation is 2.6e-4), correlation 0.9991, Amari distance 0.004, for all three; from a shared start: LL within 1.6e-6, correlation 0.99999993 ([per-backend rows](#parity-rows-per-backend)) | | Multi-model solution | distributional similarity over 20-run ensembles | indistinguishable from Fortran's own run-to-run spread ($p = 0.96$) | | Device and precision invariance | same independent components across CPU/CUDA/MPS/MLX, float32/float64, Linux/macOS | identical (1.000) across all eight torch/MLX combinations | -| Cross-backend log-likelihood | converged LL across every backend | agree to ~3 significant digits (max pairwise ~0.003) | +| Cross-backend log-likelihood | same settings and start, 25 iterations, every backend | agree to 1e-5 at 32 and 48 channels; at 70 channels ($k\approx6$) within 1.1e-3, the size of a round-off perturbation's effect ([details](#cross-backend-log-likelihood-agreement-single-model)) | | EEGLAB output | `write_amica_output` round-trip through `loadmodout15` | single-model bytes are an exact serialization; loads with correct layout | | Degenerate fits | NaN or singular log-likelihood | refused, never returned as NaN sources | @@ -514,14 +514,27 @@ narrows here too is untested. ### Cross-backend log-likelihood agreement (single-model) -Every backend converges to the same log-likelihood to ~3 significant digits on real EEG, -across device and precision, confirming the whole backend family end-to-end: - -| channels | MLX f32 | CUDA f64 | torch-CPU f64 | torch-MPS f32 | NumPy f64 | -|---:|---:|---:|---:|---:|---:| -| 32 | -3.28634 | -3.28635 | -3.28636 | -3.28635 | -3.28620 | -| 48 | -3.20951 | -3.20952 | -3.20953 | -3.20951 | -3.21019 | -| 70 | -3.21579 | -3.21562 | -3.21560 | -3.21570 | -3.21315 | +The log-likelihood each backend reaches with the same settings and the same start, +from the throughput sweep's own runs (`benchmark_dimsweep.py`: the first 30000 frames of ds002718 sub-002, +the first 32, 48 or 70 channels, 25 iterations, `block_size=512`, no Newton, seed 42; +re-measured on 2026-09-23 with the code of epic #324, issue #351, on the Apple M4 Pro and, for CUDA, the RTX 4090 host): + +| channels | MLX f32 | CUDA f64 | CUDA f32 | torch-CPU f64 | torch-MPS f32 | NumPy f64 | +|---:|---:|---:|---:|---:|---:|---:| +| 32 | -3.28488 | -3.28489 | -3.28488 | -3.28489 | -3.28488 | -3.28478 | +| 48 | -3.20839 | -3.20838 | -3.20839 | -3.20838 | -3.20839 | -3.20893 | +| 70 | -3.21643 | -3.21723 | -3.21689 | -3.21746 | -3.21638 | -3.22054 | + +At 32 and 48 channels every backend that starts from the shared draw agrees to 1e-5, so float32 matches float64 to five significant digits. +At 70 channels the sweep's 30000 frames give $k\approx6$, and 25 iterations at `lrate=0.1` amplify round-off: +two float64 runs of the same code on CPU and CUDA differ by 2.3e-4, the backends by up to 1.1e-3, +and adding 1e-9 µV to one sample changes the torch-CPU value by 1.3e-15 after one iteration and 4.4e-4 after 25 +(the trajectory has a likelihood decrease on its 25th iteration). +So the 70-channel column measures that sensitivity, not a difference between the backends' arithmetic; +the code before epic #324 shows the same growth. +NumPy is called without a seed here, so it starts from its own draw, which is why its column sits apart (by up to 4.2e-3 at 70 channels). +The component-level float32 comparison is in [the per-backend rows](#parity-rows-per-backend): +from a shared start, MLX float32 and PyTorch float64 agree to a mean matched correlation of 0.99999991 after 100 iterations. ## Other validated behaviors From ab6a379b77f538aeba95060e31c745af34310771 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:44:11 -0700 Subject: [PATCH 13/58] Reword the harness and cross-backend notes --- docs/guides/validation.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/guides/validation.md b/docs/guides/validation.md index 4d3dc8e..863c4ef 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -100,14 +100,14 @@ Runtime is one run's wall-clock time for the fit alone and varies by about a thi the reference's includes process start-up and is single-threaded. Epic #324 left the runtimes unchanged: the code before it (e38aa11), run in the same session, took 10.1, 17.9, 32.5 and 3.2 seconds. -**The log-likelihood difference in these rows is set by the two starting points, not by the update rule.** +**The log-likelihood difference in these rows mostly reflects the two starting points.** The harness starts each side from its own draw: numpy's `RandomState(42)` for pamica, gfortran's generator seeded with 42 for the reference. After 100 iterations the final log-likelihood still depends on where a fit started. Over eight seeds, the reference's own final log-likelihood has a standard deviation of 2.6e-4 and a range of 8.0e-4 (pamica's: 2.7e-4 and 8.0e-4), and over the 64 pairs of a pamica start and a reference start the median difference is 3.5e-4 (range 1.7e-5 to 8.2e-4). -The 2.7e-4 in the table is one draw from that spread. -Before epic #324 the same run showed 2.9e-5, which was a cancellation for this one pair of starts, not tighter parity: -from a shared start, the code before the epic lagged the reference by 2.4e-4 after 100 iterations, and that lag happened to offset the difference between the two starts. +The 2.7e-4 in the table lies within that spread. +Before epic #324 the same run showed 2.9e-5, which reflected this particular pair of starts: +from a shared start, the code before the epic trailed the reference by 2.4e-4 after 100 iterations, which offset most of the difference between the two starts. The update rule itself is compared from a shared start: pamica's seed-42 initialization is written into the reference's `load_*` files, and both sides run the harness settings for 100 iterations, the reference on one thread @@ -530,8 +530,8 @@ At 70 channels the sweep's 30000 frames give $k\approx6$, and 25 iterations at ` two float64 runs of the same code on CPU and CUDA differ by 2.3e-4, the backends by up to 1.1e-3, and adding 1e-9 µV to one sample changes the torch-CPU value by 1.3e-15 after one iteration and 4.4e-4 after 25 (the trajectory has a likelihood decrease on its 25th iteration). -So the 70-channel column measures that sensitivity, not a difference between the backends' arithmetic; -the code before epic #324 shows the same growth. +The 70-channel differences are of the same size as that sensitivity, +and the code before epic #324 shows the same growth. NumPy is called without a seed here, so it starts from its own draw, which is why its column sits apart (by up to 4.2e-3 at 70 channels). The component-level float32 comparison is in [the per-backend rows](#parity-rows-per-backend): from a shared start, MLX float32 and PyTorch float64 agree to a mean matched correlation of 0.99999991 after 100 iterations. From 32ce997c85bafb54c070695c0b9120f3bcdc69f8 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 14:54:43 -0700 Subject: [PATCH 14/58] Pin the ensemble lrate in reproduce_table1 --- benchmarks/reproduce_table1.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/benchmarks/reproduce_table1.py b/benchmarks/reproduce_table1.py index 9d1ffa8..9eedf8d 100644 --- a/benchmarks/reproduce_table1.py +++ b/benchmarks/reproduce_table1.py @@ -499,6 +499,9 @@ def run_multimodel_ensemble( model.fit( data, max_iter=max_iter, + # The #27 protocol's rate (input.param), pinned so the ensemble does + # not follow a change of the wrapper's default. + lrate=0.05, do_newton=True, seed=MULTIMODEL_SEED_START + i, block_size=512, From 9a02a0e1c5278e132fd114381b7847564635b7d1 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:19:07 -0700 Subject: [PATCH 15/58] Add basin and pre-epic ensemble scripts --- .context/issue-351/bundled_single_basins.py | 109 +++++++++++++++++++ .context/issue-351/multimodel_ensemble.py | 9 +- .context/issue-351/multimodel_pamica_fits.py | 62 +++++++++++ 3 files changed, 178 insertions(+), 2 deletions(-) create mode 100644 .context/issue-351/bundled_single_basins.py create mode 100644 .context/issue-351/multimodel_pamica_fits.py diff --git a/.context/issue-351/bundled_single_basins.py b/.context/issue-351/bundled_single_basins.py new file mode 100644 index 0000000..f633eed --- /dev/null +++ b/.context/issue-351/bundled_single_basins.py @@ -0,0 +1,109 @@ +"""Basins of the bundled tier's single-model comparison (issue #351 item 2). + +``benchmarks/reproduce_table1.py --tier bundled`` compares five pamica fits +(seeds 301-305) with five clock-seeded reference fits, one pair per seed, on +the bundled sample (32 channels, k ~ 30), Newton off, 2000 iterations, and +reports only the means. This script repeats that single-model protocol with +the unmixing matrices kept, so every pair can be compared: the same pamica +seeds (deterministic, so they reproduce the tier's pamica fits) and seeded +reference runs (``seed`` 1..N, reproducible), with the tier's keyword sets. + + uv run python .context/issue-351/bundled_single_basins.py OUT.npz [N_FORTRAN] [--threads T] +""" + +from __future__ import annotations + +import argparse +import importlib.util +import itertools +import json +import sys +from pathlib import Path + +import numpy as np + +HERE = Path(__file__).resolve().parent +REPO = HERE.parents[1] + + +def _table1(): + spec = importlib.util.spec_from_file_location( + "reproduce_table1_basins", REPO / "benchmarks/reproduce_table1.py" + ) + assert spec is not None and spec.loader is not None + mod = importlib.util.module_from_spec(spec) + sys.modules["reproduce_table1_basins"] = mod + spec.loader.exec_module(mod) + return mod + + +def main() -> None: + p = argparse.ArgumentParser() + p.add_argument("out", type=Path) + p.add_argument("n_fortran", nargs="?", type=int, default=10) + p.add_argument("--threads", type=int, default=4) + p.add_argument("--pamica-seeds", default="301,302,303,304,305") + a = p.parse_args() + t1 = _table1() + from pamica import AMICA, AMICANative + + data, _ = t1.load_bundled_data() + binary = t1.resolve_binary(None, "v0.3.3") + runs: dict[str, dict] = {} + for s in range(1, a.n_fortran + 1): + eng = AMICANative( + binary=binary, threads=a.threads, max_threads=a.threads, timeout=3600, + n_models=1, n_mix=3, max_iter=2000, do_newton=0, use_min_dll=0, + use_grad_norm=0, block_size=512, seed=s, + ) # fmt: skip + eng.fit(data) + assert eng.output_ is not None + runs[f"fortran_seed{s}"] = { + "W": eng.output_.W[:, :, 0], + "ll": float(eng.output_.LL[-1]), + } + print(f"fortran seed {s}: LL={runs[f'fortran_seed{s}']['ll']:.6f}", flush=True) + for s in [int(x) for x in a.pamica_seeds.split(",") if x]: + model = AMICA(n_models=1, n_mix=3, device="cpu", verbose=False) + model.fit( + data, max_iter=2000, lrate=0.05, do_mean=True, do_sphere=True, + do_approx_sphere=True, do_newton=False, seed=s, block_size=512, + minlrate=1e-8, lratefact=0.5, maxdecs=3, newt_start=50, newt_ramp=10, + newtrate=1.0, rho0=1.5, minrho=1.0, maxrho=2.0, rholrate=0.05, + rholratefact=0.5, invsigmin=0.0, invsigmax=100.0, doscaling=True, + scalestep=1, + ) # fmt: skip + runs[f"pamica_seed{s}"] = { + "W": model.get_unmixing_matrix(0), + "ll": float(model.final_ll_), + "iters": len(model.ll_history_), + "stop": str(model.stop_reason_), + } + print( + f"pamica seed {s}: LL={model.final_ll_:.6f} iters={len(model.ll_history_)} " + f"stop={model.stop_reason_}", + flush=True, + ) + names = list(runs) + np.savez( + a.out, + names=np.array(names), + W=np.stack([runs[k]["W"] for k in names]), + ll=np.array([runs[k]["ll"] for k in names]), + ) + rep: dict = {"ll": {k: runs[k]["ll"] for k in names}, "pairs": {}} + for x, y in itertools.combinations(names, 2): + c = t1.xcorr(runs[x]["W"], runs[y]["W"]) + rep["pairs"][f"{x} vs {y}"] = { + "mean_corr": float(c.mean()), + "min_corr": float(c.min()), + "amari": float(t1.amari_distance(runs[x]["W"], runs[y]["W"])), + } + for k in ("iters", "stop"): + rep[k] = {n: runs[n][k] for n in names if k in runs[n]} + a.out.with_suffix(".json").write_text(json.dumps(rep, indent=2)) + print(json.dumps(rep["ll"], indent=2)) + + +if __name__ == "__main__": + main() diff --git a/.context/issue-351/multimodel_ensemble.py b/.context/issue-351/multimodel_ensemble.py index 85c273f..52ffdde 100644 --- a/.context/issue-351/multimodel_ensemble.py +++ b/.context/issue-351/multimodel_ensemble.py @@ -64,7 +64,10 @@ def main() -> None: p.add_argument("n", nargs="?", type=int, default=20) p.add_argument("--from-npz", type=Path) p.add_argument("--threads", type=int, default=4) + p.add_argument("--tag", default="", help="suffix for the output file names") + p.add_argument("--no-figure", action="store_true") a = p.parse_args() + sfx = f"_{a.tag}" if a.tag else "" ens27 = _load(REPO / ".context/issue-27/multimodel_ensemble.py", "ens27") ama27 = _load(REPO / ".context/issue-27/amari_distance.py", "ama27") @@ -111,14 +114,14 @@ def main() -> None: "range_within_pamica": [float(wG.min()), float(wG.max())], "range_between": [float(bt.min()), float(bt.max())], } - (HERE / "multimodel_summary.json").write_text(json.dumps(summary, indent=2)) + (HERE / f"multimodel_summary{sfx}.json").write_text(json.dumps(summary, indent=2)) print(json.dumps(summary, indent=2)) corr_detail = { (r["implementation"], r["run"]): r for r in ama27.per_run_detail(Fs, Gs, ama27.xcorr) } - with open(HERE / "per_run_detail.csv", "w", newline="") as f: + with open(HERE / f"per_run_detail{sfx}.csv", "w", newline="") as f: w = csv.writer(f) w.writerow( [ @@ -138,6 +141,8 @@ def main() -> None: ] ) # fmt: skip + if a.no_figure: + return ens27.figure(within_F, within_G, between, F_ll, G_ll, diff, p_perm, ks, HERE) shutil.copyfile(HERE / "multimodel_ensemble_distributions.png", FIGURE) print(f"figure -> {FIGURE} (n={n} each)") diff --git a/.context/issue-351/multimodel_pamica_fits.py b/.context/issue-351/multimodel_pamica_fits.py new file mode 100644 index 0000000..43f561f --- /dev/null +++ b/.context/issue-351/multimodel_pamica_fits.py @@ -0,0 +1,62 @@ +"""Refit the pamica side of the bundled tier's multi-model ensemble with the +pamica tree at ROOT (issue #351 item 3), for a comparison against the SAME +reference fits: the reference half is copied from ``--fortran-npz`` (the +bundled tier's ``bundled_multimodel_ensemble.npz``), the pamica half is fitted +here with ``reproduce_table1.run_multimodel_ensemble``'s keyword set (seeds +1-20, 100 iterations). With ROOT at the code before epic #324 this separates the +epic's effect on the ensemble from the draw of the reference runs. + + uv run python .context/issue-351/multimodel_pamica_fits.py ROOT --fortran-npz PATH OUT.npz +""" + +from __future__ import annotations + +import argparse +import sys +from pathlib import Path + +import numpy as np + + +def main() -> None: + p = argparse.ArgumentParser() + p.add_argument("root", type=Path) + p.add_argument("out", type=Path) + p.add_argument("--fortran-npz", type=Path, required=True) + p.add_argument("--n", type=int, default=20) + a = p.parse_args() + root = a.root.resolve() + sys.path.insert(0, str(root)) + import pamica + from pamica import AMICA + from pamica.torch_impl.utils import load_eeglab_data + + assert pamica.__file__.startswith(str(root)), pamica.__file__ + data = load_eeglab_data( + str(root / "pamica/sample_data/eeglab_data.fdt"), + data_dim=32, + field_dim=30504, + dtype=np.float32, + ).astype(np.float64) + Gs, G_ll = [], [] + for i in range(a.n): + model = AMICA(n_models=2, n_mix=3, device="cpu", verbose=False) + model.fit( + data, max_iter=100, lrate=0.05, do_newton=True, seed=1 + i, + block_size=512, minlrate=1e-8, lratefact=0.5, maxdecs=3, newt_start=50, + newt_ramp=10, newtrate=1.0, rho0=1.5, minrho=1.0, maxrho=2.0, + rholrate=0.05, rholratefact=0.5, invsigmin=1e-8, invsigmax=100.0, + doscaling=True, scalestep=1, + ) # fmt: skip + assert model.converged_, model.stop_reason_ + Gs.append( + np.vstack([model.get_unmixing_matrix(0), model.get_unmixing_matrix(1)]) + ) + G_ll.append(float(model.final_ll_)) + print(f"pamica {i + 1}/{a.n}: LL={G_ll[-1]:.4f}", flush=True) + f = np.load(a.fortran_npz) + np.savez(a.out, Fs=f["Fs"], F_ll=f["F_ll"], Gs=np.array(Gs), G_ll=np.array(G_ll)) + + +if __name__ == "__main__": + main() From 4811f5b77d20723440ed87e173897605fc9b8237 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:19:08 -0700 Subject: [PATCH 16/58] Record the bundled tier, basin, ensemble and MLX Newton runs --- .../multimodel_ensemble_distributions.pdf | Bin 0 -> 43258 bytes .../multimodel_ensemble_distributions.png | Bin 0 -> 152206 bytes .context/issue-351/multimodel_summary.json | 70 +++ .../multimodel_summary_pre_epic_e38aa11.json | 70 +++ .context/issue-351/per_run_detail.csv | 41 ++ .../per_run_detail_pre_epic_e38aa11.csv | 41 ++ .../bundled_basins/bundled_single_basins.json | 560 ++++++++++++++++++ .../bundled_basins/bundled_single_basins.npz | Bin 0 -> 124574 bytes .../issue-351/raw/bundled_basins/stdout.log | 33 ++ .../pre_epic_e38aa11_vs_bundled_fortran.npz | Bin 0 -> 656654 bytes .../raw/multimodel/pre_epic_stdout.log | 30 + .../raw/newton_mlx/pamica_seed42_mlx.npz | Bin 0 -> 68314 bytes .../raw/newton_mlx/pamica_seed7_mlx.npz | Bin 0 -> 68506 bytes .context/issue-351/raw/newton_mlx/stdout.log | 4 + .../bundled_multimodel_ensemble.npz | Bin 0 -> 656654 bytes .../issue-351/raw/table1_bundled/report.json | 59 ++ 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z@YyvJyDR%ScdQ?xF!+?daXcKPFcRWBlKTfJjId&Lnb?;UhUFG-3MXl|*ZRlm`YsA% zP>wD3GpYYq&*rDL&HZoBs{cRsZ2yoLIBL0UN3p( z!|fD?d{z9R4LuZwllNjEm9*c)VzqrcDF-)xU*|=xmrff_=^Q3@w)$ODqzC5{3h!u= z9%xoj<{WwP$Fs~!cC!4>s0DqaRc=hnnEvd`|1p;T6mEYTv1;~zM)1Ge@J*hm`p-6n z0.999) + measured: correlation diff=+0.006 (perm p=0.884) + measured: Amari diff=+0.005 (perm p=0.051) +------------------------------------------------------------------------------ +Row: Multi | Ensemble log-likelihood: Fortran; pamica + paper: -3.3539; -3.3629 (KS p=6e-5) + measured: Fortran=-3.3543 (sd 0.002); pamica=-3.3541 (sd 0.003); KS p=8.32e-01 (n=20/20 Fortran, 20/20 pamica runs ok) +------------------------------------------------------------------------------ +bundled tier wall-clock: 2842s + +wrote .context/issue-351/raw/table1_bundled/report.json From 124c3ec660b2690bbda8f4b0d8b27fcb0b1715e9 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:30:42 -0700 Subject: [PATCH 17/58] Add the equivalence-margin check on saved ensembles --- .context/issue-351/equivalence_check.py | 100 ++++++++++++++++++ .../raw/multimodel/equivalence_check.json | 68 ++++++++++++ 2 files changed, 168 insertions(+) create mode 100644 .context/issue-351/equivalence_check.py create mode 100644 .context/issue-351/raw/multimodel/equivalence_check.json diff --git a/.context/issue-351/equivalence_check.py b/.context/issue-351/equivalence_check.py new file mode 100644 index 0000000..2fa3bd1 --- /dev/null +++ b/.context/issue-351/equivalence_check.py @@ -0,0 +1,100 @@ +"""The ±0.05 equivalence margin of the #27 multi-model study, on saved ensembles +(issue #351 item 3). No refitting. + +The #27 record states its acceptance criterion as "between not worse than +within-Fortran; TOST within a margin" of ±0.05 on the mean Hungarian-matched +correlation. Its first TOST was computed on the 190/400 pairwise values as if +they were independent, which the record later retired as pseudoreplicated (each +run appears in ~39 pairs) in favor of the run-level permutation test. For each +ensemble given, this script reports, for the correlation and the Amari distance: + +* ``diff``: mean(between) - mean(within-Fortran), and whether it lies inside + ±0.05 (the documented descriptive check, stated for the correlation only); +* ``pairwise_tost_p``: the retired pairwise TOST with the same margin, for + continuity with the old record (its p-value is not valid, as the record says); +* ``run_bootstrap_90ci``: a run-level bootstrap 90% interval of ``diff`` + (runs resampled with replacement within each implementation, 5000 draws), + which respects the shared-run dependence; an interval inside ±0.05 is the + run-level analogue of the TOST at the 5% level. + + uv run python .context/issue-351/equivalence_check.py OUT.json NAME=PATH.npz [NAME=PATH.npz ...] +""" + +from __future__ import annotations + +import importlib.util +import json +import sys +from pathlib import Path + +import numpy as np +from scipy import stats + +HERE = Path(__file__).resolve().parent +REPO = HERE.parents[1] +DELTA = 0.05 + + +def _load(path: Path, name: str): + spec = importlib.util.spec_from_file_location(name, path) + assert spec is not None and spec.loader is not None + mod = importlib.util.module_from_spec(spec) + sys.modules[name] = mod + spec.loader.exec_module(mod) + return mod + + +def analyze(Fs: np.ndarray, Gs: np.ndarray, metric) -> dict: + allW = np.concatenate([Fs, Gs]) + m, n = len(allW), len(Fs) + P = np.zeros((m, m)) + for i in range(m): + for j in range(i + 1, m): + P[i, j] = P[j, i] = metric(allW[i], allW[j]) + F = np.arange(n) + G = np.arange(n, m) + wF = P[np.ix_(F, F)][np.triu_indices(n, 1)] + bt = P[np.ix_(G, F)].ravel() + diff = float(bt.mean() - wF.mean()) + se = np.sqrt(bt.var(ddof=1) / bt.size + wF.var(ddof=1) / wF.size) + p_tost = float( + max(stats.norm.sf((diff + DELTA) / se), stats.norm.cdf((diff - DELTA) / se)) + ) + rng = np.random.default_rng(0) + boot = [] + for _ in range(5000): + f = rng.choice(F, n, replace=True) + g = rng.choice(G, len(G), replace=True) + # within-Fortran over distinct draws only (a run is not paired with itself) + sub = P[np.ix_(f, f)] + mask = f[:, None] != f[None, :] + w = sub[np.triu(mask, 1)].mean() + b = P[np.ix_(g, f)].mean() + boot.append(b - w) + lo, hi = np.percentile(boot, [5, 95]) + return { + "diff_between_minus_within_fortran": diff, + "inside_pm_0.05": bool(abs(diff) < DELTA), + "pairwise_tost_p_retired": p_tost, + "run_bootstrap_90ci": [float(lo), float(hi)], + "run_bootstrap_90ci_inside_pm_0.05": bool(lo > -DELTA and hi < DELTA), + } + + +def main() -> None: + out = Path(sys.argv[1]) + ama27 = _load(REPO / ".context/issue-27/amari_distance.py", "ama27_eq") + rep = {} + for arg in sys.argv[2:]: + name, path = arg.split("=", 1) + d = np.load(path) + rep[name] = { + "corr": analyze(d["Fs"], d["Gs"], ama27.xcorr), + "amari": analyze(d["Fs"], d["Gs"], ama27.model_amari), + } + print(name, json.dumps(rep[name], indent=1), flush=True) + out.write_text(json.dumps(rep, indent=2)) + + +if __name__ == "__main__": + main() diff --git a/.context/issue-351/raw/multimodel/equivalence_check.json b/.context/issue-351/raw/multimodel/equivalence_check.json new file mode 100644 index 0000000..d5b63b9 --- /dev/null +++ b/.context/issue-351/raw/multimodel/equivalence_check.json @@ -0,0 +1,68 @@ +{ + "epic": { + "corr": { + "diff_between_minus_within_fortran": 0.006353741104652144, + "inside_pm_0.05": true, + "pairwise_tost_p_retired": 7.870934892230386e-39, + "run_bootstrap_90ci": [ + -0.001620542183333956, + 0.013584039734506483 + ], + "run_bootstrap_90ci_inside_pm_0.05": true + }, + "amari": { + "diff_between_minus_within_fortran": 0.005250350286082228, + "inside_pm_0.05": true, + "pairwise_tost_p_retired": 6.022688870443557e-162, + "run_bootstrap_90ci": [ + 0.0017433353384238724, + 0.009241831154639021 + ], + "run_bootstrap_90ci_inside_pm_0.05": true + } + }, + "pre_epic_e38aa11": { + "corr": { + "diff_between_minus_within_fortran": 0.017115269613346862, + "inside_pm_0.05": true, + "pairwise_tost_p_retired": 2.5848991508815386e-24, + "run_bootstrap_90ci": [ + 0.008744046089008656, + 0.024728234934179267 + ], + "run_bootstrap_90ci_inside_pm_0.05": true + }, + "amari": { + "diff_between_minus_within_fortran": -0.006185999147623633, + "inside_pm_0.05": true, + "pairwise_tost_p_retired": 1.9105708981926756e-185, + "run_bootstrap_90ci": [ + -0.009394198264366046, + -0.0023177856345205686 + ], + "run_bootstrap_90ci_inside_pm_0.05": true + } + }, + "issue27_2026_07": { + "corr": { + "diff_between_minus_within_fortran": 0.010710885528479874, + "inside_pm_0.05": true, + "pairwise_tost_p_retired": 7.036653532145984e-27, + "run_bootstrap_90ci": [ + -0.002246375834945718, + 0.022055090189855832 + ], + "run_bootstrap_90ci_inside_pm_0.05": true + }, + "amari": { + "diff_between_minus_within_fortran": -0.011060832125423692, + "inside_pm_0.05": true, + "pairwise_tost_p_retired": 1.6322880293241592e-82, + "run_bootstrap_90ci": [ + -0.01697131581609501, + -0.004339750305150138 + ], + "run_bootstrap_90ci_inside_pm_0.05": true + } + } +} \ No newline at end of file From 0880ba248d3955069bdb9f63d4616978831d6b3b Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:31:10 -0700 Subject: [PATCH 18/58] Record the seeded keep_best ensemble --- .../issue-351/raw/keep_best/ensemble.json | 71 +++++++++++++ .context/issue-351/raw/keep_best/ensemble.npz | Bin 0 -> 98750 bytes .context/issue-351/raw/keep_best/stdout.log | 93 ++++++++++++++++++ .context/issue-351/raw/keep_best/verify.json | 18 ++++ 4 files changed, 182 insertions(+) create mode 100644 .context/issue-351/raw/keep_best/ensemble.json create mode 100644 .context/issue-351/raw/keep_best/ensemble.npz create mode 100644 .context/issue-351/raw/keep_best/stdout.log create mode 100644 .context/issue-351/raw/keep_best/verify.json diff --git a/.context/issue-351/raw/keep_best/ensemble.json b/.context/issue-351/raw/keep_best/ensemble.json new file mode 100644 index 0000000..bd635ea --- /dev/null +++ b/.context/issue-351/raw/keep_best/ensemble.json @@ -0,0 +1,71 @@ +{ + "n": 20, + "keep_best_tol": 1e-09, + "budgets": { + "100": { + "fortran_mean": -3.35503721537913, + "fortran_sd": 0.002902508714644331, + "return_last_mean": -3.3542282783344946, + "return_last_sd": 0.002895896178028667, + "keep_best_mean": -3.3542282783344946, + "keep_best_sd": 0.002895896178028667, + "sd_ratio_return_last": 0.9977217857840354, + "sd_ratio_keep_best": 0.9977217857840354, + "gap_return_last": 0.0008089370446353605, + "gap_keep_best": 0.0008089370446353605, + "ks_p_keep_best": 0.8319696107963263, + "ks_p_return_last": 0.8319696107963263, + "tost_p_keep_best": 7.482078444204207e-23, + "n_restored": 0, + "restored_seeds": [], + "max_restore_gain": 0.0 + }, + "200": { + "fortran_mean": -3.3418448453873153, + "fortran_sd": 0.002960879790217216, + "return_last_mean": -3.3416384843303377, + "return_last_sd": 0.002220142292228306, + "keep_best_mean": -3.3416384843303377, + 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z;X;-Rydtpc=Bj?O{`oomEla83U8PW~LG)+%-~SM3fQCBp93}AdiXZIh(AGb7O$7X; zE8b)Wtqp%Tka>A@$s4{4z_6+d>SP?9NBm`P5j>)@@J1@kUZkCW7P4$)r#k^pnHlns zx)imyji4TkjkwTH=Gg`Bj;xV}T3=+Ial>!Nx5P2R6uv0G$;UVkk33Q!{V5}*qYLZd zEW^mM7f@8|awh3t`G~KaPKE3VqIMB*_lOd!FWj)~jj0V>8y@ zNvKylxRcbuW@{MLjzON3yCs%Td(T4ZwUobo2~etrxasG9eKAnjC~78F#~e)U);TzN zQBjsr_^JN(gY!mf>1k>kQc>I~-Xa#3F6Pc63j899R&pY1_(iN7on4(x9ZVdZEiB33 z?=-b@vBclI95r>a#P_1>rPhe8;XlRyKmVe4E02#SgVP%825*o-b8+f{4^ilJa?`Pw zlSyWG94ox8!X-!RSd-8>oWH5{{LL5VZxS@WnEm{stMiM4%`ajxf3fBKMFI1Z*X9RV z=Zk^!q4lpf?nA9*qw^b={*R68;_B!$zilZCfBhDI`PbW4@87m>O7s5p0d(x& zb^zfR`9J;j`vzV|{p|ew24=q!BZ7v#_>w{ri3r_v=H<`_~`hpWIJm{?#^&pWfov z`>FWlnqQ5q_8zJQYZv}!+k7Z9{5It=eh3fxUq4Im`{U<#njAgm;!2K%KR?fZ{OQ5J zex4%!C$<0fc_a&vV~IQ%etSJnPpW@R27i7*($4+SnxQ58{f)jyicm9|Z}tBCJaUZB zzaZ0ZFUWlAj~D#MBmU1%Ci^ehEy;uVw`dk9&~z U9vWKm-!H Date: Wed, 23 Sep 2026 15:31:55 -0700 Subject: [PATCH 19/58] Add the re-measured keep_best figures to ADR 0003 --- .../decisions/0003-best-iterate-safeguard.md | 46 +++++++++++++++++++ 1 file changed, 46 insertions(+) diff --git a/.context/decisions/0003-best-iterate-safeguard.md b/.context/decisions/0003-best-iterate-safeguard.md index cd86b44..6502b99 100644 --- a/.context/decisions/0003-best-iterate-safeguard.md +++ b/.context/decisions/0003-best-iterate-safeguard.md @@ -76,10 +76,56 @@ latter joined in Phase 3, issue #289) -- see `pamica/mlx_impl/core.py`'s `_snapshot_params`/`_restore_params` and `pamica/tests/mlx_tests/test_mlx_keepbest.py`. +## Re-measured after epic #324 (2026-09-23, issue #351) + +Epic #324 changed the default trajectory of every backend (component-row +`doscaling` #333, 1-based schedule gates #335, the reference's iteration order +and unconditional `A`-freeze #339/#345, the normalized initial `A` #341, +single-precision constants #344), so the figures above describe code that no +longer ships. The ensemble was re-run with the #51 protocol +(`.context/issue-351/keep_best_ensemble.py`: the sample EEG, `n_models=2`, the +#51 keyword set, N = 20, pamica seeds 0-19), with two changes: +the reference is the pinned v0.3.3 native binary, seeded 0-19 and +single-threaded (the #51 runs used the clock-seeded `amica15mac`), and each +fit runs 300 iterations once, with the 100- and 200-iteration values read from +its trajectory (checked equal to separate 100-iteration fits, with `keep_best` +on and off, on two seeds on both sides). + +| budget | Fortran mean (sd) | pamica return-last mean (sd) | pamica `keep_best` mean (sd) | sd ratio | pamica minus Fortran | KS p | restores | +|---:|---:|---:|---:|---:|---:|---:|---:| +| 100 | -3.3550 (0.0029) | -3.3542 (0.0029) | -3.3542 (0.0029) | 1.0x | +0.0008 | 0.83 | 0 of 20 | +| 200 | -3.3418 (0.0030) | -3.3416 (0.0022) | -3.3416 (0.0022) | 0.75x | +0.0002 | 0.57 | 0 of 20 | +| 300 | -3.3393 (0.0027) | -3.3392 (0.0020) | -3.3392 (0.0020) | 0.75x | +0.0001 | 0.98 | 1 of 20 | + +- The late overshoots that motivated this decision do not occur in these + fits: the largest likelihood decrease in any of the 20 pamica trajectories + is 1.2e-5, and none of them used a natural-gradient fallback. At 100 + iterations the return-last and `keep_best` distributions are identical, and + their spread equals the reference's (sd ratio 1.0x, where #51 measured 12.7x + and 2.0x). Phase 7 of the epic (#340) traced most of the old overshoots to + the column-rule `doscaling` (#333). +- A restore fired once in the 60 fit-budget pairs: seed 3 at 300 iterations, + whose best iterate (iteration 299) beat its last by 4.2e-6. +- The mean gap is gone at every budget: pamica's mean is within 8e-4 of the + reference's at 100 iterations and within 2e-4 at 200 and 300, where #51 + measured -0.009 at 100 and attributed it to convergence speed. The + bundled tier's clock-seeded ensemble (`benchmarks/reproduce_table1.py`, + `AMICA` seeds 1-20) agrees: -3.3541 against -3.3543, KS p 0.83. Refitting + that ensemble's pamica half with the code before the epic's changes to the fit (e38aa11) against + the same 20 reference fits gives -3.3627 (sd 0.006, KS p 1e-5), close to + the #27/#51 figures; 7 of those 20 fits stopped early on `min_dll`, which + counted likelihood dips as small gains until #339. +- The decision stands: `keep_best` stays on by default. With these fits it + rarely acts, and when it does the gain is small, but a run that ends below + its peak (a likelihood decrease near the end, or a Newton fallback) still + returns its best iterate. + ## Receipts - `pamica/torch_impl/amica_torch_ng.py` (`keep_best`, `_snapshot_params`/ `_restore_params`, `final_ll_`, `_KEEP_BEST_TOL`). - `pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_*`. - `.context/issue-51/ensemble_ll.py` (Fortran-vs-NG LL ensemble, real data). +- `.context/issue-351/keep_best_ensemble.py` and `raw/keep_best/` (the + re-measurement above), `.context/issue-351/findings.md`. - Fortran schedule: `pamica/amica15.f90:1038-1058` (anneal-on-decrease). From e7acb00b3b99deba64d24416100039f382295182 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:31:55 -0700 Subject: [PATCH 20/58] Name the pre-change code precisely in validation guide --- docs/guides/validation.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/guides/validation.md b/docs/guides/validation.md index 863c4ef..e8bd5af 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -98,7 +98,7 @@ MLX computes in float32 (about seven significant digits per operation), so its b it lands within about five significant digits of the float64 likelihood, which is float32 consistency, not float64 parity. Runtime is one run's wall-clock time for the fit alone and varies by about a third between runs on the same host; the reference's includes process start-up and is single-threaded. -Epic #324 left the runtimes unchanged: the code before it (e38aa11), run in the same session, took 10.1, 17.9, 32.5 and 3.2 seconds. +Epic #324 left the runtimes unchanged: the code before its changes to the fit (e38aa11), run in the same session, took 10.1, 17.9, 32.5 and 3.2 seconds. **The log-likelihood difference in these rows mostly reflects the two starting points.** The harness starts each side from its own draw: numpy's `RandomState(42)` for pamica, gfortran's generator seeded with 42 for the reference. @@ -106,8 +106,8 @@ After 100 iterations the final log-likelihood still depends on where a fit start Over eight seeds, the reference's own final log-likelihood has a standard deviation of 2.6e-4 and a range of 8.0e-4 (pamica's: 2.7e-4 and 8.0e-4), and over the 64 pairs of a pamica start and a reference start the median difference is 3.5e-4 (range 1.7e-5 to 8.2e-4). The 2.7e-4 in the table lies within that spread. -Before epic #324 the same run showed 2.9e-5, which reflected this particular pair of starts: -from a shared start, the code before the epic trailed the reference by 2.4e-4 after 100 iterations, which offset most of the difference between the two starts. +Before those changes the same run showed 2.9e-5, which reflected this particular pair of starts: +from a shared start, that code trailed the reference by 2.4e-4 after 100 iterations, which offset most of the difference between the two starts. The update rule itself is compared from a shared start: pamica's seed-42 initialization is written into the reference's `load_*` files, and both sides run the harness settings for 100 iterations, the reference on one thread @@ -115,8 +115,8 @@ pamica's seed-42 initialization is written into the reference's `load_*` files, | Code | LL difference | Mean matched correlation | Amari distance | |---|---:|---:|---:| -| before epic #324 (e38aa11) | 2.4e-4 | 0.99999 | 5.8e-4 | -| epic #324 | 1.6e-6 | 0.99999993 | 3.9e-5 | +| before epic #324's changes to the fit (e38aa11) | 2.4e-4 | 0.99999 | 5.8e-4 | +| with them | 1.6e-6 | 0.99999993 | 3.9e-5 | The earlier row starts from that code's own initialization, which predates the component-row layout (issue #334) and the normalized initial mixing matrix (issue #341); from each code's seeded state, the reference's first-iteration log-likelihood matches pamica's to 9e-16, so the state was written in the orientation the reference reads. @@ -531,7 +531,7 @@ two float64 runs of the same code on CPU and CUDA differ by 2.3e-4, the backends and adding 1e-9 µV to one sample changes the torch-CPU value by 1.3e-15 after one iteration and 4.4e-4 after 25 (the trajectory has a likelihood decrease on its 25th iteration). The 70-channel differences are of the same size as that sensitivity, -and the code before epic #324 shows the same growth. +and the code before epic #324's changes to the fit (e38aa11) shows the same growth. NumPy is called without a seed here, so it starts from its own draw, which is why its column sits apart (by up to 4.2e-3 at 70 channels). The component-level float32 comparison is in [the per-backend rows](#parity-rows-per-backend): from a shared start, MLX float32 and PyTorch float64 agree to a mean matched correlation of 0.99999991 after 100 iterations. 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z{y=IH=S}g81A3`;qU%g5Ji=OZljGJjvxu|UCvP)!s=>M%`;3PP#x0}aI*D~YR$tYO z%ssA!AGlo?d7tmgsrc(=H436@Ou~3CS3K9CAI%Y@t13E%=k->!^Eg~$G4wJY-X%J9 gxuQOIn$3vy!K%otH%s_e%F1t5VuA=^k2cf)0M}nnRR910 From 7c40e982da4383cef19794870ee6d2258163a138 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:34:25 -0700 Subject: [PATCH 23/58] Re-state the bundled single-model and multi-model results --- docs/guides/validation.md | 186 +++++++++++++++++++++++--------------- 1 file changed, 113 insertions(+), 73 deletions(-) diff --git a/docs/guides/validation.md b/docs/guides/validation.md index c9d125c..37495d8 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -21,9 +21,9 @@ Throughout, IC abbreviates independent component and LL log-likelihood. | Source-density score and log-density (non-GG families) | vs the literal `amica15.f90` expressions | bit-exact ($<10^{-12}$) | | Per-block sufficient statistics and one M-step | vs Fortran | bit-exact ($\sim\!10^{-15}$) | | Single-model solution (`do_newton=0`, $k\approx153$) | log-likelihood, component correlation vs Fortran | LL within ~0.0005 of $-3.6993$; correlation 0.998 | -| Single-model solution (`do_newton=0`, bundled, $k\approx30$) | Amari distance vs Fortran | 0.006 | +| Single-model solution (`do_newton=0`, bundled, $k\approx30$) | Amari distance vs Fortran | 0.011 over the protocol's 5 run pairs, one of whose reference runs ended in another basin; 0.004 over 50 pairs (Fortran vs Fortran 0.005) | | Every backend against the reference (harness defaults, bundled) | `validate_implementations.py --backend all`: PyTorch, NumPy and MLX each vs Fortran | from independent starts: LL within 2.8e-4 (the reference's own seed-to-seed standard deviation is 2.6e-4), correlation 0.9991, Amari distance 0.004, for all three; from a shared start: LL within 1.6e-6, correlation 0.99999993 ([per-backend rows](#parity-rows-per-backend)) | -| Multi-model solution | distributional similarity over 20-run ensembles | indistinguishable from Fortran's own run-to-run spread ($p = 0.96$) | +| Multi-model solution | distributional similarity over 20-run ensembles | between-implementation correlation within 0.006 of Fortran's own run-to-run agreement (one-sided permutation $p = 0.88$; Amari distance $p = 0.051$); final log-likelihood $-3.3541$ against $-3.3543$ (KS $p = 0.83$) | | Device and precision invariance | same independent components across CPU/CUDA/MPS/MLX, float32/float64, Linux/macOS | identical (1.000) across all eight torch/MLX combinations | | Cross-backend log-likelihood | same settings and start, 25 iterations, every backend | agree to 1e-5 at 32 and 48 channels; at 70 channels ($k\approx6$) within 1.1e-3, the size of a round-off perturbation's effect ([details](#cross-backend-log-likelihood-agreement-single-model)) | | EEGLAB output | `write_amica_output` round-trip through `loadmodout15` | single-model bytes are an exact serialization; loads with correct layout | @@ -141,9 +141,31 @@ distance: - Log-likelihood ~ -3.6993 ($k\approx153$; Fortran ~ -3.6993, gap ~0.0003). - Hungarian-matched component correlation ~0.998 ($k\approx153$; Fortran-vs-Fortran self-consistency - over the same 5 seeds: ~0.999), clearing the >0.95 gate. On the bundled sample ($k\approx30$) both - numbers are consistent: ~0.998 pamica-vs-Fortran, ~0.998 Fortran-vs-Fortran. -- Amari distance ~0.006 (bundled sample; Fortran-vs-Fortran: ~0.005). + over the same 5 seeds: ~0.999), clearing the >0.95 gate. +- Amari distance on the bundled sample: 0.011 over the protocol's five run pairs, 0.004 over 50 pairs (next subsection). + +### The bundled sample + +On the bundled 32-channel sample ($k\approx30$) the reproduction tier fits five pamica seeds (301-305) and five reference runs, one pair per seed, +Newton off, 2000 iterations (re-measured on 2026-09-23 with the code of epic #324; `.context/issue-351/raw/table1_bundled/`): + +| seed | reference final LL | pamica final LL | mean matched correlation | min matched correlation | Amari distance | +|---:|---:|---:|---:|---:|---:| +| 301 | -3.3995 | -3.3997 | 0.9995 | 0.9960 | 0.0031 | +| 302 | -3.3996 | -3.3996 | 0.9993 | 0.9952 | 0.0037 | +| 303 | -3.4006 | -3.3997 | 0.9267 | 0.4528 | 0.0380 | +| 304 | -3.3995 | -3.3995 | 0.9997 | 0.9981 | 0.0029 | +| 305 | -3.3996 | -3.3994 | 0.9982 | 0.9893 | 0.0069 | + +The five pairs average a correlation of 0.985 and an Amari distance of 0.011; +the ten pairs among the five reference runs average 0.971 and 0.019. +The reference run of seed 303 ended in a lower-likelihood basin (-3.4006, against -3.3995 to -3.3996 for the other four), and its pair sets the five-pair means. +The tier does not seed its reference runs (`AMICANative` draws a clock-based seed per run), so a rerun draws new starts, and an event like this one may or may not recur. +With the unmixing matrices kept (`.context/issue-351/bundled_single_basins.py`), +ten seeded reference runs (seeds 1-10, final LL -3.39984 to -3.39945) against the same five pamica fits give, over all 50 pairs, +a mean Amari distance of 0.0044 (largest 0.0083) and a mean correlation of 0.9988; +the reference against itself, over 45 pairs, 0.0054 (largest 0.0101) and 0.9985; pamica against itself, over 10 pairs, 0.0039 and 0.9991. +Before epic #324 the five-pair figures were an Amari distance of ~0.006 (Fortran against Fortran ~0.005) and a correlation of ~0.998. The fixed source-density families are bit-exact against the literal Fortran score/derivative expressions (~1e-15), and the backend converges to the binary's solution within ~0.005 log-likelihood on either dataset. @@ -192,100 +214,118 @@ See `pamica/tests/torch_tests/test_ng_pdf_families.py` and ADR 0002. ## Multi-model distributional similarity -Multi-model AMICA is not partition-identifiable, so exact partition parity with Fortran is the wrong acceptance bar. -The right test is whether the two implementations sample a similar distribution over solutions. Running an ensemble of `N = 20` fits per implementation on the bundled sample EEG (`n_models = 2`, 3 mixture components, 100 iterations, matched schedule), -the pamica-vs-Fortran partition cross-correlation distribution overlaps Fortran's own run-to-run distribution: +Multi-model AMICA is not partition-identifiable: fits from different starts reach different partitions of nearly the same likelihood, +so a single-run partition comparison with Fortran cannot serve as the acceptance bar. +The comparison is between the distributions of solutions the two implementations sample. +An ensemble of `N = 20` fits per implementation on the bundled sample EEG (`n_models = 2`, 3 mixture components, 100 iterations, matched schedule) +gives these distributions of pairwise agreement +(`benchmarks/reproduce_table1.py --tier bundled`, re-measured on 2026-09-23 with the code of epic #324 against the pinned v0.3.3 native binary, +whose runs here draw their own clock-based seeds; the 40 fits are saved in `.context/issue-351/raw/table1_bundled/bundled_multimodel_ensemble.npz`): | Distribution (pairwise Hungarian-matched \|corr\|) | Mean | SD | Range | |---|---:|---:|---| -| within-Fortran (Fortran vs Fortran) | 0.638 | 0.040 | [0.572, 0.797] | -| within-pamica (pamica vs pamica) | 0.661 | 0.045 | [0.583, 0.820] | -| between (pamica vs Fortran) | 0.649 | 0.045 | [0.582, 0.886] | +| within-Fortran (Fortran vs Fortran) | 0.626 | 0.036 | [0.568, 0.868] | +| within-pamica (pamica vs pamica) | 0.638 | 0.042 | [0.578, 0.805] | +| between (pamica vs Fortran) | 0.632 | 0.042 | [0.564, 0.845] | -![Multi-model solution-ensemble cross-correlation distributions for pamica and Fortran.](../assets/figures/multimodel-ensemble.png){ width=640 } +![Multi-model solution-ensemble cross-correlation and log-likelihood distributions for pamica and Fortran.](../assets/figures/multimodel-ensemble.png){ width=640 } /// caption -Pairwise Hungarian-matched component correlation for 20 pamica and 20 Fortran multi-model fits of the sample EEG. -The within-Fortran, within-pamica, and between-implementation distributions overlap: the estimators sample the same solution space. +Pairwise Hungarian-matched component correlation (A) and final log-likelihood (B) for 20 pamica and 20 Fortran multi-model fits of the sample EEG. +The three agreement distributions overlap, and so do the two likelihood distributions. /// -The three distribution means lie within 0.011 of each other (between 0.649, within-Fortran 0.638), well inside a $\pm 0.05$ margin. To test this at the correct unit of analysis, we use a **run-level permutation test**: -the 190/400 pairwise correlations are *not* independent (each of the 40 runs appears in ~39 pairs), +The three means lie within 0.012 of each other. +The between-minus-within-Fortran difference is +0.006, inside the $\pm 0.05$ margin the original study set +(run-level bootstrap 90% interval -0.002 to 0.014, `.context/issue-351/equivalence_check.py`). +The 190/400 pairwise values are not independent (each of the 40 runs appears in ~39 pairs), so a Mann-Whitney or TOST applied to the pairwise values is pseudoreplicated and its p-value is invalid. -Permuting the 40 runs as intact units instead (20000 permutations, statistic = within-Fortran minus between-implementation mean correlation) respects that dependence and finds **no evidence that cross-implementation agreement is worse than Fortran's own run-to-run agreement ($p = 0.96$)**. - -The single-run cross-correlation of ~0.65 is therefore intrinsic estimator spread, not a shortfall: Fortran agrees with *itself* at 0.64. -The per-block sufficient statistics and one M-step are bit-exact against Fortran (~$10^{-15}$), -so the update equations are correct; -a small residual in the log-likelihood *distribution* (pamica $-3.363 \pm 0.006$ vs Fortran $-3.354 \pm 0.003$; -Kolmogorov-Smirnov $p \approx 6\times10^{-5}$) is an optimizer-quality effect, -not a model-correctness defect (pamica reaches Fortran's mean with about twice as many iterations). +The significance test permutes the 40 runs as intact units instead (20000 permutations, statistic = within-Fortran minus between-implementation mean correlation). +For the one-sided hypothesis that cross-implementation agreement is worse than Fortran's own run-to-run agreement, it gives $p = 0.88$. + +The single-run cross-correlation of ~0.63 matches Fortran's agreement with itself (0.63), so it measures the estimator's run-to-run spread. +The per-block sufficient statistics and one M-step agree with the reference to round-off (~$3\times10^{-16}$ relative). +The final log-likelihoods agree too: pamica $-3.3541 \pm 0.003$, Fortran $-3.3543 \pm 0.002$ (Kolmogorov-Smirnov $p = 0.83$). +The ensembles of this study measured before epic #324's changes to the fit differed on this one metric +(pamica $-3.363 \pm 0.006$ against Fortran $-3.354 \pm 0.003$, $p \approx 6\times10^{-5}$), a gap attributed then to convergence speed. +Refitting the pamica half with that code (e38aa11) against the same 20 reference fits gives $-3.3627 \pm 0.006$ ($p = 1\times10^{-5}$), +and 7 of those 20 fits stop early on `min_dll`, whose check counted likelihood dips as small gains until issue #339 +(`.context/issue-351/multimodel_pamica_fits.py`). +A seeded ensemble with the same settings (the reference seeded 0-19 and single-threaded) agrees within $8\times10^{-4}$ at 100 iterations and within $2\times10^{-4}$ at 200 and 300 +([ADR 0003](https://github.com/sccn/pAMICA/blob/main/.context/decisions/0003-best-iterate-safeguard.md)). ### Amari distance: a second, assignment-free metric The correlation above needs a Hungarian assignment step to resolve component permutation before it can be computed. The Amari distance does not: it is permutation- and scale-invariant by construction, -so it is a genuinely independent check on the same 20-run ensembles (`.context/issue-27/ensemble.npz`; -recomputed by `.context/issue-27/amari_distance.py` with no re-fitting, since the raw unmixing matrices from the original 40 fits are already saved). +so it is an independent check on the same 20-run ensembles, computed from the saved unmixing matrices with no refitting +(`.context/issue-351/multimodel_ensemble.py`, which reuses `.context/issue-27/amari_distance.py`). Each stacked 2-model matrix is split into its per-model 32x32 blocks; since which Fortran model corresponds to which pamica model is not identified, both label pairings are tried and the lower-distance pairing is kept, per run pair. -This pairing correction is not free: on this ensemble it lowers the reported distance by ~0.02-0.03 versus always keeping the naive (unswapped) pairing, a similar order of magnitude to the within-Fortran/within-pamica gap below, so part of that gap plausibly reflects how often each group happens to need the swap, not just genuine agreement differences. +This pairing correction lowers the mean distance by 0.019 on this ensemble (333 of the 780 run pairs take the swapped pairing), +the same order as the gaps between the groups below, so part of those gaps may reflect how often each group needs the swap. | Distribution (Amari distance, lower is better) | Mean | SD | |---|---:|---:| -| within-Fortran (Fortran vs Fortran) | 0.174 | 0.023 | -| within-pamica (pamica vs pamica) | 0.154 | 0.019 | -| between (pamica vs Fortran) | 0.163 | 0.022 | +| within-Fortran (Fortran vs Fortran) | 0.166 | 0.017 | +| within-pamica (pamica vs pamica) | 0.176 | 0.025 | +| between (pamica vs Fortran) | 0.172 | 0.022 | -The same run-level permutation test (20000 permutations, intact 40-run units) finds no evidence that between-implementation agreement is worse than Fortran's own run-to-run agreement ($p > 0.999$), agreeing with the correlation-based conclusion above. +By this metric pamica's ensemble spreads slightly more than the reference's (0.176 against 0.166), +and the between-implementation distance lies between the two: +0.005 from within-Fortran (bootstrap 90% interval 0.002 to 0.009). +The same one-sided run-level permutation test gives $p = 0.051$. +Before epic #324's changes to the fit, pamica's ensemble was the tighter one: +refit with that code against the same reference fits, within-pamica 0.151 and between 0.160 ($p = 0.998$), +and the original ensembles of this study measured 0.154 and 0.163 against the bundled `amica15mac` binary's 0.174 ($p > 0.999$). ??? note "Per-run detail (all 40 runs, both metrics)" Table 1 in the paper and the group summaries above report distribution means; the table below gives each of the 40 runs' own mean agreement to its own group's other 19 runs (`within`) and to all 20 opposite-implementation runs (`between`), for both metrics. - Regenerate with `uv run python .context/issue-27/amari_distance.py`, which writes `.context/issue-27/per_run_detail.csv`. + Regenerate with `uv run python .context/issue-351/multimodel_ensemble.py --from-npz .context/issue-351/raw/table1_bundled/bundled_multimodel_ensemble.npz`, + which writes `.context/issue-351/per_run_detail.csv` (with each run's final log-likelihood) and the figure above. | implementation | run | corr within | corr between | Amari within | Amari between | |---|---:|---:|---:|---:|---:| - | Fortran | 0 | 0.6164 | 0.6274 | 0.1880 | 0.1745 | - | Fortran | 1 | 0.6292 | 0.6568 | 0.1784 | 0.1592 | - | Fortran | 2 | 0.6465 | 0.6396 | 0.1694 | 0.1654 | - | Fortran | 3 | 0.6593 | 0.6740 | 0.1627 | 0.1508 | - | Fortran | 4 | 0.6323 | 0.6522 | 0.1797 | 0.1629 | - | Fortran | 5 | 0.6692 | 0.6773 | 0.1590 | 0.1488 | - | Fortran | 6 | 0.6660 | 0.6808 | 0.1628 | 0.1502 | - | Fortran | 7 | 0.6341 | 0.6400 | 0.1786 | 0.1678 | - | Fortran | 8 | 0.6285 | 0.6491 | 0.1779 | 0.1663 | - | Fortran | 9 | 0.6212 | 0.6341 | 0.1835 | 0.1702 | - | Fortran | 10 | 0.6308 | 0.6414 | 0.1794 | 0.1663 | - | Fortran | 11 | 0.6297 | 0.6444 | 0.1736 | 0.1614 | - | Fortran | 12 | 0.6334 | 0.6416 | 0.1782 | 0.1690 | - | Fortran | 13 | 0.6513 | 0.6630 | 0.1693 | 0.1574 | - | Fortran | 14 | 0.6666 | 0.6689 | 0.1584 | 0.1540 | - | Fortran | 15 | 0.6231 | 0.6254 | 0.1827 | 0.1750 | - | Fortran | 16 | 0.6147 | 0.6258 | 0.1903 | 0.1755 | - | Fortran | 17 | 0.6280 | 0.6483 | 0.1749 | 0.1632 | - | Fortran | 18 | 0.6441 | 0.6371 | 0.1691 | 0.1665 | - | Fortran | 19 | 0.6389 | 0.6505 | 0.1733 | 0.1637 | - | pamica | 0 | 0.6317 | 0.6149 | 0.1690 | 0.1806 | - | pamica | 1 | 0.6935 | 0.6777 | 0.1440 | 0.1529 | - | pamica | 2 | 0.6624 | 0.6583 | 0.1545 | 0.1606 | - | pamica | 3 | 0.6406 | 0.6459 | 0.1527 | 0.1561 | - | pamica | 4 | 0.6493 | 0.6384 | 0.1506 | 0.1569 | - | pamica | 5 | 0.6755 | 0.6591 | 0.1548 | 0.1622 | - | pamica | 6 | 0.6339 | 0.6236 | 0.1677 | 0.1807 | - | pamica | 7 | 0.6809 | 0.6788 | 0.1417 | 0.1479 | - | pamica | 8 | 0.6780 | 0.6552 | 0.1508 | 0.1631 | - | pamica | 9 | 0.6270 | 0.6206 | 0.1703 | 0.1823 | - | pamica | 10 | 0.6855 | 0.6665 | 0.1474 | 0.1612 | - | pamica | 11 | 0.6739 | 0.6556 | 0.1506 | 0.1612 | - | pamica | 12 | 0.6321 | 0.6190 | 0.1617 | 0.1753 | - | pamica | 13 | 0.6639 | 0.6610 | 0.1519 | 0.1597 | - | pamica | 14 | 0.6866 | 0.6849 | 0.1460 | 0.1520 | - | pamica | 15 | 0.6944 | 0.6672 | 0.1417 | 0.1559 | - | pamica | 16 | 0.6576 | 0.6533 | 0.1551 | 0.1633 | - | pamica | 17 | 0.6435 | 0.6249 | 0.1615 | 0.1756 | - | pamica | 18 | 0.6753 | 0.6547 | 0.1442 | 0.1549 | - | pamica | 19 | 0.6302 | 0.6180 | 0.1562 | 0.1655 | + | Fortran | 0 | 0.6169 | 0.6061 | 0.1710 | 0.1853 | + | Fortran | 1 | 0.6348 | 0.6508 | 0.1615 | 0.1593 | + | Fortran | 2 | 0.6145 | 0.6064 | 0.1756 | 0.1876 | + | Fortran | 3 | 0.6250 | 0.6356 | 0.1655 | 0.1684 | + | Fortran | 4 | 0.6290 | 0.6424 | 0.1654 | 0.1663 | + | Fortran | 5 | 0.6118 | 0.6047 | 0.1707 | 0.1853 | + | Fortran | 6 | 0.6268 | 0.6334 | 0.1610 | 0.1648 | + | Fortran | 7 | 0.6238 | 0.6247 | 0.1700 | 0.1765 | + | Fortran | 8 | 0.6332 | 0.6471 | 0.1643 | 0.1696 | + | Fortran | 9 | 0.6344 | 0.6458 | 0.1606 | 0.1648 | + | Fortran | 10 | 0.6057 | 0.6019 | 0.1782 | 0.1876 | + | Fortran | 11 | 0.6353 | 0.6534 | 0.1627 | 0.1631 | + | Fortran | 12 | 0.6182 | 0.6147 | 0.1680 | 0.1796 | + | Fortran | 13 | 0.6497 | 0.6503 | 0.1590 | 0.1642 | + | Fortran | 14 | 0.6270 | 0.6343 | 0.1637 | 0.1679 | + | Fortran | 15 | 0.6315 | 0.6322 | 0.1653 | 0.1715 | + | Fortran | 16 | 0.6101 | 0.6119 | 0.1701 | 0.1772 | + | Fortran | 17 | 0.6181 | 0.6287 | 0.1698 | 0.1718 | + | Fortran | 18 | 0.6428 | 0.6764 | 0.1596 | 0.1537 | + | Fortran | 19 | 0.6222 | 0.6371 | 0.1638 | 0.1664 | + | pamica | 0 | 0.6507 | 0.6421 | 0.1703 | 0.1671 | + | pamica | 1 | 0.6491 | 0.6338 | 0.1687 | 0.1687 | + | pamica | 2 | 0.6264 | 0.6206 | 0.1829 | 0.1785 | + | pamica | 3 | 0.6277 | 0.6324 | 0.1860 | 0.1730 | + | pamica | 4 | 0.6390 | 0.6358 | 0.1804 | 0.1706 | + | pamica | 5 | 0.5984 | 0.6025 | 0.1983 | 0.1880 | + | pamica | 6 | 0.6608 | 0.6492 | 0.1605 | 0.1615 | + | pamica | 7 | 0.6266 | 0.6175 | 0.1823 | 0.1786 | + | pamica | 8 | 0.6177 | 0.6205 | 0.1859 | 0.1751 | + | pamica | 9 | 0.6587 | 0.6442 | 0.1633 | 0.1644 | + | pamica | 10 | 0.6385 | 0.6269 | 0.1747 | 0.1749 | + | pamica | 11 | 0.6291 | 0.6259 | 0.1800 | 0.1752 | + | pamica | 12 | 0.6608 | 0.6499 | 0.1642 | 0.1631 | + | pamica | 13 | 0.6591 | 0.6456 | 0.1638 | 0.1665 | + | pamica | 14 | 0.6237 | 0.6252 | 0.1823 | 0.1733 | + | pamica | 15 | 0.6357 | 0.6361 | 0.1795 | 0.1704 | + | pamica | 16 | 0.6256 | 0.6219 | 0.1789 | 0.1720 | + | pamica | 17 | 0.6408 | 0.6326 | 0.1784 | 0.1742 | + | pamica | 18 | 0.6173 | 0.6221 | 0.1868 | 0.1751 | + | pamica | 19 | 0.6663 | 0.6528 | 0.1574 | 0.1609 | ## Cross-platform device and precision invariance @@ -661,7 +701,7 @@ uv run pytest # the full parity/beha ``` The multi-model ensemble and Amari detail regenerate from saved fits (no re-fitting) with -`uv run python .context/issue-27/amari_distance.py`. The cross-platform benchmark and equivalence +`uv run python .context/issue-351/multimodel_ensemble.py --from-npz .context/issue-351/raw/table1_bundled/bundled_multimodel_ensemble.npz`. The cross-platform benchmark and equivalence figures are produced by `benchmarks/benchmark_decompose.py` (and the sweep scripts alongside it); the underlying findings are in `.context/issue-84/` and `.context/issue-90/`. From 32a146d9b39814e688a006196bb3f2c54bb46946 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:35:44 -0700 Subject: [PATCH 24/58] Update keep_best and multi-model figures in AGENTS and guides --- .../decisions/0003-best-iterate-safeguard.md | 9 ++++-- .context/progress_summary.md | 14 ++++++---- AGENTS.md | 28 +++++++++++-------- docs/guides/amica-differences.md | 2 +- docs/guides/validation.md | 7 +++-- 5 files changed, 36 insertions(+), 24 deletions(-) diff --git a/.context/decisions/0003-best-iterate-safeguard.md b/.context/decisions/0003-best-iterate-safeguard.md index 6502b99..2e34ebb 100644 --- a/.context/decisions/0003-best-iterate-safeguard.md +++ b/.context/decisions/0003-best-iterate-safeguard.md @@ -104,7 +104,7 @@ on and off, on two seeds on both sides). their spread equals the reference's (sd ratio 1.0x, where #51 measured 12.7x and 2.0x). Phase 7 of the epic (#340) traced most of the old overshoots to the column-rule `doscaling` (#333). -- A restore fired once in the 60 fit-budget pairs: seed 3 at 300 iterations, +- A restore fired in one of the 20 fits, and only at the 300-iteration budget: seed 3, whose best iterate (iteration 299) beat its last by 4.2e-6. - The mean gap is gone at every budget: pamica's mean is within 8e-4 of the reference's at 100 iterations and within 2e-4 at 200 and 300, where #51 @@ -113,8 +113,11 @@ on and off, on two seeds on both sides). `AMICA` seeds 1-20) agrees: -3.3541 against -3.3543, KS p 0.83. Refitting that ensemble's pamica half with the code before the epic's changes to the fit (e38aa11) against the same 20 reference fits gives -3.3627 (sd 0.006, KS p 1e-5), close to - the #27/#51 figures; 7 of those 20 fits stopped early on `min_dll`, which - counted likelihood dips as small gains until #339. + the #27/#51 figures. Seven of those 20 fits stopped early on `min_dll`, + whose check counted likelihood dips as small gains until #339 (their mean + -3.3679), and the 13 that ran the full 100 iterations average -3.3600, so + the old gap came partly from the early stops and partly from the update + rule of that code. - The decision stands: `keep_best` stays on by default. With these fits it rarely acts, and when it does the gain is small, but a run that ends below its peak (a likelihood decrease near the end, or a Newton fallback) still diff --git a/.context/progress_summary.md b/.context/progress_summary.md index cc3df6e..ee4c6da 100644 --- a/.context/progress_summary.md +++ b/.context/progress_summary.md @@ -28,18 +28,20 @@ what remains, as of epic #324 (after v0.3.3). User-facing detail is in `docs/cha ### Multi-model AMICA (issue #27) - Validated by **distributional equivalence**: multi-model AMICA is not partition-identifiable, so - the NG-vs-Fortran partition cross-correlation distribution is statistically indistinguishable - from Fortran's own run-to-run spread (Mann-Whitney p=0.97, TOST within +/-0.05). Per-block - sufficient stats are bit-exact vs Fortran. + the NG-vs-Fortran partition cross-correlation distribution is compared with Fortran's own + run-to-run spread. Re-measured under epic #324 (#351): between minus within-Fortran +0.006 + (run-level permutation p=0.88; Amari +0.005, p=0.051), final LL -3.3541 vs -3.3543 (KS p=0.83). + Per-block sufficient stats agree with Fortran to round-off. - Per-model bias `c` update (`update_c`) ported to both backends, guarded to a no-op for `n_models=1` so single-model parity stays bit-exact. See `.context/issue-27/`. ### Best-iterate safeguard (issue #51) - `AMICATorchNG.fit` returns the highest-LL iterate (`keep_best`, default on; `final_ll_` reports the returned iterate's LL, `ll_history` keeps the true trajectory), not the last iterate under - the non-monotone lrate schedule. Cuts multi-model LL sd from 12.7x to 2.0x Fortran's at a - matched 100-iter budget. Single-model #24 parity stays bit-exact (monotone => no restore). See - ADR 0003. + the non-monotone lrate schedule. It cut multi-model LL sd from 12.7x to 2.0x Fortran's at a + matched 100-iter budget; re-measured under epic #324 (#351) the sd ratio is 1.0x with or without + it, and a restore fired in one of 20 seeded fits (300-iteration budget only). Single-model #24 parity stays bit-exact + (monotone => no restore). See ADR 0003. ### Degenerate-fit contract (issues #50, #306, #339) - The `AMICA` wrapper no longer treats a degenerate fit (`stop_reason` nan_ll / singular_ll / diff --git a/AGENTS.md b/AGENTS.md index d989e13..362aa85 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -179,12 +179,14 @@ update from a merged state seeded through `load_comp_list` matches it to float64 - **Multi-model (#27): VALIDATED by distributional equivalence.** Multi-model AMICA is not partition-identifiable, so exact partition parity with Fortran is the wrong acceptance bar (the `>0.95` cross-corr in #27's title asks the algorithm to be more identifiable than it is). The right - test is whether the two implementations sample the same distribution over solutions. On an - N=20-each ensemble (real sample EEG, `n_models=2`), the NG-vs-Fortran partition cross-corr - distribution is **statistically equivalent to Fortran's own run-to-run distribution** (Mann-Whitney - p=0.97, TOST equivalent within ±0.05; within-Fortran/within-NG/between all ~0.63-0.64). The - single-run ~0.64 cross-corr is intrinsic estimator spread, not a defect -- Fortran agrees with - *itself* at 0.63. See `.context/issue-27/multimodel_distributional_equivalence.md` (+ figure). + test is whether the two implementations sample the same distribution over solutions. Re-measured + under epic #324 (#351, N=20 each, real sample EEG, `n_models=2`, pinned v0.3.3 binary): mean + pairwise cross-corr within-Fortran 0.626, within-pamica 0.638, between 0.632; between minus + within-Fortran +0.006 (inside the ±0.05 margin; run-level permutation p=0.88; by Amari distance + +0.005, p=0.051, pamica's ensemble spreading slightly more than Fortran's); final LL -3.3541 vs + -3.3543 (KS p=0.83). The single-run ~0.63 cross-corr matches Fortran's agreement with itself. + See `docs/guides/validation.md`, `.context/issue-351/` and, for the pre-epic record, + `.context/issue-27/multimodel_distributional_equivalence.md`. Supporting: per-block sufficient stats are bit-exact vs Fortran; the per-model bias `c` update (Fortran `update_c`: `c[i,h] = sum_t v_h*x / sum_t v_h`) is ported to both backends, guarded to a no-op for `n_models=1` (single-model parity stays bit-exact), see @@ -194,11 +196,15 @@ update from a merged state seeded through `load_comp_list` matches it to float64 variance was driven by late Newton-fallback overshoots (one seed peaked at -3.357 then crashed to -3.545 in its final iterations). `AMICATorchNG.fit` now returns the highest-LL iterate (`keep_best`, default on; `final_ll_` reports the returned iterate's LL, `ll_history` stays the true trajectory). - At matched 100-iter budget this cuts the LL sd from 12.7x to 2.0x Fortran's; the residual ~0.009 - mean gap is convergence speed, not a worse optimum (at 200 iters NG reaches Fortran's exact mean - -3.3541, at 300 it exceeds it -- the M-step is bit-exact vs Fortran). Single-model #24 parity stays - byte-for-byte (monotone => no restore). Inactive under `do_reject`. See ADR 0003 and - `.context/issue-51/`. + At a matched 100-iter budget it cut the LL sd from 12.7x to 2.0x Fortran's (the residual ~0.009 mean + gap was then read as convergence speed). Re-measured under epic #324 (#351, seeded 20-run ensemble + against the pinned binary): the late overshoots are gone (largest LL dip 1.2e-5 in 20 trajectories, + no Newton fallbacks), the sd ratio is 1.0x at 100 iterations with or without `keep_best`, a restore + fired in one of 20 seeded fits, at the 300-iteration budget only (gain 4.2e-6), and the mean gap is + +8e-4 at 100 iterations and within 2e-4 at 200 and 300. The pre-epic code on the same seeds + reproduces the old gap; 7 of its 20 fits stopped early on a `min_dll` check that counted LL dips as + small gains (fixed in #339), and its full-length fits trail by 0.006. `keep_best` stays on. Single-model #24 parity stays byte-for-byte (monotone => no + restore). Inactive under `do_reject`. See ADR 0003 and `.context/issue-351/`. ## Development Workflow 1. **Check context:** `.context/plan.md` for current tasks and priorities. diff --git a/docs/guides/amica-differences.md b/docs/guides/amica-differences.md index ebc6338..aa14fef 100644 --- a/docs/guides/amica-differences.md +++ b/docs/guides/amica-differences.md @@ -14,7 +14,7 @@ that is not listed, that is a bug worth |---|---|---|---|---|---| | 1 | Rank threshold | absolute floor `mineig=1e-15` | relative floor `mineig_rel=1e-12` | the absolute floor is unit-dependent: MEG in Tesla yields rank 0, and average-referenced EEG is detected by luck | `mineig_rel=None` | | 2 | Zero numerical rank | `numeigs = 0`, continues | `ValueError` naming cause and fix | fitting a zero-dimensional model is not a recoverable state | none (no reason to want it) | -| 3 | Returned iterate | last EM iterate | highest-likelihood iterate (`keep_best`) | the lrate schedule is non-monotone; late Newton overshoots cut LL variance 12.7x → 2.0x | `keep_best=False` | +| 3 | Returned iterate | last EM iterate | highest-likelihood iterate (`keep_best`) | the lrate schedule is non-monotone, so a fit can end below its peak (before epic #324, late Newton overshoots made the multi-model LL sd 12.7x Fortran's, 2.0x with `keep_best`; with the epic's code a restore fired in one of 20 seeded fits, at the 300-iteration budget only; ADR 0003) | `keep_best=False` | | 4 | Newton | off in the compiled defaults (amica15_header.f90:19); the bundled `input.param` turns it on (`do_newton 1`) | off | the compiled default; Newton-off fits isolate the algorithm from initialization for parity work | `do_newton=True`, as the bundled `input.param` sets | | 5 | Degenerate fits | returns NaN sources, and writes them out on its `writestep` cadence | the `AMICA` wrapper, on either backend, refuses `transform`/`get_*`/`save`; the raw `AMICATorchNG`, `AMICAMLXNG` and NumPy `AMICA` backends refuse their own output accessors on a degenerate fit too (issue #306); NumPy additionally reports `converged=False` with a `stop_reason`, refuses the final write, and skips each periodic checkpoint with a logged reason (leaving the last valid one on disk). Every backend stops before a non-finite value is applied or returned: a non-finite likelihood (`nan_ll`, or `singular_ll` for an infinite one; never recorded in the history), update direction (`nan_direction`) or parameter after an update (`nan_params`), where the reference applies a NaN step and exits on the next likelihood | NaN sources silently poison downstream analysis, and `loadmodout` reads a NaN checkpoint back without complaint | none (see issues #50, #240, #306 and #339) | | 6 | Precision | float64 | float64 (float32 on Apple GPUs) | Apple GPUs have no float64; float32 agrees to ~7 significant digits, not bit-parity | `dtype=torch.float64` | diff --git a/docs/guides/validation.md b/docs/guides/validation.md index 37495d8..79ac3e9 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -247,9 +247,10 @@ The per-block sufficient statistics and one M-step agree with the reference to r The final log-likelihoods agree too: pamica $-3.3541 \pm 0.003$, Fortran $-3.3543 \pm 0.002$ (Kolmogorov-Smirnov $p = 0.83$). The ensembles of this study measured before epic #324's changes to the fit differed on this one metric (pamica $-3.363 \pm 0.006$ against Fortran $-3.354 \pm 0.003$, $p \approx 6\times10^{-5}$), a gap attributed then to convergence speed. -Refitting the pamica half with that code (e38aa11) against the same 20 reference fits gives $-3.3627 \pm 0.006$ ($p = 1\times10^{-5}$), -and 7 of those 20 fits stop early on `min_dll`, whose check counted likelihood dips as small gains until issue #339 +Refitting the pamica half with that code (e38aa11) against the same 20 reference fits gives $-3.3627 \pm 0.006$ ($p = 1\times10^{-5}$) (`.context/issue-351/multimodel_pamica_fits.py`). +Seven of those 20 fits stop early on `min_dll`, whose check counted likelihood dips as small gains until issue #339 (mean $-3.3679$), +and the 13 that run the full 100 iterations average $-3.3600$, so the old gap came partly from the early stops and partly from the update rule of that code. A seeded ensemble with the same settings (the reference seeded 0-19 and single-threaded) agrees within $8\times10^{-4}$ at 100 iterations and within $2\times10^{-4}$ at 200 and 300 ([ADR 0003](https://github.com/sccn/pAMICA/blob/main/.context/decisions/0003-best-iterate-safeguard.md)). @@ -586,7 +587,7 @@ guarded to a no-op so the parity results above stay byte-for-byte unchanged. | Behavior | Status | Validation | |---|---|---| -| Best-iterate safeguard (`keep_best`, #51) | on by default | returns the highest-LL iterate; cuts multi-model LL sd from 12.7x to 2.0x Fortran's. Single-model parity stays bit-exact (monotone, no restore). ADR 0003 | +| Best-iterate safeguard (`keep_best`, #51) | on by default | returns the highest-LL iterate. It cut the multi-model LL sd from 12.7x to 2.0x Fortran's before epic #324; re-measured with the epic's code, the sd ratio is 1.0x with or without it and a restore fired in one of 20 seeded fits, at the 300-iteration budget only (gain 4.2e-6). Single-model parity stays bit-exact (monotone, no restore). ADR 0003 | | Per-model bias `c` update (#27) | on for `n_models>1` | Fortran `update_c`; per-block stats bit-exact; no-op for `n_models=1` | | Component sharing (`share_comps`, #60, #334) | off by default | Fortran `identify_shared_comps` ported; the scan itself has no bit-exact oracle (`Spinv2` is never allocated, so the reference's scan computes NaN similarities and never merges), but the update from a merged state seeded through the reference's `load_comp_list` matches the native binary to float64 round-off on PyTorch and NumPy (`test_component_rows.py`, opt-in with `AMICA_RUN_FORTRAN=1`); byte-identical when unshared | | Outlier rejection (`do_reject`, #123) | off by default | `good_idx` mechanism on all three backends (NumPy, PyTorch, MLX -- the last landed epic #278 Phase 3, #289); MLX/NumPy ports validated vs the PyTorch backend | From 551cd7296ed1b5de3d71eb971f8a42d44885d737 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:36:06 -0700 Subject: [PATCH 25/58] Update the fixture parity figures in AGENTS and progress summary --- .context/progress_summary.md | 3 ++- AGENTS.md | 8 +++++--- 2 files changed, 7 insertions(+), 4 deletions(-) diff --git a/.context/progress_summary.md b/.context/progress_summary.md index ee4c6da..bb0b216 100644 --- a/.context/progress_summary.md +++ b/.context/progress_summary.md @@ -16,7 +16,8 @@ what remains, as of epic #324 (after v0.3.3). User-facing detail is in `docs/cha - Newton is ported from the NumPy reference and stays positive-definite (0 fallbacks on the sample data). - **Metrics:** single-model LL ~ -3.40 (Fortran -3.4018); Hungarian-matched component correlation - ~0.997, clearing the >0.95 gate. + ~0.997, clearing the >0.95 gate. Re-measured under epic #324 (#351) against the bundled + 200-iteration fixture: LL -3.4017 vs -3.4019, correlation 0.998, Amari 4.8e-3, on all three backends. ### Adaptive PDF selection (issue #26) - All five `amica15.f90` `pdftype` density families ported to `AMICATorchNG`: 0 generalized diff --git a/AGENTS.md b/AGENTS.md index 362aa85..0f0c597 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -113,8 +113,9 @@ remaining MLX gap vs the PyTorch backend is float32-only precision (Apple GPUs h ## Current Status - PyTorch backend with GPU/MPS/CPU support; the `AMICATorchNG` natural-gradient EM backend now - matches the Fortran reference (LL ~ -3.40, component correlation ~0.997) with Newton enabled - and positive-definite (issue #24). + matches the Fortran reference with Newton enabled and positive-definite (issue #24): against the + bundled 200-iteration `amicaout` fixture, LL -3.4017 vs -3.4019 and component correlation 0.998 on + all three backends (re-measured under epic #324 in #351; ~0.997 when #24 closed). - `AMICA(backend="mlx")` and `AMICAICA(backend="mlx")` (epic #324 Phase 4, #313) run the MLX backend end to end: fit, `from_params_file`, `pcakeep`, the #50 degenerate-fit contract, `.pt` save/load (wrapper `format_version` 2 records the backend; version 1 still loads as torch), EEGLAB export and MNE `apply`. @@ -140,7 +141,8 @@ remaining MLX gap vs the PyTorch backend is float32-only precision (Apple GPUs h **Single-model parity: DONE (#24).** The natural-gradient A-update transpose fix (plus exact-EM mixture updates, digamma rho update, symmetric-ZCA sphere, Jacobian LL) brought both `AMICATorchNG` and the legacy NumPy `numpy_impl/core.py` to Fortran's solution (LL ~ -3.40, Hungarian-matched component -correlation ~0.997, > 0.95 gate cleared; root cause in `.context/issue-24/`). Also resolved: Newton +correlation ~0.997 at the time and 0.998 re-measured under epic #324, > 0.95 gate cleared; root cause +in `.context/issue-24/`). Also resolved: Newton stability (posdef, 0 fallbacks), backend consolidation (#32/#31), NumPy CLI save/load format (#30), NG save/load persistence (#36), and the degenerate-fit contract (#50: the `AMICA` wrapper marks a degenerate fit unusable via `converged_`/`stop_reason_` and refuses `transform`/`get_*`/`save`, From f766aff8d99de81faec1c282a83a6dce79af3604 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:36:42 -0700 Subject: [PATCH 26/58] Record the bundled tier wall-clock on the M4 Pro --- benchmarks/README_dimsweep.md | 21 ++++++++++++--------- 1 file changed, 12 insertions(+), 9 deletions(-) diff --git a/benchmarks/README_dimsweep.md b/benchmarks/README_dimsweep.md index 2ef1d66..041eeef 100644 --- a/benchmarks/README_dimsweep.md +++ b/benchmarks/README_dimsweep.md @@ -95,15 +95,18 @@ sample. Read this section before running the external tier -- it is not a quick **Bundled tier** (`--tier bundled`, default): uses `pamica/sample_data/eeglab_data.fdt` (32 channels, 30,504 frames, already committed -- no download). Default budget is 5 single-model seeds at 2000 iterations plus a 20-run multi-model ensemble at 100 iterations (matching -`docs/guides/validation.md`'s documented protocol). Measured end to end on a 2026 Apple Silicon -laptop (10 cores, no CUDA, MPS unusable here because these runs are float64 -- see below): - -| phase | measured | -|---|---| -| single-model sweep (5 seeds x 2000 iter, Fortran + pamica) | ~24 min | -| multi-model ensemble (20 runs x 100 iter, Fortran + pamica) | ~9 min | -| score-function / sufficient-statistics check | <1 s | -| **total** | **~33 min** | +`docs/guides/validation.md`'s documented protocol). Measured end to end on two Apple Silicon hosts +(no CUDA; MPS unusable here because these runs are float64 -- see below): + +| phase | 2026 laptop, 10 cores | Apple M4 Pro, 14 cores, 2026-09-23 (issue #351) | +|---|---|---| +| single-model sweep (5 seeds x 2000 iter, Fortran + pamica) | ~24 min | ~32 min | +| multi-model ensemble (20 runs x 100 iter, Fortran + pamica) | ~9 min | ~15 min | +| score-function / sufficient-statistics check | <1 s | <1 s | +| **total** | **~33 min** | **~47 min** | + +The M4 Pro run (`--threads 4`, `OMP_NUM_THREADS=4`, the code of epic #324) shared the machine with other +benchmark jobs (load average 10-24), so its times are an upper bound for that host. A `--n-seeds 2 --max-iter 100 --multimodel-runs 2 --multimodel-max-iter 20` smoke test (not the paper's protocol -- noisier numbers, just a pipeline check) completes in well under a minute. From 40e8129d09f936b4b24556b8029ba050f4bcfcdc Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 15:37:47 -0700 Subject: [PATCH 27/58] Update the cross-backend LL claim in the backends guide --- docs/guides/backends.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/docs/guides/backends.md b/docs/guides/backends.md index 4f8fca5..0a321f8 100644 --- a/docs/guides/backends.md +++ b/docs/guides/backends.md @@ -159,7 +159,9 @@ Measured on real 70-channel EEG (see the project benchmarks and - On **CPU**, intra-op threads are workload-limited; around 4 threads was the sweet spot in the measured laptop sweep, with 8+ regressing. -All backends agree on the log-likelihood to ~3 significant digits on real data. +With the same settings and the same start, the backends' log-likelihoods after 25 iterations of the throughput sweep agree to 1e-5 at 32 and 48 channels; +at 70 channels on its 30000 frames ($k\approx6$) they differ by up to 1e-3, about the effect of perturbing one sample by 1e-9 µV +([details](validation.md#cross-backend-log-likelihood-agreement-single-model)). !!! note "Cross-backend equivalence and data adequacy" Whether two backends recover the *same* independent components depends on how From 6149814cb9626ca0e41fb2bcc198e277135a6198 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 16:42:23 -0700 Subject: [PATCH 28/58] Record the Amari pairing-correction measurement --- .context/issue-351/raw/multimodel/pairing_correction.txt | 1 + 1 file changed, 1 insertion(+) create mode 100644 .context/issue-351/raw/multimodel/pairing_correction.txt diff --git a/.context/issue-351/raw/multimodel/pairing_correction.txt b/.context/issue-351/raw/multimodel/pairing_correction.txt new file mode 100644 index 0000000..2b255cf --- /dev/null +++ b/.context/issue-351/raw/multimodel/pairing_correction.txt @@ -0,0 +1 @@ +new ensemble (bundled tier, 780 run pairs): mean naive 0.1899 best 0.1714; reduction mean 0.0185, median 0.0000, max 0.1552; pairs swapped 333 of 780 From fbc9c3173f94b4baf19f9c639d728c4a5b49ddf2 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 16:43:37 -0700 Subject: [PATCH 29/58] Update paper Table 1 bundled rows and the float32 paragraph --- paper.md | 40 ++++++++++++++++++++++------------------ 1 file changed, 22 insertions(+), 18 deletions(-) diff --git a/paper.md b/paper.md index 83a7341..e4b9aa5 100644 --- a/paper.md +++ b/paper.md @@ -95,32 +95,36 @@ With Newton enabled and independent seeds, some of the weakest components settle on one seed of three this affected ten of seventy components, while the other two matched the reference at ~0.99. A matched initialization restores ~0.997, so this is a property of the initialization, not a parity defect. The single-model comparison uses a well-determined external recording ([NEMAR on002718](https://doi.org/10.82901/nemar.on002718), $k\approx153$, where $k$ = frames over squared channel count [@frank2025sufficient]) alongside the bundled 32-channel sample ($k\approx30$). -A mixture of ICA models is not partition-identifiable, so exact partition parity is the wrong bar there; -it is judged instead by whether the implementations sample a similar distribution of solutions, over ensembles of 20 runs each (\autoref{fig:ensemble}). -A permutation test finds no evidence that cross-implementation agreement is worse than Fortran's own run-to-run agreement. +On the bundled sample one of the five reference runs ended in a lower-likelihood basin and sets the five-pair Amari mean; +over 50 run pairs the distance between the implementations (0.004) is close to the reference's own run-to-run distance (0.005). +A mixture of ICA models is not partition-identifiable, +so the implementations are compared by the distributions of solutions they sample, over ensembles of 20 runs each (\autoref{fig:ensemble}). +One-sided run-level permutation tests of whether cross-implementation agreement is worse than the reference's own run-to-run agreement +give $p=0.88$ by correlation and $p=0.051$ by Amari distance, by which `pamica`'s ensemble spreads slightly more than the reference's. | Regime | Metric (dataset) | Result (mean) | |---|---|---| | Single | Log-likelihood gap (on002718) | within ~0.0005 of $-3.6993$ | | Single | Component correlation (on002718) | 0.998 | -| Single | Amari distance (bundled) | 0.006 | -| Single | Score functions, sufficient statistics | exact, $\sim\!10^{-15}$ | -| Multi | Correlation, one run: cross; within-Fortran | 0.65; 0.64 (sd 0.05) | -| Multi | Amari, one run: cross; within-Fortran | 0.163; 0.174 (sd 0.02) | -| Multi | Ensemble agreement, cross $-$ within-Fortran | correlation $+0.011$ ($p=0.96$); Amari $-0.011$ ($p>0.999$) | -| Multi | Ensemble log-likelihood: Fortran; `pamica` | $-3.3539$; $-3.3629$ (Kolmogorov-Smirnov $p=6\times10^{-5}$) | +| Single | Amari distance (bundled) | 0.011 (5 run pairs); 0.004 (50 pairs) | +| Single | Score functions, sufficient statistics | round-off, $\le 2\times10^{-15}$ (relative) | +| Multi | Correlation, one run: cross; within-Fortran | 0.632; 0.626 (sd 0.04) | +| Multi | Amari, one run: cross; within-Fortran | 0.172; 0.166 (sd 0.02) | +| Multi | Ensemble agreement, cross $-$ within-Fortran | correlation $+0.006$ ($p=0.88$); Amari $+0.005$ ($p=0.051$) | +| Multi | Ensemble log-likelihood: Fortran; `pamica` | $-3.3543$; $-3.3541$ (Kolmogorov-Smirnov $p=0.83$) | -: Parity of `pamica` with the Fortran reference. Multi-model rows are over 20-run ensembles (190 within-, 400 cross-implementation pairs); sd is the standard deviation, given where computed. -The final row is the one metric on which the ensembles differ significantly, and it is convergence speed rather than optimum quality: `pamica` reaches Fortran's mean by 200 iterations and passes it by 300. +: Parity of `pamica` with the Fortran reference. Multi-model rows are over 20-run ensembles (190 within-, 400 cross-implementation pairs); sd is the standard deviation, given where computed; +$p$ values are one-sided run-level permutation tests. ![Multi-model ensemble partition-correlation (A) and log-likelihood (B) distributions, 20 `pamica` and 20 Fortran fits of the sample EEG; dashed lines mark each mean. -A's three distributions overlap, so the single-run correlation reflects intrinsic run-to-run spread, not a gap to the reference. -B's separation is Table 1's 0.009 gap on a ~0.035 axis.\label{fig:ensemble}](docs/assets/figures/multimodel-ensemble.png){ width=100% } +A's three distributions overlap: the single-run correlation of ~0.63 matches the reference's agreement with itself. +B's two means lie 0.0002 apart on a ~0.02 axis.\label{fig:ensemble}](docs/assets/figures/multimodel-ensemble.png){ width=100% } -All backends converge to the same single-model log-likelihood on real EEG (maximum pairwise difference ~0.003), -and single precision matches double to four or five significant digits on that log-likelihood. -Component-level float32 agreement is not yet characterized at a matched iteration budget, so float64 remains the default for parity work, -and double-precision CUDA is the reproducible NVIDIA path. +From a shared start with the harness settings, the single-precision MLX backend and the double-precision PyTorch backend differ by $5\times10^{-6}$ in log-likelihood after 100 iterations, +with mean matched component correlation 0.9999999 and Amari distance $5\times10^{-5}$. +With the same settings and start, the backends' 25-iteration log-likelihoods agree to $10^{-5}$ on 32 and 48 channels of the external recording; +on a 70-channel excerpt of 30,000 frames ($k\approx6$) they differ by up to $10^{-3}$, about the effect of perturbing one sample by $10^{-9}$ µV. +Double precision remains the default for parity work, and double-precision CUDA is the reproducible NVIDIA path. On real 70-channel EEG at `block_size=512`, per-iteration cost is 25 ms for MLX on an Apple GPU, 39 ms for double-precision CUDA on an RTX 4090, and 30 ms for native Fortran on a 24-core i9-13900K, against 193 ms for PyTorch on an Apple-Silicon CPU and 255 ms for PyTorch-Metal. @@ -129,7 +133,7 @@ between `block_size=512` and `pamica`'s current 8192 default, still behind the C at a further-tuned single-block setting that is memory-limited rather than a free win, since peak block memory scales with `block_size`, which is why 8192 stays the shipped default. MLX stays the fastest Apple backend throughout the sweep. Full tables, the data-size sweep, and reproduction commands are in the [documentation](https://eeglab.org/pAMICA/guides/validation/); the correctness harness never uses synthetic data. -The harness and sample data ship with the package, and every row of Table 1 but the two on002718 entries re-runs from the bundled sample alone. +The harness and sample data are in the source repository, and every row of Table 1 but the two on002718 entries re-runs from the bundled sample alone. # Research impact statement From f701cf8102b9cacad0e2cdaa52b3b42f316d2a19 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 16:43:48 -0700 Subject: [PATCH 30/58] Clarify the benchmark excerpt in the paper --- paper.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/paper.md b/paper.md index e4b9aa5..cd17532 100644 --- a/paper.md +++ b/paper.md @@ -122,8 +122,8 @@ B's two means lie 0.0002 apart on a ~0.02 axis.\label{fig:ensemble}](docs/assets From a shared start with the harness settings, the single-precision MLX backend and the double-precision PyTorch backend differ by $5\times10^{-6}$ in log-likelihood after 100 iterations, with mean matched component correlation 0.9999999 and Amari distance $5\times10^{-5}$. -With the same settings and start, the backends' 25-iteration log-likelihoods agree to $10^{-5}$ on 32 and 48 channels of the external recording; -on a 70-channel excerpt of 30,000 frames ($k\approx6$) they differ by up to $10^{-3}$, about the effect of perturbing one sample by $10^{-9}$ µV. +In the throughput benchmark's runs on a 30,000-frame excerpt of the external recording, the backends that share a start agree after 25 iterations to $10^{-5}$ in log-likelihood on 32 and 48 channels; +with 70 channels ($k\approx6$) they differ by up to $10^{-3}$, about the effect of perturbing one sample by $10^{-9}$ µV. Double precision remains the default for parity work, and double-precision CUDA is the reproducible NVIDIA path. 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++++++++++++++++++++++++++ 2 files changed, 54 insertions(+) create mode 100644 .context/issue-351/raw/gated_tests.log create mode 100644 .context/issue-351/raw/pytest_full.log diff --git a/.context/issue-351/raw/gated_tests.log b/.context/issue-351/raw/gated_tests.log new file mode 100644 index 0000000..420ed7e --- /dev/null +++ b/.context/issue-351/raw/gated_tests.log @@ -0,0 +1,2 @@ +pamica/tests/test_component_rows.py after the first scan: gm2 reference 4.222e-03, torch 4.222e-03 +======================== 37 passed in 121.82s (0:02:01) ======================== diff --git a/.context/issue-351/raw/pytest_full.log b/.context/issue-351/raw/pytest_full.log new file mode 100644 index 0000000..3e55c54 --- /dev/null +++ b/.context/issue-351/raw/pytest_full.log @@ -0,0 +1,52 @@ +============================= test session starts ============================== +platform darwin -- Python 3.12.14, pytest-9.1.1, pluggy-1.6.0 +rootdir: /Users/yahya/Documents/git/mlx-fc-phase15-final-parity +configfile: pytest.ini +testpaths: pamica/tests +plugins: cov-7.1.0, xdist-3.8.0 +created: 8/8 workers +8 workers [1998 items] + +........................................................................ 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[100%] +=============================== warnings summary =============================== +pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll + /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.venv/lib/python3.12/site-packages/numpy/linalg/_linalg.py:2349: RuntimeWarning: divide by zero encountered in slogdet + sign, logdet = _umath_linalg.slogdet(a, signature=signature) + +pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll + /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.venv/lib/python3.12/site-packages/numpy/linalg/_linalg.py:2349: RuntimeWarning: overflow encountered in slogdet + sign, logdet = _umath_linalg.slogdet(a, signature=signature) + +pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll + /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.venv/lib/python3.12/site-packages/numpy/linalg/_linalg.py:2349: RuntimeWarning: invalid value encountered in slogdet + sign, logdet = _umath_linalg.slogdet(a, signature=signature) + +-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html +===== 1955 passed, 40 skipped, 3 xfailed, 3 warnings in 1555.73s (0:25:55) ===== From 52657214297724dc53ef44ea406fc9fe40993391 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 16:46:37 -0700 Subject: [PATCH 33/58] Add the Phase 15 re-measurement to the changelog --- docs/changelog.md | 9 +++++++++ 1 file changed, 9 insertions(+) diff --git a/docs/changelog.md b/docs/changelog.md index c6bb325..54946fa 100644 --- a/docs/changelog.md +++ b/docs/changelog.md @@ -549,6 +549,15 @@ and every backend's fitting follows the Fortran reference more closely. ### Documentation +- **Parity figures re-measured with the finished epic** (issue #351, epic #324 Phase 15). + The validation guide, the differences guide, ADR 0003 and the paper quote measurements of this release's code against the pinned v0.3.3 native binary; + the run records are in `.context/issue-351/`. + - The harness's independent-start log-likelihood difference is now 2.7e-4 (it was 2.9e-5), + within the reference's own seed-to-seed spread at 100 iterations (standard deviation 2.6e-4 over eight seeds); + from a shared start the difference is 1.6e-6 (2.4e-4 with the code before the epic). + - The multi-model ensemble's log-likelihood matches the reference's (-3.3541 against -3.3543, Kolmogorov-Smirnov p = 0.83), where it trailed by 0.009; + `keep_best` restored one of 20 seeded fits, at the 300-iteration budget only. + - The `share_comps` example fit merges one pair (it merged three), and the early scans merge 30 and 17 components at iteration 8 (they merged 32 and 24). - **The documentation describes the finished epic** (issue #352, epic #324 Phase 16). 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+++++++++++++++++++ .../dimsweep/timing70_pre_epic_e38aa11.json | 55 +++++++++++++++++++ 2 files changed, 110 insertions(+) create mode 100644 .context/issue-351/raw/dimsweep/timing70_head.json create mode 100644 .context/issue-351/raw/dimsweep/timing70_pre_epic_e38aa11.json diff --git a/.context/issue-351/raw/dimsweep/timing70_head.json b/.context/issue-351/raw/dimsweep/timing70_head.json new file mode 100644 index 0000000..b60d7a2 --- /dev/null +++ b/.context/issue-351/raw/dimsweep/timing70_head.json @@ -0,0 +1,55 @@ +{ + "platform": { + "machine": "arm64", + "system": "Darwin", + "nproc": 14, + "torch": "2.12.1", + "loadavg": [ + 3.2, + 3.9, + 4.8 + ] + }, + "config": { + "data": "/Users/yahya/Documents/git/mlx-fc-phase15-final-parity/benchmarks/data/ds002718_sub-002_eeg70.npy", + "channels": "70", + "montage": null, + "samples": 30000, + "iters": 25, + "repeats": 3, + "backends": "mlx-f32,torch-cpu-f64,torch-mps-f32", + "out": "/private/tmp/claude-501/-Users-yahya-Documents-git-pamica/3b0e67f1-eae1-4864-8013-454e2363dda4/scratchpad/p15gates/dim_mlx-fc-phase15-final-parity.json", + "report": null, + "n_models": 1, + "share": false, + "fortran_bin": "/Users/yahya/Documents/git/mlx-fc-phase15-final-parity/benchmarks/fortran/amica15", + "fortran_threads": null, + "threads": null + }, + "rows": [ + { + "config": "m1", + "channels": 70, + "backend": "mlx-f32", + "threads": null, + "ms_per_iter": 33.12467999989167, + "final_ll": -3.216428518295288 + }, + { + "config": "m1", + "channels": 70, + "backend": "torch-cpu-f64", + "threads": null, + "ms_per_iter": 189.41867836052552, + "final_ll": -3.217461695658916 + }, + { + "config": "m1", + "channels": 70, + "backend": "torch-mps-f32", + "threads": null, + "ms_per_iter": 166.6829549986869, + "final_ll": -3.2163822650909424 + } + ] +} \ No newline at end of file diff --git a/.context/issue-351/raw/dimsweep/timing70_pre_epic_e38aa11.json b/.context/issue-351/raw/dimsweep/timing70_pre_epic_e38aa11.json new file mode 100644 index 0000000..b63b486 --- /dev/null +++ b/.context/issue-351/raw/dimsweep/timing70_pre_epic_e38aa11.json @@ -0,0 +1,55 @@ +{ + "platform": { + "machine": "arm64", + "system": "Darwin", + "nproc": 14, + "torch": "2.12.1", + "loadavg": [ + 3.2, + 4.0, + 4.8 + ] + }, + "config": { + "data": "/Users/yahya/Documents/git/mlx-fc-phase15-final-parity/benchmarks/data/ds002718_sub-002_eeg70.npy", + "channels": "70", + "montage": null, + "samples": 30000, + "iters": 25, + "repeats": 3, + "backends": "mlx-f32,torch-cpu-f64,torch-mps-f32", + "out": "/private/tmp/claude-501/-Users-yahya-Documents-git-pamica/3b0e67f1-eae1-4864-8013-454e2363dda4/scratchpad/p15gates/dim_p15_pre2.json", + "report": null, + "n_models": 1, + "share": false, + "fortran_bin": "/private/tmp/claude-501/-Users-yahya-Documents-git-pamica/3b0e67f1-eae1-4864-8013-454e2363dda4/scratchpad/p15_pre2/benchmarks/fortran/amica15", + "fortran_threads": null, + "threads": null + }, + "rows": [ + { + "config": "m1", + "channels": 70, + "backend": "mlx-f32", + "threads": null, + "ms_per_iter": 33.264005000237375, + "final_ll": -3.216428518295288 + }, + { + "config": "m1", + "channels": 70, + "backend": "torch-cpu-f64", + "threads": null, + "ms_per_iter": 190.75368164107203, + "final_ll": -3.217461695658916 + }, + { + "config": "m1", + "channels": 70, + "backend": "torch-mps-f32", + "threads": null, + "ms_per_iter": 165.05729664117098, + "final_ll": -3.2163822650909424 + } + ] +} \ No newline at end of file From cc4e5c63277cebf4468eff754e37505a10461df1 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 17:05:23 -0700 Subject: [PATCH 36/58] Record the unseeded-start check of the issue-145 binary --- .../raw/seedcheck_issue145_binary/run1.log | 127 ++++++++++++++++++ .../raw/seedcheck_issue145_binary/run2.log | 127 ++++++++++++++++++ .../seedcheck_issue145_binary/seedcheck.txt | 6 + 3 files changed, 260 insertions(+) create mode 100644 .context/issue-351/raw/seedcheck_issue145_binary/run1.log create mode 100644 .context/issue-351/raw/seedcheck_issue145_binary/run2.log create mode 100644 .context/issue-351/raw/seedcheck_issue145_binary/seedcheck.txt diff --git a/.context/issue-351/raw/seedcheck_issue145_binary/run1.log b/.context/issue-351/raw/seedcheck_issue145_binary/run1.log new file mode 100644 index 0000000..0fef42b --- /dev/null +++ b/.context/issue-351/raw/seedcheck_issue145_binary/run1.log @@ -0,0 +1,127 @@ +Authorization required, but no authorization protocol specified + +Authorization required, but no authorization protocol specified + +Authorization required, but no authorization protocol specified + +Authorization required, but no authorization protocol specified + + 1 processor name = hallucinating + 1 host_num = 302850659 + This is MPI process 1 of 1 ; I am process 1 of 1 on node: hallucinating + 1 : node root process 1 of 1 +Processing arguments ... + num_files = 1 + FILES: + ./eeglab_data.fdt + num_dir_files = 1 + initial matrix block_size = 512 + do_opt_block = 0 + blk_min = 256 + blk_step = 256 + blk_max = 1024 + number of models = 1 + max_thrds = 1 + use_min_dll = 1 + min dll = 1.0000000000000001E-009 + use_grad_norm = 1 + min grad norm = 9.9999999999999995E-008 + number of density mixture components = 3 + pdf type = 0 + max_iter = 1 + num_samples = 1 + data_dim = 32 + field_dim = 30504 + do_history = 0 + histstep = 10 + share_comps = 0 + share_start = 100 + comp_thresh = 0.98999999999999999 + share_int = 100 + initial lrate = 5.0000000000000003E-002 + minimum lrate = 1.0000000000000000E-008 + minimum data covariance eigenvalue = 9.9999999999999998E-013 + lrate factor = 0.50000000000000000 + initial rholrate = 5.0000000000000003E-002 + rho0 = 1.5000000000000000 + min rho = 1.0000000000000000 + max rho = 2.0000000000000000 + rho lrate factor = 0.50000000000000000 + kurt_start = 3 + num kurt = 5 + kurt interval = 1 + do_newton = 1 + newt_start = 50 + newt_ramp = 10 + initial newton lrate = 1.0000000000000000 + do_reject = 0 + num reject = 3 + reject sigma = 3.0000000000000000 + reject start = 2 + reject interval = 3 + write step = 100 + write_nd = 0 + write_LLt = 1 + dec window = 1 + max_decs = 3 + fix_init = 0 + update_A = 1 + update_c = 1 + update_gm = 1 + update_alpha = 1 + update_mu = 1 + update_beta = 1 + invsigmax = 100.00000000000000 + invsigmin = 0.0000000000000000 + do_rho = 1 + load_rej = 0 + load_c = 0 + load_gm = 0 + load_alpha = 0 + load_mu = 0 + load_beta = 0 + load_rho = 0 + load_comp_list = 0 + do_mean = 1 + do_sphere = 1 + pcakeep = 32 + pcadb = 30.000000000000000 + byte_size = 4 + doscaling = 1 + scalestep = 1 +mkdir: cannot create directory ‘./out/’: File exists + output directory = ./out/ + 1 : setting num_thrds to 1 ... + 1 : using 1 threads. + 1 : node_thrds = 1 + bytes in real = 4 + 1 : REAL nbyte = 4 + getting segment list ... + blocks in sample = 30504 + total blocks = 30504 + node blocks = 30504 + node 1 start: file 1 sample 1 index 1 + node 1 stop : file 1 sample 1 index 30504 + 1 : data = -35.797485351562500 2.3078439235687256 + getting the mean ... + mean = -3.7090141912586323 -6.7516788952437894 2.5880450259870105 + subtracting the mean ... + getting the covariance matrix ... + cnt = 30504 + doing eig nx = 32 lwork = 10240 + minimum eigenvalues = 4.8799005132501803 6.9201197127079803 7.6562147928880702 + maximum eigenvalues = 9711.1430838537090 3039.6850435125002 1244.4129447052057 + num eigs kept = 32 + getting the sphering matrix ... + minimum eigenvalues = 4.8799005132501803 6.9201197127079803 7.6562147928880702 + maximum eigenvalues = 9711.1430838537090 3039.6850435125002 1244.4129447052057 + num eigs kept = 32 + sphering the data ... + numeigs = 32 + 1 : Allocating variables ... + 1 : Initializing variables ... + 1 : block size = 512 + 1 : entering the main loop ... + iter 1 lrate = 0.0500000000 LL = -3.5114441940 nd = 0.0556873701, D = 0.42075E-02 0.42075E-02 ( 0.10 s, 0.0 h) +... done. Execution time: 0.00 h + output directory = ./out/ diff --git a/.context/issue-351/raw/seedcheck_issue145_binary/run2.log b/.context/issue-351/raw/seedcheck_issue145_binary/run2.log new file mode 100644 index 0000000..2bb904b --- /dev/null +++ b/.context/issue-351/raw/seedcheck_issue145_binary/run2.log @@ -0,0 +1,127 @@ +Authorization required, but no authorization protocol specified + +Authorization required, but no authorization protocol specified + +Authorization required, but no authorization protocol specified + +Authorization required, but no authorization protocol specified + + 1 processor name = hallucinating + 1 host_num = 302850659 + This is MPI process 1 of 1 ; I am process 1 of 1 on node: hallucinating + 1 : node root process 1 of 1 +Processing arguments ... + num_files = 1 + FILES: + ./eeglab_data.fdt + num_dir_files = 1 + initial matrix block_size = 512 + do_opt_block = 0 + blk_min = 256 + blk_step = 256 + blk_max = 1024 + number of models = 1 + max_thrds = 1 + use_min_dll = 1 + min dll = 1.0000000000000001E-009 + use_grad_norm = 1 + min grad norm = 9.9999999999999995E-008 + number of density mixture components = 3 + pdf type = 0 + max_iter = 1 + num_samples = 1 + data_dim = 32 + field_dim = 30504 + do_history = 0 + histstep = 10 + share_comps = 0 + share_start = 100 + comp_thresh = 0.98999999999999999 + share_int = 100 + initial lrate = 5.0000000000000003E-002 + minimum lrate = 1.0000000000000000E-008 + minimum data covariance eigenvalue = 9.9999999999999998E-013 + lrate factor = 0.50000000000000000 + initial rholrate = 5.0000000000000003E-002 + rho0 = 1.5000000000000000 + min rho = 1.0000000000000000 + max rho = 2.0000000000000000 + rho lrate factor = 0.50000000000000000 + kurt_start = 3 + num kurt = 5 + kurt interval = 1 + do_newton = 1 + newt_start = 50 + newt_ramp = 10 + initial newton lrate = 1.0000000000000000 + do_reject = 0 + num reject = 3 + reject sigma = 3.0000000000000000 + reject start = 2 + reject interval = 3 + write step = 100 + write_nd = 0 + write_LLt = 1 + dec window = 1 + max_decs = 3 + fix_init = 0 + update_A = 1 + update_c = 1 + update_gm = 1 + update_alpha = 1 + update_mu = 1 + update_beta = 1 + invsigmax = 100.00000000000000 + invsigmin = 0.0000000000000000 + do_rho = 1 + load_rej = 0 + load_c = 0 + load_gm = 0 + load_alpha = 0 + load_mu = 0 + load_beta = 0 + load_rho = 0 + load_comp_list = 0 + do_mean = 1 + do_sphere = 1 + pcakeep = 32 + pcadb = 30.000000000000000 + byte_size = 4 + doscaling = 1 + scalestep = 1 +mkdir: cannot create directory ‘./out/’: File exists + output directory = ./out/ + 1 : setting num_thrds to 1 ... + 1 : using 1 threads. + 1 : node_thrds = 1 + bytes in real = 4 + 1 : REAL nbyte = 4 + getting segment list ... + blocks in sample = 30504 + total blocks = 30504 + node blocks = 30504 + node 1 start: file 1 sample 1 index 1 + node 1 stop : file 1 sample 1 index 30504 + 1 : data = -35.797485351562500 2.3078439235687256 + getting the mean ... + mean = -3.7090141912586323 -6.7516788952437894 2.5880450259870105 + subtracting the mean ... + getting the covariance matrix ... + cnt = 30504 + doing eig nx = 32 lwork = 10240 + minimum eigenvalues = 4.8799005132501803 6.9201197127079803 7.6562147928880702 + maximum eigenvalues = 9711.1430838537090 3039.6850435125002 1244.4129447052057 + num eigs kept = 32 + getting the sphering matrix ... + minimum eigenvalues = 4.8799005132501803 6.9201197127079803 7.6562147928880702 + maximum eigenvalues = 9711.1430838537090 3039.6850435125002 1244.4129447052057 + num eigs kept = 32 + sphering the data ... + numeigs = 32 + 1 : Allocating variables ... + 1 : Initializing variables ... + 1 : block size = 512 + 1 : entering the main loop ... + iter 1 lrate = 0.0500000000 LL = -3.5132320906 nd = 0.0576198453, D = 0.39757E-02 0.39757E-02 ( 0.09 s, 0.0 h) +... done. Execution time: 0.00 h + output directory = ./out/ diff --git a/.context/issue-351/raw/seedcheck_issue145_binary/seedcheck.txt b/.context/issue-351/raw/seedcheck_issue145_binary/seedcheck.txt new file mode 100644 index 0000000..1233c9c --- /dev/null +++ b/.context/issue-351/raw/seedcheck_issue145_binary/seedcheck.txt @@ -0,0 +1,6 @@ +43b9f0e3dfd7b1e05754fdd5c86e5abe0b47b784ac8019adb995d20ae2c53b59 /home/yahya/pyAMICA-issue144/pyAMICA/sample_data/amica15_linux +run1 + iter 1 lrate = 0.0500000000 LL = -3.5114441940 nd = 0.0556873701, D = 0.42075E-02 0.42075E-02 ( 0.10 s, 0.0 h) +run2 + iter 1 lrate = 0.0500000000 LL = -3.5132320906 nd = 0.0576198453, D = 0.39757E-02 0.39757E-02 ( 0.09 s, 0.0 h) +max|A1-A2| after 1 iteration: 0.009557581902372853 From f129cfc6b0b428613f8acce011d1d429c4612f85 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 17:05:54 -0700 Subject: [PATCH 37/58] Mark the sections of the validation guide that predate the epic --- docs/guides/validation.md | 8 +++++++- 1 file changed, 7 insertions(+), 1 deletion(-) diff --git a/docs/guides/validation.md b/docs/guides/validation.md index 79ac3e9..4b3fb91 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -332,7 +332,8 @@ and the original ensembles of this study measured 0.154 and 0.163 against the bu The strongest reassurance that pamica is a single, well-defined implementation is that it recovers the *same* independent components no matter where or how it runs. Fitting the same real EEG (ds002718 sub-002, 147,000 frames, 70 channels, 2000 iterations) -on every backend and Hungarian-matching the unmixing components across them: +on every backend and Hungarian-matching the unmixing components across them +(measured before epic #324's changes to the fit and not re-measured since; issue #351 re-measured the figures elsewhere on this page): ![Cross-backend IC-equivalence matrix at 70 channels.](../assets/figures/cross-backend-equivalence-matrix.png){ width=680 } /// caption @@ -361,6 +362,8 @@ Whether backends recover the *same* components depends on how well-determined th $$k = \frac{\text{frames}}{\text{channels}^2}$$ +The two sweeps below were measured before epic #324's changes to the fit and have not been re-measured since. + As `k` grows, cross-backend component equivalence rises toward 1.0; at the rule-of-thumb minimum (`k` around 20-30) only the strongest components are backend-reproducible, while the rest are under-determined and settle into different but equally valid local optima (AMICA is non-convex). @@ -455,6 +458,9 @@ Full usage is in the [EEGLAB interoperability guide](eeglab.md); tests are in `p Throughput on real EEG (OpenNeuro ds002718 sub-002; `n_mix=3`, `pdftype=0`, `block_size=512`, warmed, min-of-repeats). CPU, MPS, and MLX were measured on Apple Silicon; CUDA on a separate NVIDIA RTX 4090 host, so MLX-versus-CUDA reads as "best Apple-GPU path versus a strong NVIDIA GPU", not a same-box comparison. +These tables predate epic #324. +A same-session check on the Apple M4 Pro at 70 channels (`benchmark_dimsweep.py`, 30000 frames, 25 iterations, three repeats; issue #351) +found per-iteration cost unchanged by the epic: 33.3 and 33.1 ms for MLX, 190.8 and 189.4 ms for torch-CPU float64, 165.1 and 166.7 ms for torch-MPS float32, before and after. ### Single-model, ms/iteration From 973e03d667959e19fcad455418e7599fe207763a Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 17:19:04 -0700 Subject: [PATCH 38/58] Pin every reference setting in the Table 1 and run scripts --- .context/issue-351/_reference_settings.py | 52 ++++++ .context/issue-351/bundled_single_basins.py | 15 +- .context/issue-351/keep_best_ensemble.py | 16 +- .context/issue-351/newton_seeds.py | 32 ++-- .context/issue-351/orientation_check.py | 5 +- .context/issue-351/pin_check.py | 175 ++++++++++++++++++++ .context/issue-351/raw/pin_check.json | 34 ++++ .context/issue-351/share_comps_counts.py | 6 +- benchmarks/reproduce_table1.py | 60 +++++-- 9 files changed, 364 insertions(+), 31 deletions(-) create mode 100644 .context/issue-351/_reference_settings.py create mode 100644 .context/issue-351/pin_check.py create mode 100644 .context/issue-351/raw/pin_check.json diff --git a/.context/issue-351/_reference_settings.py b/.context/issue-351/_reference_settings.py new file mode 100644 index 0000000..ac1f46a --- /dev/null +++ b/.context/issue-351/_reference_settings.py @@ -0,0 +1,52 @@ +"""The reference settings of ``benchmarks/reproduce_table1.py``, shared by this +directory's scripts so that every native-binary run passes its protocol's +settings explicitly (a change of ``AMICANative``'s defaults cannot move them). + +``REFERENCE_SETTINGS`` is read from the script's source without importing it, +so a script that imports an older pamica tree can use it too. +""" + +from __future__ import annotations + +import ast +import importlib.util +import sys +from pathlib import Path +from typing import Any + +_TABLE1 = Path(__file__).resolve().parents[2] / "benchmarks/reproduce_table1.py" +_NAME = "reproduce_table1_351" + + +def _literal(name: str) -> dict[str, Any]: + for node in ast.parse(_TABLE1.read_text()).body: + if ( + isinstance(node, ast.AnnAssign) + and isinstance(node.target, ast.Name) + and node.target.id == name + and node.value is not None + ): + return dict(ast.literal_eval(node.value)) + raise LookupError(f"{name} not found in {_TABLE1}") + + +REFERENCE_SETTINGS: dict[str, Any] = _literal("REFERENCE_SETTINGS") + + +def _table1(): + if _NAME in sys.modules: + return sys.modules[_NAME] + spec = importlib.util.spec_from_file_location(_NAME, _TABLE1) + assert spec is not None and spec.loader is not None + mod = importlib.util.module_from_spec(spec) + sys.modules[_NAME] = mod + spec.loader.exec_module(mod) + return mod + + +def single_model_reference_kwargs(max_iter: int) -> dict[str, Any]: + return _table1().single_model_reference_kwargs(max_iter) + + +def multimodel_reference_kwargs(max_iter: int) -> dict[str, Any]: + return _table1().multimodel_reference_kwargs(max_iter) diff --git a/.context/issue-351/bundled_single_basins.py b/.context/issue-351/bundled_single_basins.py index f633eed..f076d28 100644 --- a/.context/issue-351/bundled_single_basins.py +++ b/.context/issue-351/bundled_single_basins.py @@ -37,6 +37,15 @@ def _table1(): return mod +def fortran_kwargs(t1, seed: int, threads: int) -> dict: + """``AMICANative`` keywords of the reference runs: the tier's single-model + settings, every one explicit, plus the seed.""" + return dict( + threads=threads, max_threads=threads, timeout=3600, seed=seed, + **t1.single_model_reference_kwargs(2000), + ) # fmt: skip + + def main() -> None: p = argparse.ArgumentParser() p.add_argument("out", type=Path) @@ -51,11 +60,7 @@ def main() -> None: binary = t1.resolve_binary(None, "v0.3.3") runs: dict[str, dict] = {} for s in range(1, a.n_fortran + 1): - eng = AMICANative( - binary=binary, threads=a.threads, max_threads=a.threads, timeout=3600, - n_models=1, n_mix=3, max_iter=2000, do_newton=0, use_min_dll=0, - use_grad_norm=0, block_size=512, seed=s, - ) # fmt: skip + eng = AMICANative(binary=binary, **fortran_kwargs(t1, s, a.threads)) eng.fit(data) assert eng.output_ is not None runs[f"fortran_seed{s}"] = { diff --git a/.context/issue-351/keep_best_ensemble.py b/.context/issue-351/keep_best_ensemble.py index 5246ab5..b1ed3c5 100644 --- a/.context/issue-351/keep_best_ensemble.py +++ b/.context/issue-351/keep_best_ensemble.py @@ -51,14 +51,24 @@ def load_data() -> np.ndarray: return load_eeglab_data(str(FDT), data_dim=NW, field_dim=FIELD).astype(np.float64) +def fortran_kwargs(max_iter: int, seed: int) -> dict: + """``AMICANative`` keywords of the reference runs, every protocol setting + explicit (``_reference_settings``), seeded and single-threaded.""" + from _reference_settings import multimodel_reference_kwargs + + return dict( + threads=1, max_threads=1, timeout=3600, seed=seed, + **multimodel_reference_kwargs(max_iter), + ) # fmt: skip + + def run_fortran(data: np.ndarray, seed: int, max_iter: int) -> np.ndarray: from pamica import AMICANative from pamica.native import resolver eng = AMICANative( - binary=resolver.resolve("v0.3.3"), threads=1, max_threads=1, - timeout=3600, n_models=2, n_mix=3, max_iter=max_iter, seed=seed, - ) # fmt: skip + **fortran_kwargs(max_iter, seed), binary=resolver.resolve("v0.3.3") + ) eng.fit(data) assert eng.output_ is not None ll = np.asarray(eng.output_.LL, dtype=np.float64) diff --git a/.context/issue-351/newton_seeds.py b/.context/issue-351/newton_seeds.py index a32a8d2..e260f38 100644 --- a/.context/issue-351/newton_seeds.py +++ b/.context/issue-351/newton_seeds.py @@ -56,10 +56,26 @@ rholrate=0.05, rholratefact=0.5, maxdecs=3, block_size=512, use_min_dll=False, use_grad_norm=False, ) # fmt: skip -FORTRAN_KW = dict( - num_models=1, num_mix_comps=NMIX, max_iter=MAX_ITER, do_newton=1, - use_min_dll=0, use_grad_norm=0, block_size=512, -) # fmt: skip +# The reference's settings (every one explicit, from _reference_settings): +# Newton on, early stops off, as the #145 load-path run had them. +FORTRAN_OVERRIDES = dict(do_newton=1, use_min_dll=0, use_grad_norm=0, block_size=512) + + +def fortran_kwargs(max_iter: int) -> dict: + """``AMICANative`` settings of the independent-start reference fits.""" + from _reference_settings import REFERENCE_SETTINGS + + return { + **REFERENCE_SETTINGS, "num_models": 1, "num_mix_comps": NMIX, + "max_iter": max_iter, **FORTRAN_OVERRIDES, + } # fmt: skip + + +def fixinit_kwargs() -> dict: + """``run_seeded_reference`` settings of the same-start reference fit.""" + from _reference_settings import REFERENCE_SETTINGS + + return {**REFERENCE_SETTINGS, **FORTRAN_OVERRIDES} def load_data(path: Path) -> np.ndarray: @@ -151,7 +167,7 @@ def run_fortran( if not fixinit: eng = AMICANative( binary=binary, threads=threads, max_threads=threads, timeout=6 * 3600, - seed=seed, **{**FORTRAN_KW, "max_iter": max_iter}, + seed=seed, **fortran_kwargs(max_iter), ) # fmt: skip eng.fit(data) out = eng.output_ @@ -168,11 +184,7 @@ def run_fortran( np.ascontiguousarray(data.T).astype(" None: + from _reference_settings import REFERENCE_SETTINGS + root = Path(sys.argv[1]).resolve() sys.path.insert(0, str(root)) import numpy as np @@ -67,7 +69,8 @@ def main() -> None: with tempfile.TemporaryDirectory() as td: ref = oracle.run_seeded_reference( st, fdt, Path(td), n_samples=n, max_iter=1, threads=1, binary=BINARY, - block_size=512, do_newton=1, use_min_dll=0, use_grad_norm=0, + **{**REFERENCE_SETTINGS, "block_size": 512, "do_newton": 1, + "use_min_dll": 0, "use_grad_norm": 0}, ) # fmt: skip out[name] = float(ref.LL[0]) asym = float(np.abs(state.A - state.A.T).max()) diff --git a/.context/issue-351/pin_check.py b/.context/issue-351/pin_check.py new file mode 100644 index 0000000..832f681 --- /dev/null +++ b/.context/issue-351/pin_check.py @@ -0,0 +1,175 @@ +"""Check that pinning every reference setting explicitly is a no-op today +(issue #351): each native-binary call of ``benchmarks/reproduce_table1.py`` and +of this directory's scripts writes a byte-identical ``input.param`` with the +explicit settings and with the keywords it passed before the pin (which relied +on ``AMICANative``'s defaults, then the bundled ``input.param`` values). + +The binary is never run: ``subprocess.run`` in the engine and the seeded runner +of ``pamica/tests/native_oracle.py`` are replaced by functions that record the +parameter file and stop. + + uv run python .context/issue-351/pin_check.py OUT.json +""" + +from __future__ import annotations + +import json +import sys +from pathlib import Path + +import numpy as np + +HERE = Path(__file__).resolve().parent +REPO = HERE.parents[1] +sys.path.insert(0, str(HERE)) + + +class _Stop(Exception): + pass + + +def native_param(**kw) -> str: + """The input.param ``AMICANative(**kw).fit`` would run the binary with.""" + import pamica.native.engine as engine + + captured: dict[str, str] = {} + + def fake_run(cmd, cwd=None, **_): + captured["param"] = (Path(cwd) / "input.param").read_text() + raise _Stop + + real = engine.subprocess.run + engine.subprocess.run = fake_run + try: + engine.AMICANative(binary=sys.executable, **kw).fit( + np.zeros((32, 64), dtype=np.float64) + ) + except _Stop: + pass + finally: + engine.subprocess.run = real + return captured["param"] + + +def seeded_param(state_models: int = 1, **kw) -> str: + """The parameter dict ``run_seeded_reference(state, ..., **kw)`` would run.""" + import pamica.tests.native_oracle as oracle + + captured: dict[str, str] = {} + + def fake_run_reference(param, workdir, **_): + from pamica.native.engine import _render_param + + captured["param"] = _render_param(param) + raise _Stop + + nw, nmix = 32, 3 + num_models = state_models + state = oracle.SeedState( + A=np.eye(nw * num_models)[:nw].copy() if num_models == 1 else np.ones((nw, nw * num_models)), + mean=np.zeros(nw), + mu=np.zeros((nmix, nw * num_models)), + sbeta=np.ones((nmix, nw * num_models)), + rho=np.ones((nmix, nw * num_models)), + alpha=np.ones((nmix, nw * num_models)) / nmix, + gm=np.ones(num_models) / num_models, + c=np.zeros((nw, num_models)), + ) # fmt: skip + real = oracle._run_reference + oracle._run_reference = fake_run_reference + try: + import tempfile + + with tempfile.TemporaryDirectory() as td: + oracle.run_seeded_reference( + state, REPO / "pamica/sample_data/eeglab_data.fdt", Path(td), + n_samples=64, max_iter=kw.pop("max_iter", 5), threads=1, + binary=Path(sys.executable), **kw, + ) # fmt: skip + except _Stop: + pass + finally: + oracle._run_reference = real + return captured["param"] + + +def main() -> None: + import _reference_settings as rs + import bundled_single_basins as basins + import keep_best_ensemble as kb + import newton_seeds as ns + from pamica.tests.test_component_rows import _REF_OPT + + t1 = rs._table1() + checks = { + # (before: the keywords each call passed before the pin, after: now) + "reproduce_table1 single-model sweep": ( + dict(threads=4, max_threads=4, timeout=3600, n_models=1, n_mix=3, + max_iter=2000, do_newton=0, use_min_dll=0, use_grad_norm=0, + block_size=512), + dict(threads=4, max_threads=4, timeout=3600, + **t1.single_model_reference_kwargs(2000)), + ), + "reproduce_table1 multi-model ensemble": ( + dict(threads=4, max_threads=4, timeout=1800, n_models=2, n_mix=3, + max_iter=100), + dict(threads=4, max_threads=4, timeout=1800, + **t1.multimodel_reference_kwargs(100)), + ), + "keep_best_ensemble reference": ( + dict(threads=1, max_threads=1, timeout=3600, n_models=2, n_mix=3, + max_iter=300, seed=3), + kb.fortran_kwargs(300, 3), + ), + "bundled_single_basins reference": ( + dict(threads=3, max_threads=3, timeout=3600, n_models=1, n_mix=3, + max_iter=2000, do_newton=0, use_min_dll=0, use_grad_norm=0, + block_size=512, seed=4), + basins.fortran_kwargs(t1, 4, 3), + ), + "newton_seeds reference": ( + dict(threads=10, max_threads=10, timeout=6 * 3600, seed=1, + num_models=1, num_mix_comps=3, max_iter=2000, do_newton=1, + use_min_dll=0, use_grad_norm=0, block_size=512), + dict(threads=10, max_threads=10, timeout=6 * 3600, seed=1, + **ns.fortran_kwargs(2000)), + ), + } # fmt: skip + out = {} + for name, (before, after) in checks.items(): + a, b = native_param(**before), native_param(**after) + out[name] = {"identical": a == b, "lines": a.count("\n")} + seeded = { + "newton_seeds same-start reference": ( + dict(max_iter=2000, do_newton=1, use_min_dll=0, use_grad_norm=0, + block_size=512), + dict(max_iter=2000, **ns.fixinit_kwargs()), + ), + "orientation_check": ( + dict(max_iter=1, block_size=512, do_newton=1, use_min_dll=0, + use_grad_norm=0), + dict(max_iter=1, **{**rs.REFERENCE_SETTINGS, "block_size": 512, + "do_newton": 1, "use_min_dll": 0, + "use_grad_norm": 0}), + ), + "share_comps_counts part c": ( + dict(max_iter=8, num_models=2, + **{**_REF_OPT, "share_start": 8, "share_iter": 100, "share_comps": 0}), + dict(max_iter=8, num_models=2, + **{**rs.REFERENCE_SETTINGS, **_REF_OPT, "share_start": 8, + "share_iter": 100, "share_comps": 0}), + ), + } # fmt: skip + for name, (before, after) in seeded.items(): + nm = before.get("num_models", 1) + a = seeded_param(state_models=nm, **before) + b = seeded_param(state_models=nm, **after) + out[name] = {"identical": a == b, "lines": a.count("\n")} + Path(sys.argv[1]).write_text(json.dumps(out, indent=2)) + print(json.dumps(out, indent=2)) + if not all(v["identical"] for v in out.values()): + raise SystemExit("a pinned call writes a different input.param") + + +if __name__ == "__main__": + main() diff --git a/.context/issue-351/raw/pin_check.json b/.context/issue-351/raw/pin_check.json new file mode 100644 index 0000000..1bad30c --- /dev/null +++ b/.context/issue-351/raw/pin_check.json @@ -0,0 +1,34 @@ +{ + "reproduce_table1 single-model sweep": { + "identical": true, + "lines": 79 + }, + "reproduce_table1 multi-model ensemble": { + "identical": true, + "lines": 79 + }, + "keep_best_ensemble reference": { + "identical": true, + "lines": 80 + }, + "bundled_single_basins reference": { + "identical": true, + "lines": 80 + }, + "newton_seeds reference": { + "identical": true, + "lines": 80 + }, + "newton_seeds same-start reference": { + "identical": true, + "lines": 83 + }, + "orientation_check": { + "identical": true, + "lines": 83 + }, + "share_comps_counts part c": { + "identical": true, + "lines": 83 + } +} \ No newline at end of file diff --git a/.context/issue-351/share_comps_counts.py b/.context/issue-351/share_comps_counts.py index 0f1c53f..3f62424 100644 --- a/.context/issue-351/share_comps_counts.py +++ b/.context/issue-351/share_comps_counts.py @@ -33,6 +33,7 @@ import numpy as np import torch +from _reference_settings import REFERENCE_SETTINGS from pamica import AMICA_NumPy from pamica.numpy_impl.utils import identify_shared_components from pamica.tests.native_oracle import run_seeded_reference, seed_from_torch @@ -143,7 +144,10 @@ def torch_model(**kw): seed = dataclasses.replace(seed_from_torch(init), comp_list=default) ref8 = run_seeded_reference( seed, DATA_FILE, work / "c", n_samples=FIELD, max_iter=pre, num_models=2, - **{**_REF_OPT, "share_start": pre, "share_iter": 100, "share_comps": 0}, + **{ + **REFERENCE_SETTINGS, **_REF_OPT, + "share_start": pre, "share_iter": 100, "share_comps": 0, + }, ) # fmt: skip t8 = torch_model(share_comps=False) t8.fit(X, max_iter=pre, verbose=False) diff --git a/benchmarks/reproduce_table1.py b/benchmarks/reproduce_table1.py index 9eedf8d..cffaaca 100644 --- a/benchmarks/reproduce_table1.py +++ b/benchmarks/reproduce_table1.py @@ -72,7 +72,7 @@ import sys import time from pathlib import Path -from typing import Callable +from typing import Any, Callable import numpy as np import torch @@ -106,6 +106,52 @@ MULTIMODEL_SEED_START = 1 +# The reference's settings for every Table 1 run: the values of the bundled +# pamica/sample_data/input.param, which AMICANative's defaults mirrored when +# the table was measured. Spelled out, so that a change of AMICANative's own +# defaults cannot change this protocol; each call adds its model count, +# iteration budget and the settings it overrides. +REFERENCE_SETTINGS: dict[str, Any] = { + "block_size": 512, "do_opt_block": 0, "blk_min": 256, "blk_step": 256, + "blk_max": 1024, "use_min_dll": 1, "min_dll": 1e-09, "use_grad_norm": 1, + "min_grad_norm": 1e-07, "pdftype": 0, "share_comps": 0, "share_start": 100, + "comp_thresh": 0.99, "share_iter": 100, "lrate": 0.05, "minlrate": 1e-08, + "mineig": 1e-12, "lratefact": 0.5, "rholrate": 0.05, "rho0": 1.5, + "minrho": 1.0, "maxrho": 2.0, "rholratefact": 0.5, "kurt_start": 3, + "num_kurt": 5, "kurt_int": 1, "do_newton": 1, "newt_start": 50, + "newt_ramp": 10, "newtrate": 1.0, "do_reject": 0, "numrej": 3, + "rejsig": 3.0, "rejstart": 2, "rejint": 3, "decwindow": 1, "max_decs": 3, + "fix_init": 0, "update_A": 1, "update_c": 1, "update_gm": 1, + "update_alpha": 1, "update_mu": 1, "update_beta": 1, "invsigmax": 100.0, + "invsigmin": 0.0, "do_rho": 1, "do_mean": 1, "do_sphere": 1, "doPCA": 1, + "pcadb": 30.0, "byte_size": 4, "doscaling": 1, "scalestep": 1, +} # fmt: skip + + +def single_model_reference_kwargs(max_iter: int) -> dict[str, Any]: + """``AMICANative`` settings of the single-model sweep: Newton and the + reference's early stops off, so both sides run the full budget.""" + return { + **REFERENCE_SETTINGS, + "num_models": 1, + "num_mix_comps": 3, + "max_iter": max_iter, + "do_newton": 0, + "use_min_dll": 0, + "use_grad_norm": 0, + } + + +def multimodel_reference_kwargs(max_iter: int) -> dict[str, Any]: + """``AMICANative`` settings of the multi-model ensemble (the #27 protocol).""" + return { + **REFERENCE_SETTINGS, + "num_models": 2, + "num_mix_comps": 3, + "max_iter": max_iter, + } + + # --------------------------------------------------------------------------- # Parity metrics (Amari, Cichocki & Yang 1996; Hungarian-matched correlation), # reimplemented here rather than imported from validate_implementations.py -- @@ -334,13 +380,7 @@ def run_single_model_sweep( threads=threads, max_threads=threads, timeout=3600, - n_models=1, - n_mix=3, - max_iter=max_iter, - do_newton=0, - use_min_dll=0, - use_grad_norm=0, - block_size=512, + **single_model_reference_kwargs(max_iter), ) eng.fit(data) except (RuntimeError, TimeoutError) as exc: @@ -481,9 +521,7 @@ def run_multimodel_ensemble( threads=threads, max_threads=threads, timeout=1800, - n_models=2, - n_mix=3, - max_iter=max_iter, + **multimodel_reference_kwargs(max_iter), ) eng.fit(data) except RuntimeError as exc: From e095df9853d2d7dea58dbd2ae0d33866c251cc23 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 17:58:32 -0700 Subject: [PATCH 39/58] Re-state the Newton-enabled basin results --- .context/issue-351/raw/newton/gpu_queue2.log | 2 + .../raw/newton/newton_seeds_report.json | 238 ++++++++++++++++++ .../issue-351/raw/newton/pamica_fixinit.npz | Bin 0 -> 96478 bytes docs/guides/validation.md | 43 +++- paper.md | 7 +- 5 files changed, 280 insertions(+), 10 deletions(-) create mode 100644 .context/issue-351/raw/newton/gpu_queue2.log create mode 100644 .context/issue-351/raw/newton/newton_seeds_report.json create mode 100644 .context/issue-351/raw/newton/pamica_fixinit.npz diff --git a/.context/issue-351/raw/newton/gpu_queue2.log b/.context/issue-351/raw/newton/gpu_queue2.log new file mode 100644 index 0000000..f280858 --- /dev/null +++ b/.context/issue-351/raw/newton/gpu_queue2.log @@ -0,0 +1,2 @@ +pamica seed13: final_ll=-3.697816 iters=2000 stop_reason=max_iter n_newton_fallbacks=0 end_newtrate=0.5 time=6239s +pamica fixinit: final_ll=-3.697812 iters=2000 stop_reason=max_iter n_newton_fallbacks=0 end_newtrate=0.5 time=4323s diff --git a/.context/issue-351/raw/newton/newton_seeds_report.json b/.context/issue-351/raw/newton/newton_seeds_report.json new file mode 100644 index 0000000..afce262 --- /dev/null +++ b/.context/issue-351/raw/newton/newton_seeds_report.json @@ -0,0 +1,238 @@ +{ + "runs": { + "fortran_fixinit": { + "final_ll": -3.697811900183683, + "seconds": 3393.1054351329803 + }, + "fortran_seed1": { + "final_ll": -3.6978038496639263, + "seconds": 3529.269710302353 + }, + "fortran_seed2": { + "final_ll": -3.6977085058389902, + "seconds": 2824.826691389084 + }, + "pamica_fixinit": { + "final_ll": -3.697811975919964, + "stop_reason": "max_iter", + "n_newton_fallbacks": 0, + "end_newtrate": 0.5, + "seconds": 4322.5316915512085 + }, + "pamica_seed13": { + "final_ll": -3.6978163881752835, + "stop_reason": "max_iter", + "n_newton_fallbacks": 0, + "end_newtrate": 0.5, + "seconds": 6239.20730638504 + }, + "pamica_seed42": { + "final_ll": -3.6975690998613517, + "stop_reason": "max_iter", + "n_newton_fallbacks": 0, + "end_newtrate": 0.5, + "seconds": 5206.991969823837 + }, + "pamica_seed7": { + "final_ll": -3.6978123737664954, + "stop_reason": "max_iter", + "n_newton_fallbacks": 0, + "end_newtrate": 0.5, + "seconds": 5979.722954750061 + } + }, + "pairs": { + "fortran_seed1 vs fortran_seed2": { + "mean": 0.9845232160684182, + "min": 0.8413590217123816, + "n_below_0.9": 2, + "worst5": [ + 0.841, + 0.851, + 0.932, + 0.937, + 0.94 + ] + }, + "pamica_seed13 vs fortran_seed1": { + "mean": 0.9956494072840422, + "min": 0.9456874180196005, + "n_below_0.9": 0, + "worst5": [ + 0.946, + 0.966, + 0.986, + 0.989, + 0.989 + ] + }, + "pamica_seed13 vs fortran_seed2": { + "mean": 0.9814609218531232, + "min": 0.7726103993365133, + "n_below_0.9": 3, + "worst5": [ + 0.773, + 0.838, + 0.897, + 0.918, + 0.938 + ] + }, + "pamica_seed42 vs fortran_seed1": { + "mean": 0.9632013836844461, + "min": 0.6669135684644986, + "n_below_0.9": 8, + "worst5": [ + 0.667, + 0.757, + 0.8, + 0.822, + 0.832 + ] + }, + "pamica_seed42 vs fortran_seed2": { + "mean": 0.9864819095469834, + "min": 0.8583950552591829, + "n_below_0.9": 3, + "worst5": [ + 0.858, + 0.863, + 0.896, + 0.908, + 0.964 + ] + }, + "pamica_seed7 vs fortran_seed1": { + "mean": 0.9949488656298753, + "min": 0.9431185504188633, + "n_below_0.9": 0, + "worst5": [ + 0.943, + 0.978, + 0.984, + 0.984, + 0.988 + ] + }, + "pamica_seed7 vs fortran_seed2": { + "mean": 0.9818638960989596, + "min": 0.785890714613924, + "n_below_0.9": 3, + "worst5": [ + 0.786, + 0.825, + 0.897, + 0.925, + 0.935 + ] + }, + "pamica_seed13 vs pamica_seed42": { + "mean": 0.9623214361648936, + "min": 0.657888742144425, + "n_below_0.9": 7, + "worst5": [ + 0.658, + 0.675, + 0.809, + 0.846, + 0.861 + ] + }, + "pamica_seed13 vs pamica_seed7": { + "mean": 0.9991797816142324, + "min": 0.9906842414174939, + "n_below_0.9": 0, + "worst5": [ + 0.991, + 0.995, + 0.997, + 0.997, + 0.998 + ] + }, + "pamica_seed42 vs pamica_seed7": { + "mean": 0.9643885413233992, + "min": 0.6694651529069076, + "n_below_0.9": 7, + "worst5": [ + 0.669, + 0.679, + 0.806, + 0.848, + 0.868 + ] + }, + "pamica_fixinit vs fortran_fixinit": { + "mean": 0.9999997990780136, + "min": 0.9999964129902119, + "n_below_0.9": 0, + "worst5": [ + 1.0, + 1.0, + 1.0, + 1.0, 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metric that needs no assignment step. Both implementations ran AMICA's default 2000 iterations with Newton disabled (`pamica`'s own default), to isolate the algorithm from initialization. With Newton enabled, some of the weakest components settle into different basins of equal or higher likelihood from different starts, in the reference's runs as in `pamica`'s: -against one reference run, one `pamica` seed of three differed on eight of seventy components and the other two matched at 0.995, +against one reference run, one `pamica` seed of three differed on eight of seventy components and the other two matched at 0.995 and 0.996, and two reference runs from different seeds differed on two. From a shared start the two implementations end with the same components (correlation 0.9999998). The single-model comparison uses a well-determined external recording ([NEMAR on002718](https://doi.org/10.82901/nemar.on002718), $k\approx153$, where $k$ = frames over squared channel count [@frank2025sufficient]) alongside the bundled 32-channel sample ($k\approx30$). 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zQeUQzbjXIxV8T5a)Xs)}B*C@V$59?Oq_XEPk?H6OIT^}P9?DQ(cQA+8tA{W_&41^|e1gXjt{1tx*8%IvV&t&G* zxB02U67|%-b*>lAx}I7G`$y*VT&<`1yti)xjpTt;!zVcvz4cU+8Vr7(;4N~GwH&{O zAsI5%NN(5xtEClEjj)}SECSOqpT_0ajC_?UdJ8xmR0w~hg5;%-(;mJMMEZ v9M;QuH^`jYd4577zPDEXzeB Date: Wed, 23 Sep 2026 17:59:58 -0700 Subject: [PATCH 42/58] Document the ensemble's invsigmin difference --- docs/guides/validation.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/docs/guides/validation.md b/docs/guides/validation.md index 94ccd5b..66f308f 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -249,7 +249,9 @@ The comparison is between the distributions of solutions the two implementations An ensemble of `N = 20` fits per implementation on the bundled sample EEG (`n_models = 2`, 3 mixture components, 100 iterations, matched schedule) gives these distributions of pairwise agreement (`benchmarks/reproduce_table1.py --tier bundled`, re-measured on 2026-09-23 with the code of epic #324 against the pinned v0.3.3 native binary, -whose runs here draw their own clock-based seeds; the 40 fits are saved in `.context/issue-351/raw/table1_bundled/bundled_multimodel_ensemble.npz`): +whose runs here draw their own clock-based seeds; the 40 fits are saved in `.context/issue-351/raw/table1_bundled/bundled_multimodel_ensemble.npz`). +The schedule matches except for one setting: the reference runs with `invsigmin` 0.0, the value EEGLAB's `runamica15.m` writes, and pamica with 1e-8. +The distributions: | Distribution (pairwise Hungarian-matched \|corr\|) | Mean | SD | Range | |---|---:|---:|---| From 26be0c07150794509edf27fe0620b964c75091af Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 18:00:07 -0700 Subject: [PATCH 43/58] Smooth the ensemble protocol sentence --- docs/guides/validation.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/docs/guides/validation.md b/docs/guides/validation.md index 66f308f..629b9dc 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -247,11 +247,10 @@ Multi-model AMICA is not partition-identifiable: fits from different starts reac so a single-run partition comparison with Fortran cannot serve as the acceptance bar. The comparison is between the distributions of solutions the two implementations sample. An ensemble of `N = 20` fits per implementation on the bundled sample EEG (`n_models = 2`, 3 mixture components, 100 iterations, matched schedule) -gives these distributions of pairwise agreement +gives the distributions of pairwise agreement below (`benchmarks/reproduce_table1.py --tier bundled`, re-measured on 2026-09-23 with the code of epic #324 against the pinned v0.3.3 native binary, whose runs here draw their own clock-based seeds; the 40 fits are saved in `.context/issue-351/raw/table1_bundled/bundled_multimodel_ensemble.npz`). The schedule matches except for one setting: the reference runs with `invsigmin` 0.0, the value EEGLAB's `runamica15.m` writes, and pamica with 1e-8. -The distributions: | Distribution (pairwise Hungarian-matched \|corr\|) | Mean | SD | Range | |---|---:|---:|---| From 315ff0c1c1be94fa409b5fb58e38d55e7ff1e440 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 18:15:15 -0700 Subject: [PATCH 44/58] Address the docs-claims review findings --- .context/decisions/0003-best-iterate-safeguard.md | 2 +- .context/progress_summary.md | 4 ++-- AGENTS.md | 4 ++-- docs/guides/amica-differences.md | 2 +- docs/guides/validation.md | 2 +- 5 files changed, 7 insertions(+), 7 deletions(-) diff --git a/.context/decisions/0003-best-iterate-safeguard.md b/.context/decisions/0003-best-iterate-safeguard.md index 2e34ebb..2f8fbb7 100644 --- a/.context/decisions/0003-best-iterate-safeguard.md +++ b/.context/decisions/0003-best-iterate-safeguard.md @@ -91,7 +91,7 @@ fit runs 300 iterations once, with the 100- and 200-iteration values read from its trajectory (checked equal to separate 100-iteration fits, with `keep_best` on and off, on two seeds on both sides). -| budget | Fortran mean (sd) | pamica return-last mean (sd) | pamica `keep_best` mean (sd) | sd ratio | pamica minus Fortran | KS p | restores | +| budget | Fortran mean (sd) | pamica return-last mean (sd) | pamica `keep_best` mean (sd) | sd ratio | pamica minus Fortran | Kolmogorov-Smirnov (KS) p | restores | |---:|---:|---:|---:|---:|---:|---:|---:| | 100 | -3.3550 (0.0029) | -3.3542 (0.0029) | -3.3542 (0.0029) | 1.0x | +0.0008 | 0.83 | 0 of 20 | | 200 | -3.3418 (0.0030) | -3.3416 (0.0022) | -3.3416 (0.0022) | 0.75x | +0.0002 | 0.57 | 0 of 20 | diff --git a/.context/progress_summary.md b/.context/progress_summary.md index bb0b216..440c885 100644 --- a/.context/progress_summary.md +++ b/.context/progress_summary.md @@ -17,7 +17,7 @@ what remains, as of epic #324 (after v0.3.3). User-facing detail is in `docs/cha sample data). - **Metrics:** single-model LL ~ -3.40 (Fortran -3.4018); Hungarian-matched component correlation ~0.997, clearing the >0.95 gate. Re-measured under epic #324 (#351) against the bundled - 200-iteration fixture: LL -3.4017 vs -3.4019, correlation 0.998, Amari 4.8e-3, on all three backends. + 200-iteration fixture: LL within 1.4e-4, correlation 0.998, Amari 4.8e-3, on all three backends. ### Adaptive PDF selection (issue #26) - All five `amica15.f90` `pdftype` density families ported to `AMICATorchNG`: 0 generalized @@ -31,7 +31,7 @@ what remains, as of epic #324 (after v0.3.3). User-facing detail is in `docs/cha - Validated by **distributional equivalence**: multi-model AMICA is not partition-identifiable, so the NG-vs-Fortran partition cross-correlation distribution is compared with Fortran's own run-to-run spread. Re-measured under epic #324 (#351): between minus within-Fortran +0.006 - (run-level permutation p=0.88; Amari +0.005, p=0.051), final LL -3.3541 vs -3.3543 (KS p=0.83). + (run-level permutation p=0.88; Amari +0.005, p=0.051), final LL -3.3541 vs -3.3543 (Kolmogorov-Smirnov (KS) p=0.83). Per-block sufficient stats agree with Fortran to round-off. - Per-model bias `c` update (`update_c`) ported to both backends, guarded to a no-op for `n_models=1` so single-model parity stays bit-exact. See `.context/issue-27/`. diff --git a/AGENTS.md b/AGENTS.md index 0f0c597..72ce073 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -114,7 +114,7 @@ remaining MLX gap vs the PyTorch backend is float32-only precision (Apple GPUs h ## Current Status - PyTorch backend with GPU/MPS/CPU support; the `AMICATorchNG` natural-gradient EM backend now matches the Fortran reference with Newton enabled and positive-definite (issue #24): against the - bundled 200-iteration `amicaout` fixture, LL -3.4017 vs -3.4019 and component correlation 0.998 on + bundled 200-iteration `amicaout` fixture, LL within 1.4e-4 and component correlation 0.998 on all three backends (re-measured under epic #324 in #351; ~0.997 when #24 closed). - `AMICA(backend="mlx")` and `AMICAICA(backend="mlx")` (epic #324 Phase 4, #313) run the MLX backend end to end: fit, `from_params_file`, `pcakeep`, the #50 degenerate-fit contract, `.pt` save/load (wrapper @@ -186,7 +186,7 @@ update from a merged state seeded through `load_comp_list` matches it to float64 pairwise cross-corr within-Fortran 0.626, within-pamica 0.638, between 0.632; between minus within-Fortran +0.006 (inside the ±0.05 margin; run-level permutation p=0.88; by Amari distance +0.005, p=0.051, pamica's ensemble spreading slightly more than Fortran's); final LL -3.3541 vs - -3.3543 (KS p=0.83). The single-run ~0.63 cross-corr matches Fortran's agreement with itself. + -3.3543 (Kolmogorov-Smirnov (KS) p=0.83). The single-run ~0.63 cross-corr matches Fortran's agreement with itself. See `docs/guides/validation.md`, `.context/issue-351/` and, for the pre-epic record, `.context/issue-27/multimodel_distributional_equivalence.md`. Supporting: per-block sufficient stats are bit-exact vs Fortran; the per-model bias `c` update diff --git a/docs/guides/amica-differences.md b/docs/guides/amica-differences.md index aa14fef..5ebdd1f 100644 --- a/docs/guides/amica-differences.md +++ b/docs/guides/amica-differences.md @@ -451,7 +451,7 @@ the PyTorch and NumPy updates match the native binary to float64 round-off after with `doscaling` on and off (`pamica/tests/test_component_rows.py`, opt-in with `AMICA_RUN_FORTRAN=1`). On the bundled sample (2 models, seed 42, Newton on, 300 iterations, `share_start=100`, `share_iter=100`, `comp_thresh=0.95`) the scan at iteration 100 merges one pair whose maps agree (|cos| 0.970) and the scans at 200 and 300 merge nothing, -so the fit ends with 63 of 64 components at log-likelihood -3.3410 (-3.3394 with sharing off; measured with the finished epic #324, issue #351). +so the fit ends with 63 of 64 components at log-likelihood -3.3410 (-3.3393 with sharing off; measured with the finished epic #324, issue #351). Right after this change, before the reference's iteration order (issue #339) and the later changes of epic #324, the same fit merged three such pairs (|cos| 0.956 to 0.971), and the old metric three whose maps did not (|cos| 0.06, 0.35 and 0.55). diff --git a/docs/guides/validation.md b/docs/guides/validation.md index 629b9dc..c038a84 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -159,7 +159,7 @@ Newton off, 2000 iterations (re-measured on 2026-09-23 with the code of epic #32 The five pairs average a correlation of 0.985 and an Amari distance of 0.011; the ten pairs among the five reference runs average 0.971 and 0.019. -The reference run of seed 303 ended in a lower-likelihood basin (-3.4006, against -3.3995 to -3.3996 for the other four), and its pair sets the five-pair means. +The reference run of seed 303 ended in a lower-likelihood basin (-3.4006, against -3.3995 to -3.3996 for the other four), and that pair dominates the five-pair means. The tier does not seed its reference runs (`AMICANative` draws a clock-based seed per run), so a rerun draws new starts, and an event like this one may or may not recur. With the unmixing matrices kept (`.context/issue-351/bundled_single_basins.py`), ten seeded reference runs (seeds 1-10, final LL -3.39984 to -3.39945) against the same five pamica fits give, over all 50 pairs, From 1136ae3c234a5dd9a35af5591c719208208b1822 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 18:15:58 -0700 Subject: [PATCH 45/58] Address the paper review findings --- docs/guides/validation.md | 2 +- paper.md | 25 ++++++++++++++----------- 2 files changed, 15 insertions(+), 12 deletions(-) diff --git a/docs/guides/validation.md b/docs/guides/validation.md index c038a84..afe597a 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -267,7 +267,7 @@ The three agreement distributions overlap, and so do the two likelihood distribu The three means lie within 0.012 of each other. The between-minus-within-Fortran difference is +0.006, inside the $\pm 0.05$ margin the original study set (run-level bootstrap 90% interval -0.002 to 0.014, `.context/issue-351/equivalence_check.py`). -The 190/400 pairwise values are not independent (each of the 40 runs appears in ~39 pairs), +The pairwise values (190 within-Fortran and 190 within-pamica, plus 400 cross-implementation pairs) are not independent (each of the 40 runs appears in 39 pairs), so a Mann-Whitney or TOST applied to the pairwise values is pseudoreplicated and its p-value is invalid. The significance test permutes the 40 runs as intact units instead (20000 permutations, statistic = within-Fortran minus between-implementation mean correlation). For the one-sided hypothesis that cross-implementation agreement is worse than Fortran's own run-to-run agreement, it gives $p = 0.88$. diff --git a/paper.md b/paper.md index 3073acf..1d1ccde 100644 --- a/paper.md +++ b/paper.md @@ -30,13 +30,15 @@ bibliography: paper.bib # Summary Independent Component Analysis (ICA) separates electroencephalographic and magnetoencephalographic (EEG/MEG) recordings into maximally independent sources that isolate brain, muscle, and artifact activities for downstream analysis [@makeig1995independent; @vigario1997independent; @iversen2019megeeg]. -Adaptive Mixture ICA (AMICA) [@palmer2006super; @palmer2007modeling; @palmer2012amica] models each source with a flexible, self-adjusting probability density and lets several ICA models coexist, one per segment of a recording. +Adaptive Mixture ICA (AMICA) [@palmer2006super; @palmer2007modeling; @palmer2012amica] models each source with a flexible, self-adjusting probability density and lets several ICA models coexist, +one per segment of a recording. Among the algorithms benchmarked by @delorme2012independent it returned the least dependent and most dipolar decompositions, -properties that study links to physiological interpretability. +properties that the study links to physiological interpretability. Its reference implementation, by Jason Palmer, is a Fortran program distributed as a compiled binary and usually run from MATLAB/EEGLAB; it runs only on the central processing unit (CPU) and has no Python interface. -`pamica` reproduces the reference Fortran results within numerical tolerance while running on the CPU, NVIDIA graphics processing units (GPUs, via CUDA), and Apple GPUs (through Apple's MLX array framework [@mlx2023]). +`pamica` reproduces the reference Fortran's single-model results within numerical tolerance, and its multi-model solutions spread like the reference's own, +while running on the CPU, NVIDIA graphics processing units (GPUs, via CUDA), and Apple GPUs (through Apple's MLX array framework [@mlx2023]). It reimplements the algorithm on PyTorch [@paszke2019pytorch], NumPy [@harris2020array], and SciPy [@virtanen2020scipy], and exposes a scikit-learn-style estimator under a BSD-3-Clause license. It writes the format EEGLAB's AMICA loader reads, so established MATLAB tooling consumes its results unchanged. @@ -52,10 +54,10 @@ General-purpose Python ICA implementations do not fill this gap. `scikit-learn` and `MNE-Python` provide FastICA [@hyvarinen2000independent] and Infomax [@bell1995information; @lee1999independent], while Picard [@ablin2018faster] offers faster-converging maximum-likelihood ICA; none implement AMICA's mixture of models, adaptive generalized-Gaussian densities, or Newton updates, so none can reproduce its decompositions. -`pamica` is for analysts who want AMICA-quality decompositions in Python, for anyone with a GPU who wants faster runs than the CPU-only binary, -and for methodologists who need a transparent reference to build on. +`pamica` serves analysts who want AMICA-quality decompositions in Python and anyone with a GPU who wants faster runs than the CPU-only binary; +it is also a transparent reference for methodologists to build on. The parity measurements reported here use EEG. -The algorithm itself is modality-agnostic, and an external user has fit rank-reduced, Maxwell-filtered MEG with it end to end, +The algorithm itself is modality-agnostic, and an external user has fit rank-reduced, Maxwell-filtered MEG with it end to end (see the research impact statement), but parity with the reference has not yet been measured on MEG. # State of the field @@ -90,12 +92,13 @@ Double precision is the default because the parity comparisons need it; single p Parity is measured two ways: by Hungarian-matched component correlation, and by the Amari distance [@amari1996new], a relabeling- and scale-invariant metric that needs no assignment step. -Both implementations ran AMICA's default 2000 iterations with Newton disabled (`pamica`'s own default), to isolate the algorithm from initialization. +Both implementations ran EEGLAB's default of 2000 iterations with Newton disabled (`pamica`'s own default), to isolate the algorithm from initialization. With Newton enabled, some of the weakest components settle into different basins of equal or higher likelihood from different starts, in the reference's runs as in `pamica`'s: against one reference run, one `pamica` seed of three differed on eight of seventy components and the other two matched at 0.995 and 0.996, and two reference runs from different seeds differed on two. From a shared start the two implementations end with the same components (correlation 0.9999998). -The single-model comparison uses a well-determined external recording ([NEMAR on002718](https://doi.org/10.82901/nemar.on002718), $k\approx153$, where $k$ = frames over squared channel count [@frank2025sufficient]) alongside the bundled 32-channel sample ($k\approx30$). +The single-model comparison uses a well-determined external recording (OpenNeuro ds002718, mirrored in the NEMAR archive [@delorme2022nemar] as [on002718](https://doi.org/10.82901/nemar.on002718), +$k\approx153$, where $k$ = frames over squared channel count [@frank2025sufficient]) alongside the bundled 32-channel sample ($k\approx30$). On the bundled sample one of the five reference runs ended in a lower-likelihood basin and sets the five-pair Amari mean; over 50 run pairs the distance between the implementations (0.004) is close to the reference's own run-to-run distance (0.005). A mixture of ICA models is not partition-identifiable, @@ -114,7 +117,7 @@ give $p=0.88$ by correlation and $p=0.051$ by Amari distance, by which `pamica`' | Multi | Ensemble agreement, cross $-$ within-Fortran | correlation $+0.006$ ($p=0.88$); Amari $+0.005$ ($p=0.051$) | | Multi | Ensemble log-likelihood: Fortran; `pamica` | $-3.3543$; $-3.3541$ (Kolmogorov-Smirnov $p=0.83$) | -: Parity of `pamica` with the Fortran reference. Multi-model rows are over 20-run ensembles (190 within-, 400 cross-implementation pairs); sd is the standard deviation, given where computed; +: Parity of `pamica` with the Fortran reference. Multi-model rows are over 20-run ensembles (190 within-Fortran and 190 within-`pamica`, plus 400 cross-implementation pairs); sd is the standard deviation, given where computed; $p$ values are one-sided run-level permutation tests. ![Multi-model ensemble partition-correlation (A) and log-likelihood (B) distributions, 20 `pamica` and 20 Fortran fits of the sample EEG; dashed lines mark each mean. @@ -145,10 +148,10 @@ where an MNE core developer and the author of a competing port lean toward `pami since this Center develops AMICA and maintains the reference Fortran and EEGLAB. `sccn/pAMICA` has been public since 2021, with public issues, pull requests, nine releases (six on PyPI), and a Zenodo archive. -Three researchers outside the author group have filed issues, two mid-analysis on their own data: +Three researchers outside the author group have filed issues, two of them mid-analysis on their own data: a 236-channel, 8.3-million-sample EEG decomposition (issue 207) and Maxwell-filtered 306-channel MEG (issue 221); the third is adopting AMICA for a multiverse analysis in MNE-Python (issue 206). -Integration into this Center's Python preprocessing and into NEMAR [@delorme2022nemar], the public archive we operate (800 datasets, ~40,000 participants, 55 TB), is in progress. +Integration into this Center's Python preprocessing and into NEMAR, the public archive we operate (800 datasets, ~40,000 participants, 55 TB), is in progress. # AI usage disclosure From caa381d3f28cb69d61215565274d2b7c0b4c8aa2 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 18:16:42 -0700 Subject: [PATCH 46/58] Give each ensemble distribution its own line style --- .context/issue-351/multimodel_ensemble.py | 137 +++++++++++++++++- .../multimodel_ensemble_distributions.pdf | Bin 43258 -> 43454 bytes .../multimodel_ensemble_distributions.png | Bin 152206 -> 159225 bytes docs/assets/figures/multimodel-ensemble.png | Bin 152206 -> 159225 bytes paper.md | 2 +- 5 files changed, 137 insertions(+), 2 deletions(-) diff --git a/.context/issue-351/multimodel_ensemble.py b/.context/issue-351/multimodel_ensemble.py index 52ffdde..6248b74 100644 --- a/.context/issue-351/multimodel_ensemble.py +++ b/.context/issue-351/multimodel_ensemble.py @@ -31,9 +31,13 @@ import sys from pathlib import Path +import matplotlib import numpy as np from scipy import stats +matplotlib.use("Agg") +import matplotlib.pyplot as plt # noqa: E402 + HERE = Path(__file__).resolve().parent REPO = HERE.parents[1] FIGURE = REPO / "docs/assets/figures/multimodel-ensemble.png" @@ -59,6 +63,137 @@ def fit_ensemble(n: int, threads: int) -> dict[str, np.ndarray]: return raw +# The figure of `.context/issue-27/multimodel_ensemble.py`, with a line style +# for each distribution besides its color (the #27 record keeps its own copy). +C_FORT, C_NG, C_BET = "#0072B2", "#E69F00", "#009E73" # Okabe-Ito + + +def figure(within_F, within_G, between, F_ll, G_ll, diff, p_perm, ks, out): + # Sized to its ACTUAL print footprint, not a big on-screen canvas: paper.md + # embeds this at width=100% of a ~5.36in single-column page (measured from the + # compiled paper.pdf), so figsize is set to that width directly -- LaTeX then + # displays it near 1:1 instead of shrinking a much larger canvas down to fit, + # which previously collapsed every font to an unreadable ~3pt in the printed + # PDF even though it looked fine on screen (figure-qa print-scale finding). + plt.rcParams.update( + {"font.size": 7, "axes.spines.top": False, "axes.spines.right": False} + ) + fig, (axA, axB) = plt.subplots(1, 2, figsize=(5.36, 4.2)) + bins = np.linspace(0.5, 1.0, 26) + for arr, col, ls, lab in [ + (within_F, C_FORT, "-", "within-Fortran"), + (within_G, C_NG, "--", "within-pamica"), + (between, C_BET, ":", "between (pamica-Fortran)"), + ]: + axA.hist(arr, bins=bins, density=True, color=col, alpha=0.25) + axA.hist( + arr, bins=bins, density=True, histtype="step", color=col, ls=ls, lw=2, + label=lab, + ) # fmt: skip + axA.axvline(arr.mean(), color=col, ls=ls, lw=1.2) + axA.set_xlabel("Hungarian-matched cross-correlation\n(stacked 2x32 components)") + axA.set_ylabel("density") + axA.set_title( + "A Partition-agreement distributions", + loc="left", + fontweight="bold", + fontsize=8, + ) + bins_ll = np.linspace( + min(F_ll.min(), G_ll.min()) - 0.005, max(F_ll.max(), G_ll.max()) + 0.005, 24 + ) + for arr, col, ls, lab in [ + (F_ll, C_FORT, "-", "Fortran"), + (G_ll, C_NG, "--", "pamica"), + ]: + axB.hist(arr, bins=bins_ll, density=True, color=col, alpha=0.25) + axB.hist( + arr, bins=bins_ll, density=True, histtype="step", color=col, ls=ls, lw=2, + label=lab, + ) # fmt: skip + axB.axvline(arr.mean(), color=col, ls=ls, lw=1.2) + axB.set_xlabel("final log-likelihood\n(mean per sample-channel)") + axB.set_ylabel("density") + axB.set_title( + "B Likelihood distributions", loc="left", fontweight="bold", fontsize=8 + ) + + # Both the legend and the stats box previously sat inside the axes and ended up + # overlapping the histogram bars (and each other) no matter where they were + # anchored -- with 3 distributions filling most of the plotted range, there was + # no empty pocket big enough to hold either. Reserve a fixed bottom margin for + # both instead and place them with figure-fraction (not axes-fraction) + # coordinates: axes-fraction anchors turned out to depend on the final axes + # height that tight_layout picks, which isn't known in advance and caused the + # legend/text to collide with the xlabel above it. get_position() gives each + # axes' true horizontal center after the layout below is fixed, so this keeps + # each panel's legend/text under its own histogram, not bleeding into the + # other panel. + fig.subplots_adjust(top=0.80, bottom=0.42, left=0.11, right=0.97, wspace=0.45) + cx_a = sum(axA.get_position().intervalx) / 2 + cx_b = sum(axB.get_position().intervalx) / 2 + + handles_a, labels_a = axA.get_legend_handles_labels() + fig.legend( + handles_a, labels_a, frameon=False, fontsize=6, + loc="upper center", bbox_to_anchor=(cx_a, 0.31), + ) # fmt: skip + fig.text( + cx_a, + 0.20, + f"mean corr. (run pairs)\n" + f"within-Fortran: {within_F.mean():.3f} (n={len(within_F)})\n" + f"within-pamica: {within_G.mean():.3f} (n={len(within_G)})\n" + f"between: {between.mean():.3f} (n={len(between)})\n" + f"diff: {diff:+.3f} (margin +/-0.05)\n" + f"perm. p={p_perm:.2f}", + ha="center", + va="top", + fontsize=5.5, + bbox=dict(boxstyle="round", fc="white", ec="0.7", alpha=0.95), + ) + + handles_b, labels_b = axB.get_legend_handles_labels() + fig.legend( + handles_b, labels_b, frameon=False, fontsize=6, + loc="upper center", bbox_to_anchor=(cx_b, 0.31), + ) # fmt: skip + fig.text( + cx_b, + 0.23, + f"mean final LL\n" + f"Fortran: {F_ll.mean():.4f} (sd {F_ll.std():.3f})\n" + f"pamica: {G_ll.mean():.4f} (sd {G_ll.std():.3f})\n" + f"gap: {abs(F_ll.mean() - G_ll.mean()):.4f} (100-iter budget)\n" + f"KS p={ks:.2f}" + if ks >= 0.01 + else f"KS p={ks:.0e}", + ha="center", + va="top", + fontsize=5.5, + bbox=dict(boxstyle="round", fc="white", ec="0.7", alpha=0.9), + ) + + fig.text( + 0.5, + 0.90, + "Vertical lines mark each distribution's mean, in its line style.", + ha="center", + fontsize=6.5, + style="italic", + ) + fig.suptitle( + "Multi-model AMICA (n_models=2): pamica vs Fortran ensembles, real sample EEG", + fontweight="bold", + fontsize=8.5, + y=0.97, + ) + fig.savefig( + out / "multimodel_ensemble_distributions.png", bbox_inches="tight", dpi=300 + ) + fig.savefig(out / "multimodel_ensemble_distributions.pdf", bbox_inches="tight") + + def main() -> None: p = argparse.ArgumentParser() p.add_argument("n", nargs="?", type=int, default=20) @@ -143,7 +278,7 @@ def main() -> None: if a.no_figure: return - ens27.figure(within_F, within_G, between, F_ll, G_ll, diff, p_perm, ks, HERE) + figure(within_F, within_G, between, F_ll, G_ll, diff, p_perm, ks, HERE) shutil.copyfile(HERE / "multimodel_ensemble_distributions.png", FIGURE) print(f"figure -> {FIGURE} (n={n} each)") diff --git a/.context/issue-351/multimodel_ensemble_distributions.pdf 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zyRD*q`Zk@;4=q{~Z|Bh{GWGPX3vxX*zPd-^{SL=uo7FJ)(Nng#u}s!(ZF^{;x`BJ1N`r>&1A%kx*u9N|cl!VBtXiUykhI{4*9PdT+2# zr!aQg{z}GM$U0AA0Zw6yI;jhimCPH`m$C%z@C!-6x!tb}iOdx*L5>de#6THbEtQ*^ zx{{~FzpfQBMxfN25Yfn)Q^fLeH$#G=WeC}}C40tQfRBYg_-R|9)QW?pU2z-X0(HZ= zN{C`G02*-sA^3@ORf48wmf%pnTT5}4j6NNHq4(NB34bIc=Wd2HrF;f-&swWT#^{YA znnSCd{A)W3A+v7NLC1rc`44w&xY5y&lRXiugR!K>qp~Ihj6>-PqWnKCw2EJ;Cp0@k z_ck^>R7~nk4lp4*iQDZ(bW&9PBEw~rh*I-qo)A}zfqg58Q}Zc8aj?pN8Z@>CL~eGQ z_@5Lp7c11Yn5-MNMw;Oq%Dvy2do`K}k3?1(FRfKcQBr|YDcEoPsEuCin Date: Wed, 23 Sep 2026 18:17:12 -0700 Subject: [PATCH 47/58] Label the external single-model figures as pre-epic --- README.md | 2 +- docs/guides/validation.md | 4 +++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 4dc7449..66b7ac1 100644 --- a/README.md +++ b/README.md @@ -14,7 +14,7 @@ single-model output is written in exactly the reference's on-disk format and loads directly in EEGLAB. Single-model results match the Fortran reference (Hungarian-matched component correlation ~ 0.998 -on well-determined data, Newton disabled); see the +on well-determined data, Newton disabled, measured before the fitting changes of epic #324; re-measurement in issue #357); see the [documentation](https://eeglab.org/pAMICA/) for validation details and the backend-selection guide. diff --git a/docs/guides/validation.md b/docs/guides/validation.md index afe597a..0bd59b0 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -20,7 +20,7 @@ Throughout, IC abbreviates independent component and LL log-likelihood. |---|---|---| | Source-density score and log-density (non-GG families) | vs the literal `amica15.f90` expressions | bit-exact ($<10^{-12}$) | | Per-block sufficient statistics and one M-step | vs Fortran | bit-exact ($\sim\!10^{-15}$) | -| Single-model solution (`do_newton=0`, $k\approx153$) | log-likelihood, component correlation vs Fortran | LL within ~0.0005 of $-3.6993$; correlation 0.998 | +| Single-model solution (`do_newton=0`, $k\approx153$) | log-likelihood, component correlation vs Fortran | LL gap ~0.0003 from $-3.6993$; correlation 0.998 (measured before epic #324; re-measurement tracked in issue #357) | | Single-model solution (`do_newton=0`, bundled, $k\approx30$) | Amari distance vs Fortran | 0.011 over the protocol's 5 run pairs, one of whose reference runs ended in another basin; 0.004 over 50 pairs (Fortran vs Fortran 0.005) | | Every backend against the reference (harness defaults, bundled) | `validate_implementations.py --backend all`: PyTorch, NumPy and MLX each vs Fortran | from independent starts: LL within 2.8e-4 (the reference's own seed-to-seed standard deviation is 2.6e-4), correlation 0.9991, Amari distance 0.004, for all three; from a shared start: LL within 1.6e-6, correlation 0.99999993 ([per-backend rows](#parity-rows-per-backend)) | | Multi-model solution | distributional similarity over 20-run ensembles | between-implementation correlation within 0.006 of Fortran's own run-to-run agreement (one-sided permutation $p = 0.88$; Amari distance $p = 0.051$); final log-likelihood $-3.3541$ against $-3.3543$ (KS $p = 0.83$) | @@ -142,6 +142,8 @@ distance: - Log-likelihood ~ -3.6993 ($k\approx153$; Fortran ~ -3.6993, gap ~0.0003). - Hungarian-matched component correlation ~0.998 ($k\approx153$; Fortran-vs-Fortran self-consistency over the same 5 seeds: ~0.999), clearing the >0.95 gate. +- The two $k\approx153$ figures above were measured before epic #324's changes to the fit; + their re-measurement with the epic's code is tracked in issue #357. - Amari distance on the bundled sample: 0.011 over the protocol's five run pairs, 0.004 over 50 pairs (next subsection). ### The bundled sample From ef79da9a0b5831ae6952addcf4246aabdd1c57ed Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 18:17:21 -0700 Subject: [PATCH 48/58] Reflow the README parity sentence --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 66b7ac1..9b8df1d 100644 --- a/README.md +++ b/README.md @@ -14,9 +14,9 @@ single-model output is written in exactly the reference's on-disk format and loads directly in EEGLAB. Single-model results match the Fortran reference (Hungarian-matched component correlation ~ 0.998 -on well-determined data, Newton disabled, measured before the fitting changes of epic #324; re-measurement in issue #357); see the -[documentation](https://eeglab.org/pAMICA/) for validation details and the -backend-selection guide. +on well-determined data, Newton disabled; measured before the fitting changes of epic #324, +re-measurement in issue #357); see the [documentation](https://eeglab.org/pAMICA/) for +validation details and the backend-selection guide. ## Overview From c19c588ff9fd523f98b3864308bed7bb4646533c Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 21:43:36 -0700 Subject: [PATCH 49/58] Record the external tier run --- .../issue-351/raw/table1_external/report.json | 28 +++++++++++++ .../issue-351/raw/table1_external/stdout.log | 42 +++++++++++++++++++ 2 files changed, 70 insertions(+) create mode 100644 .context/issue-351/raw/table1_external/report.json create mode 100644 .context/issue-351/raw/table1_external/stdout.log diff --git a/.context/issue-351/raw/table1_external/report.json b/.context/issue-351/raw/table1_external/report.json new file mode 100644 index 0000000..3520b5e --- /dev/null +++ b/.context/issue-351/raw/table1_external/report.json @@ -0,0 +1,28 @@ +{ + "external": { + "tier": "external", + "n_channels": 70, + "n_frames": 747750, + "k": 152.60204081632654, + "wall_clock_s": 26185.370152069023, + "single_model": { + "n_channels": 70, + "n_seeds_requested": 5, + "n_seeds_ok": 5, + "n_fortran_ok": 5, + "ng_vs_fortran_corr_mean": 0.9996495858496243, + "ng_vs_fortran_corr_min": 0.9602403962666957, + "ng_vs_fortran_corr_sd": 0.000479692302794331, + "ng_vs_fortran_amari_mean": 0.001258754660040508, + "ng_vs_fortran_amari_sd": 0.0006199672303702011, + "fortran_vs_fortran_corr_mean": 0.998267073292794, + "fortran_vs_fortran_corr_min": 0.9167018463145121, + "fortran_vs_fortran_amari_mean": 0.002489315961253494, + "fortran_ll_mean": -3.699346392049425, + "fortran_ll_sd": 6.525058589552108e-05, + "ng_ll_mean": -3.6993407627685135, + "ng_ll_sd": 4.121894736588951e-05, + "ll_gap_of_means": 5.629280911634282e-06 + } + } +} \ No newline at end of file diff --git a/.context/issue-351/raw/table1_external/stdout.log b/.context/issue-351/raw/table1_external/stdout.log new file mode 100644 index 0000000..47746fc --- /dev/null +++ b/.context/issue-351/raw/table1_external/stdout.log @@ -0,0 +1,42 @@ +reproduce_table1: tier=external, threads=16, out_dir=/home/yahya/epic324-runs/external +device: CUDA (NVIDIA GeForce RTX 4090) +Fortran reference binary: /home/yahya/.cache/pamica/bin/v0.3.3/amica15-linux-x64 (native/v0.3.3) + +### external tier ### +data: benchmarks/data/ds002718_sub-002_eeg70_full.npy (70ch x 747750fr, k=152.6) +[external] seed 201: Fortran (16 threads, do_newton=0)... +[external] seed 201: Fortran done in 2246s, LL=-3.6993 +[external] seed 201: pamica (device=cuda, do_newton=0)... +[external] seed 201: pamica done in 1941s, LL=-3.6993, mean_corr=0.9999, min_corr=0.9996, amari=0.0008 +[external] seed 202: Fortran (16 threads, do_newton=0)... +[external] seed 202: Fortran done in 2559s, LL=-3.6994 +[external] seed 202: pamica (device=cuda, do_newton=0)... +[external] seed 202: pamica done in 5013s, LL=-3.6993, mean_corr=0.9987, min_corr=0.9602, amari=0.0024 +[external] seed 203: Fortran (16 threads, do_newton=0)... +[external] seed 203: Fortran done in 2363s, LL=-3.6993 +[external] seed 203: pamica (device=cuda, do_newton=0)... +[external] seed 203: pamica done in 4320s, LL=-3.6993, mean_corr=0.9999, min_corr=0.9985, amari=0.0012 +[external] seed 204: Fortran (16 threads, do_newton=0)... +[external] seed 204: Fortran done in 1972s, LL=-3.6993 +[external] seed 204: pamica (device=cuda, do_newton=0)... +[external] seed 204: pamica done in 1893s, LL=-3.6993, mean_corr=1.0000, min_corr=0.9998, amari=0.0007 +[external] seed 205: Fortran (16 threads, do_newton=0)... +[external] seed 205: Fortran done in 1992s, LL=-3.6995 +[external] seed 205: pamica (device=cuda, do_newton=0)... +[external] seed 205: pamica done in 1886s, LL=-3.6994, mean_corr=0.9998, min_corr=0.9955, amari=0.0012 +============================================================================== +EXTERNAL tier: 70ch x 747750fr, k=152.6 +============================================================================== +------------------------------------------------------------------------------ +Row: Single | Log-likelihood gap (on002718) + paper: within ~0.0005 of -3.6993 + measured: Fortran mean=-3.6993 (sd 0.0001); pamica mean=-3.6993 (sd 0.0000); gap=0.0000 (n=5/5 seeds ok) +------------------------------------------------------------------------------ +Row: Single | Component correlation (on002718) + paper: 0.998 + measured: pamica vs Fortran: mean=0.9996 (min=0.9602, sd 0.0005) + measured: Fortran vs Fortran self-consistency: mean=0.9983 (min=0.9167) +------------------------------------------------------------------------------ +external tier wall-clock: 26185s + +wrote /home/yahya/epic324-runs/external/report.json From 4fdfbbb8a17638e85200bfb30f67c0c44381488c Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 21:44:40 -0700 Subject: [PATCH 50/58] Fill the external-tier figures and fix rounding slips --- .../decisions/0003-best-iterate-safeguard.md | 6 ++-- AGENTS.md | 2 +- README.md | 7 ++--- benchmarks/README_dimsweep.md | 6 ++++ docs/guides/validation.md | 31 +++++++++++++------ paper.md | 6 ++-- 6 files changed, 38 insertions(+), 20 deletions(-) diff --git a/.context/decisions/0003-best-iterate-safeguard.md b/.context/decisions/0003-best-iterate-safeguard.md index 2f8fbb7..4dd982c 100644 --- a/.context/decisions/0003-best-iterate-safeguard.md +++ b/.context/decisions/0003-best-iterate-safeguard.md @@ -95,7 +95,7 @@ on and off, on two seeds on both sides). |---:|---:|---:|---:|---:|---:|---:|---:| | 100 | -3.3550 (0.0029) | -3.3542 (0.0029) | -3.3542 (0.0029) | 1.0x | +0.0008 | 0.83 | 0 of 20 | | 200 | -3.3418 (0.0030) | -3.3416 (0.0022) | -3.3416 (0.0022) | 0.75x | +0.0002 | 0.57 | 0 of 20 | -| 300 | -3.3393 (0.0027) | -3.3392 (0.0020) | -3.3392 (0.0020) | 0.75x | +0.0001 | 0.98 | 1 of 20 | +| 300 | -3.3392 (0.0027) | -3.3391 (0.0020) | -3.3391 (0.0020) | 0.75x | +0.0001 | 0.98 | 1 of 20 | - The late overshoots that motivated this decision do not occur in these fits: the largest likelihood decrease in any of the 20 pamica trajectories @@ -106,8 +106,8 @@ on and off, on two seeds on both sides). the column-rule `doscaling` (#333). - A restore fired in one of the 20 fits, and only at the 300-iteration budget: seed 3, whose best iterate (iteration 299) beat its last by 4.2e-6. -- The mean gap is gone at every budget: pamica's mean is within 8e-4 of the - reference's at 100 iterations and within 2e-4 at 200 and 300, where #51 +- The mean gap is gone at every budget: pamica's mean lies 8.1e-4 above the + reference's at 100 iterations, 2.1e-4 at 200 and 1.0e-4 at 300, where #51 measured -0.009 at 100 and attributed it to convergence speed. The bundled tier's clock-seeded ensemble (`benchmarks/reproduce_table1.py`, `AMICA` seeds 1-20) agrees: -3.3541 against -3.3543, KS p 0.83. Refitting diff --git a/AGENTS.md b/AGENTS.md index 72ce073..864f635 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -203,7 +203,7 @@ update from a merged state seeded through `load_comp_list` matches it to float64 against the pinned binary): the late overshoots are gone (largest LL dip 1.2e-5 in 20 trajectories, no Newton fallbacks), the sd ratio is 1.0x at 100 iterations with or without `keep_best`, a restore fired in one of 20 seeded fits, at the 300-iteration budget only (gain 4.2e-6), and the mean gap is - +8e-4 at 100 iterations and within 2e-4 at 200 and 300. The pre-epic code on the same seeds + +8.1e-4 at 100 iterations, +2.1e-4 at 200 and +1.0e-4 at 300. The pre-epic code on the same seeds reproduces the old gap; 7 of its 20 fits stopped early on a `min_dll` check that counted LL dips as small gains (fixed in #339), and its full-length fits trail by 0.006. `keep_best` stays on. Single-model #24 parity stays byte-for-byte (monotone => no restore). Inactive under `do_reject`. See ADR 0003 and `.context/issue-351/`. diff --git a/README.md b/README.md index 9b8df1d..9ec963b 100644 --- a/README.md +++ b/README.md @@ -13,10 +13,9 @@ EEG/EMG blind source separation and is a drop-in replacement for EEGLAB's AMICA: single-model output is written in exactly the reference's on-disk format and loads directly in EEGLAB. -Single-model results match the Fortran reference (Hungarian-matched component correlation ~ 0.998 -on well-determined data, Newton disabled; measured before the fitting changes of epic #324, -re-measurement in issue #357); see the [documentation](https://eeglab.org/pAMICA/) for -validation details and the backend-selection guide. +Single-model results match the Fortran reference (Hungarian-matched component correlation 0.9996 +on well-determined data, Newton disabled, with the reference agreeing with itself at 0.998); see the +[documentation](https://eeglab.org/pAMICA/) for validation details and the backend-selection guide. ## Overview diff --git a/benchmarks/README_dimsweep.md b/benchmarks/README_dimsweep.md index 041eeef..b544577 100644 --- a/benchmarks/README_dimsweep.md +++ b/benchmarks/README_dimsweep.md @@ -148,6 +148,12 @@ Single-fit wall-clock at this exact configuration (70ch, 747,750 frames, 2000 it | native-fortran-f64 | 1303 s (~22 min) | | pamica, CUDA float64 | 1856 s (~31 min) | +The full external tier was re-run on 2026-09-23 with the code of epic #324 (issue #351) on the same +kind of host (32 cores, RTX 4090), shared with other users' jobs, with the v0.3.3 reference at +`--threads 16`: the Fortran fits took 1972-2559 s each, the pamica CUDA float64 fits 1886-5013 s +(the slowest while the GPU was shared), and the whole tier, run sequentially, 26185 s (~7.3 hours). +On an unshared host expect the pipelined estimates below. + Scaling those to the paper's 5-seed protocol (Fortran phases can run back to back while each seed's GPU phase overlaps the next seed's Fortran phase, the way the original workstation script pipelined them): diff --git a/docs/guides/validation.md b/docs/guides/validation.md index 0bd59b0..b56a3c3 100644 --- a/docs/guides/validation.md +++ b/docs/guides/validation.md @@ -20,7 +20,7 @@ Throughout, IC abbreviates independent component and LL log-likelihood. |---|---|---| | Source-density score and log-density (non-GG families) | vs the literal `amica15.f90` expressions | bit-exact ($<10^{-12}$) | | Per-block sufficient statistics and one M-step | vs Fortran | bit-exact ($\sim\!10^{-15}$) | -| Single-model solution (`do_newton=0`, $k\approx153$) | log-likelihood, component correlation vs Fortran | LL gap ~0.0003 from $-3.6993$; correlation 0.998 (measured before epic #324; re-measurement tracked in issue #357) | +| Single-model solution (`do_newton=0`, $k\approx153$) | log-likelihood, component correlation vs Fortran | both at LL $-3.6993$ (gap of the means $6\times10^{-6}$); correlation 0.9996 (Fortran vs Fortran 0.998) | | Single-model solution (`do_newton=0`, bundled, $k\approx30$) | Amari distance vs Fortran | 0.011 over the protocol's 5 run pairs, one of whose reference runs ended in another basin; 0.004 over 50 pairs (Fortran vs Fortran 0.005) | | Every backend against the reference (harness defaults, bundled) | `validate_implementations.py --backend all`: PyTorch, NumPy and MLX each vs Fortran | from independent starts: LL within 2.8e-4 (the reference's own seed-to-seed standard deviation is 2.6e-4), correlation 0.9991, Amari distance 0.004, for all three; from a shared start: LL within 1.6e-6, correlation 0.99999993 ([per-backend rows](#parity-rows-per-backend)) | | Multi-model solution | distributional similarity over 20-run ensembles | between-implementation correlation within 0.006 of Fortran's own run-to-run agreement (one-sided permutation $p = 0.88$; Amari distance $p = 0.051$); final log-likelihood $-3.3541$ against $-3.3543$ (KS $p = 0.83$) | @@ -139,13 +139,26 @@ it is not sensitive to whether a particular small dataset happens to be well-con 32-channel sample ($k\approx30$, at the project's own data-adequacy boundary) gives a consistent Amari distance: -- Log-likelihood ~ -3.6993 ($k\approx153$; Fortran ~ -3.6993, gap ~0.0003). -- Hungarian-matched component correlation ~0.998 ($k\approx153$; Fortran-vs-Fortran self-consistency - over the same 5 seeds: ~0.999), clearing the >0.95 gate. -- The two $k\approx153$ figures above were measured before epic #324's changes to the fit; - their re-measurement with the epic's code is tracked in issue #357. +- Log-likelihood $-3.6993$ on both sides ($k\approx153$): Fortran $-3.699346$ (sd $6.5\times10^{-5}$), pamica $-3.699341$ (sd $4.1\times10^{-5}$), + a gap of the means of $5.6\times10^{-6}$. +- Hungarian-matched component correlation 0.9996 ($k\approx153$; sd 0.0005, lowest single component 0.960), + against the reference's own agreement over the same five runs of 0.998 (lowest component 0.917), clearing the >0.95 gate; + Amari distance 0.0013 (Fortran against Fortran 0.0025). - Amari distance on the bundled sample: 0.011 over the protocol's five run pairs, 0.004 over 50 pairs (next subsection). +Per seed on the external recording (re-measured on 2026-09-23 with the code of epic #324; `benchmarks/reproduce_table1.py --tier external` on the RTX 4090 host, +pamica on CUDA in float64, the pinned v0.3.3 reference at 16 threads, clock-seeded; `.context/issue-351/raw/table1_external/`): + +| seed | mean matched correlation | min matched correlation | Amari distance | +|---:|---:|---:|---:| +| 201 | 0.9999 | 0.9996 | 0.0008 | +| 202 | 0.9987 | 0.9602 | 0.0024 | +| 203 | 0.9999 | 0.9985 | 0.0012 | +| 204 | 1.0000 | 0.9998 | 0.0007 | +| 205 | 0.9998 | 0.9955 | 0.0012 | + +Before epic #324's changes to the fit, the same protocol gave a log-likelihood gap of ~0.0003, a correlation of ~0.998 and a Fortran-vs-Fortran agreement of ~0.999. + ### The bundled sample On the bundled 32-channel sample ($k\approx30$) the reproduction tier fits five pamica seeds (301-305) and five reference runs, one pair per seed, @@ -206,7 +219,7 @@ The seeded pair above (0.985) is a second measurement of the reference's own see See issue #145 and the optional init-robustness follow-up #198. A single-seed supplementary run gives the float32 side at this data size: -the MLX backend (float32), with the same keywords and the same start as the CUDA seed-7 fit, stops on its learning-rate floor at iteration 951, +the MLX backend (float32), with the same keywords and the same start as the CUDA seed-7 fit, stops on its learning-rate floor after 952 iterations, after about 120 likelihood decreases below float32 resolution, at log-likelihood -3.69809 (the float64 fit was at -3.69791 at that iteration). Its components match the float64 seed-7 fit at a mean correlation of 0.985 (minimum 0.907) and the reference's seed 1 at 0.983 (minimum 0.905); with seed 42, float32 and float64 differ on 10 of the 70 components (mean 0.955). @@ -283,7 +296,7 @@ Refitting the pamica half with that code (e38aa11) against the same 20 reference (`.context/issue-351/multimodel_pamica_fits.py`). Seven of those 20 fits stop early on `min_dll`, whose check counted likelihood dips as small gains until issue #339 (mean $-3.3679$), and the 13 that run the full 100 iterations average $-3.3600$, so the old gap came partly from the early stops and partly from the update rule of that code. -A seeded ensemble with the same settings (the reference seeded 0-19 and single-threaded) agrees within $8\times10^{-4}$ at 100 iterations and within $2\times10^{-4}$ at 200 and 300 +A seeded ensemble with the same settings (the reference seeded 0-19 and single-threaded) puts pamica's mean $8.1\times10^{-4}$ above the reference's at 100 iterations, $2.1\times10^{-4}$ at 200 and $1.0\times10^{-4}$ at 300 ([ADR 0003](https://github.com/sccn/pAMICA/blob/main/.context/decisions/0003-best-iterate-safeguard.md)). ### Amari distance: a second, assignment-free metric @@ -294,7 +307,7 @@ so it is an independent check on the same 20-run ensembles, computed from the sa (`.context/issue-351/multimodel_ensemble.py`, which reuses `.context/issue-27/amari_distance.py`). Each stacked 2-model matrix is split into its per-model 32x32 blocks; since which Fortran model corresponds to which pamica model is not identified, both label pairings are tried and the lower-distance pairing is kept, per run pair. -This pairing correction lowers the mean distance by 0.019 on this ensemble (333 of the 780 run pairs take the swapped pairing), +This pairing correction lowers the mean distance by 0.0185 on this ensemble (333 of the 780 run pairs take the swapped pairing), the same order as the gaps between the groups below, so part of those gaps may reflect how often each group needs the swap. | Distribution (Amari distance, lower is better) | Mean | SD | diff --git a/paper.md b/paper.md index e890d97..5d613a1 100644 --- a/paper.md +++ b/paper.md @@ -108,10 +108,10 @@ give $p=0.88$ by correlation and $p=0.051$ by Amari distance, by which `pamica`' | Regime | Metric (dataset) | Result (mean) | |---|---|---| -| Single | Log-likelihood gap (on002718) | within ~0.0005 of $-3.6993$ | -| Single | Component correlation (on002718) | 0.998 | +| Single | Log-likelihood gap (on002718) | $6\times10^{-6}$, both at $-3.6993$ | +| Single | Component correlation (on002718) | 0.9996 (Fortran vs Fortran 0.998) | | Single | Amari distance (bundled) | 0.011 (5 run pairs); 0.004 (50 pairs) | -| Single | Score functions, sufficient statistics | round-off, $\le 2\times10^{-15}$ (relative) | +| Single | Score functions; sufficient statistics | $\le 2\times10^{-15}$ absolute; $3\times10^{-16}$ relative | | Multi | Correlation, one run: cross; within-Fortran | 0.632; 0.626 (sd 0.04) | | Multi | Amari, one run: cross; within-Fortran | 0.172; 0.166 (sd 0.02) | | Multi | Ensemble agreement, cross $-$ within-Fortran | correlation $+0.006$ ($p=0.88$); Amari $+0.005$ ($p=0.051$) | From b8db96a882f8b607ab11dd1ac89038a4581e3065 Mon Sep 17 00:00:00 2001 From: "github-actions[bot]" Date: Thu, 24 Sep 2026 04:45:53 +0000 Subject: [PATCH 51/58] Rebuild paper.pdf --- paper.pdf | Bin 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zZoRVCk*V~IDZN=Rqx8)wC-ap$vtM{!7L@ZZm4RPMe~dEtPPq{QUzL#y$}K)3Exa?i v%IGO&oLxODRVFUM2bfi!2P Date: Wed, 23 Sep 2026 22:09:05 -0700 Subject: [PATCH 52/58] Save the pinned parameter files before Phase 17 --- .context/issue-351/pin_check.py | 27 ++++++++++++++-- .../pin_check_pinned_params_pre_phase17.json | 10 ++++++ .context/issue-351/raw/pytest_full.log | 32 +++++++++---------- 3 files changed, 51 insertions(+), 18 deletions(-) create mode 100644 .context/issue-351/raw/pin_check_pinned_params_pre_phase17.json diff --git a/.context/issue-351/pin_check.py b/.context/issue-351/pin_check.py index 832f681..d6fc824 100644 --- a/.context/issue-351/pin_check.py +++ b/.context/issue-351/pin_check.py @@ -9,6 +9,11 @@ parameter file and stop. uv run python .context/issue-351/pin_check.py OUT.json + +With ``--dump PATH`` it also saves the pinned calls' parameter files, and with +``--against PATH`` it compares them with a saved dump instead, so a change of +``AMICANative``'s defaults (epic #324 Phase 17) can be checked to leave every +pinned call's ``input.param`` unchanged. """ from __future__ import annotations @@ -136,8 +141,10 @@ def main() -> None: ), } # fmt: skip out = {} + pinned: dict[str, str] = {} for name, (before, after) in checks.items(): a, b = native_param(**before), native_param(**after) + pinned[name] = b out[name] = {"identical": a == b, "lines": a.count("\n")} seeded = { "newton_seeds same-start reference": ( @@ -164,10 +171,26 @@ def main() -> None: nm = before.get("num_models", 1) a = seeded_param(state_models=nm, **before) b = seeded_param(state_models=nm, **after) + pinned[name] = b out[name] = {"identical": a == b, "lines": a.count("\n")} - Path(sys.argv[1]).write_text(json.dumps(out, indent=2)) + args = sys.argv[1:] + if "--dump" in args: + Path(args[args.index("--dump") + 1]).write_text(json.dumps(pinned, indent=2)) + if "--against" in args: + saved = json.loads(Path(args[args.index("--against") + 1]).read_text()) + out = { + name: { + "pinned_identical_to_saved": pinned[name] == saved[name], + "unpinned_identical_to_pinned": out[name]["identical"], + } + for name in pinned + } + ok = all(v["pinned_identical_to_saved"] for v in out.values()) + else: + ok = all(v["identical"] for v in out.values()) + Path(args[0]).write_text(json.dumps(out, indent=2)) print(json.dumps(out, indent=2)) - if not all(v["identical"] for v in out.values()): + if not ok: raise SystemExit("a pinned call writes a different input.param") diff --git a/.context/issue-351/raw/pin_check_pinned_params_pre_phase17.json b/.context/issue-351/raw/pin_check_pinned_params_pre_phase17.json new file mode 100644 index 0000000..54dd392 --- /dev/null +++ b/.context/issue-351/raw/pin_check_pinned_params_pre_phase17.json @@ -0,0 +1,10 @@ +{ + "reproduce_table1 single-model sweep": "files ./data.fdt\noutdir ./amicaout/\nblock_size 512\ndo_opt_block 0\nblk_min 256\nblk_step 256\nblk_max 1024\nnum_models 1\nmax_threads 4\nuse_min_dll 0\nmin_dll 1.000000e-09\nuse_grad_norm 0\nmin_grad_norm 1.000000e-07\nnum_mix_comps 3\npdftype 0\nmax_iter 2000\nnum_samples 1\nfield_blocksize 1\ndo_history 0\nhiststep 10\nshare_comps 0\nshare_start 100\ncomp_thresh 0.990000\nshare_iter 100\nlrate 0.050000\nminlrate 1.000000e-08\nmineig 1.000000e-12\nlratefact 0.500000\nrholrate 0.050000\nrho0 1.500000\nminrho 1.000000\nmaxrho 2.000000\nrholratefact 0.500000\nkurt_start 3\nnum_kurt 5\nkurt_int 1\ndo_newton 0\nnewt_start 50\nnewt_ramp 10\nnewtrate 1.000000\ndo_reject 0\nnumrej 3\nrejsig 3.000000\nrejstart 2\nrejint 3\nwritestep 20\nwrite_nd 0\nwrite_LLt 1\ndecwindow 1\nmax_decs 3\nfix_init 0\nupdate_A 1\nupdate_c 1\nupdate_gm 1\nupdate_alpha 1\nupdate_mu 1\nupdate_beta 1\ninvsigmax 100.000000\ninvsigmin 0.000000\ndo_rho 1\nload_rej 0\nload_W 0\nload_c 0\nload_gm 0\nload_alpha 0\nload_mu 0\nload_beta 0\nload_rho 0\nload_comp_list 0\ndo_mean 1\ndo_sphere 1\ndoPCA 1\npcakeep 32\npcadb 30.000000\nbyte_size 4\ndoscaling 1\nscalestep 1\ndata_dim 32\nfield_dim 64\n", + "reproduce_table1 multi-model ensemble": "files ./data.fdt\noutdir ./amicaout/\nblock_size 512\ndo_opt_block 0\nblk_min 256\nblk_step 256\nblk_max 1024\nnum_models 2\nmax_threads 4\nuse_min_dll 1\nmin_dll 1.000000e-09\nuse_grad_norm 1\nmin_grad_norm 1.000000e-07\nnum_mix_comps 3\npdftype 0\nmax_iter 100\nnum_samples 1\nfield_blocksize 1\ndo_history 0\nhiststep 10\nshare_comps 0\nshare_start 100\ncomp_thresh 0.990000\nshare_iter 100\nlrate 0.050000\nminlrate 1.000000e-08\nmineig 1.000000e-12\nlratefact 0.500000\nrholrate 0.050000\nrho0 1.500000\nminrho 1.000000\nmaxrho 2.000000\nrholratefact 0.500000\nkurt_start 3\nnum_kurt 5\nkurt_int 1\ndo_newton 1\nnewt_start 50\nnewt_ramp 10\nnewtrate 1.000000\ndo_reject 0\nnumrej 3\nrejsig 3.000000\nrejstart 2\nrejint 3\nwritestep 20\nwrite_nd 0\nwrite_LLt 1\ndecwindow 1\nmax_decs 3\nfix_init 0\nupdate_A 1\nupdate_c 1\nupdate_gm 1\nupdate_alpha 1\nupdate_mu 1\nupdate_beta 1\ninvsigmax 100.000000\ninvsigmin 0.000000\ndo_rho 1\nload_rej 0\nload_W 0\nload_c 0\nload_gm 0\nload_alpha 0\nload_mu 0\nload_beta 0\nload_rho 0\nload_comp_list 0\ndo_mean 1\ndo_sphere 1\ndoPCA 1\npcakeep 32\npcadb 30.000000\nbyte_size 4\ndoscaling 1\nscalestep 1\ndata_dim 32\nfield_dim 64\n", + "keep_best_ensemble reference": "files ./data.fdt\noutdir ./amicaout/\nblock_size 512\ndo_opt_block 0\nblk_min 256\nblk_step 256\nblk_max 1024\nnum_models 2\nmax_threads 1\nuse_min_dll 1\nmin_dll 1.000000e-09\nuse_grad_norm 1\nmin_grad_norm 1.000000e-07\nnum_mix_comps 3\npdftype 0\nmax_iter 300\nnum_samples 1\nfield_blocksize 1\ndo_history 0\nhiststep 10\nshare_comps 0\nshare_start 100\ncomp_thresh 0.990000\nshare_iter 100\nlrate 0.050000\nminlrate 1.000000e-08\nmineig 1.000000e-12\nlratefact 0.500000\nrholrate 0.050000\nrho0 1.500000\nminrho 1.000000\nmaxrho 2.000000\nrholratefact 0.500000\nkurt_start 3\nnum_kurt 5\nkurt_int 1\ndo_newton 1\nnewt_start 50\nnewt_ramp 10\nnewtrate 1.000000\ndo_reject 0\nnumrej 3\nrejsig 3.000000\nrejstart 2\nrejint 3\nwritestep 20\nwrite_nd 0\nwrite_LLt 1\ndecwindow 1\nmax_decs 3\nfix_init 0\nupdate_A 1\nupdate_c 1\nupdate_gm 1\nupdate_alpha 1\nupdate_mu 1\nupdate_beta 1\ninvsigmax 100.000000\ninvsigmin 0.000000\ndo_rho 1\nload_rej 0\nload_W 0\nload_c 0\nload_gm 0\nload_alpha 0\nload_mu 0\nload_beta 0\nload_rho 0\nload_comp_list 0\ndo_mean 1\ndo_sphere 1\ndoPCA 1\npcakeep 32\npcadb 30.000000\nbyte_size 4\ndoscaling 1\nscalestep 1\nseed 3\ndata_dim 32\nfield_dim 64\n", + "bundled_single_basins reference": "files ./data.fdt\noutdir ./amicaout/\nblock_size 512\ndo_opt_block 0\nblk_min 256\nblk_step 256\nblk_max 1024\nnum_models 1\nmax_threads 3\nuse_min_dll 0\nmin_dll 1.000000e-09\nuse_grad_norm 0\nmin_grad_norm 1.000000e-07\nnum_mix_comps 3\npdftype 0\nmax_iter 2000\nnum_samples 1\nfield_blocksize 1\ndo_history 0\nhiststep 10\nshare_comps 0\nshare_start 100\ncomp_thresh 0.990000\nshare_iter 100\nlrate 0.050000\nminlrate 1.000000e-08\nmineig 1.000000e-12\nlratefact 0.500000\nrholrate 0.050000\nrho0 1.500000\nminrho 1.000000\nmaxrho 2.000000\nrholratefact 0.500000\nkurt_start 3\nnum_kurt 5\nkurt_int 1\ndo_newton 0\nnewt_start 50\nnewt_ramp 10\nnewtrate 1.000000\ndo_reject 0\nnumrej 3\nrejsig 3.000000\nrejstart 2\nrejint 3\nwritestep 20\nwrite_nd 0\nwrite_LLt 1\ndecwindow 1\nmax_decs 3\nfix_init 0\nupdate_A 1\nupdate_c 1\nupdate_gm 1\nupdate_alpha 1\nupdate_mu 1\nupdate_beta 1\ninvsigmax 100.000000\ninvsigmin 0.000000\ndo_rho 1\nload_rej 0\nload_W 0\nload_c 0\nload_gm 0\nload_alpha 0\nload_mu 0\nload_beta 0\nload_rho 0\nload_comp_list 0\ndo_mean 1\ndo_sphere 1\ndoPCA 1\npcakeep 32\npcadb 30.000000\nbyte_size 4\ndoscaling 1\nscalestep 1\nseed 4\ndata_dim 32\nfield_dim 64\n", + "newton_seeds reference": "files ./data.fdt\noutdir ./amicaout/\nblock_size 512\ndo_opt_block 0\nblk_min 256\nblk_step 256\nblk_max 1024\nnum_models 1\nmax_threads 10\nuse_min_dll 0\nmin_dll 1.000000e-09\nuse_grad_norm 0\nmin_grad_norm 1.000000e-07\nnum_mix_comps 3\npdftype 0\nmax_iter 2000\nnum_samples 1\nfield_blocksize 1\ndo_history 0\nhiststep 10\nshare_comps 0\nshare_start 100\ncomp_thresh 0.990000\nshare_iter 100\nlrate 0.050000\nminlrate 1.000000e-08\nmineig 1.000000e-12\nlratefact 0.500000\nrholrate 0.050000\nrho0 1.500000\nminrho 1.000000\nmaxrho 2.000000\nrholratefact 0.500000\nkurt_start 3\nnum_kurt 5\nkurt_int 1\ndo_newton 1\nnewt_start 50\nnewt_ramp 10\nnewtrate 1.000000\ndo_reject 0\nnumrej 3\nrejsig 3.000000\nrejstart 2\nrejint 3\nwritestep 20\nwrite_nd 0\nwrite_LLt 1\ndecwindow 1\nmax_decs 3\nfix_init 0\nupdate_A 1\nupdate_c 1\nupdate_gm 1\nupdate_alpha 1\nupdate_mu 1\nupdate_beta 1\ninvsigmax 100.000000\ninvsigmin 0.000000\ndo_rho 1\nload_rej 0\nload_W 0\nload_c 0\nload_gm 0\nload_alpha 0\nload_mu 0\nload_beta 0\nload_rho 0\nload_comp_list 0\ndo_mean 1\ndo_sphere 1\ndoPCA 1\npcakeep 32\npcadb 30.000000\nbyte_size 4\ndoscaling 1\nscalestep 1\nseed 1\ndata_dim 32\nfield_dim 64\n", + "newton_seeds same-start reference": "files ./data.fdt\noutdir ./out/\nblock_size 512\ndo_opt_block 0\nblk_min 256\nblk_step 256\nblk_max 1024\nnum_models 1\nmax_threads 1\nuse_min_dll 0\nmin_dll 1.000000e-09\nuse_grad_norm 0\nmin_grad_norm 1.000000e-07\nnum_mix_comps 3\npdftype 0\nmax_iter 2000\nnum_samples 1\nfield_blocksize 1\ndo_history 0\nhiststep 10\nshare_comps 0\nshare_start 100\ncomp_thresh 0.990000\nshare_iter 100\nlrate 0.050000\nminlrate 1.000000e-08\nmineig 1.000000e-12\nlratefact 0.500000\nrholrate 0.050000\nrho0 1.500000\nminrho 1.000000\nmaxrho 2.000000\nrholratefact 0.500000\nkurt_start 3\nnum_kurt 5\nkurt_int 1\ndo_newton 1\nnewt_start 50\nnewt_ramp 10\nnewtrate 1.000000\ndo_reject 0\nnumrej 3\nrejsig 3.000000\nrejstart 2\nrejint 3\nwritestep 2001\nwrite_nd 0\nwrite_LLt 0\ndecwindow 1\nmax_decs 3\nfix_init 0\nupdate_A 1\nupdate_c 1\nupdate_gm 1\nupdate_alpha 1\nupdate_mu 1\nupdate_beta 1\ninvsigmax 100.000000\ninvsigmin 0.000000\ndo_rho 1\nload_rej 0\nload_W 0\nload_c 1\nload_gm 1\nload_alpha 1\nload_mu 1\nload_beta 1\nload_rho 1\nload_comp_list 0\ndo_mean 1\ndo_sphere 1\ndoPCA 1\npcakeep 32\npcadb 30.000000\nbyte_size 4\ndoscaling 1\nscalestep 1\nindir ./init\ndata_dim 32\nfield_dim 64\nload_mean 1\nload_sphere 0\nload_A 1\n", + "orientation_check": "files ./data.fdt\noutdir ./out/\nblock_size 512\ndo_opt_block 0\nblk_min 256\nblk_step 256\nblk_max 1024\nnum_models 1\nmax_threads 1\nuse_min_dll 0\nmin_dll 1.000000e-09\nuse_grad_norm 0\nmin_grad_norm 1.000000e-07\nnum_mix_comps 3\npdftype 0\nmax_iter 1\nnum_samples 1\nfield_blocksize 1\ndo_history 0\nhiststep 10\nshare_comps 0\nshare_start 100\ncomp_thresh 0.990000\nshare_iter 100\nlrate 0.050000\nminlrate 1.000000e-08\nmineig 1.000000e-12\nlratefact 0.500000\nrholrate 0.050000\nrho0 1.500000\nminrho 1.000000\nmaxrho 2.000000\nrholratefact 0.500000\nkurt_start 3\nnum_kurt 5\nkurt_int 1\ndo_newton 1\nnewt_start 50\nnewt_ramp 10\nnewtrate 1.000000\ndo_reject 0\nnumrej 3\nrejsig 3.000000\nrejstart 2\nrejint 3\nwritestep 2\nwrite_nd 0\nwrite_LLt 0\ndecwindow 1\nmax_decs 3\nfix_init 0\nupdate_A 1\nupdate_c 1\nupdate_gm 1\nupdate_alpha 1\nupdate_mu 1\nupdate_beta 1\ninvsigmax 100.000000\ninvsigmin 0.000000\ndo_rho 1\nload_rej 0\nload_W 0\nload_c 1\nload_gm 1\nload_alpha 1\nload_mu 1\nload_beta 1\nload_rho 1\nload_comp_list 0\ndo_mean 1\ndo_sphere 1\ndoPCA 1\npcakeep 32\npcadb 30.000000\nbyte_size 4\ndoscaling 1\nscalestep 1\nindir ./init\ndata_dim 32\nfield_dim 64\nload_mean 1\nload_sphere 0\nload_A 1\n", + "share_comps_counts part c": "files ./data.fdt\noutdir ./out/\nblock_size 512\ndo_opt_block 0\nblk_min 256\nblk_step 256\nblk_max 1024\nnum_models 2\nmax_threads 1\nuse_min_dll 1\nmin_dll 1.000000e-09\nuse_grad_norm 1\nmin_grad_norm 1.000000e-07\nnum_mix_comps 3\npdftype 0\nmax_iter 8\nnum_samples 1\nfield_blocksize 1\ndo_history 0\nhiststep 10\nshare_comps 0\nshare_start 8\ncomp_thresh 0.990000\nshare_iter 100\nlrate 0.050000\nminlrate 1.000000e-08\nmineig 1.000000e-12\nlratefact 0.500000\nrholrate 0.050000\nrho0 1.500000\nminrho 1.000000\nmaxrho 2.000000\nrholratefact 0.500000\nkurt_start 3\nnum_kurt 5\nkurt_int 1\ndo_newton 0\nnewt_start 50\nnewt_ramp 10\nnewtrate 1.000000\ndo_reject 0\nnumrej 3\nrejsig 3.000000\nrejstart 2\nrejint 3\nwritestep 9\nwrite_nd 0\nwrite_LLt 0\ndecwindow 1\nmax_decs 3\nfix_init 0\nupdate_A 1\nupdate_c 1\nupdate_gm 1\nupdate_alpha 1\nupdate_mu 1\nupdate_beta 1\ninvsigmax 100.000000\ninvsigmin 0.000000\ndo_rho 1\nload_rej 0\nload_W 0\nload_c 1\nload_gm 1\nload_alpha 1\nload_mu 1\nload_beta 1\nload_rho 1\nload_comp_list 0\ndo_mean 1\ndo_sphere 1\ndoPCA 1\npcakeep 32\npcadb 30.000000\nbyte_size 4\ndoscaling 1\nscalestep 1\nindir ./init\ndata_dim 32\nfield_dim 64\nload_mean 1\nload_sphere 0\nload_A 1\n" +} \ No newline at end of file diff --git a/.context/issue-351/raw/pytest_full.log b/.context/issue-351/raw/pytest_full.log index 3e55c54..c9236c3 100644 --- a/.context/issue-351/raw/pytest_full.log +++ b/.context/issue-351/raw/pytest_full.log @@ -11,29 +11,29 @@ created: 8/8 workers ........................................................................ 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[100%] =============================== warnings summary =============================== pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll @@ -49,4 +49,4 @@ pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll sign, logdet = _umath_linalg.slogdet(a, signature=signature) -- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html -===== 1955 passed, 40 skipped, 3 xfailed, 3 warnings in 1555.73s (0:25:55) ===== +===== 1955 passed, 40 skipped, 3 xfailed, 3 warnings in 1404.05s (0:23:24) ===== From 4c9aa9b926a72fa5265b919731b5f4c5495b5a27 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 22:15:07 -0700 Subject: [PATCH 53/58] Re-check the reference pins after Phase 17 --- .context/issue-351/pin_check.py | 38 +++++- .context/issue-351/pin_run_check.py | 113 ++++++++++++++++ .../issue-351/raw/pin_check_post_phase17.json | 76 +++++++++++ .../raw/pin_run_check_post_phase17.json | 128 ++++++++++++++++++ 4 files changed, 353 insertions(+), 2 deletions(-) create mode 100644 .context/issue-351/pin_run_check.py create mode 100644 .context/issue-351/raw/pin_check_post_phase17.json create mode 100644 .context/issue-351/raw/pin_run_check_post_phase17.json diff --git a/.context/issue-351/pin_check.py b/.context/issue-351/pin_check.py index d6fc824..b4856bf 100644 --- a/.context/issue-351/pin_check.py +++ b/.context/issue-351/pin_check.py @@ -13,7 +13,10 @@ With ``--dump PATH`` it also saves the pinned calls' parameter files, and with ``--against PATH`` it compares them with a saved dump instead, so a change of ``AMICANative``'s defaults (epic #324 Phase 17) can be checked to leave every -pinned call's ``input.param`` unchanged. +pinned call's settings unchanged. Phase 17 reorders the keys and adds +``do_approx_sphere 1``, the binary's compiled value, so this mode reports the +settings added, removed and changed as well as byte identity; +``pin_run_check.py`` runs the binary on both forms. """ from __future__ import annotations @@ -98,6 +101,29 @@ def fake_run_reference(param, workdir, **_): return captured["param"] +def _settings(text: str) -> dict[str, str]: + """An ``input.param`` text as {key: value}; a repeated key is an error.""" + out: dict[str, str] = {} + for line in text.splitlines(): + if line.strip(): + key, _, value = line.partition(" ") + if key in out: + raise ValueError(f"repeated key {key!r}") + out[key] = value.strip() + return out + + +def settings_diff(saved: str, now: str) -> dict: + """How two ``input.param`` texts differ as settings, ignoring key order.""" + a, b = _settings(saved), _settings(now) + return { + "same_key_order": list(a) == list(b), + "added": {k: b[k] for k in b.keys() - a.keys()}, + "removed": {k: a[k] for k in a.keys() - b.keys()}, + "changed": {k: [a[k], b[k]] for k in a.keys() & b.keys() if a[k] != b[k]}, + } + + def main() -> None: import _reference_settings as rs import bundled_single_basins as basins @@ -181,11 +207,19 @@ def main() -> None: out = { name: { "pinned_identical_to_saved": pinned[name] == saved[name], + **settings_diff(saved[name], pinned[name]), "unpinned_identical_to_pinned": out[name]["identical"], } for name in pinned } - ok = all(v["pinned_identical_to_saved"] for v in out.values()) + # Byte identity, or the same settings in another order plus keys at + # the binary's compiled value (pin_run_check.py runs both forms). + ok = all( + v["pinned_identical_to_saved"] + or (not v["changed"] and not v["removed"] + and v["added"] == {"do_approx_sphere": "1"}) + for v in out.values() + ) # fmt: skip else: ok = all(v["identical"] for v in out.values()) Path(args[0]).write_text(json.dumps(out, indent=2)) diff --git a/.context/issue-351/pin_run_check.py b/.context/issue-351/pin_run_check.py new file mode 100644 index 0000000..dfdd4db --- /dev/null +++ b/.context/issue-351/pin_run_check.py @@ -0,0 +1,113 @@ +"""Run the reference binary on both forms of a pinned ``input.param`` +(issue #351, after epic #324 Phase 17). + +Phase 17 (#354) rebuilt ``AMICANative``'s parameter table, so a pinned call +now writes its keys in a new order and adds ``do_approx_sphere 1``, the value +compiled into the binary (``amica15_header.f90``), with every other key and +value unchanged (``pin_check.py --against``). The binary reads keys by name, +so the two files should give the same run. This script checks that on the +bundled sample: for each pinned configuration it lets ``AMICANative`` write +its current ``input.param``, runs the binary on it, then runs it again in a +copy of the work directory whose ``input.param`` has the pre-Phase-17 key +order and no ``do_approx_sphere`` line, and compares every output file byte +for byte, except that the per-iteration wall-clock times are removed from +``out.txt`` first. Seeded and single-threaded, so each run is deterministic. + + uv run python .context/issue-351/pin_run_check.py OUT.json +""" + +from __future__ import annotations + +import filecmp +import json +import re +import shutil +import sys +from pathlib import Path + +HERE = Path(__file__).resolve().parent +sys.path.insert(0, str(HERE)) + +SAVED = HERE / "raw/pin_check_pinned_params_pre_phase17.json" +# The end of each iteration line of out.txt, e.g. "( 0.19 s, 0.0 h)". +TIMING = re.compile(r"\(\s*[0-9.]+ s,\s*[0-9.]+ h\)") + + +def old_form(new_text: str, old_text: str) -> str: + """``new_text``'s lines in ``old_text``'s key order, without the key + Phase 17 added; keys ``old_text`` lacks (``seed``) keep their place last.""" + lines = {ln.split(None, 1)[0]: ln for ln in new_text.splitlines() if ln.strip()} + lines.pop("do_approx_sphere") + order = [ln.split(None, 1)[0] for ln in old_text.splitlines() if ln.strip()] + keys = [k for k in order if k in lines] + [k for k in lines if k not in order] + return "\n".join(lines[k] for k in keys) + "\n" + + +def compare_run(name: str, kwargs: dict, data, saved: dict) -> dict: + import pamica.native.engine as engine + + real = engine.subprocess.run + record: dict = {} + + def both_forms(cmd, cwd=None, **kw): + work = Path(cwd) + twin = work.parent / (work.name + "_old_form") + shutil.copytree(work, twin) + new_text = (work / "input.param").read_text() + (twin / "input.param").write_text(old_form(new_text, saved[name])) + record["new_has_approx"] = "do_approx_sphere 1" in new_text + proc_old = real(cmd, cwd=twin, **kw) + proc = real(cmd, cwd=cwd, **kw) + a, b = work / "amicaout", twin / "amicaout" + files = sorted(p.name for p in a.iterdir()) + binary = [f for f in files if f != "out.txt"] + match, mismatch, errors = filecmp.cmpfiles(a, b, binary, shallow=False) + logs = [TIMING.sub("", (d / "out.txt").read_text()) for d in (a, b)] + (match if logs[0] == logs[1] else mismatch).append("out.txt (times removed)") + record.update( + files=files, identical=match, different=mismatch, missing=errors, + returncodes=[proc.returncode, proc_old.returncode], + ) # fmt: skip + shutil.rmtree(twin) + return proc + + engine.subprocess.run = both_forms + try: + engine.AMICANative(**kwargs).fit(data) + finally: + engine.subprocess.run = real + record["all_identical"] = ( + not record["different"] and not record["missing"] and bool(record["identical"]) + ) + return record + + +def main() -> None: + import _reference_settings as rs + import keep_best_ensemble as kb + import newton_seeds as ns + + data = kb.load_data() + saved = json.loads(SAVED.read_text()) + t1 = rs._table1() + one = dict(threads=1, max_threads=1, timeout=3600, seed=1) + configs = { + "reproduce_table1 single-model sweep": { + **one, **t1.single_model_reference_kwargs(20)}, + "reproduce_table1 multi-model ensemble": { + **one, **t1.multimodel_reference_kwargs(20)}, + "newton_seeds reference": {**one, **ns.fortran_kwargs(60)}, + } # fmt: skip + out = {name: compare_run(name, kw, data, saved) for name, kw in configs.items()} + Path(sys.argv[1]).write_text(json.dumps(out, indent=2)) + print( + json.dumps( + {k: (v["all_identical"], len(v["identical"])) for k, v in out.items()} + ) + ) + if not all(v["all_identical"] for v in out.values()): + raise SystemExit("the two forms of a pinned input.param gave different runs") + + +if __name__ == "__main__": + main() diff --git a/.context/issue-351/raw/pin_check_post_phase17.json b/.context/issue-351/raw/pin_check_post_phase17.json new file mode 100644 index 0000000..812312a --- /dev/null +++ b/.context/issue-351/raw/pin_check_post_phase17.json @@ -0,0 +1,76 @@ +{ + "reproduce_table1 single-model sweep": { + "pinned_identical_to_saved": false, + "same_key_order": false, + "added": { + "do_approx_sphere": "1" + }, + "removed": {}, + "changed": {}, + "unpinned_identical_to_pinned": false + }, + "reproduce_table1 multi-model ensemble": { + "pinned_identical_to_saved": false, + "same_key_order": false, + "added": { + "do_approx_sphere": "1" + }, + "removed": {}, + "changed": {}, + "unpinned_identical_to_pinned": false + }, + "keep_best_ensemble reference": { + "pinned_identical_to_saved": false, + "same_key_order": false, + "added": { + "do_approx_sphere": "1" + }, + "removed": {}, + "changed": {}, + "unpinned_identical_to_pinned": false + }, + "bundled_single_basins reference": { + "pinned_identical_to_saved": false, + "same_key_order": false, + "added": { + "do_approx_sphere": "1" + }, + "removed": {}, + "changed": {}, + "unpinned_identical_to_pinned": false + }, + "newton_seeds reference": { + "pinned_identical_to_saved": false, + "same_key_order": false, + "added": { + "do_approx_sphere": "1" + }, + "removed": {}, + "changed": {}, + "unpinned_identical_to_pinned": false + }, + "newton_seeds same-start reference": { + "pinned_identical_to_saved": true, + "same_key_order": true, + "added": {}, + "removed": {}, + "changed": {}, + "unpinned_identical_to_pinned": true + }, + "orientation_check": { + "pinned_identical_to_saved": true, + "same_key_order": true, + "added": {}, + "removed": {}, + "changed": {}, + "unpinned_identical_to_pinned": true + }, + "share_comps_counts part c": { + "pinned_identical_to_saved": true, + "same_key_order": true, + "added": {}, + "removed": {}, + "changed": {}, + "unpinned_identical_to_pinned": true + } +} \ No newline at end of file diff --git a/.context/issue-351/raw/pin_run_check_post_phase17.json b/.context/issue-351/raw/pin_run_check_post_phase17.json new file mode 100644 index 0000000..60b0ddb --- /dev/null +++ b/.context/issue-351/raw/pin_run_check_post_phase17.json @@ -0,0 +1,128 @@ +{ + "reproduce_table1 single-model sweep": { + "new_has_approx": true, + "files": [ + "A", + "LL", + "LLt", + "S", + "W", + "alpha", + "c", + "comp_list", + "gm", + "mean", + "mu", + "out.txt", + "rho", + "sbeta" + ], + "identical": [ + "A", + "LL", + "LLt", + "S", + "W", + "alpha", + "c", + "comp_list", + "gm", + "mean", + "mu", + "rho", + "sbeta", + "out.txt (times removed)" + ], + "different": [], + "missing": [], + "returncodes": [ + 0, + 0 + ], + "all_identical": true + }, + "reproduce_table1 multi-model ensemble": { + "new_has_approx": true, + "files": [ + "A", + "LL", + "LLt", + "S", + "W", + "alpha", + "c", + "comp_list", + "gm", + "mean", + "mu", + "out.txt", + "rho", + "sbeta" + ], + "identical": [ + "A", + "LL", + "LLt", + "S", + "W", + "alpha", + "c", + "comp_list", + "gm", + "mean", + "mu", + "rho", + "sbeta", + "out.txt (times removed)" + ], + "different": [], + "missing": [], + "returncodes": [ + 0, + 0 + ], + "all_identical": true + }, + "newton_seeds reference": { + "new_has_approx": true, + "files": [ + "A", + "LL", + "LLt", + "S", + "W", + "alpha", + "c", + "comp_list", + "gm", + "mean", + "mu", + "out.txt", + "rho", + "sbeta" + ], + "identical": [ + "A", + "LL", + "LLt", + "S", + "W", + "alpha", + "c", + "comp_list", + "gm", + "mean", + "mu", + "rho", + "sbeta", + "out.txt (times removed)" + ], + "different": [], + "missing": [], + "returncodes": [ + 0, + 0 + ], + "all_identical": true + } +} \ No newline at end of file From ae5c90a5879a88b0b0e77cdd54157f9c95f36261 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 22:16:32 -0700 Subject: [PATCH 54/58] Pin do_approx_sphere in the reference settings --- .context/issue-351/pin_run_check.py | 5 ++-- .../issue-351/raw/pin_check_post_phase17.json | 30 +++++++++++-------- benchmarks/reproduce_table1.py | 13 ++++---- 3 files changed, 29 insertions(+), 19 deletions(-) diff --git a/.context/issue-351/pin_run_check.py b/.context/issue-351/pin_run_check.py index dfdd4db..636c68c 100644 --- a/.context/issue-351/pin_run_check.py +++ b/.context/issue-351/pin_run_check.py @@ -4,8 +4,9 @@ Phase 17 (#354) rebuilt ``AMICANative``'s parameter table, so a pinned call now writes its keys in a new order and adds ``do_approx_sphere 1``, the value compiled into the binary (``amica15_header.f90``), with every other key and -value unchanged (``pin_check.py --against``). The binary reads keys by name, -so the two files should give the same run. This script checks that on the +value unchanged (``pin_check.py --against``); ``REFERENCE_SETTINGS`` in +``benchmarks/reproduce_table1.py`` now pins that key too. The binary reads +keys by name, so the two files should give the same run. This script checks that on the bundled sample: for each pinned configuration it lets ``AMICANative`` write its current ``input.param``, runs the binary on it, then runs it again in a copy of the work directory whose ``input.param`` has the pre-Phase-17 key diff --git a/.context/issue-351/raw/pin_check_post_phase17.json b/.context/issue-351/raw/pin_check_post_phase17.json index 812312a..dae97b5 100644 --- a/.context/issue-351/raw/pin_check_post_phase17.json +++ b/.context/issue-351/raw/pin_check_post_phase17.json @@ -50,27 +50,33 @@ "unpinned_identical_to_pinned": false }, "newton_seeds same-start reference": { - "pinned_identical_to_saved": true, - "same_key_order": true, - "added": {}, + "pinned_identical_to_saved": false, + "same_key_order": false, + "added": { + "do_approx_sphere": "1" + }, "removed": {}, "changed": {}, - "unpinned_identical_to_pinned": true + "unpinned_identical_to_pinned": false }, "orientation_check": { - "pinned_identical_to_saved": true, - "same_key_order": true, - "added": {}, + "pinned_identical_to_saved": false, + "same_key_order": false, + "added": { + "do_approx_sphere": "1" + }, "removed": {}, "changed": {}, - "unpinned_identical_to_pinned": true + "unpinned_identical_to_pinned": false }, "share_comps_counts part c": { - "pinned_identical_to_saved": true, - "same_key_order": true, - "added": {}, + "pinned_identical_to_saved": false, + "same_key_order": false, + "added": { + "do_approx_sphere": "1" + }, "removed": {}, "changed": {}, - "unpinned_identical_to_pinned": true + "unpinned_identical_to_pinned": false } } \ No newline at end of file diff --git a/benchmarks/reproduce_table1.py b/benchmarks/reproduce_table1.py index cffaaca..cef2ae9 100644 --- a/benchmarks/reproduce_table1.py +++ b/benchmarks/reproduce_table1.py @@ -108,9 +108,11 @@ # The reference's settings for every Table 1 run: the values of the bundled # pamica/sample_data/input.param, which AMICANative's defaults mirrored when -# the table was measured. Spelled out, so that a change of AMICANative's own -# defaults cannot change this protocol; each call adds its model count, -# iteration budget and the settings it overrides. +# the table was measured, and do_approx_sphere 1, the binary's compiled value +# for a key that file leaves unset (AMICANative writes it since issue #354). +# Spelled out, so that a change of AMICANative's own defaults cannot change +# this protocol; each call adds its model count, iteration budget and the +# settings it overrides. REFERENCE_SETTINGS: dict[str, Any] = { "block_size": 512, "do_opt_block": 0, "blk_min": 256, "blk_step": 256, "blk_max": 1024, "use_min_dll": 1, "min_dll": 1e-09, "use_grad_norm": 1, @@ -123,8 +125,9 @@ "rejsig": 3.0, "rejstart": 2, "rejint": 3, "decwindow": 1, "max_decs": 3, "fix_init": 0, "update_A": 1, "update_c": 1, "update_gm": 1, "update_alpha": 1, "update_mu": 1, "update_beta": 1, "invsigmax": 100.0, - "invsigmin": 0.0, "do_rho": 1, "do_mean": 1, "do_sphere": 1, "doPCA": 1, - "pcadb": 30.0, "byte_size": 4, "doscaling": 1, "scalestep": 1, + "invsigmin": 0.0, "do_rho": 1, "do_mean": 1, "do_sphere": 1, + "do_approx_sphere": 1, "doPCA": 1, "pcadb": 30.0, "byte_size": 4, + "doscaling": 1, "scalestep": 1, } # fmt: skip From 8ef629b7741a2425acecbb3a0b3c2e3bc058c558 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 22:42:29 -0700 Subject: [PATCH 55/58] Record the test runs after the Phase 17 merge --- .../raw/gated_tests_post_phase17.log | 109 + .../raw/pytest_full_post_phase17.log | 4063 +++++++++++++++++ 2 files changed, 4172 insertions(+) create mode 100644 .context/issue-351/raw/gated_tests_post_phase17.log create mode 100644 .context/issue-351/raw/pytest_full_post_phase17.log diff --git a/.context/issue-351/raw/gated_tests_post_phase17.log b/.context/issue-351/raw/gated_tests_post_phase17.log new file mode 100644 index 0000000..9c9aea8 --- /dev/null +++ b/.context/issue-351/raw/gated_tests_post_phase17.log @@ -0,0 +1,109 @@ +============================= test session starts ============================== +platform darwin -- Python 3.12.14, pytest-9.1.1, pluggy-1.6.0 +rootdir: /Users/yahya/Documents/git/mlx-fc-phase15-final-parity +configfile: pytest.ini +plugins: cov-7.1.0, xdist-3.8.0 +collected 37 items + +pamica/tests/test_fortran_param_forwarding.py .....................Running PyTorch AMICA (natural-gradient EM backend)... +WARNING: params.json settings with no AMICATorchNG equivalent are ignored (NG uses its own behavior): ['do_history', 'histstep', 'writestep']. The Fortran run may honor them, so a parity comparison can differ. +Fitting AMICA with 32 channels, 4096 samples +Models: 1, Mixture components: 3 + AMICA-NG: 0%| | 0/2 [00:00= 1] +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_validate_rejects_unusable_sweeps[0-1024-128-blk_min must be >= 1] +pamica/tests/test_blocktune.py::test_validate_rejects_unusable_sweeps[-4096-1024-128-blk_min must be >= 1] +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_validate_rejects_unusable_sweeps[-4096-1024-128-blk_min must be >= 1] +pamica/tests/test_blocktune.py::test_validate_rejects_unusable_sweeps[128-1024-0-blk_step must be >= 1] +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_validate_rejects_unusable_sweeps[128-1024-0-blk_step must be >= 1] +pamica/tests/test_blocktune.py::test_validate_rejects_unusable_sweeps[128-1024--8-blk_step must be >= 1] +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_validate_rejects_unusable_sweeps[128-1024--8-blk_step must be >= 1] +pamica/tests/test_blocktune.py::test_validate_rejects_unusable_sweeps[2048-1024-128-blk_max must be >= blk_min] +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_validate_rejects_unusable_sweeps[2048-1024-128-blk_max must be >= blk_min] +pamica/tests/test_blocktune.py::test_validate_accepts_fortran_and_pamica_defaults +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_validate_accepts_fortran_and_pamica_defaults +pamica/tests/test_blocktune.py::test_candidates_use_fortran_arithmetic_stepping +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_candidates_use_fortran_arithmetic_stepping +pamica/tests/test_blocktune.py::test_default_sweep_brackets_the_measured_optimum +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_default_sweep_brackets_the_measured_optimum +pamica/tests/test_blocktune.py::test_candidates_are_clamped_to_n_samples +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_candidates_are_clamped_to_n_samples +pamica/tests/test_blocktune.py::test_candidates_clamped_when_floor_exceeds_data +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_candidates_clamped_when_floor_exceeds_data +pamica/tests/test_blocktune.py::test_candidates_are_capped_by_the_memory_estimate +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_candidates_are_capped_by_the_memory_estimate +pamica/tests/test_blocktune.py::test_candidates_reject_empty_data +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_candidates_reject_empty_data +pamica/tests/test_blocktune.py::test_memory_cap_shrinks_as_channels_and_models_rise +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_memory_cap_shrinks_as_channels_and_models_rise +pamica/tests/test_blocktune.py::test_memory_cap_is_none_when_memory_is_unknown +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_memory_cap_is_none_when_memory_is_unknown +pamica/tests/test_blocktune.py::test_host_memory_is_positive_or_unavailable +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_host_memory_is_positive_or_unavailable +pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc0] +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc0] +pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc1] +[gw7] [ 3%] PASSED pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc1] +pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc2] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc2] +pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc3] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc3] +pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc4] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc4] +pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc5] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc5] +pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc6] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_recognizes_every_backend_allocation_failure[exc6] +pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc0] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc0] +pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc1] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc1] +pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc2] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc2] +pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc3] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc3] +pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc4] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc4] +pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc5] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc5] +pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc6] +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_does_not_mistake_a_real_bug_for_memory_pressure[exc6] +pamica/tests/test_blocktune.py::test_picks_the_fastest_candidate +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_picks_the_fastest_candidate +pamica/tests/test_blocktune.py::test_logs_the_choice_and_every_timing_at_info +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_logs_the_choice_and_every_timing_at_info +pamica/tests/test_blocktune.py::test_scores_each_candidate_on_its_fastest_pass +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_scores_each_candidate_on_its_fastest_pass +pamica/tests/test_blocktune.py::test_repeats_must_be_at_least_one +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_repeats_must_be_at_least_one +pamica/tests/test_blocktune.py::test_falls_back_to_last_working_size_on_allocation_failure +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_falls_back_to_last_working_size_on_allocation_failure +pamica/tests/test_blocktune.py::test_does_not_try_larger_candidates_after_a_failure +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_does_not_try_larger_candidates_after_a_failure +pamica/tests/test_blocktune.py::test_keeps_the_static_default_when_nothing_can_be_timed +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_keeps_the_static_default_when_nothing_can_be_timed +pamica/tests/test_blocktune.py::test_first_candidate_failure_does_not_claim_a_size_ran +[gw7] [ 4%] PASSED pamica/tests/test_blocktune.py::test_first_candidate_failure_does_not_claim_a_size_ran +pamica/tests/test_blocktune.py::test_a_non_allocation_error_propagates +[gw7] [ 5%] PASSED pamica/tests/test_blocktune.py::test_a_non_allocation_error_propagates +pamica/tests/test_blocktune.py::test_a_non_allocation_error_stops_on_the_very_first_pass +[gw7] [ 5%] PASSED pamica/tests/test_blocktune.py::test_a_non_allocation_error_stops_on_the_very_first_pass +pamica/tests/test_blocktune.py::test_empty_candidate_list_is_a_programming_error +[gw7] [ 5%] PASSED pamica/tests/test_blocktune.py::test_empty_candidate_list_is_a_programming_error +pamica/tests/test_blocktune.py::test_search_composes_the_cap_and_the_sweep +[gw7] [ 5%] PASSED pamica/tests/test_blocktune.py::test_search_composes_the_cap_and_the_sweep +pamica/tests/test_blocktune.py::test_every_backend_resolves_the_same_tuner_defaults[torch] +[gw7] [ 5%] PASSED pamica/tests/test_blocktune.py::test_every_backend_resolves_the_same_tuner_defaults[torch] +pamica/tests/test_blocktune.py::test_every_backend_resolves_the_same_tuner_defaults[numpy] +[gw7] [ 5%] PASSED pamica/tests/test_blocktune.py::test_every_backend_resolves_the_same_tuner_defaults[numpy] +pamica/tests/test_blocktune.py::test_every_backend_resolves_the_same_tuner_defaults[mlx] +[gw7] [ 5%] PASSED pamica/tests/test_blocktune.py::test_every_backend_resolves_the_same_tuner_defaults[mlx] +pamica/tests/test_channel_selection.py::test_read_electrode_positions +[gw7] [ 5%] PASSED pamica/tests/test_channel_selection.py::test_read_electrode_positions +pamica/tests/test_channel_selection.py::test_positions_for_channels_alignment +[gw7] [ 5%] PASSED pamica/tests/test_channel_selection.py::test_positions_for_channels_alignment +pamica/tests/test_channel_selection.py::test_selection_deterministic_unique_sorted +[gw7] [ 5%] PASSED pamica/tests/test_channel_selection.py::test_selection_deterministic_unique_sorted +pamica/tests/test_channel_selection.py::test_distributed_more_spread_than_first_n +[gw4] [ 5%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_get_rho_raises_on_force_set_nan_rho +pamica/tests/mlx_tests/test_mlx_transform.py::test_fit_path_is_unchanged_by_phase1 +[gw7] [ 5%] PASSED pamica/tests/test_channel_selection.py::test_distributed_more_spread_than_first_n +pamica/tests/test_channel_selection.py::test_n_ge_localized_returns_all_localized +[gw7] [ 5%] PASSED pamica/tests/test_channel_selection.py::test_n_ge_localized_returns_all_localized +pamica/tests/test_channel_selection.py::test_unlocalized_rows_excluded +[gw7] [ 5%] PASSED pamica/tests/test_channel_selection.py::test_unlocalized_rows_excluded +pamica/tests/test_channel_selection.py::test_n_zero_returns_empty +[gw7] [ 5%] PASSED pamica/tests/test_channel_selection.py::test_n_zero_returns_empty +pamica/tests/test_channel_selection.py::test_seed_is_centroid_nearest +[gw7] [ 5%] PASSED pamica/tests/test_channel_selection.py::test_seed_is_centroid_nearest +pamica/tests/test_channel_selection.py::test_coincident_coordinates_stay_unique +[gw7] [ 5%] PASSED pamica/tests/test_channel_selection.py::test_coincident_coordinates_stay_unique +pamica/tests/test_component_layout.py::test_an_unmerged_payload_converts_block_for_block +[gw7] [ 5%] PASSED pamica/tests/test_component_layout.py::test_an_unmerged_payload_converts_block_for_block +pamica/tests/test_component_layout.py::test_a_one_dimensional_comp_list_is_refused +[gw7] [ 5%] PASSED pamica/tests/test_component_layout.py::test_a_one_dimensional_comp_list_is_refused +pamica/tests/test_component_layout.py::test_a_non_integer_comp_list_is_refused[float-ids] +[gw7] [ 5%] PASSED pamica/tests/test_component_layout.py::test_a_non_integer_comp_list_is_refused[float-ids] +pamica/tests/test_component_layout.py::test_a_non_integer_comp_list_is_refused[nan-id] +[gw7] [ 5%] PASSED pamica/tests/test_component_layout.py::test_a_non_integer_comp_list_is_refused[nan-id] +pamica/tests/test_component_layout.py::test_a_mismatched_A_shape_is_refused[transposed] +[gw7] [ 6%] PASSED pamica/tests/test_component_layout.py::test_a_mismatched_A_shape_is_refused[transposed] +pamica/tests/test_component_layout.py::test_a_mismatched_A_shape_is_refused[one-column-short] +[gw7] [ 6%] PASSED pamica/tests/test_component_layout.py::test_a_mismatched_A_shape_is_refused[one-column-short] +pamica/tests/test_component_layout.py::test_a_mismatched_A_shape_is_refused[three-dimensional] +[gw7] [ 6%] PASSED pamica/tests/test_component_layout.py::test_a_mismatched_A_shape_is_refused[three-dimensional] +pamica/tests/test_component_layout.py::test_an_out_of_range_id_is_refused[negative] +[gw7] [ 6%] PASSED pamica/tests/test_component_layout.py::test_an_out_of_range_id_is_refused[negative] +pamica/tests/test_component_layout.py::test_an_out_of_range_id_is_refused[past-the-end] +[gw7] [ 6%] PASSED pamica/tests/test_component_layout.py::test_an_out_of_range_id_is_refused[past-the-end] +pamica/tests/test_component_layout.py::test_an_id_repeated_within_a_model_is_refused +[gw7] [ 6%] PASSED pamica/tests/test_component_layout.py::test_an_id_repeated_within_a_model_is_refused +pamica/tests/test_component_layout.py::test_an_id_shared_across_models_asks_for_a_refit +[gw7] [ 6%] PASSED pamica/tests/test_component_layout.py::test_an_id_shared_across_models_asks_for_a_refit +pamica/tests/test_component_rows.py::test_numpy_rejects_other_pdftypes +[gw7] [ 6%] PASSED pamica/tests/test_component_rows.py::test_numpy_rejects_other_pdftypes +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-scale-ng-pdf0] +[gw3] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_best_of_n_returns_the_argmax_of_the_independent_fits +pamica/tests/mlx_tests/test_mlx_restarts.py::test_records_are_aligned_with_the_independent_fits +[gw4] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_fit_path_is_unchanged_by_phase1 +[gw2] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_with_newton[4-1] +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_applies_with_annotation_rejection +pamica/tests/mlx_tests/test_mlx_pdf.py::test_logcosh_stability[88.0] +[gw2] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_logcosh_stability[88.0] +pamica/tests/mlx_tests/test_mlx_pdf.py::test_logcosh_stability[90.0] +[gw2] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_logcosh_stability[90.0] +pamica/tests/mlx_tests/test_mlx_pdf.py::test_logcosh_stability[500.0] +[gw2] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_logcosh_stability[500.0] +pamica/tests/mlx_tests/test_mlx_pdf.py::test_logcosh_stability[1000.0] +[gw2] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_logcosh_stability[1000.0] +pamica/tests/mlx_tests/test_mlx_pdf.py::test_sharing_with_adaptive_switcher_smoke +[gw3] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_records_are_aligned_with_the_independent_fits +pamica/tests/mlx_tests/test_mlx_restarts.py::test_derived_seeds_run_the_documented_sequence +[gw3] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_derived_seeds_run_the_documented_sequence +pamica/tests/mlx_tests/test_mlx_restarts.py::test_a_refit_repeats_the_same_search +[gw5] [ 6%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_n_iter_counts_the_e_steps_that_ran[torch-max_iter] +pamica/tests/mne_tests/test_mne_backends.py::test_n_iter_counts_the_e_steps_that_ran[torch-min_dll] +[gw7] [ 6%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-scale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m1-scale-ng-pdf0] +[gw3] [ 6%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_a_refit_repeats_the_same_search +pamica/tests/mlx_tests/test_mlx_restarts.py::test_a_degenerate_restart_is_recorded_but_never_selected +[gw1] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_pdftype1_forced_restore_rolls_back_n_kurt_done_with_pdtype +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_inactive_under_share_comps_logs_and_never_restores +[gw3] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_a_degenerate_restart_is_recorded_but_never_selected +pamica/tests/mlx_tests/test_mlx_restarts.py::test_all_degenerate_restarts_keep_the_last_one +[gw3] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_all_degenerate_restarts_keep_the_last_one +pamica/tests/mlx_tests/test_mlx_restarts.py::test_a_crashing_restart_does_not_kill_the_search +[gw3] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_a_crashing_restart_does_not_kill_the_search +pamica/tests/mlx_tests/test_mlx_restarts.py::test_a_single_restart_still_raises +[gw3] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_a_single_restart_still_raises +pamica/tests/mlx_tests/test_mlx_restarts.py::test_all_restarts_crashing_keeps_the_degenerate_contract +[gw3] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_all_restarts_crashing_keeps_the_degenerate_contract +pamica/tests/mlx_tests/test_mlx_restarts.py::test_the_winners_tuned_block_size_is_restored +[gw7] [ 7%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m1-scale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-scale-ng-pdf0] +[gw4] [ 7%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_applies_with_annotation_rejection +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_sources_are_timeline_shaped_and_rank_sized +[gw4] [ 7%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_sources_are_timeline_shaped_and_rank_sized +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_scoring_is_timeline_aligned +[gw4] [ 7%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_scoring_is_timeline_aligned +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_pmi_scores_good_samples_only +[gw3] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_restarts.py::test_the_winners_tuned_block_size_is_restored +pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_reproduces_the_estep_forward_pass +[gw0] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_backend.py::test_backend_stable_on_full_data +pamica/tests/mlx_tests/test_mlx_backend.py::test_converged_ll_matches_torch_float32 +[gw7] [ 7%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-scale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-scale-ng-pdf1] +[gw2] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_sharing_with_adaptive_switcher_smoke +pamica/tests/mlx_tests/test_mlx_pdf.py::test_get_pdftype_rejects_bad_model_idx +[gw3] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_reproduces_the_estep_forward_pass +pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_is_the_estep_before_the_last_m_step +[gw2] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_get_pdftype_rejects_bad_model_idx +pamica/tests/mlx_tests/test_mlx_pdf.py::test_get_pdftype_requires_fit +[gw2] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_get_pdftype_requires_fit +pamica/tests/mlx_tests/test_mlx_pdf.py::test_sharing_newton_and_fixed_family_fit_completes +[gw5] [ 7%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_n_iter_counts_the_e_steps_that_ran[torch-min_dll] +pamica/tests/mne_tests/test_mne_backends.py::test_n_iter_counts_the_e_steps_that_ran[mlx-max_iter] +[gw1] [ 7%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_inactive_under_share_comps_logs_and_never_restores +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_round_trips_through_state_dict +[gw7] [ 7%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-scale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-scale-ng-pdf1] +[gw1] [ 8%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_round_trips_through_state_dict +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_missing_keep_best_key_loads_with_the_default +[gw4] [ 8%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_pmi_scores_good_samples_only +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_mir_still_refuses_pca_reduction +[gw1] [ 8%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_missing_keep_best_key_loads_with_the_default +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_does_not_rescue_a_diverged_fit_that_peaked_earlier +[gw4] [ 8%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_mir_still_refuses_pca_reduction +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_export_is_rank_sized_and_orthonormal +[gw4] [ 8%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_pcakeep_export_is_rank_sized_and_orthonormal +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_detection_applies_with_annotation_rejection +[gw7] [ 8%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-scale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-scale-newton-pdf0] +[gw5] [ 8%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_n_iter_counts_the_e_steps_that_ran[mlx-max_iter] +pamica/tests/mne_tests/test_mne_backends.py::test_n_iter_counts_the_e_steps_that_ran[mlx-min_dll] +[gw1] [ 8%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_does_not_rescue_a_diverged_fit_that_peaked_earlier +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_restart_record_reports_the_restored_iterate +[gw3] [ 8%] PASSED pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_is_the_estep_before_the_last_m_step +pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_probability_is_normalized +[gw7] [ 8%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-scale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m1-scale-newton-pdf0] +[gw3] [ 8%] PASSED pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_probability_is_normalized +pamica/tests/mlx_tests/test_mlx_scoring.py::test_single_model_probability_is_all_ones +[gw3] [ 8%] PASSED pamica/tests/mlx_tests/test_mlx_scoring.py::test_single_model_probability_is_all_ones +pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_uses_stored_sphere_not_reprocess +[gw5] [ 8%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_n_iter_counts_the_e_steps_that_ran[mlx-min_dll] +pamica/tests/mne_tests/test_mne_meg.py::test_pre_whitener_is_one_scale_per_channel_type +[gw3] [ 8%] PASSED pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_uses_stored_sphere_not_reprocess +pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_requires_fit +[gw3] [ 8%] PASSED pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_requires_fit +pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_rejects_non_finite_input +[gw4] [ 8%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_detection_applies_with_annotation_rejection +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_sources_are_timeline_shaped_and_rank_sized +[gw4] [ 8%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_sources_are_timeline_shaped_and_rank_sized +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_scoring_is_timeline_aligned +[gw4] [ 8%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_scoring_is_timeline_aligned +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_pmi_scores_good_samples_only +[gw7] [ 8%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m1-scale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-scale-newton-pdf0] +[gw3] [ 8%] PASSED pamica/tests/mlx_tests/test_mlx_scoring.py::test_model_loglik_rejects_non_finite_input +pamica/tests/mlx_tests/test_mlx_sharing.py::test_unscheduled_sharing_is_bit_identical[1] +[gw7] [ 9%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-scale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-scale-newton-pdf1] +[gw6] [ 9%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_pmi_nbins_passthrough +pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_pmi_respect_model_idx_bounds +[gw6] [ 9%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_pmi_respect_model_idx_bounds +pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_pmi_require_fit +[gw6] [ 9%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_pmi_require_fit +pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_pmi_refuse_degenerate +[gw3] [ 9%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_unscheduled_sharing_is_bit_identical[1] +pamica/tests/mlx_tests/test_mlx_sharing.py::test_unscheduled_sharing_is_bit_identical[2] +[gw2] [ 9%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_sharing_newton_and_fixed_family_fit_completes +pamica/tests/mlx_tests/test_mlx_pdf.py::test_sharing_newton_and_adaptive_switcher_fit_completes +[gw1] [ 9%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_restart_record_reports_the_restored_iterate +pamica/tests/mlx_tests/test_mlx_kitchen_sink.py::test_kitchen_sink_lifecycle +[gw4] [ 9%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_pmi_scores_good_samples_only +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_mir_raises_pca_reduction_error +[gw4] [ 9%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_auto_rank_mir_raises_pca_reduction_error +pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_full_rank_mir_succeeds +[gw5] [ 9%] PASSED pamica/tests/mne_tests/test_mne_meg.py::test_pre_whitener_is_one_scale_per_channel_type +pamica/tests/mne_tests/test_mne_meg.py::test_scaling_equalizes_channel_type_variance +[gw3] [ 9%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_unscheduled_sharing_is_bit_identical[2] +pamica/tests/mlx_tests/test_mlx_sharing.py::test_default_multimodel_fit_leaves_every_component_distinct +[gw7] [ 9%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-scale-newton-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-scale-newton-pdf1] +[gw3] [ 9%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_default_multimodel_fit_leaves_every_component_distinct +pamica/tests/mlx_tests/test_mlx_sharing.py::test_two_model_share_fit_completes_and_merges +[gw7] [ 9%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-scale-newton-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-noscale-ng-pdf0] +[gw7] [ 9%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-noscale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m1-noscale-ng-pdf0] +[gw3] [ 9%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_two_model_share_fit_completes_and_merges +pamica/tests/mlx_tests/test_mlx_sharing.py::test_merge_on_the_final_iteration_completes +[gw3] [ 9%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_merge_on_the_final_iteration_completes +pamica/tests/mlx_tests/test_mlx_sharing.py::test_convergence_stop_can_fire_while_A_is_frozen +[gw3] [ 9%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_convergence_stop_can_fire_while_A_is_frozen +pamica/tests/mlx_tests/test_mlx_sharing.py::test_three_model_share_fit_completes +[gw5] [ 9%] PASSED pamica/tests/mne_tests/test_mne_meg.py::test_scaling_equalizes_channel_type_variance +pamica/tests/mne_tests/test_mne_meg.py::test_roundtrip_holds_for_mixed_channel_types +[gw2] [ 9%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_sharing_newton_and_adaptive_switcher_fit_completes +pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_params_are_bit_identical +[gw7] [ 10%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m1-noscale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-noscale-ng-pdf0] +[gw2] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_params_are_bit_identical +pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_config_and_extra_are_equal +[gw7] [ 10%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-noscale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-noscale-ng-pdf1] +[gw2] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_config_and_extra_are_equal +pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_transform_is_bit_identical +[gw2] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_transform_is_bit_identical +pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_accessors_are_bit_identical +[gw1] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_kitchen_sink.py::test_kitchen_sink_lifecycle +pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_llt_invariant_holds_for_a_default_fit +[gw2] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_accessors_are_bit_identical +pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_sensor_mixing_matrix_is_close +[gw4] [ 10%] PASSED pamica/tests/mne_tests/test_annotation_rank_reduction.py::test_full_rank_mir_succeeds +pamica/tests/mne_tests/test_bad_annotation.py::test_fit_omits_bad_annotated_samples +[gw2] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_round_trip_sensor_mixing_matrix_is_close +pamica/tests/mlx_tests/test_mlx_persistence.py::test_save_load_round_trip_bit_identical +[gw1] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_llt_invariant_holds_for_a_default_fit +pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_llt_is_the_logsumexp_of_lht +[gw3] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_three_model_share_fit_completes +pamica/tests/mlx_tests/test_mlx_sharing.py::test_rank_reduced_share_fit_completes +[gw2] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_save_load_round_trip_bit_identical +pamica/tests/mlx_tests/test_mlx_persistence.py::test_save_load_npz_layout +[gw1] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_llt_is_the_logsumexp_of_lht +pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_llt_stashed_at_one_model_too +[gw2] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_save_load_npz_layout +pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_bit_identical_on_rank_reduced_fit +[gw1] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_llt_stashed_at_one_model_too +pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_stashed_llt_is_one_m_step_behind_the_written_parameters +[gw7] [ 10%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-noscale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-noscale-ng-pdf1] +[gw2] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_bit_identical_on_rank_reduced_fit +pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_preserves_forced_merge_state +[gw2] [ 10%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_preserves_forced_merge_state +pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_preserves_adaptive_switcher_state +[gw7] [ 10%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-noscale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-noscale-newton-pdf0] +[gw5] [ 10%] PASSED pamica/tests/mne_tests/test_mne_meg.py::test_roundtrip_holds_for_mixed_channel_types +pamica/tests/mne_tests/test_mne_meg.py::test_eeg_only_scaling_is_absorbed_by_the_sphere +[gw1] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_stashed_llt_is_one_m_step_behind_the_written_parameters +pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_llt_stash_is_none_before_any_estep_ran +[gw1] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_llt_stash_is_none_before_any_estep_ran +pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_keep_best_restore_rolls_the_llt_stash_back +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_rank_reduced_share_fit_completes +pamica/tests/mlx_tests/test_mlx_sharing.py::test_second_identify_call_does_not_resurrect_merged_columns +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_second_identify_call_does_not_resurrect_merged_columns +pamica/tests/mlx_tests/test_mlx_sharing.py::test_merged_away_columns_keep_their_last_finite_value +[gw7] [ 11%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-noscale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m1-noscale-newton-pdf0] +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_merged_away_columns_keep_their_last_finite_value +pamica/tests/mlx_tests/test_mlx_sharing.py::test_a_frozen_window_matches_the_torch_schedule[True-2] +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_a_frozen_window_matches_the_torch_schedule[True-2] +pamica/tests/mlx_tests/test_mlx_sharing.py::test_a_frozen_window_matches_the_torch_schedule[False-2] +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_a_frozen_window_matches_the_torch_schedule[False-2] +pamica/tests/mlx_tests/test_mlx_sharing.py::test_a_frozen_window_matches_the_torch_schedule[False-1] +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_a_frozen_window_matches_the_torch_schedule[False-1] +pamica/tests/mlx_tests/test_mlx_sharing.py::test_a_frozen_applies_to_a_single_model_without_sharing +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_a_frozen_applies_to_a_single_model_without_sharing +pamica/tests/mlx_tests/test_mlx_sharing.py::test_freeze_holds_A_while_the_mixture_keeps_moving +[gw2] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_preserves_adaptive_switcher_state +pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_preserves_newton_fallback_count +[gw1] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_llt_stash.py::test_keep_best_restore_rolls_the_llt_stash_back +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_composes_unmixing_the_documented_way +[gw2] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_preserves_newton_fallback_count +pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_preserves_multi_restart_records +[gw1] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_composes_unmixing_the_documented_way +pamica/tests/mlx_tests/test_mlx_mir.py::test_pmi_matches_pairwise_mi_on_transform +[gw6] [ 11%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_pmi_refuse_degenerate +pamica/tests/mne_tests/test_pca_residual.py::test_full_rank_export_is_unchanged +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_freeze_holds_A_while_the_mixture_keeps_moving +pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs0-share_start] +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs0-share_start] +pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs1-share_iter] +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs1-share_iter] +pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs2-share_iter] +[gw2] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_round_trip_preserves_multi_restart_records +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs2-share_iter] +pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs3-comp_thresh] +[gw3] [ 11%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs3-comp_thresh] +pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs4-comp_thresh] +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_constructor_validation[kwargs4-comp_thresh] +pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_refuses_unfitted_model +pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_settings_are_not_validated_when_sharing_is_off +[gw2] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_refuses_unfitted_model +pamica/tests/mlx_tests/test_mlx_persistence.py::test_save_refuses_unfitted_model +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_share_settings_are_not_validated_when_sharing_is_off +[gw2] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_save_refuses_unfitted_model +pamica/tests/mlx_tests/test_mlx_sharing.py::test_single_model_sharing_is_accepted_and_inert +pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_refuses_degenerate_fit +[gw2] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_refuses_degenerate_fit +pamica/tests/mlx_tests/test_mlx_persistence.py::test_save_refuses_degenerate_fit +[gw2] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_save_refuses_degenerate_fit +pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_refuses_force_set_nonfinite_param_naming_it +[gw2] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_state_dict_refuses_force_set_nonfinite_param_naming_it +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_wrong_format_version +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_single_model_sharing_is_accepted_and_inert +pamica/tests/mlx_tests/test_mlx_sharing.py::test_non_finite_sphere_fails_loudly +[gw2] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_wrong_format_version +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_missing_section[config] +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_non_finite_sphere_fails_loudly +pamica/tests/mlx_tests/test_mlx_sharing.py::test_pinv_sphere_before_fit_raises +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_sharing.py::test_pinv_sphere_before_fit_raises +pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_requires_fitted_model +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_requires_fitted_model +pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[get_mixing_matrix] +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[get_mixing_matrix] +pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[get_unmixing_matrix] +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[get_unmixing_matrix] +pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[get_sensor_mixing_matrix] +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[get_sensor_mixing_matrix] +pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[get_rho] +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[get_rho] +pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[variance_order] +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_accessors_require_fitted_model[variance_order] +pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_rejects_invalid_model_idx[-1] +[gw2] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_missing_section[config] +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_missing_section[params] +[gw1] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_pmi_matches_pairwise_mi_on_transform +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_and_pmi_honour_model_idx +[gw3] [ 12%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_rejects_invalid_model_idx[-1] +pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_rejects_invalid_model_idx[1] +[gw7] [ 13%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m1-noscale-newton-pdf0] +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_missing_section[params] +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_missing_section[extra] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-noscale-newton-pdf0] +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_missing_section[extra] +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_missing_param +[gw3] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_rejects_invalid_model_idx[1] +pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_rejects_invalid_model_idx[2] +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_missing_param +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_comp_list_shape_drift +[gw3] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_rejects_invalid_model_idx[2] +pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_rejects_invalid_model_idx[100] +[gw7] [ 13%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-noscale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-noscale-newton-pdf1] +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_comp_list_shape_drift +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift_for_every_param[mean] +[gw3] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_transform.py::test_transform_rejects_invalid_model_idx[100] +pamica/tests/test_component_rows.py::test_the_metric_compares_the_sensor_maps[mlx] +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift_for_every_param[mean] +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift_for_every_param[W] +[gw4] [ 13%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_fit_omits_bad_annotated_samples +pamica/tests/mne_tests/test_bad_annotation.py::test_mask_indexes_exactly_the_fitted_columns +[gw4] [ 13%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_mask_indexes_exactly_the_fitted_columns +pamica/tests/mne_tests/test_bad_annotation.py::test_fit_equals_manual_column_drop +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift_for_every_param[W] +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift_for_every_param[mu] +[gw1] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_and_pmi_honour_model_idx +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_and_pmi_honour_nbins +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift_for_every_param[mu] +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift_for_every_param[gm] +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_shape_drift_for_every_param[gm] +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_nan_comp_list +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_nan_comp_list +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_non_integer_valued_comp_list +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_non_integer_valued_comp_list +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_accepts_whole_valued_float_comp_list +[gw2] [ 13%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_accepts_whole_valued_float_comp_list +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_nonfinite_mu +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_nonfinite_mu +pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_singular_restored_W +[gw1] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_and_pmi_honour_nbins +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_real_fitted_unmixing_is_large_and_positive +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_from_state_dict_rejects_singular_restored_W +pamica/tests/mlx_tests/test_mlx_persistence.py::test_load_rejects_wrong_format_version +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_load_rejects_wrong_format_version +pamica/tests/mlx_tests/test_mlx_persistence.py::test_load_rejects_truncated_file +[gw7] [ 14%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-noscale-newton-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-noscale-newton-pdf1] +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_load_rejects_truncated_file +pamica/tests/mlx_tests/test_mlx_persistence.py::test_load_rejects_byte_truncated_file +[gw1] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_real_fitted_unmixing_is_large_and_positive +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_on_a_share_comps_merged_model +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_load_rejects_byte_truncated_file +pamica/tests/mlx_tests/test_mlx_persistence.py::test_load_rejects_missing_param_array +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_persistence.py::test_load_rejects_missing_param_array +pamica/tests/mlx_tests/test_mlx_reject.py::test_reject_param_validation +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_reject_param_validation +pamica/tests/mlx_tests/test_mlx_reject.py::test_reject_defaults_match_torch +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_reject_defaults_match_torch +pamica/tests/mlx_tests/test_mlx_reject.py::test_do_reject_false_leaves_good_idx_unset +[gw7] [ 14%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-noscale-newton-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-scale-ng-pdf0] +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_do_reject_false_leaves_good_idx_unset +pamica/tests/mlx_tests/test_mlx_reject.py::test_rejection_shrinks_good_sample_set_on_the_expected_schedule +[gw6] [ 14%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_full_rank_export_is_unchanged +pamica/tests/mne_tests/test_pca_residual.py::test_full_rank_two_model_export_is_unchanged +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_rejection_shrinks_good_sample_set_on_the_expected_schedule +pamica/tests/mlx_tests/test_mlx_reject.py::test_maxrej_zero_disables_rejection +[gw5] [ 14%] PASSED pamica/tests/mne_tests/test_mne_meg.py::test_eeg_only_scaling_is_absorbed_by_the_sphere +pamica/tests/mne_tests/test_mne_meg.py::test_rank_deficient_fit_exports_and_roundtrips +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_maxrej_zero_disables_rejection +pamica/tests/mlx_tests/test_mlx_reject.py::test_none_rejected_in_a_pass_still_counts_as_a_pass +[gw2] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_none_rejected_in_a_pass_still_counts_as_a_pass +pamica/tests/mlx_tests/test_mlx_reject.py::test_multimodel_rejection_keeps_gm_and_c_finite +[gw1] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_on_a_share_comps_merged_model +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_requires_a_fitted_model +[gw1] [ 14%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_requires_a_fitted_model +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_populates_history_at_right_iterations +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_populates_history_at_right_iterations +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_zero_leaves_history_empty +[gw2] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_multimodel_rejection_keeps_gm_and_c_finite +pamica/tests/mlx_tests/test_mlx_reject.py::test_keep_best_inactive_under_do_reject_warns +[gw7] [ 15%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-scale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-scale-ng-pdf0] +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_zero_leaves_history_empty +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_negative_raises +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_negative_raises +pamica/tests/mlx_tests/test_mlx_mir.py::test_max_iter_zero_raises +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_max_iter_zero_raises +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_zero_matches_omitted_argument +[gw2] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_keep_best_inactive_under_do_reject_warns +pamica/tests/mlx_tests/test_mlx_reject.py::test_keep_best_inactive_reason_prefers_do_reject_when_both_are_on +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_zero_matches_omitted_argument +pamica/tests/mlx_tests/test_mlx_mir.py::test_failing_mir_waypoint_does_not_kill_the_fit +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_failing_mir_waypoint_does_not_kill_the_fit +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_raises_under_auto_detected_rank_reduction +[gw2] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_keep_best_inactive_reason_prefers_do_reject_when_both_are_on +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_raises_under_auto_detected_rank_reduction +pamica/tests/mlx_tests/test_mlx_reject.py::test_keep_best_restore_never_fires_under_do_reject +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_full_rank_succeeds +[gw4] [ 15%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_fit_equals_manual_column_drop +pamica/tests/mne_tests/test_bad_annotation.py::test_reject_false_keeps_all_samples +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_full_rank_succeeds +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_on_rank_reduced_data_completes_with_one_warned_nan_waypoint +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_step_on_rank_reduced_data_completes_with_one_warned_nan_waypoint +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_history_survives_keep_best_restore +[gw5] [ 15%] PASSED pamica/tests/mne_tests/test_mne_meg.py::test_rank_deficient_fit_exports_and_roundtrips +pamica/tests/mne_tests/test_mne_meg.py::test_rank_deficient_components_are_sensor_shaped +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_history_survives_keep_best_restore +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_history_empty_after_state_dict_round_trip +[gw1] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_history_empty_after_state_dict_round_trip +pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_history_survives_best_of_n_restarts_winner_not_last +[gw2] [ 15%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_keep_best_restore_never_fires_under_do_reject +pamica/tests/mlx_tests/test_mlx_reject.py::test_do_reject_survives_best_of_n_restarts_winner_not_last +[gw4] [ 15%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_reject_false_keeps_all_samples +pamica/tests/mne_tests/test_bad_annotation.py::test_non_bad_annotations_are_inert +[gw7] [ 15%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-scale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-scale-ng-pdf0] +[gw2] [ 16%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_do_reject_survives_best_of_n_restarts_winner_not_last +pamica/tests/mlx_tests/test_mlx_reject.py::test_do_reject_with_a_genuine_share_comps_merge +[gw7] [ 16%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-scale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-scale-ng-pdf1] +[gw5] [ 16%] PASSED pamica/tests/mne_tests/test_mne_meg.py::test_rank_deficient_components_are_sensor_shaped +pamica/tests/mne_tests/test_mne_meg.py::test_rank_deficient_apply_reconstructs +[gw1] [ 16%] PASSED pamica/tests/mlx_tests/test_mlx_mir.py::test_mir_history_survives_best_of_n_restarts_winner_not_last +pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_fit_is_stable_on_full_data[1] +[gw4] [ 16%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_non_bad_annotations_are_inert +pamica/tests/mne_tests/test_bad_annotation.py::test_start_stop_composes_with_rejection +[gw2] [ 16%] PASSED pamica/tests/mlx_tests/test_mlx_reject.py::test_do_reject_with_a_genuine_share_comps_merge +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[torch--1] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[torch--1] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[torch-2.5] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[torch-2.5] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[torch-True] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[torch-True] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[numpy-0] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[numpy-0] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[numpy--1] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[numpy--1] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[numpy-2.5] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[numpy-2.5] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[numpy-True] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[numpy-True] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[mlx-0] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[mlx-0] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[mlx--1] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[mlx--1] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[mlx-2.5] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[mlx-2.5] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[mlx-True] +[gw2] [ 16%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[mlx-True] +pamica/tests/test_doscaling_rows.py::test_doscaling_matches_the_seeded_reference[1] +[gw2] [ 16%] SKIPPED pamica/tests/test_doscaling_rows.py::test_doscaling_matches_the_seeded_reference[1] +pamica/tests/test_doscaling_rows.py::test_doscaling_matches_the_seeded_reference[2] +[gw2] [ 16%] SKIPPED pamica/tests/test_doscaling_rows.py::test_doscaling_matches_the_seeded_reference[2] +pamica/tests/test_fortran_adapter.py::test_write_fdt_roundtrip +[gw2] [ 16%] PASSED pamica/tests/test_fortran_adapter.py::test_write_fdt_roundtrip +pamica/tests/test_fortran_adapter.py::test_write_fdt_channel_subset +[gw2] [ 17%] PASSED pamica/tests/test_fortran_adapter.py::test_write_fdt_channel_subset +pamica/tests/test_fortran_adapter.py::test_parse_fortran_out +[gw2] [ 17%] PASSED pamica/tests/test_fortran_adapter.py::test_parse_fortran_out +pamica/tests/test_fortran_adapter.py::test_write_fortran_param +[gw2] [ 17%] PASSED pamica/tests/test_fortran_adapter.py::test_write_fortran_param +pamica/tests/test_fortran_adapter.py::test_write_fortran_param_multimodel +[gw2] [ 17%] PASSED pamica/tests/test_fortran_adapter.py::test_write_fortran_param_multimodel +pamica/tests/test_fortran_adapter.py::test_fortran_availability_and_dispatch +[gw2] [ 17%] PASSED pamica/tests/test_fortran_adapter.py::test_fortran_availability_and_dispatch +pamica/tests/test_fortran_adapter.py::test_run_fortran_raises_on_nonzero_exit +[gw2] [ 17%] PASSED pamica/tests/test_fortran_adapter.py::test_run_fortran_raises_on_nonzero_exit +pamica/tests/test_fortran_adapter.py::test_run_fortran_smoke +[gw2] [ 17%] SKIPPED pamica/tests/test_fortran_adapter.py::test_run_fortran_smoke +pamica/tests/test_fortran_adapter.py::test_run_fortran_never_reports_a_bogus_zero +[gw2] [ 17%] SKIPPED pamica/tests/test_fortran_adapter.py::test_run_fortran_never_reports_a_bogus_zero +pamica/tests/test_fortran_adapter.py::test_run_fortran_requires_two_timed_iters +[gw2] [ 17%] SKIPPED pamica/tests/test_fortran_adapter.py::test_run_fortran_requires_two_timed_iters +pamica/tests/test_fortran_param_forwarding.py::test_accepted_keys_come_from_the_reference_source +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_accepted_keys_come_from_the_reference_source +pamica/tests/test_fortran_param_forwarding.py::test_missing_source_disables_filtering +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_missing_source_disables_filtering +pamica/tests/test_fortran_param_forwarding.py::test_do_newton_is_forwarded +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_do_newton_is_forwarded +pamica/tests/test_fortran_param_forwarding.py::test_block_size_is_forwarded +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_block_size_is_forwarded +pamica/tests/test_fortran_param_forwarding.py::test_aliased_names_are_translated +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_aliased_names_are_translated +pamica/tests/test_fortran_param_forwarding.py::test_canonical_names_are_also_translated +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_canonical_names_are_also_translated +pamica/tests/test_fortran_param_forwarding.py::test_load_sample_data_writes_fortran_spellings_end_to_end +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_load_sample_data_writes_fortran_spellings_end_to_end +pamica/tests/test_fortran_param_forwarding.py::test_keys_absent_from_the_template_are_appended +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_keys_absent_from_the_template_are_appended +pamica/tests/test_fortran_param_forwarding.py::test_overrides_beat_params +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_overrides_beat_params +pamica/tests/test_fortran_param_forwarding.py::test_untouched_template_values_survive +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_untouched_template_values_survive +pamica/tests/test_fortran_param_forwarding.py::test_unsupported_key_is_reported +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_unsupported_key_is_reported +pamica/tests/test_fortran_param_forwarding.py::test_python_only_keys_are_not_reported +[gw2] [ 17%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_python_only_keys_are_not_reported +pamica/tests/test_fortran_param_forwarding.py::test_real_params_json_produces_a_parseable_file +[gw2] [ 18%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_real_params_json_produces_a_parseable_file +pamica/tests/test_fortran_param_forwarding.py::test_list_values_are_space_separated +[gw2] [ 18%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_list_values_are_space_separated +pamica/tests/test_fortran_param_forwarding.py::test_default_reference_binary_falls_back_loudly +[gw2] [ 18%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_default_reference_binary_falls_back_loudly +pamica/tests/test_fortran_param_forwarding.py::test_env_override_selects_the_native_engine +[gw2] [ 18%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_env_override_selects_the_native_engine +pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_parses_names_lists_and_all +[gw2] [ 18%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_parses_names_lists_and_all +pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_rejects_unknown_names[cuda] +[gw2] [ 18%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_rejects_unknown_names[cuda] +pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_rejects_unknown_names[torch,] +[gw2] [ 18%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_rejects_unknown_names[torch,] +pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_rejects_unknown_names[] +[gw2] [ 18%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_rejects_unknown_names[] +pamica/tests/test_fortran_params.py::TestZeroRecognizedKeysGuard::test_genuinely_empty_file_raises +[gw2] [ 18%] PASSED pamica/tests/test_fortran_params.py::TestZeroRecognizedKeysGuard::test_genuinely_empty_file_raises +pamica/tests/test_fortran_params.py::TestZeroRecognizedKeysGuard::test_comment_only_file_raises +[gw2] [ 18%] PASSED pamica/tests/test_fortran_params.py::TestZeroRecognizedKeysGuard::test_comment_only_file_raises +pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_param_extension_is_detected +[gw2] [ 18%] PASSED pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_param_extension_is_detected +pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_kwargs_still_override_the_param_path +[gw2] [ 18%] PASSED pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_kwargs_still_override_the_param_path +pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_param_and_json_agree_on_model_construction +[gw2] [ 18%] PASSED pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_param_and_json_agree_on_model_construction +pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_param_extension_with_json_content_is_sniffed_as_json +[gw2] [ 18%] PASSED pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_param_extension_with_json_content_is_sniffed_as_json +pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_compact_json_named_param_does_not_silently_default +[gw2] [ 18%] PASSED pamica/tests/test_fortran_params.py::TestFromParamsFileIntegration::test_compact_json_named_param_does_not_silently_default +pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_file_defaults_reach_the_fitted_backend +[gw4] [ 18%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_start_stop_composes_with_rejection +pamica/tests/mne_tests/test_bad_annotation.py::test_model_probability_is_timeline_aligned +[gw6] [ 18%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_full_rank_two_model_export_is_unchanged +pamica/tests/mne_tests/test_pca_residual.py::test_full_rank_apply_is_unchanged[exclude0] +[gw6] [ 18%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_full_rank_apply_is_unchanged[exclude0] +pamica/tests/mne_tests/test_pca_residual.py::test_full_rank_apply_is_unchanged[exclude1] +[gw6] [ 18%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_full_rank_apply_is_unchanged[exclude1] +pamica/tests/mne_tests/test_pca_residual.py::test_fitted_basis_is_full_and_exported_unaltered +[gw4] [ 18%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_model_probability_is_timeline_aligned +pamica/tests/mne_tests/test_bad_annotation.py::test_scoring_follows_the_passed_instances_annotations +[gw4] [ 19%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_scoring_follows_the_passed_instances_annotations +pamica/tests/mne_tests/test_bad_annotation.py::test_mir_scores_good_samples_only +[gw4] [ 19%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_mir_scores_good_samples_only +pamica/tests/mne_tests/test_bad_annotation.py::test_epochs_fit_is_unaffected +[gw5] [ 19%] PASSED pamica/tests/mne_tests/test_mne_meg.py::test_rank_deficient_apply_reconstructs +pamica/tests/mne_tests/test_mne_wrapper.py::test_get_sources_matches_amica_transform +[gw2] [ 19%] PASSED pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_file_defaults_reach_the_fitted_backend +pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_explicit_kwargs_win_over_file_defaults +[gw2] [ 19%] PASSED pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_explicit_kwargs_win_over_file_defaults +pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_unhandled_file_settings_warn_once +[gw7] [ 19%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-scale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-scale-ng-pdf1] +[gw2] [ 19%] PASSED pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_unhandled_file_settings_warn_once +pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_checkpoint_settings_warn_not_applied +[gw7] [ 19%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-scale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-scale-newton-pdf0] +[gw2] [ 19%] PASSED pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_checkpoint_settings_warn_not_applied +pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_json_alias_settings_now_reach_the_backend +[gw4] [ 19%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_epochs_fit_is_unaffected +pamica/tests/mne_tests/test_bad_annotation.py::test_nan_inside_bad_segment_is_tolerated +[gw6] [ 19%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_fitted_basis_is_full_and_exported_unaltered +pamica/tests/mne_tests/test_pca_residual.py::test_exported_basis_is_orthonormal +[gw6] [ 19%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_exported_basis_is_orthonormal +pamica/tests/mne_tests/test_pca_residual.py::test_residual_variances_are_the_discarded_eigenvalues +[gw6] [ 19%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_residual_variances_are_the_discarded_eigenvalues +pamica/tests/mne_tests/test_pca_residual.py::test_apply_restores_the_residual +[gw6] [ 19%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_apply_restores_the_residual +pamica/tests/mne_tests/test_pca_residual.py::test_n_pca_components_restores_the_reference_reconstruction +[gw6] [ 19%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_n_pca_components_restores_the_reference_reconstruction +pamica/tests/mne_tests/test_pca_residual.py::test_exclude_leaves_the_residual_untouched[0] +[gw6] [ 19%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_exclude_leaves_the_residual_untouched[0] +pamica/tests/mne_tests/test_pca_residual.py::test_exclude_leaves_the_residual_untouched[19] +[gw6] [ 19%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_exclude_leaves_the_residual_untouched[19] +pamica/tests/mne_tests/test_pca_residual.py::test_get_sources_matches_amica_transform +[gw6] [ 19%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_get_sources_matches_amica_transform +pamica/tests/mne_tests/test_pca_residual.py::test_residual_export_is_logged +[gw2] [ 19%] PASSED pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_json_alias_settings_now_reach_the_backend +pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_fit_without_from_params_file_is_unaffected +[gw2] [ 19%] PASSED pamica/tests/test_fortran_params.py::TestFitAppliesFileDefaults::test_fit_without_from_params_file_is_unaffected +pamica/tests/test_fortran_params.py::TestReadParamsFile::test_param_and_json_agree_on_overlapping_settings +[gw2] [ 20%] PASSED pamica/tests/test_fortran_params.py::TestReadParamsFile::test_param_and_json_agree_on_overlapping_settings +pamica/tests/test_fortran_params.py::TestReadParamsFile::test_json_top_level_must_be_an_object +[gw2] [ 20%] PASSED pamica/tests/test_fortran_params.py::TestReadParamsFile::test_json_top_level_must_be_an_object +pamica/tests/test_fortran_params.py::TestReadParamsFile::test_json_alias_and_canonical_key_conflict_raises +[gw2] [ 20%] PASSED pamica/tests/test_fortran_params.py::TestReadParamsFile::test_json_alias_and_canonical_key_conflict_raises +pamica/tests/test_fortran_params.py::TestReadParamsFile::test_json_alias_is_translated_to_canonical +[gw2] [ 20%] PASSED pamica/tests/test_fortran_params.py::TestReadParamsFile::test_json_alias_is_translated_to_canonical +pamica/tests/test_fortran_params.py::TestReadParamsFile::test_json_non_aliased_keys_pass_through_unchanged +[gw2] [ 20%] PASSED pamica/tests/test_fortran_params.py::TestReadParamsFile::test_json_non_aliased_keys_pass_through_unchanged +pamica/tests/test_fortran_params.py::TestReadParamsFile::test_unparsable_non_json_text_raises +[gw2] [ 20%] PASSED pamica/tests/test_fortran_params.py::TestReadParamsFile::test_unparsable_non_json_text_raises +pamica/tests/test_fortran_params.py::TestReadParamsFile::test_fortran_text_still_dispatches_to_the_fortran_reader +[gw2] [ 20%] PASSED pamica/tests/test_fortran_params.py::TestReadParamsFile::test_fortran_text_still_dispatches_to_the_fortran_reader +pamica/tests/test_fortran_params.py::TestReadParamsFile::test_alias_table_derived_from_fortran_renames_plus_share_int +[gw2] [ 20%] PASSED pamica/tests/test_fortran_params.py::TestReadParamsFile::test_alias_table_derived_from_fortran_renames_plus_share_int +pamica/tests/test_initial_mixing.py::test_the_shared_draw_is_the_reference_recipe[1] +[gw2] [ 20%] PASSED pamica/tests/test_initial_mixing.py::test_the_shared_draw_is_the_reference_recipe[1] +pamica/tests/test_initial_mixing.py::test_the_shared_draw_is_the_reference_recipe[2] +[gw2] [ 20%] PASSED pamica/tests/test_initial_mixing.py::test_the_shared_draw_is_the_reference_recipe[2] +pamica/tests/test_initial_mixing.py::test_the_shared_draw_is_the_reference_recipe[3] +[gw2] [ 20%] PASSED pamica/tests/test_initial_mixing.py::test_the_shared_draw_is_the_reference_recipe[3] +pamica/tests/test_initial_mixing.py::test_normalizing_a_zero_or_nan_component_raises[zero] +[gw2] [ 20%] PASSED pamica/tests/test_initial_mixing.py::test_normalizing_a_zero_or_nan_component_raises[zero] +pamica/tests/test_initial_mixing.py::test_normalizing_a_zero_or_nan_component_raises[nan] +[gw2] [ 20%] PASSED pamica/tests/test_initial_mixing.py::test_normalizing_a_zero_or_nan_component_raises[nan] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[torch-1-1] +[gw7] [ 20%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-scale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-scale-newton-pdf0] +[gw6] [ 20%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_residual_export_is_logged +pamica/tests/mne_tests/test_pca_residual.py::test_every_model_restores_the_residual +[gw2] [ 20%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[torch-1-1] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[torch-1-2] +[gw2] [ 20%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[torch-1-2] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[torch-2-1] +[gw2] [ 20%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[torch-2-1] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[torch-2-2] +[gw4] [ 20%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_nan_inside_bad_segment_is_tolerated +pamica/tests/mne_tests/test_bad_annotation.py::test_fully_annotated_range_raises +[gw4] [ 20%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_fully_annotated_range_raises +pamica/tests/mne_tests/test_bad_annotation.py::test_empty_start_stop_range_blames_the_range +[gw4] [ 21%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_empty_start_stop_range_blames_the_range +pamica/tests/mne_tests/test_bad_annotation.py::test_fully_annotated_scoring_raises +[gw4] [ 21%] PASSED pamica/tests/mne_tests/test_bad_annotation.py::test_fully_annotated_scoring_raises +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_average_reference_leaves_rank_n_minus_one +[gw2] [ 21%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[torch-2-2] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[numpy-1-1] +[gw4] [ 21%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_average_reference_leaves_rank_n_minus_one +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_fit_keeps_n_minus_one_components[torch] +[gw2] [ 21%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[numpy-1-1] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[numpy-1-2] +[gw1] [ 21%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_fit_is_stable_on_full_data[1] +pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_fit_is_stable_on_full_data[3] +[gw5] [ 21%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_get_sources_matches_amica_transform +pamica/tests/mne_tests/test_mne_wrapper.py::test_get_components_are_channel_space_maps +[gw5] [ 21%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_get_components_are_channel_space_maps +pamica/tests/mne_tests/test_mne_wrapper.py::test_apply_without_exclude_reconstructs +[gw5] [ 21%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_apply_without_exclude_reconstructs +pamica/tests/mne_tests/test_mne_wrapper.py::test_apply_excludes_component +[gw5] [ 21%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_apply_excludes_component +pamica/tests/mne_tests/test_mne_wrapper.py::test_to_mne_ica_returns_valid_fitted_ica +[gw5] [ 21%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_to_mne_ica_returns_valid_fitted_ica +pamica/tests/mne_tests/test_mne_wrapper.py::test_export_is_cached_and_invalidated_on_refit +[gw2] [ 21%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[numpy-1-2] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[numpy-2-1] +[gw2] [ 21%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[numpy-2-1] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[numpy-2-2] +[gw2] [ 21%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[numpy-2-2] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[mlx-1-1] +[gw7] [ 21%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-scale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-scale-newton-pdf0] +[gw2] [ 21%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[mlx-1-1] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[mlx-1-2] +[gw2] [ 21%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[mlx-1-2] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[mlx-2-1] +[gw2] [ 21%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[mlx-2-1] +pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[mlx-2-2] +[gw2] [ 21%] PASSED pamica/tests/test_initial_mixing.py::test_every_fit_starts_from_unit_norm_components[mlx-2-2] +pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[torch-1] +[gw7] [ 21%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-scale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-scale-newton-pdf1] +[gw4] [ 22%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_fit_keeps_n_minus_one_components[torch] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_fit_keeps_n_minus_one_components[mlx] +[gw2] [ 22%] PASSED pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[torch-1] +pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[torch-2] +[gw2] [ 22%] PASSED pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[torch-2] +pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[numpy-1] +[gw4] [ 22%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_fit_keeps_n_minus_one_components[mlx] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_excluding_a_component_removes_only_its_back_projection[torch] +[gw4] [ 22%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_excluding_a_component_removes_only_its_back_projection[torch] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_excluding_a_component_removes_only_its_back_projection[mlx] +[gw2] [ 22%] PASSED pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[numpy-1] +pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[numpy-2] +[gw4] [ 22%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_excluding_a_component_removes_only_its_back_projection[mlx] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_eeglab_export_reloads_with_the_reduced_rank[torch] +[gw4] [ 22%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_eeglab_export_reloads_with_the_reduced_rank[torch] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_eeglab_export_reloads_with_the_reduced_rank[mlx] +[gw4] [ 22%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_eeglab_export_reloads_with_the_reduced_rank[mlx] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_save_load_gives_identical_sources[torch] +[gw4] [ 22%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_save_load_gives_identical_sources[torch] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_save_load_gives_identical_sources[mlx] +[gw4] [ 22%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_save_load_gives_identical_sources[mlx] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_input_param_drives_the_fit[torch] +[gw6] [ 22%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_every_model_restores_the_residual +pamica/tests/mne_tests/test_pca_residual.py::test_epochs_apply_restores_the_residual +[gw7] [ 22%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-scale-newton-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-scale-newton-pdf1] +[gw2] [ 22%] PASSED pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[numpy-2] +pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[mlx-1] +[gw2] [ 22%] PASSED pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[mlx-1] +pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[mlx-2] +[gw2] [ 22%] PASSED pamica/tests/test_initial_mixing.py::test_the_pre_change_code_fails_the_start_checks[mlx-2] +pamica/tests/test_initial_mixing.py::test_numpy_uses_an_A_supplied_before_fit_as_is +[gw1] [ 22%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_fit_is_stable_on_full_data[3] +pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_fit_is_stable_on_full_data[42] +[gw7] [ 22%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-scale-newton-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-noscale-ng-pdf0] +[gw2] [ 22%] PASSED pamica/tests/test_initial_mixing.py::test_numpy_uses_an_A_supplied_before_fit_as_is +pamica/tests/test_initial_mixing.py::test_numpy_refit_continues_from_its_fitted_A_as_is +[gw0] [ 22%] PASSED pamica/tests/mlx_tests/test_mlx_backend.py::test_converged_ll_matches_torch_float32 +pamica/tests/mlx_tests/test_mlx_backend.py::test_multimodel_matches_torch_float32 +[gw7] [ 23%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-noscale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-noscale-ng-pdf0] +[gw6] [ 23%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_epochs_apply_restores_the_residual +pamica/tests/mne_tests/test_pca_residual.py::test_saved_ica_restores_the_residual +[gw6] [ 23%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_saved_ica_restores_the_residual +pamica/tests/mne_tests/test_pca_residual.py::test_float_n_pca_components_selects_by_explained_variance +[gw6] [ 23%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_float_n_pca_components_selects_by_explained_variance +pamica/tests/mne_tests/test_pca_residual.py::test_mixed_channel_types_restore_the_residual_in_original_units +[gw2] [ 23%] PASSED pamica/tests/test_initial_mixing.py::test_numpy_refit_continues_from_its_fitted_A_as_is +pamica/tests/test_initial_mixing.py::test_a_torch_state_dict_restores_A_as_is +[gw5] [ 23%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_export_is_cached_and_invalidated_on_refit +pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_with_channel_subset +[gw2] [ 23%] PASSED pamica/tests/test_initial_mixing.py::test_a_torch_state_dict_restores_A_as_is +pamica/tests/test_initial_mixing.py::test_an_mlx_save_restores_A_as_is +[gw2] [ 23%] PASSED pamica/tests/test_initial_mixing.py::test_an_mlx_save_restores_A_as_is +pamica/tests/test_initial_mixing.py::test_a_wrapper_save_restores_A_as_is +[gw2] [ 23%] PASSED pamica/tests/test_initial_mixing.py::test_a_wrapper_save_restores_A_as_is +pamica/tests/test_initial_mixing.py::test_numpy_fix_init_starts_from_the_identity +[gw2] [ 23%] PASSED pamica/tests/test_initial_mixing.py::test_numpy_fix_init_starts_from_the_identity +pamica/tests/test_initial_mixing.py::test_numpy_refuses_a_supplied_A_no_fit_can_start_from[columns] +[gw2] [ 23%] PASSED pamica/tests/test_initial_mixing.py::test_numpy_refuses_a_supplied_A_no_fit_can_start_from[columns] +pamica/tests/test_initial_mixing.py::test_numpy_refuses_a_supplied_A_no_fit_can_start_from[nan] +[gw2] [ 23%] PASSED pamica/tests/test_initial_mixing.py::test_numpy_refuses_a_supplied_A_no_fit_can_start_from[nan] +pamica/tests/test_initial_mixing.py::test_numpy_refuses_a_supplied_A_no_fit_can_start_from[zero-row] +[gw2] [ 23%] PASSED pamica/tests/test_initial_mixing.py::test_numpy_refuses_a_supplied_A_no_fit_can_start_from[zero-row] +pamica/tests/test_initial_mixing.py::test_the_numpy_restart_redraws_unit_norm_components[1] +[gw2] [ 23%] PASSED pamica/tests/test_initial_mixing.py::test_the_numpy_restart_redraws_unit_norm_components[1] +pamica/tests/test_initial_mixing.py::test_the_numpy_restart_redraws_unit_norm_components[2] +[gw6] [ 23%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_mixed_channel_types_restore_the_residual_in_original_units +pamica/tests/mne_tests/test_pca_residual.py::test_average_reference_rank_reduction_reconstructs +[gw4] [ 23%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_input_param_drives_the_fit[torch] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_input_param_drives_the_fit[mlx] +[gw7] [ 23%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-noscale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-noscale-ng-pdf0] +[gw4] [ 23%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_input_param_drives_the_fit[mlx] +pamica/tests/mne_tests/test_end_to_end_workflow.py::test_torch_and_mlx_find_the_same_components +[gw5] [ 23%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_with_channel_subset +pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_from_epochs +[gw7] [ 23%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-noscale-ng-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-noscale-ng-pdf1] +[gw4] [ 23%] PASSED pamica/tests/mne_tests/test_end_to_end_workflow.py::test_torch_and_mlx_find_the_same_components +pamica/tests/mne_tests/test_mne_backends.py::test_backend_is_validated_like_amica +[gw4] [ 24%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_backend_is_validated_like_amica +pamica/tests/mne_tests/test_mne_backends.py::test_unfitted_repr_names_the_backend[torch] +[gw4] [ 24%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_unfitted_repr_names_the_backend[torch] +pamica/tests/mne_tests/test_mne_backends.py::test_unfitted_repr_names_the_backend[mlx] +[gw4] [ 24%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_unfitted_repr_names_the_backend[mlx] +pamica/tests/mne_tests/test_mne_backends.py::test_fitted_repr_names_the_backend +[gw2] [ 24%] PASSED pamica/tests/test_initial_mixing.py::test_the_numpy_restart_redraws_unit_norm_components[2] +pamica/tests/test_initial_mixing.py::test_the_pre_change_numpy_restart_redrew_unnormalized_components +[gw1] [ 24%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_fit_is_stable_on_full_data[42] +pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_inactive_is_bit_identical +[gw4] [ 24%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_fitted_repr_names_the_backend +pamica/tests/mne_tests/test_mne_backends.py::test_mlx_without_mlx_raises_import_error +[gw4] [ 24%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_mlx_without_mlx_raises_import_error +pamica/tests/mne_tests/test_mne_backends.py::test_unknown_fit_keyword_propagates_from_amica +[gw4] [ 24%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_unknown_fit_keyword_propagates_from_amica +pamica/tests/mne_tests/test_mne_backends.py::test_mlx_rejects_a_dtype +[gw4] [ 24%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_mlx_rejects_a_dtype +pamica/tests/mne_tests/test_mne_backends.py::test_fit_without_lrate_uses_the_backend_default[torch_keep] +[gw4] [ 24%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_fit_without_lrate_uses_the_backend_default[torch_keep] +pamica/tests/mne_tests/test_mne_backends.py::test_fit_without_lrate_uses_the_backend_default[mlx_keep] +[gw4] [ 24%] PASSED pamica/tests/mne_tests/test_mne_backends.py::test_fit_without_lrate_uses_the_backend_default[mlx_keep] +pamica/tests/test_default_settings.py::test_native_block_is_pamicas_block_split_over_the_threads +[gw4] [ 24%] PASSED pamica/tests/test_default_settings.py::test_native_block_is_pamicas_block_split_over_the_threads +pamica/tests/test_default_settings.py::test_native_input_param_writes_every_setting_it_can +[gw2] [ 24%] PASSED pamica/tests/test_initial_mixing.py::test_the_pre_change_numpy_restart_redrew_unnormalized_components +pamica/tests/test_initial_mixing.py::test_the_reference_draws_unit_norm_components[1-1] +[gw2] [ 24%] SKIPPED pamica/tests/test_initial_mixing.py::test_the_reference_draws_unit_norm_components[1-1] +pamica/tests/test_initial_mixing.py::test_the_reference_draws_unit_norm_components[1-42] +[gw2] [ 24%] SKIPPED pamica/tests/test_initial_mixing.py::test_the_reference_draws_unit_norm_components[1-42] +pamica/tests/test_initial_mixing.py::test_the_reference_draws_unit_norm_components[2-1] +[gw2] [ 24%] SKIPPED pamica/tests/test_initial_mixing.py::test_the_reference_draws_unit_norm_components[2-1] +pamica/tests/test_initial_mixing.py::test_the_reference_draws_unit_norm_components[2-42] +[gw2] [ 24%] SKIPPED pamica/tests/test_initial_mixing.py::test_the_reference_draws_unit_norm_components[2-42] +pamica/tests/test_initial_mixing.py::test_the_reference_normalizes_pamicas_draw_as_pamica_does[1] +[gw4] [ 24%] PASSED pamica/tests/test_default_settings.py::test_native_input_param_writes_every_setting_it_can +[gw2] [ 24%] SKIPPED pamica/tests/test_initial_mixing.py::test_the_reference_normalizes_pamicas_draw_as_pamica_does[1] +pamica/tests/test_initial_mixing.py::test_the_reference_normalizes_pamicas_draw_as_pamica_does[2] +[gw2] [ 24%] SKIPPED pamica/tests/test_initial_mixing.py::test_the_reference_normalizes_pamicas_draw_as_pamica_does[2] +pamica/tests/test_dimsweep_threads.py::test_is_cpu_classifies_backends +pamica/tests/test_iteration_order.py::test_a_is_held_on_exactly_the_reference_iterations_without_sharing[torch] +[gw4] [ 25%] PASSED pamica/tests/test_dimsweep_threads.py::test_is_cpu_classifies_backends +pamica/tests/test_dimsweep_threads.py::test_is_cpu_covers_every_backend +[gw4] [ 25%] PASSED pamica/tests/test_dimsweep_threads.py::test_is_cpu_covers_every_backend +pamica/tests/test_dimsweep_threads.py::test_report_surfaces_all_failed_backend +[gw4] [ 25%] PASSED pamica/tests/test_dimsweep_threads.py::test_report_surfaces_all_failed_backend +pamica/tests/test_dimsweep_threads.py::test_threads_recorded_end_to_end +[gw1] [ 25%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_inactive_is_bit_identical +pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_direction_matches_formula +[gw1] [ 25%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_direction_matches_formula +pamica/tests/mlx_tests/test_mlx_newton.py::test_lrate_ramps_toward_newtrate_while_posdef +[gw4] [ 25%] PASSED pamica/tests/test_dimsweep_threads.py::test_threads_recorded_end_to_end +pamica/tests/test_dimsweep_threads.py::test_run_torch_restores_global_thread_count +[gw4] [ 25%] PASSED pamica/tests/test_dimsweep_threads.py::test_run_torch_restores_global_thread_count +pamica/tests/test_doscaling_rows.py::test_torch_rescale_is_an_exact_change_of_scale[1-ng] +[gw6] [ 25%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_average_reference_rank_reduction_reconstructs +pamica/tests/mne_tests/test_pca_residual.py::test_pcadb_reduction_restores_the_residual +[gw2] [ 25%] PASSED pamica/tests/test_iteration_order.py::test_a_is_held_on_exactly_the_reference_iterations_without_sharing[torch] +pamica/tests/test_iteration_order.py::test_a_is_held_on_exactly_the_reference_iterations_without_sharing[numpy] +[gw1] [ 25%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_lrate_ramps_toward_newtrate_while_posdef +pamica/tests/mlx_tests/test_mlx_newton.py::test_fallback_ramps_toward_lrate_cap_and_counts +[gw4] [ 25%] PASSED pamica/tests/test_doscaling_rows.py::test_torch_rescale_is_an_exact_change_of_scale[1-ng] +pamica/tests/test_doscaling_rows.py::test_torch_rescale_is_an_exact_change_of_scale[1-newton] +[gw7] [ 25%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-noscale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-noscale-ng-pdf1] +[gw1] [ 25%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_fallback_ramps_toward_lrate_cap_and_counts +pamica/tests/mlx_tests/test_mlx_newton.py::test_newtrate_ratchet_is_suppressed_before_newt_start +[gw4] [ 25%] PASSED pamica/tests/test_doscaling_rows.py::test_torch_rescale_is_an_exact_change_of_scale[1-newton] +pamica/tests/test_doscaling_rows.py::test_torch_rescale_is_an_exact_change_of_scale[2-ng] +[gw7] [ 25%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-noscale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-noscale-newton-pdf0] +[gw4] [ 25%] PASSED pamica/tests/test_doscaling_rows.py::test_torch_rescale_is_an_exact_change_of_scale[2-ng] +pamica/tests/test_doscaling_rows.py::test_torch_rescale_is_an_exact_change_of_scale[2-newton] +[gw5] [ 25%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_from_epochs +pamica/tests/mne_tests/test_mne_wrapper.py::test_plot_components_returns_figure +[gw2] [ 25%] PASSED pamica/tests/test_iteration_order.py::test_a_is_held_on_exactly_the_reference_iterations_without_sharing[numpy] +pamica/tests/test_iteration_order.py::test_a_is_held_on_exactly_the_reference_iterations_without_sharing[mlx] +[gw5] [ 25%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_plot_components_returns_figure +pamica/tests/mne_tests/test_mne_wrapper.py::test_pca_components_orthonormal_and_variance_ordered +[gw5] [ 25%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_pca_components_orthonormal_and_variance_ordered +pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_with_start_stop_subranges_raw +[gw4] [ 26%] PASSED pamica/tests/test_doscaling_rows.py::test_torch_rescale_is_an_exact_change_of_scale[2-newton] +pamica/tests/test_doscaling_rows.py::test_numpy_rescale_is_an_exact_change_of_scale[1-ng] +[gw2] [ 26%] PASSED pamica/tests/test_iteration_order.py::test_a_is_held_on_exactly_the_reference_iterations_without_sharing[mlx] +pamica/tests/test_iteration_order.py::test_a_held_iteration_only_rescales_with_doscaling_on[torch] +[gw7] [ 26%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-noscale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-noscale-newton-pdf0] +[gw6] [ 26%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_pcadb_reduction_restores_the_residual +pamica/tests/mne_tests/test_pca_residual.py::test_float32_fit_restores_the_residual +[gw2] [ 26%] PASSED pamica/tests/test_iteration_order.py::test_a_held_iteration_only_rescales_with_doscaling_on[torch] +pamica/tests/test_iteration_order.py::test_a_held_iteration_only_rescales_with_doscaling_on[numpy] +[gw4] [ 26%] PASSED pamica/tests/test_doscaling_rows.py::test_numpy_rescale_is_an_exact_change_of_scale[1-ng] +pamica/tests/test_doscaling_rows.py::test_numpy_rescale_is_an_exact_change_of_scale[1-newton] +[gw6] [ 26%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_float32_fit_restores_the_residual +pamica/tests/mne_tests/test_pca_residual.py::test_float32_retained_basis_matches_the_float32_sphere +[gw6] [ 26%] PASSED pamica/tests/mne_tests/test_pca_residual.py::test_float32_retained_basis_matches_the_float32_sphere +pamica/tests/test_amari_distance.py::test_amari_distance_self_is_zero +[gw6] [ 26%] PASSED pamica/tests/test_amari_distance.py::test_amari_distance_self_is_zero +pamica/tests/test_amari_distance.py::test_amari_distance_invariant_to_permutation_and_scale +[gw6] [ 26%] PASSED pamica/tests/test_amari_distance.py::test_amari_distance_invariant_to_permutation_and_scale +pamica/tests/test_amari_distance.py::test_amari_distance_nonzero_for_unrelated +[gw6] [ 26%] PASSED pamica/tests/test_amari_distance.py::test_amari_distance_nonzero_for_unrelated +pamica/tests/test_amari_distance.py::test_amari_distance_nonnegative +[gw6] [ 26%] PASSED pamica/tests/test_amari_distance.py::test_amari_distance_nonnegative +pamica/tests/test_amari_distance.py::test_amari_distance_symmetric +[gw6] [ 26%] PASSED pamica/tests/test_amari_distance.py::test_amari_distance_symmetric +pamica/tests/test_amari_distance.py::test_amari_distance_rejects_degenerate_input +[gw6] [ 26%] PASSED pamica/tests/test_amari_distance.py::test_amari_distance_rejects_degenerate_input +pamica/tests/test_amari_distance.py::test_amari_distance_rejects_scalar_input +[gw6] [ 26%] PASSED pamica/tests/test_amari_distance.py::test_amari_distance_rejects_scalar_input +pamica/tests/test_amari_ensemble_script.py::test_model_amari_finds_swapped_pairing +[gw6] [ 26%] PASSED pamica/tests/test_amari_ensemble_script.py::test_model_amari_finds_swapped_pairing +pamica/tests/test_amari_ensemble_script.py::test_model_amari_matches_best_of_naive_pairings +[gw6] [ 26%] PASSED pamica/tests/test_amari_ensemble_script.py::test_model_amari_matches_best_of_naive_pairings +pamica/tests/test_amari_ensemble_script.py::test_perm_test_distance_metric_detects_worse_between +[gw6] [ 26%] PASSED pamica/tests/test_amari_ensemble_script.py::test_perm_test_distance_metric_detects_worse_between +pamica/tests/test_amari_ensemble_script.py::test_perm_test_similarity_metric_detects_worse_between +[gw6] [ 26%] PASSED pamica/tests/test_amari_ensemble_script.py::test_perm_test_similarity_metric_detects_worse_between +pamica/tests/test_amari_ensemble_script.py::test_perm_test_no_evidence_when_groups_are_equivalent +[gw6] [ 26%] PASSED pamica/tests/test_amari_ensemble_script.py::test_perm_test_no_evidence_when_groups_are_equivalent +pamica/tests/test_amica.py::TestAMICA::test_data_loading +[gw6] [ 27%] PASSED pamica/tests/test_amica.py::TestAMICA::test_data_loading +pamica/tests/test_amica.py::TestAMICA::test_pdf_computation +[gw6] [ 27%] PASSED pamica/tests/test_amica.py::TestAMICA::test_pdf_computation +pamica/tests/test_amica.py::TestAMICA::test_preprocessing +[gw6] [ 27%] PASSED pamica/tests/test_amica.py::TestAMICA::test_preprocessing +pamica/tests/test_amicaout_reduced.py::test_sphere_is_padded_to_the_fortran_record_shape +[gw4] [ 27%] PASSED pamica/tests/test_doscaling_rows.py::test_numpy_rescale_is_an_exact_change_of_scale[1-newton] +pamica/tests/test_doscaling_rows.py::test_numpy_rescale_is_an_exact_change_of_scale[2-ng] +[gw2] [ 27%] PASSED pamica/tests/test_iteration_order.py::test_a_held_iteration_only_rescales_with_doscaling_on[numpy] +pamica/tests/test_iteration_order.py::test_a_held_iteration_only_rescales_with_doscaling_on[mlx] +[gw7] [ 27%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-noscale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-noscale-newton-pdf0] +[gw2] [ 27%] PASSED pamica/tests/test_iteration_order.py::test_a_held_iteration_only_rescales_with_doscaling_on[mlx] +pamica/tests/test_iteration_order.py::test_default_fits_hold_a_on_iterations_100_to_105[torch] +[gw7] [ 27%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-noscale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-noscale-newton-pdf1] +[gw5] [ 27%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_with_start_stop_subranges_raw +pamica/tests/mne_tests/test_mne_wrapper.py::test_apply_on_epochs +[gw6] [ 27%] PASSED pamica/tests/test_amicaout_reduced.py::test_sphere_is_padded_to_the_fortran_record_shape +pamica/tests/test_amicaout_reduced.py::test_loadmodout_reads_a_reduced_fit +[gw6] [ 27%] PASSED pamica/tests/test_amicaout_reduced.py::test_loadmodout_reads_a_reduced_fit +pamica/tests/test_amicaout_reduced.py::test_sources_roundtrip_under_reduced_rank +[gw6] [ 27%] PASSED pamica/tests/test_amicaout_reduced.py::test_sources_roundtrip_under_reduced_rank +pamica/tests/test_amicaout_reduced.py::test_sphere_is_written_and_read_column_major[True] +[gw4] [ 27%] PASSED pamica/tests/test_doscaling_rows.py::test_numpy_rescale_is_an_exact_change_of_scale[2-ng] +pamica/tests/test_doscaling_rows.py::test_numpy_rescale_is_an_exact_change_of_scale[2-newton] +[gw6] [ 27%] PASSED pamica/tests/test_amicaout_reduced.py::test_sphere_is_written_and_read_column_major[True] +pamica/tests/test_amicaout_reduced.py::test_sphere_is_written_and_read_column_major[False] +[gw7] [ 27%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-noscale-newton-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-noscale-newton-pdf1] +[gw6] [ 27%] PASSED pamica/tests/test_amicaout_reduced.py::test_sphere_is_written_and_read_column_major[False] +pamica/tests/test_backend_accessors.py::test_unfitted_accessors_raise[torch] +[gw6] [ 27%] PASSED pamica/tests/test_backend_accessors.py::test_unfitted_accessors_raise[torch] +pamica/tests/test_backend_accessors.py::test_unfitted_accessors_raise[mlx] +[gw6] [ 27%] PASSED pamica/tests/test_backend_accessors.py::test_unfitted_accessors_raise[mlx] +pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[full-torch] +[gw6] [ 27%] PASSED pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[full-torch] +pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[full-mlx] +[gw7] [ 27%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-noscale-newton-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-reject-newton] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[full-mlx] +pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[reduced-torch] +[gw5] [ 28%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_apply_on_epochs +pamica/tests/mne_tests/test_mne_wrapper.py::test_exported_ica_saves_and_reloads +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[reduced-torch] +pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[reduced-mlx] +[gw5] [ 28%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_exported_ica_saves_and_reloads +pamica/tests/mne_tests/test_mne_wrapper.py::test_plot_sources_returns_figure +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[reduced-mlx] +pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[two_models-torch] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[two_models-torch] +pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[two_models-mlx] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_accessors_return_the_fitted_state_as_float64[two_models-mlx] +pamica/tests/test_backend_accessors.py::test_accessors_return_independent_copies[torch] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_accessors_return_independent_copies[torch] +pamica/tests/test_backend_accessors.py::test_accessors_return_independent_copies[mlx] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_accessors_return_independent_copies[mlx] +pamica/tests/test_backend_accessors.py::test_model_center_validates_the_index[torch] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_model_center_validates_the_index[torch] +pamica/tests/test_backend_accessors.py::test_model_center_validates_the_index[mlx] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_model_center_validates_the_index[mlx] +pamica/tests/test_backend_accessors.py::test_single_model_center_is_zero +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_single_model_center_is_zero +pamica/tests/test_backend_accessors.py::test_float32_torch_fit_still_returns_float64 +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_float32_torch_fit_still_returns_float64 +pamica/tests/test_backend_accessors.py::test_mlx_accessors_agree_with_torch[full] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_mlx_accessors_agree_with_torch[full] +pamica/tests/test_backend_accessors.py::test_mlx_accessors_agree_with_torch[reduced] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_mlx_accessors_agree_with_torch[reduced] +pamica/tests/test_backend_accessors.py::test_mlx_accessors_agree_with_torch[two_models] +[gw6] [ 28%] PASSED pamica/tests/test_backend_accessors.py::test_mlx_accessors_agree_with_torch[two_models] +pamica/tests/test_llt_stash.py::test_numpy_stashed_llt_is_the_estep_behind_reported_ll +[gw5] [ 28%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_plot_sources_returns_figure +pamica/tests/mne_tests/test_mne_wrapper.py::test_seed_determinism +[gw2] [ 28%] PASSED pamica/tests/test_iteration_order.py::test_default_fits_hold_a_on_iterations_100_to_105[torch] +pamica/tests/test_iteration_order.py::test_default_fits_hold_a_on_iterations_100_to_105[numpy] +[gw4] [ 28%] PASSED pamica/tests/test_doscaling_rows.py::test_numpy_rescale_is_an_exact_change_of_scale[2-newton] +pamica/tests/test_doscaling_rows.py::test_mlx_rescale_is_an_exact_change_of_scale[1-ng] +[gw7] [ 28%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-reject-newton] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-reject-newton] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_mlx_rescale_is_an_exact_change_of_scale[1-ng] +pamica/tests/test_doscaling_rows.py::test_mlx_rescale_is_an_exact_change_of_scale[1-newton] +[gw1] [ 29%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newtrate_ratchet_is_suppressed_before_newt_start +pamica/tests/mlx_tests/test_mlx_newton.py::test_newtrate_ratchets_at_maxdecs_once_newton_runs +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_mlx_rescale_is_an_exact_change_of_scale[1-newton] +pamica/tests/test_doscaling_rows.py::test_mlx_rescale_is_an_exact_change_of_scale[2-ng] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_mlx_rescale_is_an_exact_change_of_scale[2-ng] +pamica/tests/test_doscaling_rows.py::test_mlx_rescale_is_an_exact_change_of_scale[2-newton] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_mlx_rescale_is_an_exact_change_of_scale[2-newton] +pamica/tests/test_doscaling_rows.py::test_numpy_rescales_like_torch[disjoint] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_numpy_rescales_like_torch[disjoint] +pamica/tests/test_doscaling_rows.py::test_mlx_rescales_like_torch[disjoint] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_mlx_rescales_like_torch[disjoint] +pamica/tests/test_doscaling_rows.py::test_numpy_rescales_like_torch[permuted] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_numpy_rescales_like_torch[permuted] +pamica/tests/test_doscaling_rows.py::test_mlx_rescales_like_torch[permuted] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_mlx_rescales_like_torch[permuted] +pamica/tests/test_doscaling_rows.py::test_numpy_rescales_like_torch[merged] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_numpy_rescales_like_torch[merged] +pamica/tests/test_doscaling_rows.py::test_mlx_rescales_like_torch[merged] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_mlx_rescales_like_torch[merged] +pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[torch-zero] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[torch-zero] +pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[torch-nan] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[torch-nan] +pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[numpy-zero] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[numpy-zero] +pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[numpy-nan] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[numpy-nan] +pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[mlx-zero] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[mlx-zero] +pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[mlx-nan] +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_a_zero_or_nan_norm_row_is_left_untouched[mlx-nan] +pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[torch-1] +[gw6] [ 29%] PASSED pamica/tests/test_llt_stash.py::test_numpy_stashed_llt_is_the_estep_behind_reported_ll +pamica/tests/test_llt_stash.py::test_stashed_llt_is_one_m_step_behind_the_written_parameters +[gw4] [ 29%] PASSED pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[torch-1] +pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[torch-2] +[gw7] [ 29%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-reject-newton] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-reject-newton] +[gw7] [ 29%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-reject-newton] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m3-scale-newton-pdf0] +[gw6] [ 30%] PASSED pamica/tests/test_llt_stash.py::test_stashed_llt_is_one_m_step_behind_the_written_parameters +pamica/tests/test_llt_stash.py::test_torch_and_numpy_stash_the_same_llt_on_matched_state +[gw4] [ 30%] PASSED pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[torch-2] +pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[numpy-1] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_default_fits_hold_a_on_iterations_100_to_105[numpy] +pamica/tests/test_iteration_order.py::test_default_fits_hold_a_on_iterations_100_to_105[mlx] +[gw6] [ 30%] PASSED pamica/tests/test_llt_stash.py::test_torch_and_numpy_stash_the_same_llt_on_matched_state +pamica/tests/test_llt_stash.py::test_llt_invariant_breaks_when_rejection_fires_on_the_last_iteration +[gw7] [ 30%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m3-scale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m3-scale-newton-pdf0] +[gw1] [ 30%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newtrate_ratchets_at_maxdecs_once_newton_runs +pamica/tests/mlx_tests/test_mlx_newton.py::test_newtrate_never_ratchets_without_newton +[gw6] [ 30%] PASSED pamica/tests/test_llt_stash.py::test_llt_invariant_breaks_when_rejection_fires_on_the_last_iteration +pamica/tests/test_llt_stash.py::test_llt_invariant_returns_one_iteration_after_a_rejection +[gw4] [ 30%] PASSED pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[numpy-1] +pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[numpy-2] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_default_fits_hold_a_on_iterations_100_to_105[mlx] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-6-False] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-6-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-6-True] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-6-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-1-False] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-1-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-1-True] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-1-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-0-False] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-0-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-0-True] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-0-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch--3-False] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch--3-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch--3-True] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch--3-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-2.5-False] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-2.5-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-2.5-True] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-2.5-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-True-False] +[gw2] [ 30%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-True-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-True-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[torch-True-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-6-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-6-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-6-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-6-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-1-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-1-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-1-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-1-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-0-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-0-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-0-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-0-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy--3-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy--3-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy--3-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy--3-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-2.5-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-2.5-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-2.5-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-2.5-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-True-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-True-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-True-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[numpy-True-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-6-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-6-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-6-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-6-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-1-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-1-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-1-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-1-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-0-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-0-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-0-True] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-0-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx--3-False] +[gw2] [ 31%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx--3-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx--3-True] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx--3-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-2.5-False] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-2.5-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-2.5-True] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-2.5-True] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-True-False] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-True-False] +pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-True-True] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_every_backend_rejects_a_share_iter_below_7[mlx-True-True] +pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[torch-share_iter-6-must be an integer >= 7, got 6: below 7] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[torch-share_iter-6-must be an integer >= 7, got 6: below 7] +pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[torch-share_start-0-share_start must be an integer >= 1, got 0] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[torch-share_start-0-share_start must be an integer >= 1, got 0] +pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[numpy-share_iter-6-must be an integer >= 7, got 6: below 7] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[numpy-share_iter-6-must be an integer >= 7, got 6: below 7] +pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[numpy-share_start-0-share_start must be an integer >= 1, got 0] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[numpy-share_start-0-share_start must be an integer >= 1, got 0] +pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[mlx-share_iter-6-must be an integer >= 7, got 6: below 7] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[mlx-share_iter-6-must be an integer >= 7, got 6: below 7] +pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[mlx-share_start-0-share_start must be an integer >= 1, got 0] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_a_params_file_reaches_the_share_validation[mlx-share_start-0-share_start must be an integer >= 1, got 0] +pamica/tests/test_iteration_order.py::test_the_step_after_a_decrease_already_uses_the_halved_rate[torch] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_the_step_after_a_decrease_already_uses_the_halved_rate[torch] +pamica/tests/test_iteration_order.py::test_the_step_after_a_decrease_already_uses_the_halved_rate[numpy] +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_the_step_after_a_decrease_already_uses_the_halved_rate[numpy] +pamica/tests/test_iteration_order.py::test_the_step_after_a_decrease_already_uses_the_halved_rate[mlx] +[gw6] [ 32%] PASSED pamica/tests/test_llt_stash.py::test_llt_invariant_returns_one_iteration_after_a_rejection +pamica/tests/test_llt_stash.py::test_keep_best_restore_rolls_the_llt_stash_back +[gw5] [ 32%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_seed_determinism +pamica/tests/mne_tests/test_mne_wrapper.py::test_unfitted_calls_raise +[gw5] [ 32%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_unfitted_calls_raise +pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_rejects_non_mne_input +[gw5] [ 32%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_rejects_non_mne_input +pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_rejects_start_stop_on_epochs +[gw2] [ 32%] PASSED pamica/tests/test_iteration_order.py::test_the_step_after_a_decrease_already_uses_the_halved_rate[mlx] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_one_mstep_matches_torch_twin[4-1] +[gw5] [ 32%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_rejects_start_stop_on_epochs +pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_rejects_out_of_range_stop +[gw5] [ 32%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_rejects_out_of_range_stop +pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_rejects_non_finite_data +[gw5] [ 33%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_fit_rejects_non_finite_data +pamica/tests/mne_tests/test_mne_wrapper.py::test_pca_reduction_is_supported +[gw2] [ 33%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_one_mstep_matches_torch_twin[4-1] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_one_mstep_matches_torch_twin[1-1] +[gw2] [ 33%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_one_mstep_matches_torch_twin[1-1] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_full_fit_ll_matches_torch_float64[2-3] +[gw7] [ 33%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m3-scale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m3-scale-newton-pdf0] +[gw1] [ 33%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newtrate_never_ratchets_without_newton +pamica/tests/mlx_tests/test_mlx_newton.py::test_grad_norm_floor_fires_under_newton +[gw5] [ 33%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_pca_reduction_is_supported +pamica/tests/mne_tests/test_mne_wrapper.py::test_degenerate_fit_is_refused_and_labeled +[gw7] [ 33%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m3-scale-newton-pdf0] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m3-noscale-ng-pdf1] +[gw1] [ 33%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_grad_norm_floor_fires_under_newton +pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_schedule_state_resets_at_fit_start +[gw1] [ 33%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_schedule_state_resets_at_fit_start +pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_finalize_uses_preupdate_mu +[gw1] [ 33%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_newton_finalize_uses_preupdate_mu +pamica/tests/mlx_tests/test_mlx_newton.py::test_multimodel_newton_mstep_is_finite[1] +[gw1] [ 33%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_multimodel_newton_mstep_is_finite[1] +pamica/tests/mlx_tests/test_mlx_newton.py::test_multimodel_newton_mstep_is_finite[2] +[gw1] [ 33%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_multimodel_newton_mstep_is_finite[2] +pamica/tests/mlx_tests/test_mlx_newton.py::test_multimodel_newton_fit_completes +[gw1] [ 33%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_multimodel_newton_fit_completes +pamica/tests/mlx_tests/test_mlx_newton.py::test_three_model_newton_mstep_and_fit_are_finite +[gw4] [ 33%] PASSED pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[numpy-2] +pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[mlx-1] +[gw4] [ 33%] PASSED pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[mlx-1] +pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[mlx-2] +[gw5] [ 33%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_degenerate_fit_is_refused_and_labeled +pamica/tests/mne_tests/test_mne_wrapper.py::test_failed_refit_leaves_prior_state_intact +[gw7] [ 33%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m3-noscale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m3-noscale-ng-pdf1] +[gw4] [ 33%] PASSED pamica/tests/test_doscaling_rows.py::test_doscaling_off_is_byte_identical_to_the_pre_fix_code[mlx-2] +pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[1-torch] +[gw7] [ 33%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m3-noscale-ng-pdf1] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-ng-pdf2] +[gw6] [ 33%] PASSED pamica/tests/test_llt_stash.py::test_keep_best_restore_rolls_the_llt_stash_back +pamica/tests/test_llt_stash.py::test_torch_write_runs_no_forward_pass +[gw7] [ 34%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-ng-pdf2] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-ng-pdf2] +[gw1] [ 34%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_three_model_newton_mstep_and_fit_are_finite +pamica/tests/mlx_tests/test_mlx_newton.py::test_frozen_iterations_do_not_count_newton_fallbacks +[gw1] [ 34%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_frozen_iterations_do_not_count_newton_fallbacks +pamica/tests/mlx_tests/test_mlx_newton.py::test_sharing_and_newton_fit_completes +[gw7] [ 34%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-ng-pdf2] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-ng-pdf3] +[gw6] [ 34%] PASSED pamica/tests/test_llt_stash.py::test_torch_write_runs_no_forward_pass +pamica/tests/test_llt_stash.py::test_numpy_checkpoint_runs_no_forward_pass +[gw4] [ 34%] PASSED pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[1-torch] +pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[1-numpy] +[gw7] [ 34%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-ng-pdf3] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-ng-pdf3] +[gw7] [ 34%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-ng-pdf3] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-ng-pdf4] +[gw5] [ 34%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_failed_refit_leaves_prior_state_intact +pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_export_roundtrips_with_nonzero_c +[gw7] [ 34%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m1-ng-pdf4] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-ng-pdf4] +[gw7] [ 34%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m1-ng-pdf4] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-newton-4blocks] +[gw0] [ 34%] PASSED pamica/tests/mlx_tests/test_mlx_backend.py::test_multimodel_matches_torch_float32 +pamica/tests/mlx_tests/test_mlx_backend.py::test_degenerate_fit_stops_and_reports_nan +[gw0] [ 34%] PASSED pamica/tests/mlx_tests/test_mlx_backend.py::test_degenerate_fit_stops_and_reports_nan +pamica/tests/mlx_tests/test_mlx_backend.py::test_init_matches_torch_seed +[gw0] [ 34%] PASSED pamica/tests/mlx_tests/test_mlx_backend.py::test_init_matches_torch_seed +pamica/tests/mlx_tests/test_mlx_backend.py::test_multimodel_dead_model_keeps_prior_c +[gw6] [ 34%] PASSED pamica/tests/test_llt_stash.py::test_numpy_checkpoint_runs_no_forward_pass +pamica/tests/test_llt_stash.py::test_llt_stash_is_none_before_any_estep_ran +[gw6] [ 34%] PASSED pamica/tests/test_llt_stash.py::test_llt_stash_is_none_before_any_estep_ran +pamica/tests/test_metrics_mir.py::test_marginal_entropies_default_nbins_matches_formula +[gw0] [ 34%] PASSED pamica/tests/mlx_tests/test_mlx_backend.py::test_multimodel_dead_model_keeps_prior_c +pamica/tests/mlx_tests/test_mlx_backend.py::test_rholrate_ratchets_at_maxdecs_not_per_decrease +[gw6] [ 34%] PASSED pamica/tests/test_metrics_mir.py::test_marginal_entropies_default_nbins_matches_formula +pamica/tests/test_metrics_mir.py::test_marginal_entropies_matches_histogram_rederivation +[gw6] [ 34%] PASSED pamica/tests/test_metrics_mir.py::test_marginal_entropies_matches_histogram_rederivation +pamica/tests/test_metrics_mir.py::test_mir_identity_unmixing_is_approximately_zero +[gw1] [ 34%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_sharing_and_newton_fit_completes +pamica/tests/mlx_tests/test_mlx_newton.py::test_rank_reduced_newton_fit_completes +[gw6] [ 35%] PASSED pamica/tests/test_metrics_mir.py::test_mir_identity_unmixing_is_approximately_zero +pamica/tests/test_metrics_mir.py::test_mir_scaled_identity_matches_closed_form +[gw6] [ 35%] PASSED pamica/tests/test_metrics_mir.py::test_mir_scaled_identity_matches_closed_form +pamica/tests/test_metrics_mir.py::test_mir_returns_finite_scalars_for_full_channel_data +[gw6] [ 35%] PASSED pamica/tests/test_metrics_mir.py::test_mir_returns_finite_scalars_for_full_channel_data +pamica/tests/test_metrics_mir.py::test_mir_real_fitted_unmixing_is_large_and_positive +[gw6] [ 35%] PASSED pamica/tests/test_metrics_mir.py::test_mir_real_fitted_unmixing_is_large_and_positive +pamica/tests/test_metrics_mir.py::test_mir_nbins_passthrough_matches_manual_computation +[gw6] [ 35%] PASSED pamica/tests/test_metrics_mir.py::test_mir_nbins_passthrough_matches_manual_computation +pamica/tests/test_metrics_mir.py::test_mir_raises_on_singular_unmixing +[gw6] [ 35%] PASSED pamica/tests/test_metrics_mir.py::test_mir_raises_on_singular_unmixing +pamica/tests/test_metrics_mir.py::test_mir_raises_on_non_square_unmixing +[gw6] [ 35%] PASSED pamica/tests/test_metrics_mir.py::test_mir_raises_on_non_square_unmixing +pamica/tests/test_metrics_mir.py::test_mir_raises_on_non_finite_data +[gw6] [ 35%] PASSED pamica/tests/test_metrics_mir.py::test_mir_raises_on_non_finite_data +pamica/tests/test_metrics_mir.py::test_marginal_entropies_raises_on_constant_channel +[gw6] [ 35%] PASSED pamica/tests/test_metrics_mir.py::test_marginal_entropies_raises_on_constant_channel +pamica/tests/test_metrics_pmi.py::test_pairwise_mi_is_exactly_symmetric +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_pairwise_mi_is_exactly_symmetric +pamica/tests/test_metrics_pmi.py::test_pairwise_mi_diagonal_matches_marginal_entropy +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_pairwise_mi_diagonal_matches_marginal_entropy +pamica/tests/test_metrics_pmi.py::test_ica_sources_have_lower_pairwise_mi_than_raw_channels +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_ica_sources_have_lower_pairwise_mi_than_raw_channels +pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_returns_valid_permutation +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_returns_valid_permutation +pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_increases_adjacent_weight +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_increases_adjacent_weight +pamica/tests/test_metrics_pmi.py::test_pairwise_mi_raises_on_non_finite_data +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_pairwise_mi_raises_on_non_finite_data +pamica/tests/test_metrics_pmi.py::test_pairwise_mi_raises_on_constant_channel +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_pairwise_mi_raises_on_constant_channel +pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_trivial_cases +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_trivial_cases +pamica/tests/test_metrics_pmi.py::test_pairwise_mi_nbins_passthrough_matches_manual_computation +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_pairwise_mi_nbins_passthrough_matches_manual_computation +pamica/tests/test_metrics_pmi.py::test_pairwise_mi_raises_on_invalid_nbins +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_pairwise_mi_raises_on_invalid_nbins +pamica/tests/test_metrics_pmi.py::test_pairwise_mi_raises_on_nbins_too_sparse +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_pairwise_mi_raises_on_nbins_too_sparse +pamica/tests/test_metrics_pmi.py::test_pairwise_mi_single_component +[gw6] [ 35%] PASSED pamica/tests/test_metrics_pmi.py::test_pairwise_mi_single_component +pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_two_components +[gw6] [ 36%] PASSED pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_two_components +pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_raises_on_non_square +[gw6] [ 36%] PASSED pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_raises_on_non_square +pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_raises_on_non_finite +[gw6] [ 36%] PASSED pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_raises_on_non_finite +pamica/tests/test_numpy_block_tuning.py::test_allocation_failure_falls_back_to_the_last_working_size +[gw1] [ 36%] PASSED pamica/tests/mlx_tests/test_mlx_newton.py::test_rank_reduced_newton_fit_completes +pamica/tests/mlx_tests/test_mlx_pdf.py::test_pdftype_validation +[gw1] [ 36%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_pdftype_validation +pamica/tests/mlx_tests/test_mlx_pdf.py::test_kurt_schedule_validation +[gw1] [ 36%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_kurt_schedule_validation +pamica/tests/mlx_tests/test_mlx_pdf.py::test_pdtype_h_is_none_only_for_gg +[gw1] [ 36%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_pdtype_h_is_none_only_for_gg +pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[0-3] +[gw6] [ 36%] PASSED pamica/tests/test_numpy_block_tuning.py::test_allocation_failure_falls_back_to_the_last_working_size +pamica/tests/test_numpy_block_tuning.py::test_a_real_error_in_the_probe_is_not_swallowed +[gw6] [ 36%] PASSED pamica/tests/test_numpy_block_tuning.py::test_a_real_error_in_the_probe_is_not_swallowed +pamica/tests/test_numpy_cli.py::test_cli_accepts_fortran_text_params_file +[gw1] [ 36%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[0-3] +pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[2-3] +[gw4] [ 36%] PASSED pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[1-numpy] +pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[1-mlx] +[gw1] [ 36%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[2-3] +pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[3-3] +[gw7] [ 36%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-newton-4blocks] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-newton-4blocks] +[gw4] [ 36%] PASSED pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[1-mlx] +pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[3-torch] +[gw1] [ 36%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[3-3] +pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[4-1] +[gw1] [ 36%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[4-1] +pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[1-1] +[gw6] [ 36%] PASSED pamica/tests/test_numpy_cli.py::test_cli_accepts_fortran_text_params_file +pamica/tests/test_numpy_cli.py::test_cli_still_accepts_json_params_file +[gw1] [ 36%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_family_fit_finite_and_monotone[1-1] +pamica/tests/mlx_tests/test_mlx_pdf.py::test_multimodel_fixed_family +[gw5] [ 36%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_export_roundtrips_with_nonzero_c +pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_export_is_distinct_and_cached +[gw5] [ 36%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_export_is_distinct_and_cached +pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_apply_reconstructs +[gw5] [ 37%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_apply_reconstructs +pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_apply_exclude_differs_by_model +[gw5] [ 37%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_apply_exclude_differs_by_model +pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_get_components_and_plot +[gw5] [ 37%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_per_model_get_components_and_plot +pamica/tests/mne_tests/test_mne_wrapper.py::test_model_probability_is_normalized +[gw1] [ 37%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_multimodel_fixed_family +pamica/tests/mlx_tests/test_mlx_pdf.py::test_auto_switcher_runs_and_is_stable +[gw5] [ 37%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_model_probability_is_normalized +pamica/tests/mne_tests/test_mne_wrapper.py::test_single_model_probability_is_all_ones +[gw5] [ 37%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_single_model_probability_is_all_ones +pamica/tests/mne_tests/test_mne_wrapper.py::test_model_probability_and_plot_on_epochs +[gw4] [ 37%] PASSED pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[3-torch] +pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[3-numpy] +[gw1] [ 37%] PASSED pamica/tests/mlx_tests/test_mlx_pdf.py::test_auto_switcher_runs_and_is_stable +pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_rejects_unknown_names[ALL] +[gw1] [ 37%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_backend_flag_rejects_unknown_names[ALL] +pamica/tests/test_fortran_param_forwarding.py::test_every_backend_returns_the_comparison_contract[torch] +[gw7] [ 37%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-newton-4blocks] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-newton-4blocks] +[gw5] [ 37%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_model_probability_and_plot_on_epochs +pamica/tests/mne_tests/test_mne_wrapper.py::test_plot_model_probability_default_srate_gives_seconds +[gw6] [ 37%] PASSED pamica/tests/test_numpy_cli.py::test_cli_still_accepts_json_params_file +pamica/tests/test_numpy_cli.py::test_load_params_maps_canonical_keys_for_fortran_text +[gw6] [ 37%] PASSED pamica/tests/test_numpy_cli.py::test_load_params_maps_canonical_keys_for_fortran_text +pamica/tests/test_numpy_cli.py::test_cli_without_outdir_still_writes_to_output +[gw5] [ 37%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_plot_model_probability_default_srate_gives_seconds +pamica/tests/mne_tests/test_mne_wrapper.py::test_out_of_range_model_idx_raises +[gw5] [ 37%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_out_of_range_model_idx_raises +pamica/tests/mne_tests/test_mne_wrapper.py::test_get_model_probability_rejects_non_mne_input +[gw5] [ 37%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_get_model_probability_rejects_non_mne_input +pamica/tests/mne_tests/test_mne_wrapper.py::test_degenerate_fit_refused_on_dominance_methods +[gw1] [ 37%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_every_backend_returns_the_comparison_contract[torch] +pamica/tests/test_fortran_param_forwarding.py::test_every_backend_returns_the_comparison_contract[numpy] +[gw1] [ 37%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_every_backend_returns_the_comparison_contract[numpy] +pamica/tests/test_fortran_param_forwarding.py::test_every_backend_returns_the_comparison_contract[mlx] +[gw1] [ 37%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_every_backend_returns_the_comparison_contract[mlx] +pamica/tests/test_fortran_param_forwarding.py::test_torch_and_numpy_runners_apply_the_same_params +[gw1] [ 37%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_torch_and_numpy_runners_apply_the_same_params +pamica/tests/test_fortran_param_forwarding.py::test_mlx_runner_applies_the_same_params_as_torch +[gw1] [ 38%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_mlx_runner_applies_the_same_params_as_torch +pamica/tests/test_fortran_param_forwarding.py::test_numpy_runner_writes_under_the_output_dir +[gw1] [ 38%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_numpy_runner_writes_under_the_output_dir +pamica/tests/test_fortran_param_forwarding.py::test_main_writes_one_report_per_backend_and_a_summary +[gw7] [ 38%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-newton-4blocks] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-keepbest-restores] +[gw7] [ 38%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-keepbest-restores] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-keepbest-restores] +[gw6] [ 38%] PASSED pamica/tests/test_numpy_cli.py::test_cli_without_outdir_still_writes_to_output +pamica/tests/test_numpy_grad_norm.py::test_grad_norm_is_on_fortran_scale +[gw7] [ 38%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-keepbest-restores] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-restarts] +[gw4] [ 38%] PASSED pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[3-numpy] +pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[3-mlx] +[gw6] [ 38%] PASSED pamica/tests/test_numpy_grad_norm.py::test_grad_norm_is_on_fortran_scale +pamica/tests/test_numpy_grad_norm.py::test_grad_norm_tracks_convergence +[gw1] [ 38%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_main_writes_one_report_per_backend_and_a_summary +pamica/tests/test_fortran_param_forwarding.py::test_default_run_is_the_historical_torch_only_run +[gw4] [ 38%] PASSED pamica/tests/test_doscaling_rows.py::test_scalestep_counts_iterations_from_one[3-mlx] +pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[torch-0] +[gw4] [ 38%] PASSED pamica/tests/test_doscaling_rows.py::test_every_backend_rejects_an_invalid_scalestep[torch-0] +pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_raises_on_asymmetric +[gw4] [ 38%] PASSED pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_raises_on_asymmetric +pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_handles_ties +[gw4] [ 38%] PASSED pamica/tests/test_metrics_pmi.py::test_block_diagonal_order_handles_ties +pamica/tests/test_metrics_posterior.py::test_healthy_lht_columns_sum_to_one_and_match_model_probability +[gw7] [ 38%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[torch-m2-restarts] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-restarts] +[gw4] [ 38%] PASSED pamica/tests/test_metrics_posterior.py::test_healthy_lht_columns_sum_to_one_and_match_model_probability +pamica/tests/test_metrics_posterior.py::test_all_models_neg_inf_at_a_sample_raises_distinct_message +[gw4] [ 38%] PASSED pamica/tests/test_metrics_posterior.py::test_all_models_neg_inf_at_a_sample_raises_distinct_message +pamica/tests/test_metrics_posterior.py::test_nan_loglik_raises_a_different_message_than_neg_inf +[gw4] [ 38%] PASSED pamica/tests/test_metrics_posterior.py::test_nan_loglik_raises_a_different_message_than_neg_inf +pamica/tests/test_metrics_posterior.py::test_caller_prefix_appears_in_both_error_messages +[gw4] [ 38%] PASSED pamica/tests/test_metrics_posterior.py::test_caller_prefix_appears_in_both_error_messages +pamica/tests/test_mlx_convergence_stops.py::test_negative_maxincs_is_rejected +[gw4] [ 38%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_negative_maxincs_is_rejected +pamica/tests/test_mlx_convergence_stops.py::test_min_dll_stops_at_the_same_iteration_as_torch +[gw1] [ 38%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_default_run_is_the_historical_torch_only_run +pamica/tests/test_fortran_param_forwarding.py::test_parity_summary_renders_every_numeric_column +[gw1] [ 39%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_parity_summary_renders_every_numeric_column +pamica/tests/test_fortran_param_forwarding.py::test_mlx_backend_without_mlx_exits_with_the_install_hint[torch,mlx] +[gw1] [ 39%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_mlx_backend_without_mlx_exits_with_the_install_hint[torch,mlx] +pamica/tests/test_fortran_param_forwarding.py::test_mlx_backend_without_mlx_exits_with_the_install_hint[all] +[gw1] [ 39%] PASSED pamica/tests/test_fortran_param_forwarding.py::test_mlx_backend_without_mlx_exits_with_the_install_hint[all] +pamica/tests/test_fortran_param_forwarding.py::test_backend_meets_its_parity_bar_against_fortran[torch] +[gw1] [ 39%] SKIPPED pamica/tests/test_fortran_param_forwarding.py::test_backend_meets_its_parity_bar_against_fortran[torch] +pamica/tests/test_fortran_param_forwarding.py::test_backend_meets_its_parity_bar_against_fortran[numpy] +[gw1] [ 39%] SKIPPED pamica/tests/test_fortran_param_forwarding.py::test_backend_meets_its_parity_bar_against_fortran[numpy] +pamica/tests/test_fortran_param_forwarding.py::test_backend_meets_its_parity_bar_against_fortran[mlx] +[gw1] [ 39%] SKIPPED pamica/tests/test_fortran_param_forwarding.py::test_backend_meets_its_parity_bar_against_fortran[mlx] +pamica/tests/test_fortran_params.py::test_known_scalar_mappings_land +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_known_scalar_mappings_land +pamica/tests/test_fortran_params.py::test_renamed_keys_translate +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_renamed_keys_translate +pamica/tests/test_fortran_params.py::test_boolean_flags_are_python_bool +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_boolean_flags_are_python_bool +pamica/tests/test_fortran_params.py::test_list_valued_keys +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_list_valued_keys +pamica/tests/test_fortran_params.py::test_unrecognized_keys_warn_and_are_dropped +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_unrecognized_keys_warn_and_are_dropped +pamica/tests/test_fortran_params.py::test_unsupported_keys_warn_and_are_dropped +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_unsupported_keys_warn_and_are_dropped +pamica/tests/test_fortran_params.py::test_block_size_search_keys_translate +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_block_size_search_keys_translate +pamica/tests/test_fortran_params.py::test_checkpoint_keys_translate +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_checkpoint_keys_translate +pamica/tests/test_fortran_params.py::test_block_size_search_keys_reach_the_backend +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_block_size_search_keys_reach_the_backend +pamica/tests/test_fortran_params.py::test_mapping_tables_partition_every_known_fortran_key +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_mapping_tables_partition_every_known_fortran_key +pamica/tests/test_fortran_params.py::test_table_sizes_match_the_documented_counts +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_table_sizes_match_the_documented_counts +pamica/tests/test_fortran_params.py::test_missing_source_disables_unrecognized_filtering +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_missing_source_disables_unrecognized_filtering +pamica/tests/test_fortran_params.py::test_repeated_key_last_line_wins +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_repeated_key_last_line_wins +pamica/tests/test_fortran_params.py::test_comments_and_blank_lines_are_skipped +[gw1] [ 39%] PASSED pamica/tests/test_fortran_params.py::test_comments_and_blank_lines_are_skipped +pamica/tests/test_fortran_params.py::test_out_of_range_flag_matches_fortran_semantics +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::test_out_of_range_flag_matches_fortran_semantics +pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_inline_comment_is_stripped_from_scalar_value +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_inline_comment_is_stripped_from_scalar_value +pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_inline_comment_is_stripped_from_list_value +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_inline_comment_is_stripped_from_list_value +pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_hash_without_leading_space_is_not_treated_as_a_comment +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_hash_without_leading_space_is_not_treated_as_a_comment +pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_fortran_double_precision_exponent_uppercase +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_fortran_double_precision_exponent_uppercase +pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_fortran_double_precision_exponent_lowercase +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestInlineCommentsAndExponents::test_fortran_double_precision_exponent_lowercase +pamica/tests/test_fortran_params.py::TestMalformedLines::test_key_with_no_value_raises +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestMalformedLines::test_key_with_no_value_raises +pamica/tests/test_fortran_params.py::TestMalformedLines::test_unparsable_int_value_raises +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestMalformedLines::test_unparsable_int_value_raises +pamica/tests/test_fortran_params.py::TestMalformedLines::test_unparsable_float_value_raises +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestMalformedLines::test_unparsable_float_value_raises +pamica/tests/test_fortran_params.py::TestMalformedLines::test_value_that_is_only_an_inline_comment_raises +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestMalformedLines::test_value_that_is_only_an_inline_comment_raises +pamica/tests/test_fortran_params.py::TestZeroRecognizedKeysGuard::test_all_unrecognized_content_raises +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestZeroRecognizedKeysGuard::test_all_unrecognized_content_raises +pamica/tests/test_fortran_params.py::TestZeroRecognizedKeysGuard::test_all_unsupported_content_does_not_raise +[gw1] [ 40%] PASSED pamica/tests/test_fortran_params.py::TestZeroRecognizedKeysGuard::test_all_unsupported_content_does_not_raise +pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_alternate_spelling_names_the_correct_key[n_mix-num_mix] +[gw1] [ 40%] PASSED pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_alternate_spelling_names_the_correct_key[n_mix-num_mix] +pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_n_models_and_n_mix_are_not_torch_only +[gw1] [ 40%] PASSED pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_n_models_and_n_mix_are_not_torch_only +pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_n_channels_gets_its_own_message +[gw1] [ 40%] PASSED pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_n_channels_gets_its_own_message +pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_n_channels_is_not_torch_only_or_alternate_spelling +[gw1] [ 40%] PASSED pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_n_channels_is_not_torch_only_or_alternate_spelling +pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs0-must_contain0] +[gw1] [ 40%] PASSED pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs0-must_contain0] +pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs1-must_contain1] +[gw1] [ 40%] PASSED pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs1-must_contain1] +pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs2-must_contain2] +[gw1] [ 40%] PASSED pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs2-must_contain2] +pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs3-must_contain3] +[gw5] [ 40%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_degenerate_fit_refused_on_dominance_methods +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs3-must_contain3] +pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs4-must_contain4] +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs4-must_contain4] +pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs5-must_contain5] +pamica/tests/mne_tests/test_mne_wrapper.py::test_get_pdftype_and_rho_per_model +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs5-must_contain5] +pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs6-must_contain6] +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_every_offending_key_is_named[kwargs6-must_contain6] +[gw5] [ 41%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_get_pdftype_and_rho_per_model +pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_single_category_messages_are_unchanged_by_the_refactor +pamica/tests/mne_tests/test_mne_wrapper.py::test_shared_components_empty_by_default +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestAllCategoriesNamedTogether::test_single_category_messages_are_unchanged_by_the_refactor +pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_canonical_spelling_takes_effect[min_nd-min_grad_norm-5e-06] +[gw5] [ 41%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_shared_components_empty_by_default +pamica/tests/mne_tests/test_mne_wrapper.py::test_metadata_respects_model_idx_bounds +[gw5] [ 41%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_metadata_respects_model_idx_bounds +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_canonical_spelling_takes_effect[min_nd-min_grad_norm-5e-06] +pamica/tests/mne_tests/test_mne_wrapper.py::test_metadata_requires_fit +pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_canonical_spelling_takes_effect[maxdecs-max_decs-7] +[gw5] [ 41%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_metadata_requires_fit +pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_matches_amica_per_model +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_canonical_spelling_takes_effect[maxdecs-max_decs-7] +pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_canonical_spelling_takes_effect[share_iter-share_int-42] +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_canonical_spelling_takes_effect[share_iter-share_int-42] +pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_both_spellings_at_once_raises[min_nd-min_grad_norm] +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_both_spellings_at_once_raises[min_nd-min_grad_norm] +pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_both_spellings_at_once_raises[maxdecs-max_decs] +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_both_spellings_at_once_raises[maxdecs-max_decs] +pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_both_spellings_at_once_raises[share_iter-share_int] +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_both_spellings_at_once_raises[share_iter-share_int] +pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_canonical_to_numpy_key_matches_alias_set +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestCanonicalAliasKwargs::test_canonical_to_numpy_key_matches_alias_set +pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_files_kwarg_loads_real_data_and_fits +[gw5] [ 41%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_matches_amica_per_model +pamica/tests/mne_tests/test_mne_wrapper.py::test_pmi_matches_amica_per_model +[gw1] [ 41%] PASSED pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_files_kwarg_loads_real_data_and_fits +pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_files_kwarg_matches_params_file_bit_for_bit +[gw6] [ 41%] PASSED pamica/tests/test_numpy_grad_norm.py::test_grad_norm_tracks_convergence +pamica/tests/test_numpy_grad_norm.py::test_grad_norm_uses_the_pre_step_mixing_matrix +[gw4] [ 41%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_min_dll_stops_at_the_same_iteration_as_torch +pamica/tests/test_mlx_convergence_stops.py::test_min_dll_never_fires_before_two_likelihoods +[gw4] [ 41%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_min_dll_never_fires_before_two_likelihoods +pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_stops_at_the_same_iteration_as_torch +[gw6] [ 42%] PASSED pamica/tests/test_numpy_grad_norm.py::test_grad_norm_uses_the_pre_step_mixing_matrix +pamica/tests/test_numpy_grad_norm.py::test_nd_uses_pre_update_model_weights +[gw7] [ 42%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[numpy-m2-restarts] +pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-restarts] +[gw6] [ 42%] PASSED pamica/tests/test_numpy_grad_norm.py::test_nd_uses_pre_update_model_weights +pamica/tests/test_numpy_grad_norm.py::test_nd_ignores_the_post_update_model_weights +[gw7] [ 42%] PASSED pamica/tests/test_component_rows.py::test_unshared_fits_are_byte_identical_to_the_column_layout[mlx-m2-restarts] +pamica/tests/test_component_rows.py::test_sources_grouped_by_a_merge_share_one_component_map[torch] +[gw6] [ 42%] PASSED pamica/tests/test_numpy_grad_norm.py::test_nd_ignores_the_post_update_model_weights +pamica/tests/test_numpy_grad_norm.py::test_shared_column_keeps_grad_norm_finite +[gw6] [ 42%] PASSED pamica/tests/test_numpy_grad_norm.py::test_shared_column_keeps_grad_norm_finite +pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_every_consumed_key_is_read_and_vice_versa +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_every_consumed_key_is_read_and_vice_versa +pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_no_bracket_or_non_literal_reads_are_hiding_from_the_scan +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_no_bracket_or_non_literal_reads_are_hiding_from_the_scan +pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_accepted_kwargs_is_the_union_of_its_declared_sources +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_accepted_kwargs_is_the_union_of_its_declared_sources +pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_torch_only_options_derived_from_torch_signature +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_torch_only_options_derived_from_torch_signature +pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_numpy_impl_core_has_no_module_level_torch_import +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_numpy_impl_core_has_no_module_level_torch_import +pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_every_torch_only_option_has_a_reason_and_no_numpy_equivalent +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestKeySetMatchesReadSites::test_every_torch_only_option_has_a_reason_and_no_numpy_equivalent +pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_typo_raises_type_error_with_suggestion +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_typo_raises_type_error_with_suggestion +pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_typo_of_a_named_constructor_parameter_is_suggested[verbos-verbose] +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_typo_of_a_named_constructor_parameter_is_suggested[verbos-verbose] +pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_typo_of_a_named_constructor_parameter_is_suggested[param_file-params_file] +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_typo_of_a_named_constructor_parameter_is_suggested[param_file-params_file] +pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_typo_of_a_named_constructor_parameter_is_suggested[use_tqdmm-use_tqdm] +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_typo_of_a_named_constructor_parameter_is_suggested[use_tqdmm-use_tqdm] +pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_unknown_keyword_with_no_close_match_still_raises +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_unknown_keyword_with_no_close_match_still_raises +pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_multiple_unknown_keywords_all_named +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestTypoRaises::test_multiple_unknown_keywords_all_named +pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[device] +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[device] +pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[dtype] +[gw6] [ 42%] PASSED pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[dtype] +pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[keep_best] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[keep_best] +pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[kurt_int] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[kurt_int] +pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[kurt_start] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[kurt_start] +pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[num_kurt] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_torch_only_option_raises_specific_message[num_kurt] +pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_keep_best_specifically +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_keep_best_specifically +pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_device_and_dtype_specifically +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestUnsupportedCrossBackendOption::test_device_and_dtype_specifically +pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_alternate_spelling_names_the_correct_key[n_models-num_models] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestAlternateSpellingAndNChannels::test_alternate_spelling_names_the_correct_key[n_models-num_models] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[minrho] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[minrho] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[n_restarts] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[n_restarts] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[newt_ramp] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[newt_ramp] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[newt_start] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[newt_start] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[newtrate] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[newtrate] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[num_comps] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[num_comps] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[num_mix] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[num_mix] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[num_models] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[num_models] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[pcadb] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[pcadb] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[pcakeep] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[pcakeep] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[pdftype] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[pdftype] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rejint] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rejint] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rejsig] +[gw6] [ 43%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rejsig] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rejstart] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rejstart] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[restart_seeds] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[restart_seeds] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[restartiter] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[restartiter] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rho0] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rho0] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rholrate] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rholrate] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rholratefact] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[rholratefact] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[scalestep] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[scalestep] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[seed] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[seed] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[share_comps] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[share_comps] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[share_int] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[share_int] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[share_iter] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[share_iter] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[share_start] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[share_start] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[use_grad_norm] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[use_grad_norm] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[use_min_dll] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[use_min_dll] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[writestep] +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[writestep] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_outdir_constructs_and_takes_effect +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_outdir_constructs_and_takes_effect +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_all_options_together_construct +[gw6] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_all_options_together_construct +pamica/tests/test_numpy_newton_multimodel.py::test_multimodel_newton_fit_finalizes_curvature[1] +[gw1] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_files_kwarg_matches_params_file_bit_for_bit +pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_conflicting_value_with_params_file_raises[files-kwarg_value0] +[gw1] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_conflicting_value_with_params_file_raises[files-kwarg_value0] +pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_conflicting_value_with_params_file_raises[data_dim-33] +[gw1] [ 44%] PASSED pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_conflicting_value_with_params_file_raises[data_dim-33] +pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_conflicting_value_with_params_file_raises[field_dim-kwarg_value2] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_conflicting_value_with_params_file_raises[field_dim-kwarg_value2] +pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_same_value_from_both_sources_is_not_a_conflict +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_same_value_from_both_sources_is_not_a_conflict +pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_no_files_error_message_mentions_keyword_argument +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_no_files_error_message_mentions_keyword_argument +pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_no_data_dim_error_message_mentions_keyword_argument +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestDataLocationKwargs::test_no_data_dim_error_message_mentions_keyword_argument +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_values_cover_every_consumed_key +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_values_cover_every_consumed_key +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[blk_max] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[blk_max] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[blk_min] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[blk_min] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[blk_step] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[blk_step] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[block_size] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[block_size] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[comp_thresh] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[comp_thresh] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_approx_sphere] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_approx_sphere] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_history] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_history] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_mean] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_mean] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_newton] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_newton] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_opt_block] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_opt_block] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_reject] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_reject] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_sphere] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[do_sphere] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[doscaling] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[doscaling] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[histstep] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[histstep] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[invsigmax] +[gw1] [ 45%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[invsigmax] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[invsigmin] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[invsigmin] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[lrate] +[gw4] [ 46%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_stops_at_the_same_iteration_as_torch +pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_never_fires_before_two_likelihoods +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[lrate] +[gw6] [ 46%] PASSED pamica/tests/test_numpy_newton_multimodel.py::test_multimodel_newton_fit_finalizes_curvature[1] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[lratefact] +pamica/tests/test_numpy_newton_multimodel.py::test_multimodel_newton_fit_finalizes_curvature[2] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[lratefact] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[max_decs] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[max_decs] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[max_iter] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[max_iter] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxdecs] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxdecs] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxincs] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxincs] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxrej] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxrej] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxrestarts] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxrestarts] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxrho] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[maxrho] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[min_dll] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[min_dll] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[min_grad_norm] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[min_grad_norm] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[min_nd] +[gw4] [ 46%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_never_fires_before_two_likelihoods +pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_is_the_norm_of_the_step_actually_taken +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[min_nd] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[mineig] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[mineig] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[mineig_rel] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[mineig_rel] +pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[minlrate] +[gw1] [ 46%] PASSED pamica/tests/test_numpy_kwargs.py::TestEveryDocumentedOptionConstructs::test_option_constructs_and_takes_effect[minlrate] +pamica/tests/test_numpy_restarts.py::test_records_are_aligned_with_the_independent_fits +[gw4] [ 46%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_is_the_norm_of_the_step_actually_taken +pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_floor_fires_on_a_likelihood_decrease +[gw7] [ 47%] PASSED pamica/tests/test_component_rows.py::test_sources_grouped_by_a_merge_share_one_component_map[torch] +pamica/tests/test_component_rows.py::test_sources_grouped_by_a_merge_share_one_component_map[numpy] +[gw4] [ 47%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_floor_fires_on_a_likelihood_decrease +pamica/tests/test_mlx_convergence_stops.py::test_lrate_floor_still_fires_when_grad_norm_cannot +[gw4] [ 47%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_lrate_floor_still_fires_when_grad_norm_cannot +pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_shadows_grad_norm_floor_under_shipped_defaults +[gw4] [ 47%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_grad_norm_shadows_grad_norm_floor_under_shipped_defaults +pamica/tests/test_mlx_convergence_stops.py::test_shipped_defaults_are_inert_on_a_100_iteration_fit +[gw6] [ 47%] PASSED pamica/tests/test_numpy_newton_multimodel.py::test_multimodel_newton_fit_finalizes_curvature[2] +pamica/tests/test_numpy_newton_multimodel.py::test_multimodel_newton_fit_finalizes_curvature[3] +[gw6] [ 47%] PASSED pamica/tests/test_numpy_newton_multimodel.py::test_multimodel_newton_fit_finalizes_curvature[3] +pamica/tests/test_numpy_newton_multimodel.py::test_rank_reduced_newton_fit_completes +[gw5] [ 47%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_pmi_matches_amica_per_model +pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_pmi_on_epochs +[gw1] [ 47%] PASSED pamica/tests/test_numpy_restarts.py::test_records_are_aligned_with_the_independent_fits +pamica/tests/test_numpy_restarts.py::test_derived_seeds_run_the_documented_sequence +[gw1] [ 47%] PASSED pamica/tests/test_numpy_restarts.py::test_derived_seeds_run_the_documented_sequence +pamica/tests/test_numpy_restarts.py::test_a_refit_repeats_the_same_search +[gw7] [ 47%] PASSED pamica/tests/test_component_rows.py::test_sources_grouped_by_a_merge_share_one_component_map[numpy] +pamica/tests/test_component_rows.py::test_sources_grouped_by_a_merge_share_one_component_map[mlx] +[gw7] [ 47%] PASSED pamica/tests/test_component_rows.py::test_sources_grouped_by_a_merge_share_one_component_map[mlx] +pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[torch-default] +[gw6] [ 47%] PASSED pamica/tests/test_numpy_newton_multimodel.py::test_rank_reduced_newton_fit_completes +pamica/tests/test_numpy_outdir.py::test_default_writes_nothing +[gw6] [ 47%] PASSED pamica/tests/test_numpy_outdir.py::test_default_writes_nothing +pamica/tests/test_numpy_outdir.py::test_explicit_outdir_writes_as_before +[gw6] [ 47%] PASSED pamica/tests/test_numpy_outdir.py::test_explicit_outdir_writes_as_before +pamica/tests/test_numpy_outdir.py::test_params_file_outdir_is_explicit +[gw6] [ 47%] PASSED pamica/tests/test_numpy_outdir.py::test_params_file_outdir_is_explicit +pamica/tests/test_numpy_params_file.py::TestNumpyFromBothParamsFormats::test_shared_hyperparameters_agree +[gw6] [ 47%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyFromBothParamsFormats::test_shared_hyperparameters_agree +pamica/tests/test_numpy_params_file.py::TestNumpyFromBothParamsFormats::test_fortran_text_fit_runs_with_no_explicit_data +[gw1] [ 47%] PASSED pamica/tests/test_numpy_restarts.py::test_a_refit_repeats_the_same_search +pamica/tests/test_numpy_restarts.py::test_a_restart_does_not_inherit_the_previous_restart_schedule +[gw5] [ 47%] PASSED pamica/tests/mne_tests/test_mne_wrapper.py::test_mir_pmi_on_epochs +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[torch-min_dll] +[gw4] [ 47%] PASSED pamica/tests/test_mlx_convergence_stops.py::test_shipped_defaults_are_inert_on_a_100_iteration_fit +pamica/tests/test_mlx_keepbest_cross_backend.py::test_torch_keep_best_satisfies_the_max_contract +[gw1] [ 47%] PASSED pamica/tests/test_numpy_restarts.py::test_a_restart_does_not_inherit_the_previous_restart_schedule +pamica/tests/test_numpy_restarts.py::test_a_degenerate_restart_is_recorded_but_never_selected +[gw6] [ 47%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyFromBothParamsFormats::test_fortran_text_fit_runs_with_no_explicit_data +pamica/tests/test_numpy_params_file.py::TestNumpyKwargsOverrideFile::test_explicit_kwargs_win_over_file_defaults +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyKwargsOverrideFile::test_explicit_kwargs_win_over_file_defaults +pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_non_gg_pdftype_raises[1] +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_non_gg_pdftype_raises[1] +pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_non_gg_pdftype_raises[2] +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_non_gg_pdftype_raises[2] +pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_non_gg_pdftype_raises[3] +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_non_gg_pdftype_raises[3] +pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_non_gg_pdftype_raises[4] +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_non_gg_pdftype_raises[4] +pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_gg_pdftype_constructs +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_gg_pdftype_constructs +pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_default_pdftype_is_gg +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyPdftypeGuard::test_default_pdftype_is_gg +pamica/tests/test_numpy_params_file.py::TestNumpyUnconsumedKeyWarning::test_input_param_unconsumed_keys_are_named +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyUnconsumedKeyWarning::test_input_param_unconsumed_keys_are_named +pamica/tests/test_numpy_params_file.py::TestNumpyUnconsumedKeyWarning::test_sample_params_json_has_no_unconsumed_keys +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyUnconsumedKeyWarning::test_sample_params_json_has_no_unconsumed_keys +pamica/tests/test_numpy_params_file.py::TestNumpyUnconsumedKeyWarning::test_bundled_default_has_no_unconsumed_keys +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyUnconsumedKeyWarning::test_bundled_default_has_no_unconsumed_keys +pamica/tests/test_numpy_params_file.py::TestNumpyUnconsumedKeyWarning::test_checkpoint_keys_reach_numpy_attributes +[gw6] [ 48%] PASSED pamica/tests/test_numpy_params_file.py::TestNumpyUnconsumedKeyWarning::test_checkpoint_keys_reach_numpy_attributes +pamica/tests/test_numpy_reject.py::test_reject_param_validation +[gw6] [ 48%] PASSED pamica/tests/test_numpy_reject.py::test_reject_param_validation +pamica/tests/test_numpy_reject.py::test_do_reject_false_leaves_good_idx_unset +[gw1] [ 48%] PASSED pamica/tests/test_numpy_restarts.py::test_a_degenerate_restart_is_recorded_but_never_selected +pamica/tests/test_numpy_restarts.py::test_all_degenerate_restarts_keep_the_degenerate_contract +[gw6] [ 48%] PASSED pamica/tests/test_numpy_reject.py::test_do_reject_false_leaves_good_idx_unset +pamica/tests/test_numpy_reject.py::test_rejection_shrinks_good_sample_set +[gw1] [ 48%] PASSED pamica/tests/test_numpy_restarts.py::test_all_degenerate_restarts_keep_the_degenerate_contract +pamica/tests/test_numpy_restarts.py::test_a_crashing_restart_does_not_kill_the_search +[gw5] [ 48%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[torch-min_dll] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[torch-grad_norm] +[gw6] [ 48%] PASSED pamica/tests/test_numpy_reject.py::test_rejection_shrinks_good_sample_set +pamica/tests/test_numpy_reject.py::test_rejection_does_not_spuriously_stop_fit +[gw1] [ 48%] PASSED pamica/tests/test_numpy_restarts.py::test_a_crashing_restart_does_not_kill_the_search +pamica/tests/test_numpy_restarts.py::test_a_single_restart_still_raises +[gw1] [ 48%] PASSED pamica/tests/test_numpy_restarts.py::test_a_single_restart_still_raises +pamica/tests/test_numpy_restarts.py::test_all_restarts_crashing_keeps_the_degenerate_contract +[gw1] [ 48%] PASSED pamica/tests/test_numpy_restarts.py::test_all_restarts_crashing_keeps_the_degenerate_contract +pamica/tests/test_numpy_restarts.py::test_the_written_output_is_the_winners_not_the_last_restarts +[gw6] [ 49%] PASSED pamica/tests/test_numpy_reject.py::test_rejection_does_not_spuriously_stop_fit +pamica/tests/test_numpy_reject.py::test_multimodel_rejection_keeps_gm_and_c_finite +[gw5] [ 49%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[torch-grad_norm] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[torch-grad_norm_floor] +[gw1] [ 49%] PASSED pamica/tests/test_numpy_restarts.py::test_the_written_output_is_the_winners_not_the_last_restarts +pamica/tests/test_numpy_restarts.py::test_the_winners_tuned_block_size_is_restored +[gw6] [ 49%] PASSED pamica/tests/test_numpy_reject.py::test_multimodel_rejection_keeps_gm_and_c_finite +pamica/tests/test_numpy_reject.py::test_rejection_nonfinite_ll_raises_instability_error +[gw6] [ 49%] PASSED pamica/tests/test_numpy_reject.py::test_rejection_nonfinite_ll_raises_instability_error +pamica/tests/test_numpy_restarts.py::test_single_restart_is_bit_identical_to_a_direct_fit +[gw5] [ 49%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[torch-grad_norm_floor] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[torch-lrate_floor] +[gw4] [ 49%] PASSED pamica/tests/test_mlx_keepbest_cross_backend.py::test_torch_keep_best_satisfies_the_max_contract +pamica/tests/test_mlx_keepbest_cross_backend.py::test_mlx_keep_best_satisfies_the_max_contract +[gw4] [ 49%] PASSED pamica/tests/test_mlx_keepbest_cross_backend.py::test_mlx_keep_best_satisfies_the_max_contract +pamica/tests/test_mlx_keepbest_cross_backend.py::test_both_backends_disable_the_safeguard_under_share_comps +[gw5] [ 49%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[torch-lrate_floor] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[numpy-min_dll] +[gw6] [ 49%] PASSED pamica/tests/test_numpy_restarts.py::test_single_restart_is_bit_identical_to_a_direct_fit +pamica/tests/test_numpy_restarts.py::test_single_restart_records_the_one_fit_it_ran +[gw1] [ 49%] PASSED pamica/tests/test_numpy_restarts.py::test_the_winners_tuned_block_size_is_restored +pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs0-share_start] +[gw1] [ 49%] PASSED pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs0-share_start] +pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs1-share_int] +[gw1] [ 49%] PASSED pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs1-share_int] +pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs2-share_int] +[gw1] [ 49%] PASSED pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs2-share_int] +pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs3-comp_thresh] +[gw1] [ 49%] PASSED pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs3-comp_thresh] +pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs4-comp_thresh] +[gw1] [ 49%] PASSED pamica/tests/test_numpy_share_comps.py::test_share_constructor_validation[kwargs4-comp_thresh] +pamica/tests/test_numpy_share_comps.py::test_comp_used_survives_a_second_identify_call +[gw6] [ 49%] PASSED pamica/tests/test_numpy_restarts.py::test_single_restart_records_the_one_fit_it_ran +pamica/tests/test_numpy_restarts.py::test_an_explicit_single_seed_overrides_the_constructor_seed +[gw1] [ 49%] PASSED pamica/tests/test_numpy_share_comps.py::test_comp_used_survives_a_second_identify_call +pamica/tests/test_numpy_share_comps.py::test_comp_used_matches_the_columns_comp_list_references +[gw6] [ 49%] PASSED pamica/tests/test_numpy_restarts.py::test_an_explicit_single_seed_overrides_the_constructor_seed +pamica/tests/test_numpy_restarts.py::test_best_of_n_returns_the_argmax_of_the_independent_fits +[gw1] [ 49%] PASSED pamica/tests/test_numpy_share_comps.py::test_comp_used_matches_the_columns_comp_list_references +pamica/tests/test_numpy_share_comps.py::test_sharing_leaves_finite_mixture_parameters +[gw6] [ 50%] PASSED pamica/tests/test_numpy_restarts.py::test_best_of_n_returns_the_argmax_of_the_independent_fits +pamica/tests/test_numpy_share_comps.py::test_a_frozen_window_matches_the_torch_schedule[False-2] +[gw6] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_a_frozen_window_matches_the_torch_schedule[False-2] +pamica/tests/test_numpy_share_comps.py::test_a_frozen_window_matches_the_torch_schedule[False-1] +[gw6] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_a_frozen_window_matches_the_torch_schedule[False-1] +pamica/tests/test_numpy_share_comps.py::test_a_frozen_applies_to_a_single_model_without_sharing +[gw6] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_a_frozen_applies_to_a_single_model_without_sharing +pamica/tests/test_numpy_share_comps.py::test_freeze_holds_A_but_still_measures_the_gradient +[gw4] [ 50%] PASSED pamica/tests/test_mlx_keepbest_cross_backend.py::test_both_backends_disable_the_safeguard_under_share_comps +pamica/tests/test_mlx_newton_cross_backend.py::test_newton_curvature_matches_float64_twin[1] +[gw1] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_sharing_leaves_finite_mixture_parameters +pamica/tests/test_numpy_share_comps.py::test_unused_columns_keep_their_last_finite_value +[gw6] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_freeze_holds_A_but_still_measures_the_gradient +pamica/tests/test_numpy_share_comps.py::test_shared_column_update_matches_the_torch_backend +[gw4] [ 50%] PASSED pamica/tests/test_mlx_newton_cross_backend.py::test_newton_curvature_matches_float64_twin[1] +pamica/tests/test_mlx_newton_cross_backend.py::test_newton_curvature_matches_float64_twin[55] +[gw5] [ 50%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[numpy-min_dll] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[numpy-grad_norm] +[gw2] [ 50%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_full_fit_ll_matches_torch_float64[2-3] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_full_fit_ll_matches_torch_float64[3-3] +[gw3] [ 50%] PASSED pamica/tests/test_component_rows.py::test_the_metric_compares_the_sensor_maps[mlx] +pamica/tests/test_component_rows.py::test_the_exported_A_is_the_reference_layout[torch] +[gw1] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_unused_columns_keep_their_last_finite_value +pamica/tests/test_numpy_share_comps.py::test_default_comp_list_is_unaffected +[gw4] [ 50%] PASSED pamica/tests/test_mlx_newton_cross_backend.py::test_newton_curvature_matches_float64_twin[55] +pamica/tests/test_mlx_newton_cross_backend.py::test_warmed_newton_mstep_matches_float64_twin +[gw6] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_shared_column_update_matches_the_torch_backend +pamica/tests/test_numpy_share_comps.py::test_forced_merge_fit_is_finite_in_both_backends +[gw3] [ 50%] PASSED pamica/tests/test_component_rows.py::test_the_exported_A_is_the_reference_layout[torch] +pamica/tests/test_component_rows.py::test_the_exported_A_is_the_reference_layout[numpy] +[gw1] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_default_comp_list_is_unaffected +pamica/tests/test_numpy_share_comps.py::test_non_finite_parameters_are_reported_as_failure +[gw4] [ 50%] PASSED pamica/tests/test_mlx_newton_cross_backend.py::test_warmed_newton_mstep_matches_float64_twin +pamica/tests/test_mlx_newton_cross_backend.py::test_early_block_newton_falls_back_like_the_float64_twin +[gw4] [ 50%] PASSED pamica/tests/test_mlx_newton_cross_backend.py::test_early_block_newton_falls_back_like_the_float64_twin +pamica/tests/test_mlx_newton_cross_backend.py::test_multimodel_newton_mstep_matches_float64_twin[False] +[gw1] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_non_finite_parameters_are_reported_as_failure +pamica/tests/test_numpy_share_comps.py::test_checkpoints_never_persist_non_finite_parameters +[gw1] [ 50%] PASSED pamica/tests/test_numpy_share_comps.py::test_checkpoints_never_persist_non_finite_parameters +pamica/tests/test_numpy_share_comps.py::test_shared_column_takes_one_gm_weighted_step +[gw4] [ 51%] PASSED pamica/tests/test_mlx_newton_cross_backend.py::test_multimodel_newton_mstep_matches_float64_twin[False] +pamica/tests/test_mlx_newton_cross_backend.py::test_multimodel_newton_mstep_matches_float64_twin[True] +[gw4] [ 51%] PASSED pamica/tests/test_mlx_newton_cross_backend.py::test_multimodel_newton_mstep_matches_float64_twin[True] +pamica/tests/test_mlx_newton_cross_backend.py::test_three_model_newton_curvature_matches_float64_twin +[gw5] [ 51%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[numpy-grad_norm] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[numpy-grad_norm_floor] +[gw1] [ 51%] PASSED pamica/tests/test_numpy_share_comps.py::test_shared_column_takes_one_gm_weighted_step +pamica/tests/test_numpy_share_comps.py::test_merged_away_column_does_not_move +[gw3] [ 51%] PASSED pamica/tests/test_component_rows.py::test_the_exported_A_is_the_reference_layout[numpy] +pamica/tests/test_component_rows.py::test_the_exported_A_is_the_reference_layout[mlx] +[gw4] [ 51%] PASSED pamica/tests/test_mlx_newton_cross_backend.py::test_three_model_newton_curvature_matches_float64_twin +pamica/tests/test_mlx_newton_cross_backend.py::test_newton_fit_ll_matches_float64_torch +[gw3] [ 51%] PASSED pamica/tests/test_component_rows.py::test_the_exported_A_is_the_reference_layout[mlx] +pamica/tests/test_component_rows.py::test_single_model_export_is_byte_identical_to_the_pre_change_code[torch] +[gw5] [ 51%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[numpy-grad_norm_floor] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[numpy-lrate_floor] +[gw1] [ 51%] PASSED pamica/tests/test_numpy_share_comps.py::test_merged_away_column_does_not_move +pamica/tests/test_numpy_share_comps.py::test_a_frozen_window_matches_the_torch_schedule[True-2] +[gw1] [ 51%] PASSED pamica/tests/test_numpy_share_comps.py::test_a_frozen_window_matches_the_torch_schedule[True-2] +pamica/tests/test_pamica.py::test_pdf_general_branch_is_continuous_with_the_special_cases +[gw1] [ 51%] PASSED pamica/tests/test_pamica.py::test_pdf_general_branch_is_continuous_with_the_special_cases +pamica/tests/test_pamica.py::test_data_loading +[gw1] [ 51%] PASSED pamica/tests/test_pamica.py::test_data_loading +pamica/tests/test_pamica.py::test_error_handling +[gw1] [ 51%] PASSED pamica/tests/test_pamica.py::test_error_handling +pamica/tests/test_pca_reduction_cross_backend.py::test_torch_and_numpy_agree_on_the_reduced_sphere[pcakeep] +[gw3] [ 51%] PASSED pamica/tests/test_component_rows.py::test_single_model_export_is_byte_identical_to_the_pre_change_code[torch] +pamica/tests/test_component_rows.py::test_single_model_export_is_byte_identical_to_the_pre_change_code[numpy] +[gw5] [ 51%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[numpy-lrate_floor] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[mlx-min_dll] +[gw1] [ 51%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_torch_and_numpy_agree_on_the_reduced_sphere[pcakeep] +pamica/tests/test_pca_reduction_cross_backend.py::test_torch_and_numpy_agree_on_the_reduced_sphere[pcadb] +[gw6] [ 51%] PASSED pamica/tests/test_numpy_share_comps.py::test_forced_merge_fit_is_finite_in_both_backends +pamica/tests/test_numpy_share_comps.py::test_merge_on_the_final_iteration_completes +[gw3] [ 51%] PASSED pamica/tests/test_component_rows.py::test_single_model_export_is_byte_identical_to_the_pre_change_code[numpy] +pamica/tests/test_component_rows.py::test_single_model_export_is_byte_identical_to_the_pre_change_code[mlx] +[gw3] [ 51%] PASSED pamica/tests/test_component_rows.py::test_single_model_export_is_byte_identical_to_the_pre_change_code[mlx] +pamica/tests/test_component_rows.py::test_load_results_refuses_a_pre_change_multi_model_A +[gw1] [ 51%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_torch_and_numpy_agree_on_the_reduced_sphere[pcadb] +pamica/tests/test_pca_reduction_cross_backend.py::test_mlx_agrees_with_torch_on_the_reduced_sphere[pcakeep] +[gw5] [ 52%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[mlx-min_dll] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[mlx-grad_norm] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mlx_agrees_with_torch_on_the_reduced_sphere[pcakeep] +pamica/tests/test_pca_reduction_cross_backend.py::test_mlx_agrees_with_torch_on_the_reduced_sphere[pcadb] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mlx_agrees_with_torch_on_the_reduced_sphere[pcadb] +pamica/tests/test_pca_reduction_cross_backend.py::test_pcakeep_and_pcadb_together_equal_pcakeep_alone[torch] +[gw5] [ 52%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[mlx-grad_norm] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[mlx-grad_norm_floor] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_pcakeep_and_pcadb_together_equal_pcakeep_alone[torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_pcakeep_and_pcadb_together_equal_pcakeep_alone[numpy] +[gw3] [ 52%] PASSED pamica/tests/test_component_rows.py::test_load_results_refuses_a_pre_change_multi_model_A +pamica/tests/test_component_rows.py::test_load_results_refuses_a_truncated_A[one-value-short] +[gw5] [ 52%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[mlx-grad_norm_floor] +pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[mlx-lrate_floor] +[gw5] [ 52%] PASSED pamica/tests/test_iteration_order.py::test_a_stopped_fit_returns_the_parameters_its_final_ll_describes[mlx-lrate_floor] +pamica/tests/test_iteration_order.py::test_a_keep_best_restore_returns_the_parameters_of_its_ll[torch] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_pcakeep_and_pcadb_together_equal_pcakeep_alone[numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_pcakeep_and_pcadb_together_equal_pcakeep_alone[mlx] +[gw3] [ 52%] PASSED pamica/tests/test_component_rows.py::test_load_results_refuses_a_truncated_A[one-value-short] +pamica/tests/test_component_rows.py::test_load_results_refuses_a_truncated_A[one-component-short] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_pcakeep_and_pcadb_together_equal_pcakeep_alone[mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_precedence_is_logged_once_per_model[torch] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_precedence_is_logged_once_per_model[torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_precedence_is_logged_once_per_model[numpy] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_precedence_is_logged_once_per_model[numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_precedence_is_logged_once_per_model[mlx] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_precedence_is_logged_once_per_model[mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_do_sphere_false_ignores_the_request_with_one_warning[torch] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_do_sphere_false_ignores_the_request_with_one_warning[torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_do_sphere_false_ignores_the_request_with_one_warning[numpy] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_do_sphere_false_ignores_the_request_with_one_warning[numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_do_sphere_false_ignores_the_request_with_one_warning[mlx] +[gw5] [ 52%] PASSED pamica/tests/test_iteration_order.py::test_a_keep_best_restore_returns_the_parameters_of_its_ll[torch] +pamica/tests/test_iteration_order.py::test_a_keep_best_restore_returns_the_parameters_of_its_ll[mlx] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_do_sphere_false_ignores_the_request_with_one_warning[mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs0-pcakeep-torch] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs0-pcakeep-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs0-pcakeep-numpy] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs0-pcakeep-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs0-pcakeep-mlx] +[gw1] [ 52%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs0-pcakeep-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs1-pcakeep-torch] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs1-pcakeep-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs1-pcakeep-numpy] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs1-pcakeep-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs1-pcakeep-mlx] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs1-pcakeep-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs2-pcakeep-torch] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs2-pcakeep-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs2-pcakeep-numpy] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs2-pcakeep-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs2-pcakeep-mlx] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs2-pcakeep-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs3-pcakeep-torch] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs3-pcakeep-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs3-pcakeep-numpy] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs3-pcakeep-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs3-pcakeep-mlx] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs3-pcakeep-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs2-mlx] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs2-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs3-torch] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs3-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs3-mlx] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs3-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs0-torch] +[gw6] [ 53%] PASSED pamica/tests/test_numpy_share_comps.py::test_merge_on_the_final_iteration_completes +pamica/tests/test_numpy_share_comps.py::test_numpy_merge_decision_matches_torch_backend +[gw5] [ 53%] PASSED pamica/tests/test_iteration_order.py::test_a_keep_best_restore_returns_the_parameters_of_its_ll[mlx] +pamica/tests/test_iteration_order.py::test_the_rho_rate_ceiling_survives_a_save[torch] +[gw1] [ 53%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs0-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs0-mlx] +[gw3] [ 53%] PASSED pamica/tests/test_component_rows.py::test_load_results_refuses_a_truncated_A[one-component-short] +pamica/tests/test_component_rows.py::test_updates_from_a_merged_state_match_the_seeded_reference[scale] +[gw3] [ 53%] SKIPPED pamica/tests/test_component_rows.py::test_updates_from_a_merged_state_match_the_seeded_reference[scale] +pamica/tests/test_component_rows.py::test_updates_from_a_merged_state_match_the_seeded_reference[noscale] +[gw3] [ 53%] SKIPPED pamica/tests/test_component_rows.py::test_updates_from_a_merged_state_match_the_seeded_reference[noscale] +pamica/tests/test_component_rows.py::test_the_reference_scan_never_merges +[gw3] [ 53%] SKIPPED pamica/tests/test_component_rows.py::test_the_reference_scan_never_merges +pamica/tests/test_component_rows.py::test_an_early_mass_merge_collapses_the_reference_too +[gw3] [ 53%] SKIPPED pamica/tests/test_component_rows.py::test_an_early_mass_merge_collapses_the_reference_too +pamica/tests/test_component_rows_persistence.py::test_torch_state_dict_round_trip[single] +[gw1] [ 54%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs0-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs1-torch] +[gw1] [ 54%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs1-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs1-mlx] +[gw1] [ 54%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs1-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs2-torch] +[gw1] [ 54%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs2-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs2-mlx] +[gw5] [ 54%] PASSED pamica/tests/test_iteration_order.py::test_the_rho_rate_ceiling_survives_a_save[torch] +pamica/tests/test_iteration_order.py::test_the_rho_rate_ceiling_survives_a_save[mlx] +[gw1] [ 54%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs2-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs3-torch] +[gw3] [ 54%] PASSED pamica/tests/test_component_rows_persistence.py::test_torch_state_dict_round_trip[single] +pamica/tests/test_component_rows_persistence.py::test_torch_state_dict_round_trip[unmerged] +[gw5] [ 54%] PASSED pamica/tests/test_iteration_order.py::test_the_rho_rate_ceiling_survives_a_save[mlx] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-lrate] +[gw1] [ 54%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs3-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs3-mlx] +[gw6] [ 54%] PASSED pamica/tests/test_numpy_share_comps.py::test_numpy_merge_decision_matches_torch_backend +pamica/tests/test_numpy_share_comps.py::test_rank_reduced_numpy_sharing_completes +[gw5] [ 54%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-lrate] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-lrate_cap] +[gw1] [ 54%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs3-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs4-torch] +[gw5] [ 54%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-lrate_cap] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-newtrate] +[gw1] [ 54%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs4-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs4-mlx] +[gw5] [ 54%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-newtrate] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-rholrate] +[gw1] [ 54%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_accepts_a_request_that_reduces_nothing[kwargs4-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_torch_and_mlx_reduced_fits_find_the_same_components +[gw5] [ 54%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-rholrate] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-rholrate_cap] +[gw5] [ 54%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[torch-rholrate_cap] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-lrate] +[gw5] [ 54%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-lrate] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-lrate_cap] +[gw5] [ 54%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-lrate_cap] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-newtrate] +[gw5] [ 55%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-newtrate] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-rholrate] +[gw5] [ 55%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-rholrate] +pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-rholrate_cap] +[gw5] [ 55%] PASSED pamica/tests/test_iteration_order.py::test_a_save_with_a_nonfinite_rate_is_refused_by_name[mlx-rholrate_cap] +pamica/tests/test_iteration_order.py::test_a_save_without_its_rho_rate_is_refused_by_name[torch] +[gw3] [ 55%] PASSED pamica/tests/test_component_rows_persistence.py::test_torch_state_dict_round_trip[unmerged] +pamica/tests/test_component_rows_persistence.py::test_torch_state_dict_round_trip[merged] +[gw5] [ 55%] PASSED pamica/tests/test_iteration_order.py::test_a_save_without_its_rho_rate_is_refused_by_name[torch] +pamica/tests/test_iteration_order.py::test_a_save_without_its_rho_rate_is_refused_by_name[mlx] +[gw5] [ 55%] PASSED pamica/tests/test_iteration_order.py::test_a_save_without_its_rho_rate_is_refused_by_name[mlx] +pamica/tests/test_iteration_order_native_oracle.py::test_decrease_response_matches_the_reference[decreases] +[gw5] [ 55%] SKIPPED pamica/tests/test_iteration_order_native_oracle.py::test_decrease_response_matches_the_reference[decreases] +pamica/tests/test_iteration_order_native_oracle.py::test_decrease_response_matches_the_reference[ratchet] +[gw5] [ 55%] SKIPPED pamica/tests/test_iteration_order_native_oracle.py::test_decrease_response_matches_the_reference[ratchet] +pamica/tests/test_iteration_order_native_oracle.py::test_a_freeze_without_sharing_matches_the_reference[freeze] +[gw5] [ 55%] SKIPPED pamica/tests/test_iteration_order_native_oracle.py::test_a_freeze_without_sharing_matches_the_reference[freeze] +pamica/tests/test_iteration_order_native_oracle.py::test_a_freeze_without_sharing_matches_the_reference[freeze-noscaling] +[gw5] [ 55%] SKIPPED pamica/tests/test_iteration_order_native_oracle.py::test_a_freeze_without_sharing_matches_the_reference[freeze-noscaling] +pamica/tests/test_llt_stash.py::test_fortran_reference_llt_is_the_last_estep +[gw5] [ 55%] PASSED pamica/tests/test_llt_stash.py::test_fortran_reference_llt_is_the_last_estep +pamica/tests/test_llt_stash.py::test_written_llt_matches_the_fortran_write_convention[1] +[gw3] [ 55%] PASSED pamica/tests/test_component_rows_persistence.py::test_torch_state_dict_round_trip[merged] +pamica/tests/test_component_rows_persistence.py::test_mlx_save_round_trip[single] +[gw3] [ 55%] PASSED pamica/tests/test_component_rows_persistence.py::test_mlx_save_round_trip[single] +pamica/tests/test_component_rows_persistence.py::test_mlx_save_round_trip[unmerged] +[gw3] [ 55%] PASSED pamica/tests/test_component_rows_persistence.py::test_mlx_save_round_trip[unmerged] +pamica/tests/test_component_rows_persistence.py::test_mlx_save_round_trip[merged] +[gw1] [ 55%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_torch_and_mlx_reduced_fits_find_the_same_components +pamica/tests/test_pca_reduction_cross_backend.py::test_mlx_save_load_round_trips_the_reduction +[gw1] [ 55%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mlx_save_load_round_trips_the_reduction +pamica/tests/test_pca_reduction_cross_backend.py::test_mlx_payload_without_the_keys_loads_with_defaults +[gw3] [ 55%] PASSED pamica/tests/test_component_rows_persistence.py::test_mlx_save_round_trip[merged] +pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[torch-single] +[gw1] [ 55%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mlx_payload_without_the_keys_loads_with_defaults +pamica/tests/test_pca_reduction_cross_backend.py::test_torch_payload_without_the_keys_loads_with_defaults +[gw5] [ 55%] PASSED pamica/tests/test_llt_stash.py::test_written_llt_matches_the_fortran_write_convention[1] +pamica/tests/test_llt_stash.py::test_written_llt_matches_the_fortran_write_convention[2] +[gw3] [ 55%] PASSED pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[torch-single] +pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[torch-unmerged] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_share_comps.py::test_rank_reduced_numpy_sharing_completes +pamica/tests/test_numpy_share_comps.py::test_zero_norm_column_is_not_merged_and_raises_no_warning +[gw1] [ 56%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_torch_payload_without_the_keys_loads_with_defaults +pamica/tests/test_pca_reduction_cross_backend.py::test_torch_save_load_round_trips_numpy_scalar_request +[gw6] [ 56%] PASSED pamica/tests/test_numpy_share_comps.py::test_zero_norm_column_is_not_merged_and_raises_no_warning +pamica/tests/test_numpy_share_comps.py::test_non_finite_sphere_fails_loudly +[gw3] [ 56%] PASSED pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[torch-unmerged] +pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[torch-merged] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_share_comps.py::test_non_finite_sphere_fails_loudly +pamica/tests/test_numpy_viz.py::test_maps_and_sources_match_the_accessors[full] +[gw1] [ 56%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_torch_save_load_round_trips_numpy_scalar_request +pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[pcakeep-torch] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_viz.py::test_maps_and_sources_match_the_accessors[full] +pamica/tests/test_numpy_viz.py::test_load_results_reads_a_reduced_sphere[full] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_viz.py::test_load_results_reads_a_reduced_sphere[full] +pamica/tests/test_numpy_viz.py::test_plot_components_draws_the_maps_and_the_sources[full] +[gw3] [ 56%] PASSED pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[torch-merged] +pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[mlx-single] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_viz.py::test_plot_components_draws_the_maps_and_the_sources[full] +pamica/tests/test_numpy_viz.py::test_plot_pdf_fits_histograms_the_sources[full] +[gw3] [ 56%] PASSED pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[mlx-single] +pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[mlx-unmerged] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_viz.py::test_plot_pdf_fits_histograms_the_sources[full] +pamica/tests/test_numpy_viz.py::test_plot_model_comparison_draws_the_reconstruction[full] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_viz.py::test_plot_model_comparison_draws_the_reconstruction[full] +pamica/tests/test_numpy_viz.py::test_maps_and_sources_match_the_accessors[reduced] +[gw1] [ 56%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[pcakeep-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[pcakeep-numpy] +[gw3] [ 56%] PASSED pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[mlx-unmerged] +pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[mlx-merged] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_viz.py::test_maps_and_sources_match_the_accessors[reduced] +pamica/tests/test_numpy_viz.py::test_load_results_reads_a_reduced_sphere[reduced] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_viz.py::test_load_results_reads_a_reduced_sphere[reduced] +pamica/tests/test_numpy_viz.py::test_plot_components_draws_the_maps_and_the_sources[reduced] +[gw3] [ 56%] PASSED pamica/tests/test_component_rows_persistence.py::test_wrapper_save_round_trip[mlx-merged] +pamica/tests/test_component_rows_persistence.py::test_old_torch_state_dict_converts_losslessly[single] +[gw6] [ 56%] PASSED pamica/tests/test_numpy_viz.py::test_plot_components_draws_the_maps_and_the_sources[reduced] +pamica/tests/test_numpy_viz.py::test_plot_pdf_fits_histograms_the_sources[reduced] +[gw3] [ 56%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_torch_state_dict_converts_losslessly[single] +pamica/tests/test_component_rows_persistence.py::test_old_torch_state_dict_converts_losslessly[unmerged] +[gw6] [ 57%] PASSED pamica/tests/test_numpy_viz.py::test_plot_pdf_fits_histograms_the_sources[reduced] +pamica/tests/test_numpy_viz.py::test_plot_model_comparison_draws_the_reconstruction[reduced] +[gw6] [ 57%] PASSED pamica/tests/test_numpy_viz.py::test_plot_model_comparison_draws_the_reconstruction[reduced] +pamica/tests/test_pamica.py::test_amica_initialization +[gw6] [ 57%] PASSED pamica/tests/test_pamica.py::test_amica_initialization +pamica/tests/test_pamica.py::test_data_preprocessing +[gw6] [ 57%] PASSED pamica/tests/test_pamica.py::test_data_preprocessing +pamica/tests/test_pamica.py::test_pdf_computation +[gw6] [ 57%] PASSED pamica/tests/test_pamica.py::test_pdf_computation +pamica/tests/test_pamica.py::test_pdf_is_a_normalized_density_for_general_rho +[gw6] [ 57%] PASSED pamica/tests/test_pamica.py::test_pdf_is_a_normalized_density_for_general_rho +pamica/tests/test_rank_policy.py::test_validator_accepts[None-pcadb6] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_accepts[None-pcadb6] +pamica/tests/test_rank_policy.py::test_validator_accepts[None-30.0] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_accepts[None-30.0] +pamica/tests/test_rank_policy.py::test_validator_accepts[32-30.0] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_accepts[32-30.0] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[True] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[True] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[False] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[False] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[pcakeep2] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[pcakeep2] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[pcakeep3] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[pcakeep3] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[0] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[0] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[-3] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[-3] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[2.7] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[2.7] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[20] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcakeep[20] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[0] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[0] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[-5] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[-5] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[nan] +[gw6] [ 57%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[nan] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[inf] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[inf] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[True] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[True] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[False] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[False] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[pcadb6] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[pcadb6] +pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[pcadb7] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_pcadb[pcadb7] +pamica/tests/test_rank_policy.py::test_validator_rejects_either_parameter_when_both_are_set +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_validator_rejects_either_parameter_when_both_are_set +pamica/tests/test_rank_policy.py::test_validator_never_logs +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_validator_never_logs +pamica/tests/test_rank_policy.py::test_ignored_request_logs_the_precedence_once +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_ignored_request_logs_the_precedence_once +pamica/tests/test_rank_policy.py::test_ignored_request_warns_once_without_sphering[20-None] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_ignored_request_warns_once_without_sphering[20-None] +pamica/tests/test_rank_policy.py::test_ignored_request_warns_once_without_sphering[None-30.0] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_ignored_request_warns_once_without_sphering[None-30.0] +pamica/tests/test_rank_policy.py::test_ignored_request_warns_once_without_sphering[20-30.0] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_ignored_request_warns_once_without_sphering[20-30.0] +pamica/tests/test_rank_policy.py::test_ignored_request_warns_once_without_sphering[pcakeep3-None] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_ignored_request_warns_once_without_sphering[pcakeep3-None] +pamica/tests/test_rank_policy.py::test_nothing_to_ignore_without_a_request +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_nothing_to_ignore_without_a_request +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[None-None-32-True-False] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[None-None-32-True-False] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[20-None-32-True-True] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[20-None-32-True-True] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[31-None-32-True-True] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[31-None-32-True-True] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[32-None-32-True-False] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[32-None-32-True-False] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[64-None-32-True-False] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[64-None-32-True-False] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[None-30.0-32-True-True] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[None-30.0-32-True-True] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[32-30.0-32-True-False] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[32-30.0-32-True-False] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[20-30.0-32-True-True] +[gw6] [ 58%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[20-30.0-32-True-True] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[20-None-32-False-False] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[20-None-32-False-False] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[None-30.0-32-False-False] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[None-30.0-32-False-False] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[20-30.0-32-False-False] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[20-30.0-32-False-False] +pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[None-None-32-False-False] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_truth_table[None-None-32-False-False] +pamica/tests/test_rank_policy.py::test_reduction_predicate_validates_first[-3-None-pcakeep] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_validates_first[-3-None-pcakeep] +pamica/tests/test_rank_policy.py::test_reduction_predicate_validates_first[20-None-pcakeep] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_validates_first[20-None-pcakeep] +pamica/tests/test_rank_policy.py::test_reduction_predicate_validates_first[None--5.0-pcadb] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_reduction_predicate_validates_first[None--5.0-pcadb] +pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[-3-None] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[-3-None] +pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[2.7-None] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[2.7-None] +pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[0-None] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[0-None] +pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[True-None] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[True-None] +pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[None-0.0] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[None-0.0] +pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[None--5.0] +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_numerical_rank_rejects_invalid_reduction[None--5.0] +pamica/tests/test_rank_policy.py::test_numerical_rank_pcakeep_wins_over_pcadb +[gw6] [ 59%] PASSED pamica/tests/test_rank_policy.py::test_numerical_rank_pcakeep_wins_over_pcadb +pamica/tests/test_rank_policy.py::test_all_backends_agree_on_the_rank +[gw1] [ 59%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[pcakeep-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[pcakeep-mlx] +[gw5] [ 59%] PASSED pamica/tests/test_llt_stash.py::test_written_llt_matches_the_fortran_write_convention[2] +pamica/tests/test_llt_stash.py::test_native_binary_llt_is_the_last_estep +[gw5] [ 59%] SKIPPED pamica/tests/test_llt_stash.py::test_native_binary_llt_is_the_last_estep +pamica/tests/test_llt_stash.py::test_torch_stashed_llt_is_the_estep_behind_final_ll +[gw1] [ 59%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[pcakeep-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[automatic-torch] +[gw3] [ 59%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_torch_state_dict_converts_losslessly[unmerged] +pamica/tests/test_component_rows_persistence.py::test_old_mlx_save_converts_losslessly[single] +[gw3] [ 59%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_mlx_save_converts_losslessly[single] +pamica/tests/test_component_rows_persistence.py::test_old_mlx_save_converts_losslessly[unmerged] +[gw3] [ 60%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_mlx_save_converts_losslessly[unmerged] +pamica/tests/test_component_rows_persistence.py::test_old_wrapper_save_converts_losslessly[torch-single] +[gw1] [ 60%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[automatic-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[automatic-numpy] +[gw3] [ 60%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_wrapper_save_converts_losslessly[torch-single] +pamica/tests/test_component_rows_persistence.py::test_old_wrapper_save_converts_losslessly[torch-unmerged] +[gw6] [ 60%] PASSED pamica/tests/test_rank_policy.py::test_all_backends_agree_on_the_rank +pamica/tests/test_reference_constants.py::test_log_normalizer_is_the_reference_literal_in_single_precision[LOG_SQRT_PI] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_log_normalizer_is_the_reference_literal_in_single_precision[LOG_SQRT_PI] +pamica/tests/test_reference_constants.py::test_log_normalizer_is_the_reference_literal_in_single_precision[LOG_SQRT_2PI] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_log_normalizer_is_the_reference_literal_in_single_precision[LOG_SQRT_2PI] +pamica/tests/test_reference_constants.py::test_log_normalizer_is_the_reference_literal_in_single_precision[LOG_NORM_COSH_SUB] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_log_normalizer_is_the_reference_literal_in_single_precision[LOG_NORM_COSH_SUB] +pamica/tests/test_reference_constants.py::test_log_normalizer_is_the_reference_literal_in_single_precision[LOG_NORM_COSH_SUP] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_log_normalizer_is_the_reference_literal_in_single_precision[LOG_NORM_COSH_SUP] +pamica/tests/test_reference_constants.py::test_epsdble_is_the_reference_literal_in_single_precision +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_epsdble_is_the_reference_literal_in_single_precision +pamica/tests/test_reference_constants.py::test_dyadic_normalizers_are_exact[LOG2-1308-log(dble(2.0))-2.0] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_dyadic_normalizers_are_exact[LOG2-1308-log(dble(2.0))-2.0] +pamica/tests/test_reference_constants.py::test_dyadic_normalizers_are_exact[LOG2-1324-log(dble(2.0))-2.0] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_dyadic_normalizers_are_exact[LOG2-1324-log(dble(2.0))-2.0] +pamica/tests/test_reference_constants.py::test_dyadic_normalizers_are_exact[LOG4-1346-log(dble(4.0))-4.0] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_dyadic_normalizers_are_exact[LOG4-1346-log(dble(4.0))-4.0] +pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[1.772453851] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[1.772453851] +pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[2.506628274] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[2.506628274] +pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[4.132731354] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[4.132731354] +pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[1.858073988] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[1.858073988] +pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[1.0e-16] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_the_helper_does_not_round_twice[1.0e-16] +pamica/tests/test_reference_constants.py::test_every_inexact_single_precision_literal_in_the_reference_is_accounted_for +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_every_inexact_single_precision_literal_in_the_reference_is_accounted_for +pamica/tests/test_reference_constants.py::test_every_inexact_default_in_the_reference_header_is_accounted_for +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_every_inexact_default_in_the_reference_header_is_accounted_for +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_HALF_LOG_PI = 0.5 * math.log(math.pi)] +[gw6] [ 60%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_HALF_LOG_PI = 0.5 * math.log(math.pi)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG_SQRT_2PI = math.log(2.506628274)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG_SQRT_2PI = math.log(2.506628274)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG_NORM_COSH_SUB = math.log(4.132731354)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG_NORM_COSH_SUB = math.log(4.132731354)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG_NORM_COSH_SUP = math.log(1.858073988)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG_NORM_COSH_SUP = math.log(1.858073988)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_EPSDBLE = 1e-16] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_EPSDBLE = 1e-16] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG2 = math.log(2.0)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG2 = math.log(2.0)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG4 = math.log(4.0)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[_LOG4 = math.log(4.0)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[log_pdf = -np.abs(y) - np.log(2.0)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[log_pdf = -np.abs(y) - np.log(2.0)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[log_pdf = -y * y - 0.5 * np.log(np.pi)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[log_pdf = -y * y - 0.5 * np.log(np.pi)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[logab = np.where(ayrho < 1e-16, 0.0, logab)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[logab = np.where(ayrho < 1e-16, 0.0, logab)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[pdf = np.exp(-y * y) / np.sqrt(np.pi)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[pdf = np.exp(-y * y) / np.sqrt(np.pi)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[pdf1 = np.exp(-0.5 * y * y) / np.sqrt(2 * np.pi)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[pdf1 = np.exp(-0.5 * y * y) / np.sqrt(2 * np.pi)] +pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[pdf2 = np.exp(-0.5 * y * y / rho) / np.sqrt(2 * np.pi * rho)] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_the_copy_scanner_flags_the_removed_definitions[pdf2 = np.exp(-0.5 * y * y / rho) / np.sqrt(2 * np.pi * rho)] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[mlx_impl/__init__.py] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[mlx_impl/__init__.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[mlx_impl/core.py] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[mlx_impl/core.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/__init__.py] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/__init__.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/cli.py] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/cli.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/core.py] +[gw3] [ 61%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_wrapper_save_converts_losslessly[torch-unmerged] +pamica/tests/test_component_rows_persistence.py::test_old_wrapper_save_converts_losslessly[mlx-single] +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/core.py] +[gw5] [ 61%] PASSED pamica/tests/test_llt_stash.py::test_torch_stashed_llt_is_the_estep_behind_final_ll +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/data.py] +pamica/tests/test_pre_change_loader.py::test_the_guard_catches_a_fetch_without_running_it +[gw6] [ 61%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/data.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/load.py] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/load.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/pdf.py] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/pdf.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/utils.py] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/utils.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/viz.py] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[numpy_impl/viz.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[torch_impl/__init__.py] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[torch_impl/__init__.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[torch_impl/core.py] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[torch_impl/core.py] +pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[torch_impl/utils.py] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_no_backend_keeps_a_copy_of_the_constants[torch_impl/utils.py] +pamica/tests/test_reference_constants.py::test_every_backend_imports_the_shared_constants[torch_impl] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_every_backend_imports_the_shared_constants[torch_impl] +pamica/tests/test_reference_constants.py::test_every_backend_imports_the_shared_constants[numpy_impl] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_every_backend_imports_the_shared_constants[numpy_impl] +pamica/tests/test_reference_constants.py::test_every_backend_imports_the_shared_constants[mlx_impl] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_every_backend_imports_the_shared_constants[mlx_impl] +pamica/tests/test_reference_constants.py::test_torch_and_numpy_rho2_log_density_is_the_references +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_torch_and_numpy_rho2_log_density_is_the_references +pamica/tests/test_reference_constants.py::test_the_plotted_density_is_the_fits[1.0] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_the_plotted_density_is_the_fits[1.0] +pamica/tests/test_reference_constants.py::test_the_plotted_density_is_the_fits[1.5] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_the_plotted_density_is_the_fits[1.5] +pamica/tests/test_reference_constants.py::test_the_plotted_density_is_the_fits[2.0] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_the_plotted_density_is_the_fits[2.0] +pamica/tests/test_reference_constants.py::test_mlx_rho2_normalizer_is_the_references +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_mlx_rho2_normalizer_is_the_references +pamica/tests/test_reference_constants.py::test_family_matches_the_seeded_reference[pdftype2] +[gw6] [ 62%] SKIPPED pamica/tests/test_reference_constants.py::test_family_matches_the_seeded_reference[pdftype2] +pamica/tests/test_reference_constants.py::test_family_matches_the_seeded_reference[pdftype4] +[gw6] [ 62%] SKIPPED pamica/tests/test_reference_constants.py::test_family_matches_the_seeded_reference[pdftype4] +pamica/tests/test_reference_constants.py::test_family_matches_the_seeded_reference[pdftype1] +[gw6] [ 62%] SKIPPED pamica/tests/test_reference_constants.py::test_family_matches_the_seeded_reference[pdftype1] +pamica/tests/test_reference_constants.py::test_the_pre_344_substitution_changes_every_constant_it_patches[torch] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_the_pre_344_substitution_changes_every_constant_it_patches[torch] +pamica/tests/test_reference_constants.py::test_the_pre_344_substitution_changes_every_constant_it_patches[numpy] +[gw6] [ 62%] PASSED pamica/tests/test_reference_constants.py::test_the_pre_344_substitution_changes_every_constant_it_patches[numpy] +pamica/tests/test_reference_constants.py::test_the_pre_344_substitution_changes_every_constant_it_patches[mlx] +[gw6] [ 63%] PASSED pamica/tests/test_reference_constants.py::test_the_pre_344_substitution_changes_every_constant_it_patches[mlx] +pamica/tests/test_restart_policy.py::test_single_restart_passes_the_base_seed_through_untouched +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_single_restart_passes_the_base_seed_through_untouched +pamica/tests/test_restart_policy.py::test_seeds_derive_consecutively_from_the_base_seed +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_seeds_derive_consecutively_from_the_base_seed +pamica/tests/test_restart_policy.py::test_explicit_seeds_win_over_derivation +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_explicit_seeds_win_over_derivation +pamica/tests/test_restart_policy.py::test_explicit_seeds_must_match_n_restarts +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_explicit_seeds_must_match_n_restarts +pamica/tests/test_restart_policy.py::test_n_restarts_must_be_at_least_one +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_n_restarts_must_be_at_least_one +pamica/tests/test_restart_policy.py::test_n_restarts_must_be_an_int +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_n_restarts_must_be_an_int +pamica/tests/test_restart_policy.py::test_seeds_must_be_ints +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_seeds_must_be_ints +pamica/tests/test_restart_policy.py::test_multi_restart_without_a_seed_is_refused +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_multi_restart_without_a_seed_is_refused +pamica/tests/test_restart_policy.py::test_highest_likelihood_wins +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_highest_likelihood_wins +pamica/tests/test_restart_policy.py::test_ties_keep_the_earlier_restart +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_ties_keep_the_earlier_restart +pamica/tests/test_restart_policy.py::test_degenerate_restarts_are_excluded_even_when_they_score_higher +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_degenerate_restarts_are_excluded_even_when_they_score_higher +pamica/tests/test_restart_policy.py::test_non_finite_likelihood_is_excluded_even_if_not_flagged +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_non_finite_likelihood_is_excluded_even_if_not_flagged +pamica/tests/test_restart_policy.py::test_all_degenerate_selects_nothing +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_all_degenerate_selects_nothing +pamica/tests/test_restart_policy.py::test_records_must_stay_aligned +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_records_must_stay_aligned +pamica/tests/test_restart_policy.py::test_copies_are_independent_of_the_live_value +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_copies_are_independent_of_the_live_value +pamica/tests/test_restart_policy.py::test_unknown_types_raise_rather_than_alias +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_unknown_types_raise_rather_than_alias +pamica/tests/test_restart_policy.py::test_every_backend_exposes_the_same_restart_surface[torch] +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_every_backend_exposes_the_same_restart_surface[torch] +pamica/tests/test_restart_policy.py::test_every_backend_exposes_the_same_restart_surface[numpy] +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_every_backend_exposes_the_same_restart_surface[numpy] +pamica/tests/test_restart_policy.py::test_every_backend_exposes_the_same_restart_surface[mlx] +[gw6] [ 63%] PASSED pamica/tests/test_restart_policy.py::test_every_backend_exposes_the_same_restart_surface[mlx] +pamica/tests/test_restart_policy.py::test_every_backend_validates_the_configuration_at_construction[torch] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_every_backend_validates_the_configuration_at_construction[torch] +pamica/tests/test_restart_policy.py::test_every_backend_validates_the_configuration_at_construction[numpy] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_every_backend_validates_the_configuration_at_construction[numpy] +pamica/tests/test_restart_policy.py::test_every_backend_validates_the_configuration_at_construction[mlx] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_every_backend_validates_the_configuration_at_construction[mlx] +pamica/tests/test_restart_policy.py::test_a_crashed_restart_is_degenerate_on_every_backend[torch] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_a_crashed_restart_is_degenerate_on_every_backend[torch] +pamica/tests/test_restart_policy.py::test_a_crashed_restart_is_degenerate_on_every_backend[numpy] +[gw6] [ 64%] SKIPPED pamica/tests/test_restart_policy.py::test_a_crashed_restart_is_degenerate_on_every_backend[numpy] +pamica/tests/test_restart_policy.py::test_a_crashed_restart_is_degenerate_on_every_backend[mlx] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_a_crashed_restart_is_degenerate_on_every_backend[mlx] +pamica/tests/test_restart_policy.py::test_the_error_stop_reason_is_distinct_from_the_likelihood_ones +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_the_error_stop_reason_is_distinct_from_the_likelihood_ones +pamica/tests/test_restart_policy.py::test_restart_state_lists_account_for_everything_a_fit_writes[torch] +[gw1] [ 64%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[automatic-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[automatic-mlx] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_restart_state_lists_account_for_everything_a_fit_writes[torch] +pamica/tests/test_restart_policy.py::test_restart_state_lists_account_for_everything_a_fit_writes[numpy] +[gw3] [ 64%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_wrapper_save_converts_losslessly[mlx-single] +pamica/tests/test_component_rows_persistence.py::test_old_wrapper_save_converts_losslessly[mlx-unmerged] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_restart_state_lists_account_for_everything_a_fit_writes[numpy] +pamica/tests/test_restart_policy.py::test_restart_state_lists_account_for_everything_a_fit_writes[mlx] +[gw1] [ 64%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_refit_after_a_rank_reduction[automatic-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[pcakeep-torch] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_restart_state_lists_account_for_everything_a_fit_writes[mlx] +pamica/tests/test_restart_policy.py::test_state_and_invariant_lists_do_not_overlap[torch] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_state_and_invariant_lists_do_not_overlap[torch] +pamica/tests/test_restart_policy.py::test_state_and_invariant_lists_do_not_overlap[numpy] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_state_and_invariant_lists_do_not_overlap[numpy] +pamica/tests/test_restart_policy.py::test_state_and_invariant_lists_do_not_overlap[mlx] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_state_and_invariant_lists_do_not_overlap[mlx] +pamica/tests/test_restart_policy.py::test_the_fitted_parameters_are_all_restart_state[torch] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_the_fitted_parameters_are_all_restart_state[torch] +pamica/tests/test_restart_policy.py::test_the_fitted_parameters_are_all_restart_state[numpy] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_the_fitted_parameters_are_all_restart_state[numpy] +pamica/tests/test_restart_policy.py::test_the_fitted_parameters_are_all_restart_state[mlx] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_the_fitted_parameters_are_all_restart_state[mlx] +pamica/tests/test_restart_policy.py::test_derived_seeds_are_identical_across_backends[torch] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_derived_seeds_are_identical_across_backends[torch] +pamica/tests/test_restart_policy.py::test_derived_seeds_are_identical_across_backends[numpy] +[gw6] [ 64%] PASSED pamica/tests/test_restart_policy.py::test_derived_seeds_are_identical_across_backends[numpy] +pamica/tests/test_restart_policy.py::test_derived_seeds_are_identical_across_backends[mlx] +[gw6] [ 65%] PASSED pamica/tests/test_restart_policy.py::test_derived_seeds_are_identical_across_backends[mlx] +pamica/tests/test_sample_data.py::test_loadmodout_llt_reshape_order +[gw6] [ 65%] PASSED pamica/tests/test_sample_data.py::test_loadmodout_llt_reshape_order +pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll +[gw6] [ 65%] PASSED pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll +pamica/tests/test_sample_data.py::test_amicaoutput_sources_contract_and_c_subtraction +[gw5] [ 65%] PASSED pamica/tests/test_pre_change_loader.py::test_the_guard_catches_a_fetch_without_running_it +[gw6] [ 65%] PASSED pamica/tests/test_sample_data.py::test_amicaoutput_sources_contract_and_c_subtraction +pamica/tests/test_pre_change_loader.py::test_missing_git_skips_locally +pamica/tests/test_sample_data.py::test_sample_data_scikit +[gw5] [ 65%] PASSED pamica/tests/test_pre_change_loader.py::test_missing_git_skips_locally +pamica/tests/test_pre_change_loader.py::test_missing_git_fails_under_ci +[gw5] [ 65%] PASSED pamica/tests/test_pre_change_loader.py::test_missing_git_fails_under_ci +pamica/tests/test_pre_change_loader.py::test_outside_a_checkout_skips_without_fetch_advice +[gw3] [ 65%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_wrapper_save_converts_losslessly[mlx-unmerged] +pamica/tests/test_component_rows_persistence.py::test_old_merged_save_is_refused[torch-state_dict] +[gw5] [ 65%] PASSED pamica/tests/test_pre_change_loader.py::test_outside_a_checkout_skips_without_fetch_advice +pamica/tests/test_pre_change_loader.py::test_outside_a_checkout_fails_under_ci +[gw5] [ 65%] PASSED pamica/tests/test_pre_change_loader.py::test_outside_a_checkout_fails_under_ci +pamica/tests/test_pre_change_loader.py::test_an_alias_is_never_reused_for_another_commit +[gw5] [ 65%] PASSED pamica/tests/test_pre_change_loader.py::test_an_alias_is_never_reused_for_another_commit +pamica/tests/test_rank_policy.py::test_full_rank_data_keeps_every_dimension +[gw5] [ 65%] PASSED pamica/tests/test_rank_policy.py::test_full_rank_data_keeps_every_dimension +pamica/tests/test_rank_policy.py::test_relative_floor_finds_the_true_rank +[gw1] [ 65%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[pcakeep-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[pcakeep-numpy] +[gw5] [ 65%] PASSED pamica/tests/test_rank_policy.py::test_relative_floor_finds_the_true_rank +pamica/tests/test_rank_policy.py::test_absolute_floor_over_retains +[gw5] [ 65%] PASSED pamica/tests/test_rank_policy.py::test_absolute_floor_over_retains +pamica/tests/test_rank_policy.py::test_average_reference_costs_exactly_one_dimension +[gw5] [ 65%] PASSED pamica/tests/test_rank_policy.py::test_average_reference_costs_exactly_one_dimension +pamica/tests/test_rank_policy.py::test_scale_invariance_of_the_relative_floor +[gw5] [ 65%] PASSED pamica/tests/test_rank_policy.py::test_scale_invariance_of_the_relative_floor +pamica/tests/test_rank_policy.py::test_absolute_floor_is_not_scale_invariant +[gw5] [ 65%] PASSED pamica/tests/test_rank_policy.py::test_absolute_floor_is_not_scale_invariant +pamica/tests/test_rank_policy.py::test_pcakeep_is_capped_by_the_detected_rank +[gw5] [ 65%] PASSED pamica/tests/test_rank_policy.py::test_pcakeep_is_capped_by_the_detected_rank +pamica/tests/test_rank_policy.py::test_non_finite_eigenvalues_keep_full_dimension +[gw5] [ 65%] PASSED pamica/tests/test_rank_policy.py::test_non_finite_eigenvalues_keep_full_dimension +pamica/tests/test_rank_policy.py::test_defaults_match_the_documented_constants +[gw5] [ 66%] PASSED pamica/tests/test_rank_policy.py::test_defaults_match_the_documented_constants +pamica/tests/test_rank_policy.py::test_validator_accepts[None-None] +[gw5] [ 66%] PASSED pamica/tests/test_rank_policy.py::test_validator_accepts[None-None] +pamica/tests/test_rank_policy.py::test_validator_accepts[1-None] +[gw5] [ 66%] PASSED pamica/tests/test_rank_policy.py::test_validator_accepts[1-None] +pamica/tests/test_rank_policy.py::test_validator_accepts[20-None] +[gw5] [ 66%] PASSED pamica/tests/test_rank_policy.py::test_validator_accepts[20-None] +pamica/tests/test_rank_policy.py::test_validator_accepts[pcakeep3-None] +[gw5] [ 66%] PASSED pamica/tests/test_rank_policy.py::test_validator_accepts[pcakeep3-None] +pamica/tests/test_rank_policy.py::test_validator_accepts[None-3.0] +[gw5] [ 66%] PASSED pamica/tests/test_rank_policy.py::test_validator_accepts[None-3.0] +pamica/tests/test_rank_policy.py::test_validator_accepts[None-30] +[gw5] [ 66%] PASSED pamica/tests/test_rank_policy.py::test_validator_accepts[None-30] +pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[mlx-1] +[gw3] [ 66%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_merged_save_is_refused[torch-state_dict] +pamica/tests/test_component_rows_persistence.py::test_old_merged_save_is_refused[torch-wrapper] +[gw5] [ 66%] PASSED pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[mlx-1] +pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[mlx-5] +[gw5] [ 66%] PASSED pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[mlx-5] +pamica/tests/test_schedule_gates.py::test_newt_start_zero_fits_exactly_as_one[torch] +[gw3] [ 66%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_merged_save_is_refused[torch-wrapper] +pamica/tests/test_component_rows_persistence.py::test_old_merged_save_is_refused[mlx-state_dict] +[gw3] [ 66%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_merged_save_is_refused[mlx-state_dict] +pamica/tests/test_component_rows_persistence.py::test_old_merged_save_is_refused[mlx-wrapper] +[gw1] [ 66%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[pcakeep-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[pcakeep-mlx] +[gw1] [ 66%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[pcakeep-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[automatic-torch] +[gw3] [ 66%] PASSED pamica/tests/test_component_rows_persistence.py::test_old_merged_save_is_refused[mlx-wrapper] +pamica/tests/test_decompose_equiv.py::test_match_identical_is_one +[gw3] [ 66%] PASSED pamica/tests/test_decompose_equiv.py::test_match_identical_is_one +pamica/tests/test_decompose_equiv.py::test_match_invariant_to_permutation_and_sign +[gw3] [ 66%] PASSED pamica/tests/test_decompose_equiv.py::test_match_invariant_to_permutation_and_sign +pamica/tests/test_decompose_equiv.py::test_match_low_for_unrelated +[gw3] [ 66%] PASSED pamica/tests/test_decompose_equiv.py::test_match_low_for_unrelated +pamica/tests/test_default_settings.py::test_numpy_shares_every_torch_default +[gw3] [ 66%] PASSED pamica/tests/test_default_settings.py::test_numpy_shares_every_torch_default +pamica/tests/test_default_settings.py::test_numpy_params_json_carries_the_shared_defaults +[gw3] [ 66%] PASSED pamica/tests/test_default_settings.py::test_numpy_params_json_carries_the_shared_defaults +pamica/tests/test_default_settings.py::test_mlx_shares_every_torch_default +[gw3] [ 67%] PASSED pamica/tests/test_default_settings.py::test_mlx_shares_every_torch_default +pamica/tests/test_default_settings.py::test_native_input_param_shares_every_torch_default +[gw3] [ 67%] PASSED pamica/tests/test_default_settings.py::test_native_input_param_shares_every_torch_default +pamica/tests/test_schedule_gates.py::test_rejection_first_fires_on_iteration_rejstart[mlx] +[gw3] [ 67%] PASSED pamica/tests/test_schedule_gates.py::test_rejection_first_fires_on_iteration_rejstart[mlx] +pamica/tests/test_schedule_gates.py::test_numpy_restart_window_is_the_first_restartiter_iterations[3-2-1] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[automatic-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[automatic-numpy] +[gw3] [ 67%] PASSED pamica/tests/test_schedule_gates.py::test_numpy_restart_window_is_the_first_restartiter_iterations[3-2-1] +pamica/tests/test_schedule_gates.py::test_numpy_restart_window_is_the_first_restartiter_iterations[3-3-0] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[automatic-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[automatic-mlx] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_restarts_survive_a_rank_reduction[automatic-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_channel_check_names_the_input_count[torch] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_channel_check_names_the_input_count[torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_channel_check_names_the_input_count[mlx] +[gw3] [ 67%] PASSED pamica/tests/test_schedule_gates.py::test_numpy_restart_window_is_the_first_restartiter_iterations[3-3-0] +pamica/tests/test_schedule_gates.py::test_numpy_restart_window_is_the_first_restartiter_iterations[0-0-0] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_channel_check_names_the_input_count[mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_reloaded_reduced_model_transforms_and_refits[torch] +[gw3] [ 67%] PASSED pamica/tests/test_schedule_gates.py::test_numpy_restart_window_is_the_first_restartiter_iterations[0-0-0] +pamica/tests/test_schedule_gates.py::test_numpy_restart_clears_the_small_gain_count_as_the_reference_does +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reloaded_reduced_model_transforms_and_refits[torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_reloaded_reduced_model_transforms_and_refits[mlx] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reloaded_reduced_model_transforms_and_refits[mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcakeep--3-torch] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcakeep--3-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcakeep--3-numpy] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcakeep--3-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcakeep--3-mlx] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcakeep--3-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcadb--5.0-torch] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcadb--5.0-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcadb--5.0-numpy] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcadb--5.0-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcadb--5.0-mlx] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_at_fit_time[pcadb--5.0-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_by_the_mir_step_gate[pcakeep-20-torch] +[gw1] [ 67%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_by_the_mir_step_gate[pcakeep-20-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_by_the_mir_step_gate[pcakeep-20-mlx] +[gw1] [ 68%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_by_the_mir_step_gate[pcakeep-20-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_by_the_mir_step_gate[pcadb--5.0-torch] +[gw1] [ 68%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_by_the_mir_step_gate[pcadb--5.0-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_by_the_mir_step_gate[pcadb--5.0-mlx] +[gw1] [ 68%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_reassigned_request_is_caught_by_the_mir_step_gate[pcadb--5.0-mlx] +pamica/tests/test_pre_change_loader.py::test_loading_a_present_commit_only_reads +[gw3] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_numpy_restart_clears_the_small_gain_count_as_the_reference_does +pamica/tests/test_schedule_gates.py::test_numpy_restart_iteration_applies_no_update +[gw1] [ 68%] PASSED pamica/tests/test_pre_change_loader.py::test_loading_a_present_commit_only_reads +pamica/tests/test_pre_change_loader.py::test_a_missing_commit_skips_locally_with_the_fetch_command +[gw1] [ 68%] PASSED pamica/tests/test_pre_change_loader.py::test_a_missing_commit_skips_locally_with_the_fetch_command +pamica/tests/test_pre_change_loader.py::test_a_missing_commit_fails_under_ci +[gw1] [ 68%] PASSED pamica/tests/test_pre_change_loader.py::test_a_missing_commit_fails_under_ci +pamica/tests/test_pre_change_loader.py::test_an_abbreviated_pin_is_rejected +[gw1] [ 68%] PASSED pamica/tests/test_pre_change_loader.py::test_an_abbreviated_pin_is_rejected +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-rejstart-0-1-extra4] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-rejstart-0-1-extra4] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-rejstart--2-1-extra5] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-rejstart--2-1-extra5] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-rejstart-2.0-1-extra6] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-rejstart-2.0-1-extra6] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-share_start-0-1-extra7] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-share_start-0-1-extra7] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-share_start--5-1-extra8] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-share_start--5-1-extra8] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-share_start-2.5-1-extra9] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-share_start-2.5-1-extra9] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-share_start-True-1-extra10] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-share_start-True-1-extra10] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-newt_start--1-0-extra0] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-newt_start--1-0-extra0] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-newt_start--1-0-extra1] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-newt_start--1-0-extra1] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-newt_start-2.5-0-extra2] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-newt_start-2.5-0-extra2] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-newt_start-True-0-extra3] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-newt_start-True-0-extra3] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-rejstart-0-1-extra4] +[gw1] [ 68%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-rejstart-0-1-extra4] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-rejstart--2-1-extra5] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-rejstart--2-1-extra5] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-rejstart-2.0-1-extra6] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-rejstart-2.0-1-extra6] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-share_start-0-1-extra7] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-share_start-0-1-extra7] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-share_start--5-1-extra8] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-share_start--5-1-extra8] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-share_start-2.5-1-extra9] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-share_start-2.5-1-extra9] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-share_start-True-1-extra10] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[mlx-share_start-True-1-extra10] +pamica/tests/test_schedule_gates.py::test_boundary_schedule_settings_are_accepted[torch] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_boundary_schedule_settings_are_accepted[torch] +pamica/tests/test_schedule_gates.py::test_boundary_schedule_settings_are_accepted[numpy] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_boundary_schedule_settings_are_accepted[numpy] +pamica/tests/test_schedule_gates.py::test_boundary_schedule_settings_are_accepted[mlx] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_boundary_schedule_settings_are_accepted[mlx] +pamica/tests/test_schedule_gates.py::test_numpy_only_schedule_settings_are_validated[kwargs0-histstep must be an integer >= 1, got 0] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_numpy_only_schedule_settings_are_validated[kwargs0-histstep must be an integer >= 1, got 0] +pamica/tests/test_schedule_gates.py::test_numpy_only_schedule_settings_are_validated[kwargs1-restartiter must be an integer >= 0, got -1] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_numpy_only_schedule_settings_are_validated[kwargs1-restartiter must be an integer >= 0, got -1] +pamica/tests/test_schedule_gates.py::test_numpy_only_schedule_settings_are_validated[kwargs2-maxrestarts must be an integer >= 0, got -1] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_numpy_only_schedule_settings_are_validated[kwargs2-maxrestarts must be an integer >= 0, got -1] +pamica/tests/test_schedule_gates.py::test_numpy_only_schedule_settings_are_validated[kwargs3-restartiter must be an integer >= 0, got 2.5] +[gw1] [ 69%] PASSED pamica/tests/test_schedule_gates.py::test_numpy_only_schedule_settings_are_validated[kwargs3-restartiter must be an integer >= 0, got 2.5] +pamica/tests/test_schedule_native_oracle.py::test_torch_first_newton_iterations_match_the_reference +[gw1] [ 69%] SKIPPED pamica/tests/test_schedule_native_oracle.py::test_torch_first_newton_iterations_match_the_reference +pamica/tests/test_schedule_native_oracle.py::test_numpy_first_newton_iterations_match_the_reference +[gw1] [ 69%] SKIPPED pamica/tests/test_schedule_native_oracle.py::test_numpy_first_newton_iterations_match_the_reference +pamica/tests/test_schedule_native_oracle.py::test_the_window_compared_is_newton_sensitive +[gw1] [ 69%] SKIPPED pamica/tests/test_schedule_native_oracle.py::test_the_window_compared_is_newton_sensitive +pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[torch-full] +[gw1] [ 69%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[torch-full] +pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[torch-reduced] +[gw1] [ 69%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[torch-reduced] +pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[numpy-full] +[gw1] [ 69%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[numpy-full] +pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[numpy-reduced] +[gw1] [ 69%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[numpy-reduced] +pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[mlx-full] +[gw1] [ 70%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[mlx-full] +pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[mlx-reduced] +[gw1] [ 70%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_sensor_mixing_inverts_the_spatial_filter[mlx-reduced] +pamica/tests/test_sensor_mixing_cross_backend.py::test_numpy_sensor_mixing_matches_torch[full] +[gw1] [ 70%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_numpy_sensor_mixing_matches_torch[full] +pamica/tests/test_sensor_mixing_cross_backend.py::test_numpy_sensor_mixing_matches_torch[reduced] +[gw1] [ 70%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_numpy_sensor_mixing_matches_torch[reduced] +pamica/tests/test_sensor_mixing_cross_backend.py::test_mlx_sensor_mixing_matches_torch[full] +[gw1] [ 70%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_mlx_sensor_mixing_matches_torch[full] +pamica/tests/test_sensor_mixing_cross_backend.py::test_mlx_sensor_mixing_matches_torch[reduced] +[gw1] [ 70%] PASSED pamica/tests/test_sensor_mixing_cross_backend.py::test_mlx_sensor_mixing_matches_torch[reduced] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[torch-True-full] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_numpy_restart_iteration_applies_no_update +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-newt_start--1-0-extra0] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-newt_start--1-0-extra0] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-newt_start--1-0-extra1] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-newt_start--1-0-extra1] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-newt_start-2.5-0-extra2] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-newt_start-2.5-0-extra2] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-newt_start-True-0-extra3] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-newt_start-True-0-extra3] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-rejstart-0-1-extra4] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-rejstart-0-1-extra4] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-rejstart--2-1-extra5] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-rejstart--2-1-extra5] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-rejstart-2.0-1-extra6] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-rejstart-2.0-1-extra6] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-share_start-0-1-extra7] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-share_start-0-1-extra7] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-share_start--5-1-extra8] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-share_start--5-1-extra8] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-share_start-2.5-1-extra9] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-share_start-2.5-1-extra9] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-share_start-True-1-extra10] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[torch-share_start-True-1-extra10] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-newt_start--1-0-extra0] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-newt_start--1-0-extra0] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-newt_start--1-0-extra1] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-newt_start--1-0-extra1] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-newt_start-2.5-0-extra2] +[gw3] [ 70%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-newt_start-2.5-0-extra2] +pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-newt_start-True-0-extra3] +[gw3] [ 71%] PASSED pamica/tests/test_schedule_gates.py::test_schedule_settings_are_rejected_with_one_message[numpy-newt_start-True-0-extra3] +pamica/tests/test_viz.py::test_plot_pmi_heatmap_pixels_are_actually_reordered[False] +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_pixels_are_actually_reordered[False] +pamica/tests/test_viz.py::test_plot_pmi_heatmap_pixels_are_actually_reordered[True] +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_pixels_are_actually_reordered[True] +pamica/tests/test_viz.py::test_plot_pmi_heatmap_labels_param_indexed_by_order +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_labels_param_indexed_by_order +pamica/tests/test_viz.py::test_plot_pmi_heatmap_model_title +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_model_title +pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_square +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_square +pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_finite[False-nan] +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_finite[False-nan] +pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_finite[False-inf] +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_finite[False-inf] +pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_finite[True-nan] +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_finite[True-nan] +pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_finite[True-inf] +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_raises_on_non_finite[True-inf] +pamica/tests/test_viz.py::test_plot_pmi_heatmap_accepts_existing_ax +[gw1] [ 71%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[torch-True-full] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[torch-True-reduced] +[gw3] [ 71%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_accepts_existing_ax +pamica/tests/test_viz.py::test_plot_model_probability_returns_two_axes +[gw1] [ 71%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[torch-True-reduced] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[torch-False-full] +[gw1] [ 71%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[torch-False-full] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[torch-False-reduced] +[gw1] [ 71%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[torch-False-reduced] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[numpy-True-full] +[gw1] [ 71%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[numpy-True-full] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[numpy-True-reduced] +[gw1] [ 71%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[numpy-True-reduced] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[numpy-False-full] +[gw1] [ 71%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[numpy-False-full] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[numpy-False-reduced] +[gw1] [ 71%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[numpy-False-reduced] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[mlx-True-full] +[gw1] [ 71%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[mlx-True-full] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[mlx-True-reduced] +[gw1] [ 72%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[mlx-True-reduced] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[mlx-False-full] +[gw1] [ 72%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[mlx-False-full] +pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[mlx-False-reduced] +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_returns_two_axes +pamica/tests/test_viz.py::test_plot_model_probability_one_line_per_model +[gw1] [ 72%] PASSED pamica/tests/test_sphere_export_order.py::test_loadmodout_sphere_matches_backend[mlx-False-reduced] +pamica/tests/test_viz.py::test_read_eeglab_set_metadata_tolerates_unlocalized_channels +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_one_line_per_model +pamica/tests/test_viz.py::test_plot_model_probability_probabilities_sum_to_one +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_probabilities_sum_to_one +pamica/tests/test_viz.py::test_plot_model_probability_bottom_panel_is_best_model_ll +[gw1] [ 72%] PASSED pamica/tests/test_viz.py::test_read_eeglab_set_metadata_tolerates_unlocalized_channels +pamica/tests/test_viz.py::test_plot_pmi_heatmap_returns_figure +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_bottom_panel_is_best_model_ll +pamica/tests/test_viz.py::test_plot_model_probability_xaxis_samples_without_srate +[gw1] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_returns_figure +pamica/tests/test_viz.py::test_plot_pmi_heatmap_masks_diagonal_by_default +[gw1] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_masks_diagonal_by_default +pamica/tests/test_viz.py::test_plot_pmi_heatmap_mask_diagonal_false_leaves_diagonal_visible +[gw1] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_mask_diagonal_false_leaves_diagonal_visible +pamica/tests/test_viz.py::test_plot_pmi_heatmap_default_order_matches_block_diagonal_order +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_xaxis_samples_without_srate +pamica/tests/test_viz.py::test_plot_model_probability_xaxis_seconds_with_srate +[gw1] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_default_order_matches_block_diagonal_order +pamica/tests/test_viz.py::test_plot_pmi_heatmap_custom_order_is_honored +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_xaxis_seconds_with_srate +pamica/tests/test_viz.py::test_plot_model_probability_smooth_sec_requires_srate +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_smooth_sec_requires_srate +pamica/tests/test_viz.py::test_plot_model_probability_window_sec_requires_srate +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_window_sec_requires_srate +pamica/tests/test_viz.py::test_plot_model_probability_smoothing_preserves_normalization +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_smoothing_preserves_normalization +pamica/tests/test_viz.py::test_plot_model_probability_smoothing_edge_corrected_not_dragged_to_zero +[gw1] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_pmi_heatmap_custom_order_is_honored +pamica/tests/test_viz.py::test_plot_model_probability_accepts_existing_axes +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_smoothing_edge_corrected_not_dragged_to_zero +pamica/tests/test_viz.py::test_plot_model_probability_smooth_sec_too_small_raises +[gw3] [ 72%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_smooth_sec_too_small_raises +pamica/tests/test_viz.py::test_plot_model_probability_smooth_sec_too_large_raises +[gw3] [ 73%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_smooth_sec_too_large_raises +pamica/tests/test_viz.py::test_plot_model_probability_window_sec_sets_xlim +[gw3] [ 73%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_window_sec_sets_xlim +pamica/tests/test_viz.py::test_plot_model_probability_legend_labels +[gw3] [ 73%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_legend_labels +pamica/tests/test_wrapper_backends.py::test_dtype_with_the_mlx_backend_raises_before_fitting +[gw3] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_dtype_with_the_mlx_backend_raises_before_fitting +pamica/tests/test_wrapper_backends.py::test_unknown_fit_keyword_names_the_backend[torch] +[gw3] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_unknown_fit_keyword_names_the_backend[torch] +pamica/tests/test_wrapper_backends.py::test_unknown_fit_keyword_names_the_backend[mlx] +[gw3] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_unknown_fit_keyword_names_the_backend[mlx] +pamica/tests/test_wrapper_backends.py::test_torch_only_and_unknown_together_name_both +[gw3] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_torch_only_and_unknown_together_name_both +pamica/tests/test_wrapper_backends.py::test_backend_attribute_is_rechecked_at_fit +[gw3] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_backend_attribute_is_rechecked_at_fit +pamica/tests/test_wrapper_backends.py::test_fit_publishes_the_backend_record[torch] +[gw3] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_fit_publishes_the_backend_record[torch] +pamica/tests/test_wrapper_backends.py::test_fit_publishes_the_backend_record[mlx] +[gw3] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_fit_publishes_the_backend_record[mlx] +pamica/tests/test_wrapper_backends.py::test_every_delegating_method_works[torch] +[gw1] [ 73%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_accepts_existing_axes +pamica/tests/test_viz.py::test_plot_model_probability_raises_without_lht +[gw1] [ 73%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_raises_without_lht +pamica/tests/test_viz.py::test_plot_model_probability_lht_array_matches_out +[gw1] [ 73%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_lht_array_matches_out +pamica/tests/test_viz.py::test_plot_model_probability_requires_exactly_one_source +[gw1] [ 73%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_requires_exactly_one_source +pamica/tests/test_viz.py::test_plot_model_probability_rejects_non_2d_lht +[gw1] [ 73%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_rejects_non_2d_lht +pamica/tests/test_viz.py::test_plot_model_probability_lht_with_smoothing +[gw1] [ 73%] PASSED pamica/tests/test_viz.py::test_plot_model_probability_lht_with_smoothing +pamica/tests/test_wrapper_backends.py::test_v1_payload_still_loads_and_transforms_identically +[gw3] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_every_delegating_method_works[torch] +pamica/tests/test_wrapper_backends.py::test_every_delegating_method_works[mlx] +[gw1] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_v1_payload_still_loads_and_transforms_identically +pamica/tests/test_wrapper_backends.py::test_unknown_backend_name_lists_the_valid_ones +[gw1] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_unknown_backend_name_lists_the_valid_ones +pamica/tests/test_wrapper_backends.py::test_device_with_the_mlx_backend_raises_at_construction +[gw1] [ 73%] PASSED pamica/tests/test_wrapper_backends.py::test_device_with_the_mlx_backend_raises_at_construction +pamica/tests/test_wrapper_backends.py::test_mlx_backend_without_mlx_raises_import_error +[gw1] [ 74%] PASSED pamica/tests/test_wrapper_backends.py::test_mlx_backend_without_mlx_raises_import_error +pamica/tests/test_wrapper_backends.py::test_import_pamica_never_imports_mlx +[gw4] [ 74%] PASSED pamica/tests/test_mlx_newton_cross_backend.py::test_newton_fit_ll_matches_float64_torch +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_log_pdf_matches_fortran[2] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_log_pdf_matches_fortran[2] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_log_pdf_matches_fortran[3] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_log_pdf_matches_fortran[3] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_log_pdf_matches_fortran[4] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_log_pdf_matches_fortran[4] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_log_pdf_matches_fortran[1] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_log_pdf_matches_fortran[1] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_score_matches_fortran[2] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_score_matches_fortran[2] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_score_matches_fortran[3] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_score_matches_fortran[3] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_score_matches_fortran[4] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_score_matches_fortran[4] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_score_matches_fortran[1] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_family_score_matches_fortran[1] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_gg_path_bit_identical_none_vs_code0 +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_gg_path_bit_identical_none_vs_code0 +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_one_mstep_matches_torch_twin[2-3] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_one_mstep_matches_torch_twin[2-3] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_one_mstep_matches_torch_twin[3-3] +[gw3] [ 74%] PASSED pamica/tests/test_wrapper_backends.py::test_every_delegating_method_works[mlx] +pamica/tests/test_wrapper_backends.py::test_unfitted_accessors_raise_not_fitted[torch] +[gw3] [ 74%] PASSED pamica/tests/test_wrapper_backends.py::test_unfitted_accessors_raise_not_fitted[torch] +pamica/tests/test_wrapper_backends.py::test_unfitted_accessors_raise_not_fitted[mlx] +[gw3] [ 74%] PASSED pamica/tests/test_wrapper_backends.py::test_unfitted_accessors_raise_not_fitted[mlx] +pamica/tests/test_wrapper_backends.py::test_degenerate_fit_is_refused_on_both_backends[torch] +[gw3] [ 74%] PASSED pamica/tests/test_wrapper_backends.py::test_degenerate_fit_is_refused_on_both_backends[torch] +pamica/tests/test_wrapper_backends.py::test_degenerate_fit_is_refused_on_both_backends[mlx] +[gw3] [ 74%] PASSED pamica/tests/test_wrapper_backends.py::test_degenerate_fit_is_refused_on_both_backends[mlx] +pamica/tests/test_wrapper_backends.py::test_repr_names_the_backend_and_state[torch] +[gw3] [ 74%] PASSED pamica/tests/test_wrapper_backends.py::test_repr_names_the_backend_and_state[torch] +pamica/tests/test_wrapper_backends.py::test_repr_names_the_backend_and_state[mlx] +[gw4] [ 74%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_one_mstep_matches_torch_twin[3-3] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs4-pcakeep-torch] +[gw4] [ 74%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs4-pcakeep-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs4-pcakeep-numpy] +[gw3] [ 75%] PASSED pamica/tests/test_wrapper_backends.py::test_repr_names_the_backend_and_state[mlx] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs4-pcakeep-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs4-pcakeep-mlx] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs4-pcakeep-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs5-pcadb-torch] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs5-pcadb-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs5-pcadb-numpy] +pamica/tests/test_wrapper_backends.py::test_params_file_drives_the_mlx_backend +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs5-pcadb-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs5-pcadb-mlx] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs5-pcadb-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs6-pcadb-torch] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs6-pcadb-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs6-pcadb-numpy] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs6-pcadb-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs6-pcadb-mlx] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs6-pcadb-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs7-pcadb-torch] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs7-pcadb-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs7-pcadb-numpy] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs7-pcadb-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs7-pcadb-mlx] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs7-pcadb-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs8-pcadb-torch] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs8-pcadb-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs8-pcadb-numpy] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs8-pcadb-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs8-pcadb-mlx] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs8-pcadb-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs9-pcadb-torch] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs9-pcadb-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs9-pcadb-numpy] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs9-pcadb-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs9-pcadb-mlx] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs9-pcadb-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs10-pcadb-torch] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs10-pcadb-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs10-pcadb-numpy] +[gw4] [ 75%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs10-pcadb-numpy] +pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs10-pcadb-mlx] +[gw4] [ 76%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_invalid_request_raises_at_construction[kwargs10-pcadb-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs0-torch] +[gw4] [ 76%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs0-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs0-mlx] +[gw4] [ 76%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs0-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs1-torch] +[gw4] [ 76%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs1-torch] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs1-mlx] +[gw4] [ 76%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs1-mlx] +pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs2-torch] +[gw4] [ 76%] PASSED pamica/tests/test_pca_reduction_cross_backend.py::test_mir_step_rejects_a_reduction_request_up_front[kwargs2-torch] +pamica/tests/test_wrapper_backends.py::test_torch_and_mlx_wrappers_find_the_same_components[20] +[gw3] [ 76%] PASSED pamica/tests/test_wrapper_backends.py::test_params_file_drives_the_mlx_backend +pamica/tests/test_wrapper_backends.py::test_json_params_file_drives_the_mlx_backend +[gw3] [ 76%] PASSED pamica/tests/test_wrapper_backends.py::test_json_params_file_drives_the_mlx_backend +pamica/tests/test_wrapper_backends.py::test_params_file_warning_names_the_torch_backend +[gw3] [ 76%] PASSED pamica/tests/test_wrapper_backends.py::test_params_file_warning_names_the_torch_backend +pamica/tests/test_wrapper_backends.py::test_wrapper_resolves_the_backends_own_defaults[torch] +[gw3] [ 76%] PASSED pamica/tests/test_wrapper_backends.py::test_wrapper_resolves_the_backends_own_defaults[torch] +pamica/tests/test_wrapper_backends.py::test_wrapper_resolves_the_backends_own_defaults[mlx] +[gw3] [ 76%] PASSED pamica/tests/test_wrapper_backends.py::test_wrapper_resolves_the_backends_own_defaults[mlx] +pamica/tests/test_wrapper_backends.py::test_default_wrapper_fit_is_the_default_backend_fit[torch] +[gw4] [ 76%] PASSED pamica/tests/test_wrapper_backends.py::test_torch_and_mlx_wrappers_find_the_same_components[20] +pamica/tests/test_wrapper_backends.py::test_wrapper_accessors_agree_across_backends +[gw4] [ 76%] PASSED pamica/tests/test_wrapper_backends.py::test_wrapper_accessors_agree_across_backends +pamica/tests/test_wrapper_backends.py::test_malformed_mlx_payload_raises_a_named_error[missing_params] +[gw4] [ 76%] PASSED pamica/tests/test_wrapper_backends.py::test_malformed_mlx_payload_raises_a_named_error[missing_params] +pamica/tests/test_wrapper_backends.py::test_malformed_mlx_payload_raises_a_named_error[non_tensor_param] +[gw4] [ 76%] PASSED pamica/tests/test_wrapper_backends.py::test_malformed_mlx_payload_raises_a_named_error[non_tensor_param] +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_save_requires_fit +[gw4] [ 76%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_save_requires_fit +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_save_load_roundtrip +[gw4] [ 76%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_save_load_roundtrip +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_load_rejects_unknown_version +[gw4] [ 76%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_load_rejects_unknown_version +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_default_device_avoids_mps_float64 +[gw4] [ 76%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_default_device_avoids_mps_float64 +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_raw_backend_default_construction_uses_cpu_on_mps +[gw4] [ 76%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_raw_backend_default_construction_uses_cpu_on_mps +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_raw_backend_default_fit_runs_on_cpu_on_mps +[gw4] [ 76%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_raw_backend_default_fit_runs_on_cpu_on_mps +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_raw_backend_float32_auto_selection_keeps_mps +[gw4] [ 77%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_raw_backend_float32_auto_selection_keeps_mps +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_raw_backend_explicit_mps_float64_raises +[gw4] [ 77%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_raw_backend_explicit_mps_float64_raises +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_load_without_a_device_uses_the_backend_choice +[gw4] [ 77%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_load_without_a_device_uses_the_backend_choice +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_explicit_mps_float64_raises +[gw4] [ 77%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_explicit_mps_float64_raises +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_mps_float32_escape_hatch +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_import_pamica_never_imports_mlx +pamica/tests/test_wrapper_backends.py::test_explicit_lrate_overrides_the_backend_default[torch] +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_explicit_lrate_overrides_the_backend_default[torch] +pamica/tests/test_wrapper_backends.py::test_explicit_lrate_overrides_the_backend_default[mlx] +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_explicit_lrate_overrides_the_backend_default[mlx] +pamica/tests/test_wrapper_backends.py::test_pcakeep_through_the_mlx_wrapper +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_pcakeep_through_the_mlx_wrapper +pamica/tests/test_wrapper_backends.py::test_mir_step_gate_through_the_mlx_wrapper +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_mir_step_gate_through_the_mlx_wrapper +pamica/tests/test_wrapper_backends.py::test_save_load_round_trip[torch] +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_save_load_round_trip[torch] +pamica/tests/test_wrapper_backends.py::test_save_load_round_trip[mlx] +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_save_load_round_trip[mlx] +pamica/tests/test_wrapper_backends.py::test_mlx_params_round_trip_with_their_dtypes +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_mlx_params_round_trip_with_their_dtypes +pamica/tests/test_wrapper_backends.py::test_mlx_bool_array_survives_the_payload_conversion +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_mlx_bool_array_survives_the_payload_conversion +pamica/tests/test_wrapper_backends.py::test_unsavable_state_value_names_its_key_path[config-restart_seeds-value0] +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_unsavable_state_value_names_its_key_path[config-restart_seeds-value0] +pamica/tests/test_wrapper_backends.py::test_unsavable_state_value_names_its_key_path[extra-good_idx-value1] +[gw1] [ 77%] PASSED pamica/tests/test_wrapper_backends.py::test_unsavable_state_value_names_its_key_path[extra-good_idx-value1] +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_llt_partial_final_block +[gw4] [ 77%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_mps_float32_escape_hatch +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_requires_fit +[gw4] [ 77%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_requires_fit +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_variance_order_requires_fit +[gw4] [ 77%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_variance_order_requires_fit +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_bytes +[gw4] [ 77%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_bytes +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_loadmodout_readable +[gw4] [ 77%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_loadmodout_readable +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_variance_order +[gw4] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_variance_order +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_ll_matches_kept_iterate +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_llt_partial_final_block +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_from_state_dict_write_amica_output_omits_llt +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_from_state_dict_write_amica_output_omits_llt +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_wrapper_fit_transform_real_data +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_ng_wrapper_fit_transform_real_data +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_fit_exposes_converged_and_stop_reason +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_fit_exposes_converged_and_stop_reason +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_unfitted_output_raises_not_fitted +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_unfitted_output_raises_not_fitted +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_degenerate_fit_refuses_output +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_degenerate_fit_refuses_output +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_composes_unmixing_the_documented_way +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_composes_unmixing_the_documented_way +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_pmi_matches_pairwise_mi_on_transform +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_pmi_matches_pairwise_mi_on_transform +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_and_pmi_honour_model_idx +[gw2] [ 78%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_full_fit_ll_matches_torch_float64[3-3] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_full_fit_ll_matches_torch_float64[4-1] +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_and_pmi_honour_model_idx +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_and_pmi_honour_nbins +[gw5] [ 78%] PASSED pamica/tests/test_schedule_gates.py::test_newt_start_zero_fits_exactly_as_one[torch] +pamica/tests/test_schedule_gates.py::test_newt_start_zero_fits_exactly_as_one[numpy] +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_and_pmi_honour_nbins +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_real_fitted_unmixing_is_large_and_positive +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_real_fitted_unmixing_is_large_and_positive +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_populates_history_at_right_iterations +[gw4] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_ll_matches_kept_iterate +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_llt_roundtrip +[gw4] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_llt_roundtrip +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_llt_multimodel +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_populates_history_at_right_iterations +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_zero_leaves_history_empty +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_zero_leaves_history_empty +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_negative_raises +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_negative_raises +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_max_iter_zero_raises +[gw1] [ 78%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_max_iter_zero_raises +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_failing_mir_waypoint_does_not_kill_the_fit +[gw4] [ 79%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_llt_multimodel +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_loadmodout_sources_reproduce_live_transform_multimodel +[gw1] [ 79%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_failing_mir_waypoint_does_not_kill_the_fit +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_zero_matches_omitted_argument +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_default_wrapper_fit_is_the_default_backend_fit[torch] +pamica/tests/test_wrapper_backends.py::test_default_wrapper_fit_is_the_default_backend_fit[mlx] +[gw1] [ 79%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_zero_matches_omitted_argument +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_raises_under_pca_reduction +[gw1] [ 79%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_raises_under_pca_reduction +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_raises_under_pca_reduction_up_front +[gw1] [ 79%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_step_raises_under_pca_reduction_up_front +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_bundled_input_param_passes_the_mir_step_gate +[gw4] [ 79%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_loadmodout_sources_reproduce_live_transform_multimodel +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_written_w_bytes_are_genuine_fortran_layout +[gw4] [ 79%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_written_w_bytes_are_genuine_fortran_layout +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_load_results_returns_internal_w_multimodel +[gw4] [ 79%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_load_results_returns_internal_w_multimodel +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_loadmodout_sources_roundtrip_with_share_comps +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_default_wrapper_fit_is_the_default_backend_fit[mlx] +pamica/tests/test_wrapper_backends.py::test_weights_only_safe_converts_scalars_and_names_nested_paths +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_weights_only_safe_converts_scalars_and_names_nested_paths +pamica/tests/test_wrapper_backends.py::test_numpy_scalar_settings_save_and_load[torch] +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_numpy_scalar_settings_save_and_load[torch] +pamica/tests/test_wrapper_backends.py::test_numpy_scalar_settings_save_and_load[mlx] +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_numpy_scalar_settings_save_and_load[mlx] +pamica/tests/test_wrapper_backends.py::test_v2_payload_without_a_backend_is_malformed +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_v2_payload_without_a_backend_is_malformed +pamica/tests/test_wrapper_backends.py::test_unknown_format_version_names_the_readable_ones +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_unknown_format_version_names_the_readable_ones +pamica/tests/test_wrapper_backends.py::test_mlx_payload_with_a_device_raises +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_mlx_payload_with_a_device_raises +pamica/tests/test_wrapper_backends.py::test_mlx_payload_without_mlx_names_the_backend +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_mlx_payload_without_mlx_names_the_backend +pamica/tests/test_wrapper_backends.py::test_mlx_eeglab_export_reloads_through_loadmodout[None] +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_mlx_eeglab_export_reloads_through_loadmodout[None] +pamica/tests/test_wrapper_backends.py::test_mlx_eeglab_export_reloads_through_loadmodout[20] +[gw3] [ 79%] PASSED pamica/tests/test_wrapper_backends.py::test_mlx_eeglab_export_reloads_through_loadmodout[20] +pamica/tests/test_wrapper_backends.py::test_torch_and_mlx_wrappers_find_the_same_components[None] +[gw1] [ 79%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_bundled_input_param_passes_the_mir_step_gate +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_raises_under_auto_detected_rank_reduction +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_raises_under_auto_detected_rank_reduction +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_full_rank_succeeds +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_mir_full_rank_succeeds +pamica/tests/torch_tests/test_edge_cases.py::test_fit_rejects_non_2d_input +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_edge_cases.py::test_fit_rejects_non_2d_input +pamica/tests/torch_tests/test_edge_cases.py::test_single_channel_fit_is_graceful +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_edge_cases.py::test_single_channel_fit_is_graceful +pamica/tests/torch_tests/test_edge_cases.py::test_single_sample_is_graceful +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_edge_cases.py::test_single_sample_is_graceful +pamica/tests/torch_tests/test_edge_cases.py::test_from_params_file_reads_and_overrides +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_edge_cases.py::test_from_params_file_reads_and_overrides +pamica/tests/torch_tests/test_edge_cases.py::test_load_rejects_missing_backend_key +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_edge_cases.py::test_load_rejects_missing_backend_key +pamica/tests/torch_tests/test_ng_backend.py::test_sufficient_stats_match_numpy_reference +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_sufficient_stats_match_numpy_reference +pamica/tests/torch_tests/test_ng_backend.py::test_newton_direction_matches_formula +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_newton_direction_matches_formula +pamica/tests/torch_tests/test_ng_backend.py::test_newton_posdef_mstep_composition +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_newton_posdef_mstep_composition +pamica/tests/torch_tests/test_ng_backend.py::test_newton_stats_match_at_rho_boundaries[1.0] +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_newton_stats_match_at_rho_boundaries[1.0] +pamica/tests/torch_tests/test_ng_backend.py::test_newton_stats_match_at_rho_boundaries[2.0] +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_newton_stats_match_at_rho_boundaries[2.0] +pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_sufficient_stats_match_numpy_reference +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_sufficient_stats_match_numpy_reference +pamica/tests/torch_tests/test_ng_backend.py::test_single_model_bias_c_stays_zero +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_single_model_bias_c_stays_zero +pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_bias_c_is_responsibility_weighted_data_mean +[gw1] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_bias_c_is_responsibility_weighted_data_mean +pamica/tests/torch_tests/test_ng_backend.py::test_newton_multimodel_finite_and_shaped +[gw3] [ 80%] PASSED pamica/tests/test_wrapper_backends.py::test_torch_and_mlx_wrappers_find_the_same_components[None] +pamica/tests/torch_tests/test_ng_backend.py::test_blocking_invariance +[gw4] [ 80%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_loadmodout_sources_roundtrip_with_share_comps +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_loadmodout_llt_gm_reorder_alignment +[gw3] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_blocking_invariance +pamica/tests/torch_tests/test_ng_backend.py::test_blocking_invariance_multimodel_bias +[gw3] [ 80%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_blocking_invariance_multimodel_bias +pamica/tests/torch_tests/test_ng_backend.py::test_reported_ll_includes_jacobian_near_fortran_at_init +[gw4] [ 80%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_loadmodout_llt_gm_reorder_alignment +pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_llt_reject_zeroes_rejected_samples +[gw3] [ 81%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_reported_ll_includes_jacobian_near_fortran_at_init +pamica/tests/torch_tests/test_ng_backend.py::test_forward_ll_per_source_factorization_order +[gw3] [ 81%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_forward_ll_per_source_factorization_order +pamica/tests/torch_tests/test_ng_backend.py::test_fit_produces_finite_unmixing_on_real_data +[gw4] [ 81%] PASSED pamica/tests/torch_tests/test_amica_ng_wrapper.py::test_write_amica_output_llt_reject_zeroes_rejected_samples +pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_rejection_keeps_bias_c_finite +[gw1] [ 81%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_newton_multimodel_finite_and_shaped +pamica/tests/torch_tests/test_ng_backend.py::test_newton_three_model_finite_and_shaped +[gw3] [ 81%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_fit_produces_finite_unmixing_on_real_data +pamica/tests/torch_tests/test_ng_backend.py::test_newton_stats_match_numpy_reference +[gw5] [ 81%] PASSED pamica/tests/test_schedule_gates.py::test_newt_start_zero_fits_exactly_as_one[numpy] +pamica/tests/test_schedule_gates.py::test_newt_start_zero_fits_exactly_as_one[mlx] +[gw3] [ 81%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_newton_stats_match_numpy_reference +pamica/tests/torch_tests/test_ng_backend.py::test_newton_mstep_matches_numpy_reference +[gw3] [ 81%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_newton_mstep_matches_numpy_reference +pamica/tests/torch_tests/test_ng_backend.py::test_newton_finalize_uses_preupdate_mu +[gw3] [ 81%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_newton_finalize_uses_preupdate_mu +pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_single_model_is_bit_exact +[gw7] [ 81%] PASSED pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[torch-default] +pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[torch-strict] +[gw7] [ 81%] PASSED pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[torch-strict] +pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[numpy-default] +[gw5] [ 81%] PASSED pamica/tests/test_schedule_gates.py::test_newt_start_zero_fits_exactly_as_one[mlx] +pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_opens_only_after_iteration_newt_start[torch] +[gw2] [ 81%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_full_fit_ll_matches_torch_float64[4-1] +pamica/tests/test_mlx_pdf_families_cross_backend.py::test_full_fit_ll_matches_torch_float64[1-1] +[gw7] [ 81%] PASSED pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[numpy-default] +pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[numpy-strict] +[gw7] [ 81%] PASSED pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[numpy-strict] +pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[mlx-default] +[gw7] [ 81%] PASSED pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[mlx-default] +pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[mlx-strict] +[gw7] [ 81%] PASSED pamica/tests/test_component_rows.py::test_a_planted_duplicate_is_merged_and_the_model_is_unchanged[mlx-strict] +pamica/tests/test_component_rows.py::test_the_column_semantics_misses_and_breaks_a_planted_duplicate +[gw7] [ 81%] PASSED pamica/tests/test_component_rows.py::test_the_column_semantics_misses_and_breaks_a_planted_duplicate +pamica/tests/test_component_rows.py::test_the_metric_compares_the_sensor_maps[torch] +[gw7] [ 81%] PASSED pamica/tests/test_component_rows.py::test_the_metric_compares_the_sensor_maps[torch] +pamica/tests/test_component_rows.py::test_the_metric_compares_the_sensor_maps[numpy] +[gw7] [ 81%] PASSED pamica/tests/test_component_rows.py::test_the_metric_compares_the_sensor_maps[numpy] +pamica/tests/test_native_engine.py::test_platform_tag_unsupported_raises +[gw7] [ 82%] PASSED pamica/tests/test_native_engine.py::test_platform_tag_unsupported_raises +pamica/tests/test_native_engine.py::test_asset_name_alias_and_extension +[gw7] [ 82%] PASSED pamica/tests/test_native_engine.py::test_asset_name_alias_and_extension +pamica/tests/test_native_engine.py::test_verify_checksum +[gw7] [ 82%] PASSED pamica/tests/test_native_engine.py::test_verify_checksum +pamica/tests/test_native_engine.py::test_resolve_env_override +[gw7] [ 82%] PASSED pamica/tests/test_native_engine.py::test_resolve_env_override +pamica/tests/test_native_engine.py::test_resolve_no_download_without_cache +[gw7] [ 82%] PASSED pamica/tests/test_native_engine.py::test_resolve_no_download_without_cache +pamica/tests/test_native_engine.py::test_resolve_download_verifies_and_caches +[gw7] [ 82%] PASSED pamica/tests/test_native_engine.py::test_resolve_download_verifies_and_caches +pamica/tests/test_native_engine.py::test_resolve_bad_checksum_does_not_poison_cache +[gw7] [ 82%] PASSED pamica/tests/test_native_engine.py::test_resolve_bad_checksum_does_not_poison_cache +pamica/tests/test_native_engine.py::test_native_engine_runs_and_produces_amica_output +[gw7] [ 82%] SKIPPED pamica/tests/test_native_engine.py::test_native_engine_runs_and_produces_amica_output +pamica/tests/test_native_engine.py::test_native_engine_asymmetric_sphere_reads_the_right_orientation +[gw7] [ 82%] SKIPPED pamica/tests/test_native_engine.py::test_native_engine_asymmetric_sphere_reads_the_right_orientation +pamica/tests/test_native_engine.py::test_native_engine_param_aliases_and_multimodel +[gw7] [ 82%] SKIPPED pamica/tests/test_native_engine.py::test_native_engine_param_aliases_and_multimodel +pamica/tests/test_native_engine.py::test_native_engine_degenerate_fit_raises_clearly +[gw7] [ 82%] SKIPPED pamica/tests/test_native_engine.py::test_native_engine_degenerate_fit_raises_clearly +pamica/tests/test_native_engine.py::test_native_engine_rejects_non_2d +[gw7] [ 82%] SKIPPED pamica/tests/test_native_engine.py::test_native_engine_rejects_non_2d +pamica/tests/test_native_engine.py::test_native_engine_missing_binary_errors +[gw7] [ 82%] PASSED pamica/tests/test_native_engine.py::test_native_engine_missing_binary_errors +pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_likelihood_leaves_the_same_finite_history[torch] +[gw7] [ 82%] PASSED pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_likelihood_leaves_the_same_finite_history[torch] +pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_likelihood_leaves_the_same_finite_history[numpy] +[gw7] [ 82%] PASSED pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_likelihood_leaves_the_same_finite_history[numpy] +pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_likelihood_leaves_the_same_finite_history[mlx] +[gw7] [ 82%] PASSED pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_likelihood_leaves_the_same_finite_history[mlx] +pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[torch-dAk] +[gw7] [ 82%] PASSED pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[torch-dAk] +pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[torch-ndtmpsum] +[gw7] [ 82%] PASSED pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[torch-ndtmpsum] +pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[numpy-dAk] +[gw7] [ 82%] PASSED pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[numpy-dAk] +pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[numpy-ndtmpsum] +[gw7] [ 82%] PASSED pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[numpy-ndtmpsum] +pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[mlx-dAk] +[gw7] [ 82%] PASSED pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[mlx-dAk] +pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[mlx-ndtmpsum] +[gw5] [ 83%] PASSED pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_opens_only_after_iteration_newt_start[torch] +pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_opens_only_after_iteration_newt_start[numpy] +[gw7] [ 83%] PASSED pamica/tests/test_nonfinite_stops.py::test_a_nonfinite_direction_stops_before_the_update[mlx-ndtmpsum] +pamica/tests/test_nonfinite_stops.py::test_nonfinite_parameters_after_the_last_update_stop_the_fit[torch] +[gw7] [ 83%] PASSED pamica/tests/test_nonfinite_stops.py::test_nonfinite_parameters_after_the_last_update_stop_the_fit[torch] +pamica/tests/test_nonfinite_stops.py::test_nonfinite_parameters_after_the_last_update_stop_the_fit[numpy] +[gw7] [ 83%] PASSED pamica/tests/test_nonfinite_stops.py::test_nonfinite_parameters_after_the_last_update_stop_the_fit[numpy] +pamica/tests/test_nonfinite_stops.py::test_nonfinite_parameters_after_the_last_update_stop_the_fit[mlx] +[gw7] [ 83%] PASSED pamica/tests/test_nonfinite_stops.py::test_nonfinite_parameters_after_the_last_update_stop_the_fit[mlx] +pamica/tests/test_nonfinite_stops.py::test_numpy_restart_window_takes_only_what_a_restart_repairs[params_A-True] +[gw7] [ 83%] PASSED pamica/tests/test_nonfinite_stops.py::test_numpy_restart_window_takes_only_what_a_restart_repairs[params_A-True] +pamica/tests/test_nonfinite_stops.py::test_numpy_restart_window_takes_only_what_a_restart_repairs[params-False] +[gw7] [ 83%] PASSED pamica/tests/test_nonfinite_stops.py::test_numpy_restart_window_takes_only_what_a_restart_repairs[params-False] +pamica/tests/test_numpy_block_tuning.py::test_search_is_now_off_by_default +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_search_is_now_off_by_default +pamica/tests/test_numpy_block_tuning.py::test_bare_default_fit_runs_at_the_shipped_block_size +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_bare_default_fit_runs_at_the_shipped_block_size +pamica/tests/test_numpy_block_tuning.py::test_tuner_runs_on_the_reduced_channel_count +[gw1] [ 83%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_newton_three_model_finite_and_shaped +pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_bias_c_matches_numpy_reference +[gw1] [ 83%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_bias_c_matches_numpy_reference +pamica/tests/torch_tests/test_ng_backend.py::test_numpy_multimodel_bias_c_updates +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_tuner_runs_on_the_reduced_channel_count +pamica/tests/test_numpy_block_tuning.py::test_default_sweep_bounds_match_the_other_backends +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_default_sweep_bounds_match_the_other_backends +pamica/tests/test_numpy_block_tuning.py::test_block_size_untouched_when_search_is_off +[gw1] [ 83%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_numpy_multimodel_bias_c_updates +pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_transform_applies_bias_c +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_block_size_untouched_when_search_is_off +pamica/tests/test_numpy_block_tuning.py::test_sweep_bounds_are_not_validated_when_search_is_off +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_sweep_bounds_are_not_validated_when_search_is_off +pamica/tests/test_numpy_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs0-blk_min must be >= 1] +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs0-blk_min must be >= 1] +pamica/tests/test_numpy_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs1-blk_step must be >= 1] +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs1-blk_step must be >= 1] +pamica/tests/test_numpy_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs2-blk_max must be >= blk_min] +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs2-blk_max must be >= blk_min] +pamica/tests/test_numpy_block_tuning.py::test_naive_helper_is_gone_not_deprecated +[gw7] [ 83%] PASSED pamica/tests/test_numpy_block_tuning.py::test_naive_helper_is_gone_not_deprecated +pamica/tests/test_numpy_block_tuning.py::test_chosen_block_size_is_a_valid_candidate_and_is_logged +[gw1] [ 84%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_transform_applies_bias_c +pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_dead_model_keeps_prior_c +[gw1] [ 84%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_dead_model_keeps_prior_c +pamica/tests/torch_tests/test_ng_backend.py::test_rejection_degenerate_ll_raises_clear_error +[gw1] [ 84%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_rejection_degenerate_ll_raises_clear_error +pamica/tests/torch_tests/test_ng_backend.py::test_reject_param_validation +[gw1] [ 84%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_reject_param_validation +pamica/tests/torch_tests/test_ng_backend.py::test_rejection_shrinks_good_sample_set +[gw0] [ 84%] PASSED pamica/tests/mlx_tests/test_mlx_backend.py::test_rholrate_ratchets_at_maxdecs_not_per_decrease +pamica/tests/mlx_tests/test_mlx_backend.py::test_rholrate_ceiling_ratchet_gated_on_newt_start +[gw7] [ 84%] PASSED pamica/tests/test_numpy_block_tuning.py::test_chosen_block_size_is_a_valid_candidate_and_is_logged +pamica/tests/test_numpy_block_tuning.py::test_candidates_never_exceed_the_sample_count +[gw7] [ 84%] PASSED pamica/tests/test_numpy_block_tuning.py::test_candidates_never_exceed_the_sample_count +pamica/tests/test_numpy_block_tuning.py::test_post_tune_fit_is_bit_identical_to_a_direct_fit +[gw4] [ 84%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_multimodel_rejection_keeps_bias_c_finite +pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_requires_fit +[gw4] [ 84%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_requires_fit +pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_roundtrip_all_fields +[gw7] [ 84%] PASSED pamica/tests/test_numpy_block_tuning.py::test_post_tune_fit_is_bit_identical_to_a_direct_fit +pamica/tests/test_numpy_block_tuning.py::test_post_tune_fit_is_bit_identical_under_do_reject +[gw7] [ 84%] PASSED pamica/tests/test_numpy_block_tuning.py::test_post_tune_fit_is_bit_identical_under_do_reject +pamica/tests/torch_tests/test_ng_block_tuning.py::test_defaults_are_the_shared_re_derived_bounds +[gw7] [ 84%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_defaults_are_the_shared_re_derived_bounds +pamica/tests/torch_tests/test_ng_block_tuning.py::test_block_size_untouched_when_search_is_off +[gw7] [ 84%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_block_size_untouched_when_search_is_off +pamica/tests/torch_tests/test_ng_block_tuning.py::test_sweep_bounds_are_not_validated_when_search_is_off +[gw7] [ 84%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_sweep_bounds_are_not_validated_when_search_is_off +pamica/tests/torch_tests/test_ng_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs0-blk_min must be >= 1] +[gw7] [ 84%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs0-blk_min must be >= 1] +pamica/tests/torch_tests/test_ng_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs1-blk_step must be >= 1] +[gw7] [ 84%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs1-blk_step must be >= 1] +pamica/tests/torch_tests/test_ng_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs2-blk_max must be >= blk_min] +[gw7] [ 84%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs2-blk_max must be >= blk_min] +pamica/tests/torch_tests/test_ng_block_tuning.py::test_chosen_block_size_is_a_valid_candidate_and_is_logged +[gw7] [ 84%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_chosen_block_size_is_a_valid_candidate_and_is_logged +pamica/tests/torch_tests/test_ng_block_tuning.py::test_probes_leave_block_size_and_parameters_untouched +[gw2] [ 84%] PASSED pamica/tests/test_mlx_pdf_families_cross_backend.py::test_full_fit_ll_matches_torch_float64[1-1] +pamica/tests/test_mlx_reject_cross_backend.py::test_reject_decisions_agree_up_to_float32_rounding[1-7] +[gw7] [ 84%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_probes_leave_block_size_and_parameters_untouched +pamica/tests/torch_tests/test_ng_block_tuning.py::test_allocation_failure_falls_back_to_the_last_working_size +[gw5] [ 85%] PASSED pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_opens_only_after_iteration_newt_start[numpy] +pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_opens_only_after_iteration_newt_start[mlx] +[gw2] [ 85%] PASSED pamica/tests/test_mlx_reject_cross_backend.py::test_reject_decisions_agree_up_to_float32_rounding[1-7] +pamica/tests/test_mlx_reject_cross_backend.py::test_reject_decisions_agree_up_to_float32_rounding[1-8] +[gw7] [ 85%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_allocation_failure_falls_back_to_the_last_working_size +pamica/tests/torch_tests/test_ng_block_tuning.py::test_a_real_error_in_the_probe_is_not_swallowed +[gw7] [ 85%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_a_real_error_in_the_probe_is_not_swallowed +pamica/tests/torch_tests/test_ng_block_tuning.py::test_wrapper_forwards_the_search_kwargs +[gw2] [ 85%] PASSED pamica/tests/test_mlx_reject_cross_backend.py::test_reject_decisions_agree_up_to_float32_rounding[1-8] +pamica/tests/test_mlx_reject_cross_backend.py::test_reject_decisions_agree_up_to_float32_rounding[2-7] +[gw5] [ 85%] PASSED pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_opens_only_after_iteration_newt_start[mlx] +pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_gate_at_the_shipped_default_newt_start[torch] +[gw7] [ 85%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_wrapper_forwards_the_search_kwargs +pamica/tests/torch_tests/test_ng_block_tuning.py::test_state_dict_round_trips_the_tuned_block_size +[gw2] [ 85%] PASSED pamica/tests/test_mlx_reject_cross_backend.py::test_reject_decisions_agree_up_to_float32_rounding[2-7] +pamica/tests/test_mlx_reject_cross_backend.py::test_reject_decisions_agree_up_to_float32_rounding[2-8] +[gw7] [ 85%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_state_dict_round_trips_the_tuned_block_size +pamica/tests/torch_tests/test_ng_convergence.py::test_min_dll_stop_matches_independent_reference +[gw1] [ 85%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_rejection_shrinks_good_sample_set +pamica/tests/torch_tests/test_ng_block_tuning.py::test_candidates_never_exceed_the_sample_count +[gw1] [ 85%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_candidates_never_exceed_the_sample_count +pamica/tests/torch_tests/test_ng_block_tuning.py::test_tuner_runs_on_the_reduced_channel_count +[gw5] [ 85%] PASSED pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_gate_at_the_shipped_default_newt_start[torch] +pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_gate_at_the_shipped_default_newt_start[numpy] +[gw2] [ 85%] PASSED pamica/tests/test_mlx_reject_cross_backend.py::test_reject_decisions_agree_up_to_float32_rounding[2-8] +pamica/tests/test_mlx_reject_cross_backend.py::test_reject_agreement_check_catches_a_divergence[threshold] +[gw1] [ 85%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_tuner_runs_on_the_reduced_channel_count +pamica/tests/torch_tests/test_ng_block_tuning.py::test_tuner_runs_for_multiple_models +[gw2] [ 85%] PASSED pamica/tests/test_mlx_reject_cross_backend.py::test_reject_agreement_check_catches_a_divergence[threshold] +pamica/tests/test_mlx_reject_cross_backend.py::test_reject_agreement_check_catches_a_divergence[trajectory] +[gw1] [ 85%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_tuner_runs_for_multiple_models +pamica/tests/torch_tests/test_ng_block_tuning.py::test_small_data_degrades_to_a_single_clamped_candidate +[gw1] [ 85%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_small_data_degrades_to_a_single_clamped_candidate +pamica/tests/torch_tests/test_ng_block_tuning.py::test_available_memory_falls_back_to_host_ram_on_cpu +[gw1] [ 85%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_available_memory_falls_back_to_host_ram_on_cpu +pamica/tests/torch_tests/test_ng_block_tuning.py::test_search_runs_under_do_reject +[gw5] [ 85%] PASSED pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_gate_at_the_shipped_default_newt_start[numpy] +pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_gate_at_the_shipped_default_newt_start[mlx] +[gw2] [ 85%] PASSED pamica/tests/test_mlx_reject_cross_backend.py::test_reject_agreement_check_catches_a_divergence[trajectory] +pamica/tests/test_mlx_reject_cross_backend.py::test_reject_x_pdftype1_kurtosis_switch_matches_across_backends +[gw1] [ 86%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_search_runs_under_do_reject +pamica/tests/torch_tests/test_ng_block_tuning.py::test_post_tune_fit_is_bit_identical_to_a_direct_fit +[gw5] [ 86%] PASSED pamica/tests/test_schedule_gates.py::test_rho_rate_ratchet_gate_at_the_shipped_default_newt_start[mlx] +pamica/tests/test_schedule_gates.py::test_newton_switch_on_clears_the_decrease_counter[torch] +[gw5] [ 86%] PASSED pamica/tests/test_schedule_gates.py::test_newton_switch_on_clears_the_decrease_counter[torch] +pamica/tests/test_schedule_gates.py::test_newton_switch_on_clears_the_decrease_counter[numpy] +[gw5] [ 86%] PASSED pamica/tests/test_schedule_gates.py::test_newton_switch_on_clears_the_decrease_counter[numpy] +pamica/tests/test_schedule_gates.py::test_newton_switch_on_clears_the_decrease_counter[mlx] +[gw5] [ 86%] PASSED pamica/tests/test_schedule_gates.py::test_newton_switch_on_clears_the_decrease_counter[mlx] +pamica/tests/test_schedule_gates.py::test_rejection_first_fires_on_iteration_rejstart[torch] +[gw4] [ 86%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_roundtrip_all_fields +pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_refuses_degenerate_model +[gw2] [ 86%] PASSED pamica/tests/test_mlx_reject_cross_backend.py::test_reject_x_pdftype1_kurtosis_switch_matches_across_backends +pamica/tests/test_mlx_reject_cross_backend.py::test_mir_matches_torch_on_identical_parameters +[gw4] [ 86%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_refuses_degenerate_model +pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_refuses_nonfinite_params +[gw4] [ 86%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_refuses_nonfinite_params +pamica/tests/torch_tests/test_ng_backend.py::test_write_amica_output_refuses_degenerate_model +[gw2] [ 86%] PASSED pamica/tests/test_mlx_reject_cross_backend.py::test_mir_matches_torch_on_identical_parameters +pamica/tests/test_mlx_sharing_cross_backend.py::test_merge_decision_matches_the_torch_backend +[gw4] [ 86%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_write_amica_output_refuses_degenerate_model +pamica/tests/torch_tests/test_ng_backend.py::test_write_amica_output_refuses_nonfinite_params +[gw2] [ 86%] PASSED pamica/tests/test_mlx_sharing_cross_backend.py::test_merge_decision_matches_the_torch_backend +pamica/tests/test_mlx_sharing_cross_backend.py::test_gm_prev_weighting_matches_torch[False] +[gw4] [ 86%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_write_amica_output_refuses_nonfinite_params +pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_snapshots_not_aliases +[gw4] [ 86%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_state_dict_snapshots_not_aliases +pamica/tests/torch_tests/test_ng_backend.py::test_end_to_end_correlation_vs_fortran +[gw2] [ 86%] PASSED pamica/tests/test_mlx_sharing_cross_backend.py::test_gm_prev_weighting_matches_torch[False] +pamica/tests/test_mlx_sharing_cross_backend.py::test_gm_prev_weighting_matches_torch[True] +[gw2] [ 86%] PASSED pamica/tests/test_mlx_sharing_cross_backend.py::test_gm_prev_weighting_matches_torch[True] +pamica/tests/test_mlx_sharing_cross_backend.py::test_comp_used_before_fit_raises_in_both_backends +[gw2] [ 86%] PASSED pamica/tests/test_mlx_sharing_cross_backend.py::test_comp_used_before_fit_raises_in_both_backends +pamica/tests/test_mlx_transform_cross_backend.py::test_transform_matches_float64_torch_twin +[gw5] [ 86%] PASSED pamica/tests/test_schedule_gates.py::test_rejection_first_fires_on_iteration_rejstart[torch] +pamica/tests/test_schedule_gates.py::test_rejection_first_fires_on_iteration_rejstart[numpy] +[gw2] [ 86%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_transform_matches_float64_torch_twin +pamica/tests/test_mlx_transform_cross_backend.py::test_multimodel_transform_matches_float64_twin_with_c_centering +[gw1] [ 86%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_post_tune_fit_is_bit_identical_to_a_direct_fit +pamica/tests/torch_tests/test_ng_convergence.py::test_new_stop_reasons_are_not_degenerate +[gw1] [ 87%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_new_stop_reasons_are_not_degenerate +pamica/tests/torch_tests/test_ng_convergence.py::test_min_dll_stop_leaves_backend_usable +[gw2] [ 87%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_multimodel_transform_matches_float64_twin_with_c_centering +pamica/tests/test_mlx_transform_cross_backend.py::test_accessors_match_float64_torch_twin +[gw2] [ 87%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_accessors_match_float64_torch_twin +pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_matches_float64_twin +[gw2] [ 87%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_matches_float64_twin +pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_check_catches_a_divergence[reversed-outside the float32 band] +[gw2] [ 87%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_check_catches_a_divergence[reversed-outside the float32 band] +pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_check_catches_a_divergence[shuffled-outside the float32 band] +[gw2] [ 87%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_check_catches_a_divergence[shuffled-outside the float32 band] +pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_check_catches_a_divergence[closest_pair_swap-outside the float32 band] +[gw2] [ 87%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_check_catches_a_divergence[closest_pair_swap-outside the float32 band] +pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_check_catches_a_divergence[inflated_variance-float32 cap] +[gw2] [ 87%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_variance_order_check_catches_a_divergence[inflated_variance-float32 cap] +pamica/tests/test_mlx_transform_cross_backend.py::test_sensor_mixing_matrix_matches_twin_on_rank_reduced_fit +[gw2] [ 87%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_sensor_mixing_matrix_matches_twin_on_rank_reduced_fit +pamica/tests/test_mlx_transform_cross_backend.py::test_transform_matches_forward_activations_via_twin_composition +[gw2] [ 87%] PASSED pamica/tests/test_mlx_transform_cross_backend.py::test_transform_matches_forward_activations_via_twin_composition +pamica/tests/test_native_engine.py::test_platform_tag[Darwin-arm64-macos-arm64] +[gw2] [ 87%] PASSED pamica/tests/test_native_engine.py::test_platform_tag[Darwin-arm64-macos-arm64] +pamica/tests/test_native_engine.py::test_platform_tag[Linux-x86_64-linux-x64] +[gw2] [ 87%] PASSED pamica/tests/test_native_engine.py::test_platform_tag[Linux-x86_64-linux-x64] +pamica/tests/test_native_engine.py::test_platform_tag[Linux-aarch64-linux-arm64] +[gw2] [ 87%] PASSED pamica/tests/test_native_engine.py::test_platform_tag[Linux-aarch64-linux-arm64] +pamica/tests/test_native_engine.py::test_platform_tag[Windows-AMD64-windows-x64] +[gw2] [ 87%] PASSED pamica/tests/test_native_engine.py::test_platform_tag[Windows-AMD64-windows-x64] +pamica/tests/test_native_engine.py::test_platform_tag[Windows-ARM64-windows-arm64] +[gw2] [ 87%] PASSED pamica/tests/test_native_engine.py::test_platform_tag[Windows-ARM64-windows-arm64] +pamica/tests/torch_tests/test_ng_convergence.py::test_mir_history_empty_after_save_load +[gw5] [ 87%] PASSED pamica/tests/test_schedule_gates.py::test_rejection_first_fires_on_iteration_rejstart[numpy] +pamica/tests/torch_tests/test_ng_convergence.py::test_do_reject_interaction_grad_norm_stop_leaves_good_idx_usable +[gw2] [ 87%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_mir_history_empty_after_save_load +pamica/tests/torch_tests/test_ng_exception_consistency.py::test_inv_failure_leaves_the_instance_degenerate +[gw2] [ 87%] PASSED pamica/tests/torch_tests/test_ng_exception_consistency.py::test_inv_failure_leaves_the_instance_degenerate +pamica/tests/torch_tests/test_ng_exception_consistency.py::test_inv_failure_under_multi_restart_also_leaves_it_degenerate +[gw2] [ 87%] PASSED pamica/tests/torch_tests/test_ng_exception_consistency.py::test_inv_failure_under_multi_restart_also_leaves_it_degenerate +pamica/tests/torch_tests/test_ng_exception_consistency.py::test_pinv_sphere_nonfinite_raise_sets_degenerate_stop_reason +[gw2] [ 87%] PASSED pamica/tests/torch_tests/test_ng_exception_consistency.py::test_pinv_sphere_nonfinite_raise_sets_degenerate_stop_reason +pamica/tests/torch_tests/test_ng_float32_stability.py::test_score_is_zero_at_zero_activation +[gw2] [ 88%] PASSED pamica/tests/torch_tests/test_ng_float32_stability.py::test_score_is_zero_at_zero_activation +pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[1-True] +[gw5] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_do_reject_interaction_grad_norm_stop_leaves_good_idx_usable +pamica/tests/torch_tests/test_ng_convergence.py::test_both_stops_disabled_never_produce_new_stop_reasons +[gw5] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_both_stops_disabled_never_produce_new_stop_reasons +pamica/tests/torch_tests/test_ng_convergence.py::test_disabled_stops_default_path_matches_max_iter_on_short_run +[gw1] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_min_dll_stop_leaves_backend_usable +pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_floor_stop_leaves_wrapper_usable +[gw1] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_floor_stop_leaves_wrapper_usable +pamica/tests/torch_tests/test_ng_convergence.py::test_keep_best_restores_genuine_overshoot_under_min_dll_stop +[gw1] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_keep_best_restores_genuine_overshoot_under_min_dll_stop +pamica/tests/torch_tests/test_ng_convergence.py::test_do_reject_interaction_grad_norm_floor_stop_leaves_good_idx_usable +[gw5] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_disabled_stops_default_path_matches_max_iter_on_short_run +pamica/tests/torch_tests/test_ng_convergence.py::test_min_dll_stop_reachable_at_shipped_default_threshold +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_min_dll_stop_matches_independent_reference +pamica/tests/torch_tests/test_ng_convergence.py::test_min_dll_never_fires_before_two_ll_values +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_min_dll_never_fires_before_two_ll_values +pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_stop_matches_independent_reference +[gw1] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_do_reject_interaction_grad_norm_floor_stop_leaves_good_idx_usable +pamica/tests/torch_tests/test_ng_convergence.py::test_do_reject_interaction_min_dll_stop_leaves_good_idx_usable +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_stop_matches_independent_reference +pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_never_fires_on_first_iteration +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_never_fires_on_first_iteration +pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_floor_fires_on_likelihood_decrease +[gw2] [ 88%] PASSED pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[1-True] +pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[2-False] +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_floor_fires_on_likelihood_decrease +pamica/tests/torch_tests/test_ng_convergence.py::test_lrate_floor_still_reachable_without_grad_norm +[gw1] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_do_reject_interaction_min_dll_stop_leaves_good_idx_usable +pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_ll_matches_float64[False] +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_lrate_floor_still_reachable_without_grad_norm +pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_shadows_grad_norm_floor_under_shipped_defaults +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_grad_norm_shadows_grad_norm_floor_under_shipped_defaults +pamica/tests/torch_tests/test_ng_convergence.py::test_a_frozen_window_still_computes_fresh_grad_norm +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_a_frozen_window_still_computes_fresh_grad_norm +pamica/tests/torch_tests/test_ng_metadata.py::test_pdftype_names_cover_all_codes +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_pdftype_names_cover_all_codes +pamica/tests/torch_tests/test_ng_metadata.py::test_get_pdftype_default_is_generalized_gaussian +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_get_pdftype_default_is_generalized_gaussian +pamica/tests/torch_tests/test_ng_metadata.py::test_get_pdftype_reflects_fixed_family +[gw7] [ 88%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_get_pdftype_reflects_fixed_family +pamica/tests/torch_tests/test_ng_metadata.py::test_get_rho_shape_and_bounds +[gw7] [ 89%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_get_rho_shape_and_bounds +pamica/tests/torch_tests/test_ng_metadata.py::test_shared_components_empty_without_sharing +[gw7] [ 89%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_shared_components_empty_without_sharing +pamica/tests/torch_tests/test_ng_metadata.py::test_shared_components_reports_partial_merges +[gw2] [ 89%] PASSED pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[2-False] +pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[3-True] +[gw7] [ 89%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_shared_components_reports_partial_merges +pamica/tests/torch_tests/test_ng_metadata.py::test_get_rho_differs_per_model +[gw7] [ 89%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_get_rho_differs_per_model +pamica/tests/torch_tests/test_ng_metadata.py::test_get_pdftype_adaptive_switcher_is_mixed +[gw7] [ 89%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_get_pdftype_adaptive_switcher_is_mixed +pamica/tests/torch_tests/test_ng_metadata.py::test_metadata_accessors_reject_bad_model_idx +[gw7] [ 89%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_metadata_accessors_reject_bad_model_idx +pamica/tests/torch_tests/test_ng_metadata.py::test_metadata_accessors_require_fit +[gw7] [ 89%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_metadata_accessors_require_fit +pamica/tests/torch_tests/test_ng_metadata.py::test_amica_wrapper_delegates_metadata +[gw5] [ 89%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_min_dll_stop_reachable_at_shipped_default_threshold +pamica/tests/torch_tests/test_ng_convergence.py::test_convergence_config_round_trips_through_state_dict +[gw5] [ 89%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_convergence_config_round_trips_through_state_dict +pamica/tests/torch_tests/test_ng_convergence.py::test_missing_convergence_keys_fall_back_to_fortran_defaults +[gw5] [ 89%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_missing_convergence_keys_fall_back_to_fortran_defaults +pamica/tests/torch_tests/test_ng_convergence.py::test_mir_history_survives_keep_best_restore +[gw7] [ 89%] PASSED pamica/tests/torch_tests/test_ng_metadata.py::test_amica_wrapper_delegates_metadata +pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_loglik_matches_internal_lht +[gw5] [ 89%] PASSED pamica/tests/torch_tests/test_ng_convergence.py::test_mir_history_survives_keep_best_restore +pamica/tests/torch_tests/test_ng_model_posterior.py::test_amica_wrapper_delegates +[gw1] [ 89%] PASSED pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_ll_matches_float64[False] +pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_ll_matches_float64[True] +[gw0] [ 89%] PASSED pamica/tests/mlx_tests/test_mlx_backend.py::test_rholrate_ceiling_ratchet_gated_on_newt_start +pamica/tests/mlx_tests/test_mlx_backend.py::test_rholrate_ceiling_resets_at_fit_start +[gw0] [ 89%] PASSED pamica/tests/mlx_tests/test_mlx_backend.py::test_rholrate_ceiling_resets_at_fit_start +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_search_is_off_by_default_with_the_shared_bounds +[gw0] [ 89%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_search_is_off_by_default_with_the_shared_bounds +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_block_size_untouched_when_search_is_off +[gw0] [ 89%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_block_size_untouched_when_search_is_off +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_sweep_bounds_are_not_validated_when_search_is_off +[gw0] [ 89%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_sweep_bounds_are_not_validated_when_search_is_off +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs0-blk_min must be >= 1] +[gw0] [ 89%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs0-blk_min must be >= 1] +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs1-blk_step must be >= 1] +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs1-blk_step must be >= 1] +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs2-blk_max must be >= blk_min] +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_sweep_bounds_are_validated_when_search_is_on[kwargs2-blk_max must be >= blk_min] +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_chosen_block_size_is_a_valid_candidate_and_is_logged +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_chosen_block_size_is_a_valid_candidate_and_is_logged +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_candidates_never_exceed_the_sample_count +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_candidates_never_exceed_the_sample_count +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_memory_cap_uses_the_recommended_working_set +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_memory_cap_uses_the_recommended_working_set +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_memory_cap_falls_back_to_memory_size +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_memory_cap_falls_back_to_memory_size +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_memory_cap_is_none_when_mlx_reports_nothing +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_memory_cap_is_none_when_mlx_reports_nothing +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_tuner_runs_on_the_reduced_channel_count +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_tuner_runs_on_the_reduced_channel_count +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_post_tune_fit_is_bit_identical_to_a_direct_fit +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_post_tune_fit_is_bit_identical_to_a_direct_fit +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_probe_evaluates_the_whole_lazy_graph +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_probe_evaluates_the_whole_lazy_graph +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_metal_allocation_failure_is_a_catchable_exception +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_metal_allocation_failure_is_a_catchable_exception +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_allocation_failure_falls_back_to_the_last_working_size +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_allocation_failure_falls_back_to_the_last_working_size +pamica/tests/mlx_tests/test_mlx_blocktune.py::test_a_real_error_in_the_probe_is_not_swallowed +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_blocktune.py::test_a_real_error_in_the_probe_is_not_swallowed +pamica/tests/mlx_tests/test_mlx_exception_consistency.py::test_274_guard_raise_leaves_the_instance_degenerate +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_exception_consistency.py::test_274_guard_raise_leaves_the_instance_degenerate +pamica/tests/mlx_tests/test_mlx_exception_consistency.py::test_274_guard_raise_under_multi_restart_also_leaves_it_degenerate +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_exception_consistency.py::test_274_guard_raise_under_multi_restart_also_leaves_it_degenerate +pamica/tests/mlx_tests/test_mlx_exception_consistency.py::test_choose_pdfs_invariant_raise_sets_degenerate_stop_reason +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_exception_consistency.py::test_choose_pdfs_invariant_raise_sets_degenerate_stop_reason +pamica/tests/mlx_tests/test_mlx_exception_consistency.py::test_pinv_sphere_nonfinite_raise_sets_degenerate_stop_reason +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_exception_consistency.py::test_pinv_sphere_nonfinite_raise_sets_degenerate_stop_reason +pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_round_trips_through_loadmodout[1] +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_round_trips_through_loadmodout[1] +pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_round_trips_through_loadmodout[2] +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_round_trips_through_loadmodout[2] +pamica/tests/mlx_tests/test_mlx_export.py::test_share_comps_export_round_trips_through_loadmodout +[gw0] [ 90%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_share_comps_export_round_trips_through_loadmodout +pamica/tests/mlx_tests/test_mlx_export.py::test_written_ll_ends_at_the_keep_best_restored_iterate +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_model_posterior.py::test_amica_wrapper_delegates +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_log_pdf_matches_fortran[2] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_log_pdf_matches_fortran[2] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_log_pdf_matches_fortran[3] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_log_pdf_matches_fortran[3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_log_pdf_matches_fortran[4] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_log_pdf_matches_fortran[4] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_log_pdf_matches_fortran[1] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_log_pdf_matches_fortran[1] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_score_matches_fortran[2] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_score_matches_fortran[2] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_score_matches_fortran[3] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_score_matches_fortran[3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_score_matches_fortran[4] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_score_matches_fortran[4] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_score_matches_fortran[1] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_score_matches_fortran[1] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_dpdf_is_minus_fp_times_pdf +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_dpdf_is_minus_fp_times_pdf +pamica/tests/torch_tests/test_ng_pdf_families.py::test_gg_path_bit_identical_none_vs_code0 +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_gg_path_bit_identical_none_vs_code0 +pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[None] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[None] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[0] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[0] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[1] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[1] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[2] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[2] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[3] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[4] +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_log_pdf_only_matches_log_pdf_and_deriv[4] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_block_size_default_is_8192 +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_block_size_default_is_8192 +pamica/tests/torch_tests/test_ng_pdf_families.py::test_pdtype_h_is_none_only_for_gg +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_pdtype_h_is_none_only_for_gg +pamica/tests/torch_tests/test_ng_pdf_families.py::test_pdftype_validation +[gw5] [ 91%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_pdftype_validation +pamica/tests/torch_tests/test_ng_pdf_families.py::test_kurt_schedule_validation +[gw5] [ 92%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_kurt_schedule_validation +pamica/tests/torch_tests/test_ng_pdf_families.py::test_pdtype_from_kurtosis_decision +[gw5] [ 92%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_pdtype_from_kurtosis_decision +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[0-3] +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_written_ll_ends_at_the_keep_best_restored_iterate +pamica/tests/mlx_tests/test_mlx_export.py::test_do_reject_zero_sentinel_is_written +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_do_reject_zero_sentinel_is_written +pamica/tests/mlx_tests/test_mlx_export.py::test_from_state_dict_model_warns_and_omits_llt +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_from_state_dict_model_warns_and_omits_llt +pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_requires_a_fitted_model +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_requires_a_fitted_model +pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_refuses_a_degenerate_fit +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_refuses_a_degenerate_fit +pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_refuses_force_set_nonfinite_param +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_refuses_force_set_nonfinite_param +pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_makes_no_extra_forward_pass +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_write_amica_output_makes_no_extra_forward_pass +pamica/tests/mlx_tests/test_mlx_export.py::test_export_matches_a_torch_twin_to_float32_precision[1] +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_export_matches_a_torch_twin_to_float32_precision[1] +pamica/tests/mlx_tests/test_mlx_export.py::test_export_matches_a_torch_twin_to_float32_precision[2] +[gw7] [ 92%] PASSED pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_loglik_matches_internal_lht +pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_probability_is_normalized +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_export.py::test_export_matches_a_torch_twin_to_float32_precision[2] +pamica/tests/mlx_tests/test_mlx_fit_noop.py::test_unscaled_fit_is_bit_identical_to_the_pre_phase3_epic_tip[1] +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_fit_noop.py::test_unscaled_fit_is_bit_identical_to_the_pre_phase3_epic_tip[1] +pamica/tests/mlx_tests/test_mlx_fit_noop.py::test_unscaled_fit_is_bit_identical_to_the_pre_phase3_epic_tip[2] +[gw5] [ 92%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[0-3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[2-3] +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_fit_noop.py::test_unscaled_fit_is_bit_identical_to_the_pre_phase3_epic_tip[2] +pamica/tests/mlx_tests/test_mlx_fit_noop.py::test_unscaled_fit_with_keep_best_off_is_also_bit_identical +[gw2] [ 92%] PASSED pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[3-True] +pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[4-False] +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_fit_noop.py::test_unscaled_fit_with_keep_best_off_is_also_bit_identical +pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_duplicated_column_raises_runtime_error_not_abort +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_duplicated_column_raises_runtime_error_not_abort +pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_duplicated_column_error_names_iteration_and_condition +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_duplicated_column_error_names_iteration_and_condition +pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_near_singular_column_raises +[gw0] [ 92%] PASSED pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_near_singular_column_raises +pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_killer_combination_duplicate_and_nan_raises_not_abort +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_killer_combination_duplicate_and_nan_raises_not_abort +pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_purely_nonfinite_a_flows_to_nan_params_not_abort +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_purely_nonfinite_a_flows_to_nan_params_not_abort +pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_second_model_singular_names_model_one +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_second_model_singular_names_model_one +pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_guard_is_bit_identical_on_healthy_state +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_guard_is_bit_identical_on_healthy_state +pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_healthy_full_fit_completes_unaffected +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_inv_guard.py::test_healthy_full_fit_completes_unaffected +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_defaults_to_true +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_defaults_to_true +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_off_is_accepted +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_off_is_accepted +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_monotone_default_fit_is_bit_identical_with_keep_best_on_or_off +[gw7] [ 93%] PASSED pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_probability_is_normalized +pamica/tests/torch_tests/test_ng_model_posterior.py::test_single_model_probability_is_all_ones +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_monotone_default_fit_is_bit_identical_with_keep_best_on_or_off +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_snapshot_is_a_copy_not_an_alias +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_snapshot_is_a_copy_not_an_alias +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_restores_a_genuine_overshoot +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_restores_a_genuine_overshoot +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_forced_restore_model_loglik_matches_state_dict_round_trip +[gw7] [ 93%] PASSED pamica/tests/torch_tests/test_ng_model_posterior.py::test_single_model_probability_is_all_ones +pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_loglik_uses_stored_sphere_not_reprocess +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_forced_restore_model_loglik_matches_state_dict_round_trip +pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_restore_does_not_rewrite_ll_history +[gw5] [ 93%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[2-3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[3-3] +[gw0] [ 93%] PASSED pamica/tests/mlx_tests/test_mlx_keepbest.py::test_keep_best_restore_does_not_rewrite_ll_history +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[4-1] +[gw7] [ 93%] PASSED pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_loglik_uses_stored_sphere_not_reprocess +pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_loglik_requires_fit +[gw7] [ 93%] PASSED pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_loglik_requires_fit +pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_loglik_rejects_non_finite_input +[gw0] [ 93%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[4-1] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[1-1] +[gw7] [ 93%] PASSED pamica/tests/torch_tests/test_ng_model_posterior.py::test_model_loglik_rejects_non_finite_input +pamica/tests/torch_tests/test_ng_pdf_families.py::test_adaptive_switch_with_rejection +[gw5] [ 93%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[3-3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_state_dict_roundtrips_pdftype_state +[gw0] [ 94%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_finite_and_monotone[1-1] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_auto_switcher_runs_and_is_stable +[gw7] [ 94%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_adaptive_switch_with_rejection +pamica/tests/torch_tests/test_ng_pdf_families.py::test_multimodel_fixed_family +[gw5] [ 94%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_state_dict_roundtrips_pdftype_state +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_with_newton[2-3] +[gw0] [ 94%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_auto_switcher_runs_and_is_stable +pamica/tests/torch_tests/test_ng_pdf_families.py::test_auto_switch_noop_when_num_kurt_zero +[gw0] [ 94%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_auto_switch_noop_when_num_kurt_zero +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[2-3] +[gw0] [ 94%] SKIPPED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[2-3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[3-3] +[gw0] [ 94%] SKIPPED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[3-3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[4-1] +[gw0] [ 94%] SKIPPED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[4-1] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[1-1] +[gw0] [ 94%] SKIPPED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[1-1] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_sharing_newton_and_fixed_family_fit_completes +[gw7] [ 94%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_multimodel_fixed_family +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[0-3] +[gw7] [ 94%] SKIPPED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_converged_ll_matches_fortran[0-3] +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_full_rank_model_dimension_unchanged +[gw7] [ 94%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_full_rank_model_dimension_unchanged +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_rank_deficient_fits_instead_of_going_degenerate +[gw5] [ 94%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_with_newton[2-3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_with_newton[3-3] +[gw7] [ 94%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_rank_deficient_fits_instead_of_going_degenerate +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_default_relative_threshold_recovers_the_exact_rank +[gw7] [ 94%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_default_relative_threshold_recovers_the_exact_rank +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_fortran_absolute_floor_over_retains +[gw2] [ 94%] PASSED pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[4-False] +pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[5-True] +[gw7] [ 94%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_fortran_absolute_floor_over_retains +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_sensor_mixing_matrix_reconstructs_the_input +[gw5] [ 94%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_with_newton[3-3] +pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_with_newton[4-1] +[gw7] [ 94%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_sensor_mixing_matrix_reconstructs_the_input +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_pcakeep_with_pca_whitening_no_longer_crashes +[gw7] [ 94%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_pcakeep_with_pca_whitening_no_longer_crashes +pamica/tests/torch_tests/test_ng_restarts.py::test_single_restart_is_bit_identical_to_a_direct_fit +[gw7] [ 94%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_single_restart_is_bit_identical_to_a_direct_fit +pamica/tests/torch_tests/test_ng_restarts.py::test_single_restart_records_the_one_fit_it_ran +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_single_restart_records_the_one_fit_it_ran +pamica/tests/torch_tests/test_ng_restarts.py::test_an_explicit_single_seed_overrides_the_constructor_seed +[gw5] [ 95%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_family_fit_with_newton[4-1] +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_rank_reduced_newton_fit_completes +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_an_explicit_single_seed_overrides_the_constructor_seed +pamica/tests/torch_tests/test_ng_restarts.py::test_best_of_n_returns_the_argmax_of_the_independent_fits +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_best_of_n_returns_the_argmax_of_the_independent_fits +pamica/tests/torch_tests/test_ng_restarts.py::test_records_are_aligned_with_the_independent_fits +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_records_are_aligned_with_the_independent_fits +pamica/tests/torch_tests/test_ng_restarts.py::test_derived_seeds_run_the_documented_sequence +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_derived_seeds_run_the_documented_sequence +pamica/tests/torch_tests/test_ng_restarts.py::test_a_refit_repeats_the_same_search +[gw5] [ 95%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_rank_reduced_newton_fit_completes +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_nan_data_still_reaches_the_degenerate_fit_contract +[gw5] [ 95%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_nan_data_still_reaches_the_degenerate_fit_contract +pamica/tests/torch_tests/test_ng_restarts.py::test_a_crashing_restart_does_not_kill_the_search +[gw1] [ 95%] PASSED pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_ll_matches_float64[True] +pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_mps_smoke +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_a_refit_repeats_the_same_search +pamica/tests/torch_tests/test_ng_restarts.py::test_a_degenerate_restart_is_recorded_but_never_selected +[gw5] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_a_crashing_restart_does_not_kill_the_search +pamica/tests/torch_tests/test_ng_restarts.py::test_a_single_restart_still_raises +[gw5] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_a_single_restart_still_raises +pamica/tests/torch_tests/test_ng_restarts.py::test_all_degenerate_restarts_keep_the_degenerate_contract +[gw5] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_all_degenerate_restarts_keep_the_degenerate_contract +pamica/tests/torch_tests/test_ng_restarts.py::test_the_winners_tuned_block_size_is_restored +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_a_degenerate_restart_is_recorded_but_never_selected +pamica/tests/torch_tests/test_ng_restarts.py::test_all_restarts_crashing_keeps_the_degenerate_contract +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_all_restarts_crashing_keeps_the_degenerate_contract +pamica/tests/torch_tests/test_ng_restarts.py::test_a_payload_without_restart_records_still_loads +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_a_payload_without_restart_records_still_loads +pamica/tests/torch_tests/test_ng_restarts.py::test_wrapper_forwards_n_restarts_and_mirrors_the_records +[gw5] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_the_winners_tuned_block_size_is_restored +pamica/tests/torch_tests/test_ng_restarts.py::test_state_dict_round_trips_the_configuration_and_the_records +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_wrapper_forwards_n_restarts_and_mirrors_the_records +pamica/tests/torch_tests/test_ng_restarts.py::test_wrapper_records_the_single_restart_of_a_default_fit +[gw5] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_state_dict_round_trips_the_configuration_and_the_records +pamica/tests/torch_tests/test_ng_restarts.py::test_wrapper_refuses_a_best_of_n_fit_whose_restarts_all_degenerate +[gw7] [ 95%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_wrapper_records_the_single_restart_of_a_default_fit +pamica/tests/torch_tests/test_ng_sharing.py::test_single_model_byte_identical_with_share_toggled +[gw5] [ 96%] PASSED pamica/tests/torch_tests/test_ng_restarts.py::test_wrapper_refuses_a_best_of_n_fit_whose_restarts_all_degenerate +pamica/tests/torch_tests/test_ng_sharing.py::test_default_multimodel_leaves_comps_unshared +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_mps_smoke +pamica/tests/torch_tests/test_ng_gm_ordering.py::test_ndtmpsum_uses_pre_update_model_weights +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_gm_ordering.py::test_ndtmpsum_uses_pre_update_model_weights +pamica/tests/torch_tests/test_ng_gm_ordering.py::test_a_update_uses_pre_update_model_weights +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_gm_ordering.py::test_a_update_uses_pre_update_model_weights +pamica/tests/torch_tests/test_ng_gm_ordering.py::test_same_pre_update_gm_is_deterministic +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_gm_ordering.py::test_same_pre_update_gm_is_deterministic +pamica/tests/torch_tests/test_ng_gm_ordering.py::test_single_model_is_unaffected +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_gm_ordering.py::test_single_model_is_unaffected +pamica/tests/torch_tests/test_ng_sharing.py::test_three_model_guard_and_merge +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_three_model_guard_and_merge +pamica/tests/torch_tests/test_ng_sharing.py::test_comp_thresh_one_merges_only_exact_duplicates +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_comp_thresh_one_merges_only_exact_duplicates +pamica/tests/torch_tests/test_ng_sharing.py::test_a_frozen_window[True-2] +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_a_frozen_window[True-2] +pamica/tests/torch_tests/test_ng_sharing.py::test_a_frozen_window[False-2] +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_a_frozen_window[False-2] +pamica/tests/torch_tests/test_ng_sharing.py::test_a_frozen_window[False-1] +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_a_frozen_window[False-1] +pamica/tests/torch_tests/test_ng_sharing.py::test_a_frozen_window_starting_inside_a_cycle +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_a_frozen_window_starting_inside_a_cycle +pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs0-share_start] +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs0-share_start] +pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs1-share_iter] +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs1-share_iter] +pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs2-share_iter] +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs2-share_iter] +pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs3-comp_thresh] +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs3-comp_thresh] +pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs4-comp_thresh] +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_share_constructor_validation[kwargs4-comp_thresh] +pamica/tests/torch_tests/test_ng_sharing.py::test_pca_reduction_no_longer_rejected_at_construction +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_pca_reduction_no_longer_rejected_at_construction +pamica/tests/torch_tests/test_ng_sharing.py::test_non_finite_sphere_still_fails_loudly +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_non_finite_sphere_still_fails_loudly +pamica/tests/torch_tests/test_ng_sharing.py::test_get_sensor_mixing_matrix_non_finite_sphere_fails_loudly +[gw1] [ 96%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_get_sensor_mixing_matrix_non_finite_sphere_fails_loudly +pamica/tests/torch_tests/test_ng_sharing.py::test_two_model_share_fit_survives_merge +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_single_model_byte_identical_with_share_toggled +pamica/tests/torch_tests/test_ng_sharing.py::test_identify_merges_one_collinear_pair +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_identify_merges_one_collinear_pair +pamica/tests/torch_tests/test_ng_sharing.py::test_merge_on_the_final_iteration_completes +[gw5] [ 97%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_default_multimodel_leaves_comps_unshared +pamica/tests/torch_tests/test_ng_sharing.py::test_guard_prevents_within_model_collapse +[gw5] [ 97%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_guard_prevents_within_model_collapse +pamica/tests/torch_tests/test_ng_sharing.py::test_low_rank_projected_data_share_fit_completes +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_merge_on_the_final_iteration_completes +pamica/tests/torch_tests/test_ng_sharing.py::test_rank_reduced_share_fit_completes +[gw0] [ 97%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_sharing_newton_and_fixed_family_fit_completes +pamica/tests/torch_tests/test_ng_pdf_families.py::test_sharing_newton_and_adaptive_switcher_fit_completes +[gw5] [ 97%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_low_rank_projected_data_share_fit_completes +pamica/tests/torch_tests/test_ng_sharing.py::test_full_rank_merge_decisions_unchanged_by_pinv +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_rank_reduced_share_fit_completes +pamica/tests/torch_tests/test_ng_sharing.py::test_pinv_matches_inv_on_a_fitted_full_rank_sphere +[gw1] [ 97%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_two_model_share_fit_survives_merge +pamica/tests/torch_tests/test_ng_sharing.py::test_sharing_reduces_unique_count_without_degrading_ll +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_pinv_matches_inv_on_a_fitted_full_rank_sphere +pamica/tests/torch_tests/test_ng_utils.py::test_setup_device_auto_returns_valid_device +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_setup_device_auto_returns_valid_device +pamica/tests/torch_tests/test_ng_utils.py::test_setup_device_mps_falls_back_when_unavailable +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_setup_device_mps_falls_back_when_unavailable +pamica/tests/torch_tests/test_ng_utils.py::test_check_numerical_stability_clean +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_check_numerical_stability_clean +pamica/tests/torch_tests/test_ng_utils.py::test_check_numerical_stability_flags_nan +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_check_numerical_stability_flags_nan +pamica/tests/torch_tests/test_ng_utils.py::test_check_numerical_stability_flags_inf +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_check_numerical_stability_flags_inf +pamica/tests/torch_tests/test_ng_utils.py::test_check_numerical_stability_raises_when_requested +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_check_numerical_stability_raises_when_requested +pamica/tests/torch_tests/test_ng_utils.py::test_stabilize_log_probabilities_clamps_below_floor +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_stabilize_log_probabilities_clamps_below_floor +pamica/tests/torch_tests/test_ng_utils.py::test_stabilize_log_probabilities_custom_floor +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_stabilize_log_probabilities_custom_floor +pamica/tests/torch_tests/test_ng_utils.py::test_compute_correlation_matrix_identity_on_self +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_compute_correlation_matrix_identity_on_self +pamica/tests/torch_tests/test_ng_utils.py::test_find_best_permutation_recovers_shuffle_and_sign +[gw7] [ 97%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_find_best_permutation_recovers_shuffle_and_sign +pamica/tests/torch_tests/test_ng_utils.py::test_load_eeglab_data_shape +[gw7] [ 98%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_load_eeglab_data_shape +[gw0] [ 98%] PASSED pamica/tests/torch_tests/test_ng_pdf_families.py::test_sharing_newton_and_adaptive_switcher_fit_completes +pamica/tests/torch_tests/test_ng_sharing.py::test_share_config_and_comp_list_roundtrip +[gw5] [ 98%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_full_rank_merge_decisions_unchanged_by_pinv +pamica/tests/torch_tests/test_ng_utils.py::test_setup_device_cpu_explicit +[gw5] [ 98%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_setup_device_cpu_explicit +[gw2] [ 98%] PASSED pamica/tests/torch_tests/test_ng_float32_stability.py::test_float32_stable_on_full_data[5-True] +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_tesla_scale_data_fits_by_default +[gw2] [ 98%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_tesla_scale_data_fits_by_default +pamica/tests/torch_tests/test_ng_rank_deficient.py::test_absolute_floor_rejects_tesla_scale_data +[gw2] [ 98%] PASSED pamica/tests/torch_tests/test_ng_rank_deficient.py::test_absolute_floor_rejects_tesla_scale_data +[gw0] [ 98%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_share_config_and_comp_list_roundtrip +[gw1] [ 98%] PASSED pamica/tests/torch_tests/test_ng_sharing.py::test_sharing_reduces_unique_count_without_degrading_ll +pamica/tests/torch_tests/test_ng_utils.py::test_setup_device_cuda_falls_back_when_unavailable +[gw1] [ 98%] PASSED pamica/tests/torch_tests/test_ng_utils.py::test_setup_device_cuda_falls_back_when_unavailable +[gw4] [ 98%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_end_to_end_correlation_vs_fortran +pamica/tests/torch_tests/test_ng_backend.py::test_end_to_end_correlation_vs_fortran_from_sample_params_json +[gw3] [ 98%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_single_model_is_bit_exact +pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_snapshot_restore_roundtrip +[gw3] [ 98%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_snapshot_restore_roundtrip +pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_returns_within_tol_of_peak +[gw3] [ 98%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_returns_within_tol_of_peak +pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_inactive_under_reject +[gw3] [ 98%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_inactive_under_reject +pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_does_not_rescue_a_diverged_fit_that_peaked_earlier +[gw3] [ 98%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_keep_best_does_not_rescue_a_diverged_fit_that_peaked_earlier +pamica/tests/torch_tests/test_ng_backend.py::test_rholrate_ratchets_at_maxdecs_not_per_decrease +[gw3] [ 98%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_rholrate_ratchets_at_maxdecs_not_per_decrease +pamica/tests/torch_tests/test_ng_block_tuning.py::test_search_is_off_by_default +[gw3] [ 98%] PASSED pamica/tests/torch_tests/test_ng_block_tuning.py::test_search_is_off_by_default +[gw4] [ 98%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_end_to_end_correlation_vs_fortran_from_sample_params_json +pamica/tests/torch_tests/test_ng_backend.py::test_full_fit_parity_numpy_vs_ng +[gw4] [ 98%] PASSED pamica/tests/torch_tests/test_ng_backend.py::test_full_fit_parity_numpy_vs_ng +[gw6] [ 99%] XFAIL pamica/tests/test_sample_data.py::test_sample_data_scikit +pamica/tests/test_sample_data.py::test_sample_data_cli +[gw6] [ 99%] XFAIL pamica/tests/test_sample_data.py::test_sample_data_cli +pamica/tests/test_sample_data.py::test_sample_data_light +[gw6] [ 99%] XFAIL pamica/tests/test_sample_data.py::test_sample_data_light +pamica/tests/test_sample_data.py::test_sample_data_numpy_vs_fortran +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_sample_data_numpy_vs_fortran +pamica/tests/test_sample_data.py::test_cli_output_format_roundtrip +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_cli_output_format_roundtrip +pamica/tests/test_sample_data.py::test_numpy_llt_roundtrip +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_numpy_llt_roundtrip +pamica/tests/test_sample_data.py::test_numpy_llt_reject_zeroes_rejected_samples +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_numpy_llt_reject_zeroes_rejected_samples +pamica/tests/test_sample_data.py::test_numpy_llt_multimodel_roundtrip +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_numpy_llt_multimodel_roundtrip +pamica/tests/test_sample_data.py::test_numpy_llt_partial_final_block +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_numpy_llt_partial_final_block +pamica/tests/test_sample_data.py::test_restart_on_early_nan_recovers +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_restart_on_early_nan_recovers +pamica/tests/test_sample_data.py::test_restart_gives_up_after_maxrestarts +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_restart_gives_up_after_maxrestarts +pamica/tests/test_sample_data.py::test_check_convergence_ratchets_lrate_on_decrease +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_check_convergence_ratchets_lrate_on_decrease +pamica/tests/test_sample_data.py::test_reinitialize_for_restart_resets_rho_ceiling +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_reinitialize_for_restart_resets_rho_ceiling +pamica/tests/test_sample_data.py::test_cli_subprocess_output_loadable +[gw6] [ 99%] PASSED pamica/tests/test_sample_data.py::test_cli_subprocess_output_loadable +pamica/tests/test_schedule_gates.py::test_every_gate_fires_on_the_reference_iteration +[gw6] [ 99%] PASSED pamica/tests/test_schedule_gates.py::test_every_gate_fires_on_the_reference_iteration +pamica/tests/test_schedule_gates.py::test_a_non_positive_interval_is_a_value_error_not_a_zero_division[0] +[gw6] [ 99%] PASSED pamica/tests/test_schedule_gates.py::test_a_non_positive_interval_is_a_value_error_not_a_zero_division[0] +pamica/tests/test_schedule_gates.py::test_a_non_positive_interval_is_a_value_error_not_a_zero_division[-2] +[gw6] [ 99%] PASSED pamica/tests/test_schedule_gates.py::test_a_non_positive_interval_is_a_value_error_not_a_zero_division[-2] +pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[torch-1] +[gw6] [ 99%] PASSED pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[torch-1] +pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[torch-5] +[gw6] [ 99%] PASSED pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[torch-5] +pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[numpy-1] +[gw6] [ 99%] PASSED pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[numpy-1] +pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[numpy-5] +[gw6] [100%] PASSED pamica/tests/test_schedule_gates.py::test_newton_takes_its_first_step_on_iteration_newt_start[numpy-5] + +=============================== warnings summary =============================== +pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll + /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.venv/lib/python3.12/site-packages/numpy/linalg/_linalg.py:2349: RuntimeWarning: divide by zero encountered in slogdet + sign, logdet = _umath_linalg.slogdet(a, signature=signature) + +pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll + /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.venv/lib/python3.12/site-packages/numpy/linalg/_linalg.py:2349: RuntimeWarning: overflow encountered in slogdet + sign, logdet = _umath_linalg.slogdet(a, signature=signature) + +pamica/tests/test_sample_data.py::test_loadmodout_reproduces_fortran_reported_ll + /Users/yahya/Documents/git/mlx-fc-phase15-final-parity/.venv/lib/python3.12/site-packages/numpy/linalg/_linalg.py:2349: RuntimeWarning: invalid value encountered in slogdet + sign, logdet = _umath_linalg.slogdet(a, signature=signature) + +-- Docs: https://docs.pytest.org/en/stable/how-to/capture-warnings.html +===== 1974 passed, 40 skipped, 3 xfailed, 3 warnings in 1417.81s (0:23:37) ===== +EXIT=0 From 337ecfce48de4e362aebd6f16885077ef866a886 Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 23:09:14 -0700 Subject: [PATCH 56/58] Add the issue-351 findings record --- .context/issue-351/findings.md | 158 +++++++++++++++++++++++++++++++++ 1 file changed, 158 insertions(+) create mode 100644 .context/issue-351/findings.md diff --git a/.context/issue-351/findings.md b/.context/issue-351/findings.md new file mode 100644 index 0000000..0425576 --- /dev/null +++ b/.context/issue-351/findings.md @@ -0,0 +1,158 @@ +# Phase 15 findings: parity re-measured under epic #324 (issue #351) + +Recorded 2026-09-23. +Every user-facing parity figure of pamica, the Python port of Adaptive Mixture Independent Component Analysis (AMICA), +was re-measured with the library code of epic #324 at 09b8247 (with Phase 16's documentation, #353) +against the pinned v0.3.3 native reference binary (`pamica.native.resolver`). +No library code changed in this phase. +Phase 17 (#354, bb22df6) was merged afterwards; the reference settings are pinned so that its default changes leave these protocols as measured (see "Pins after Phase 17"). + +Hosts: +- Mac: Apple M4 Pro, 14 cores, 64 GB, macOS 27; MLX 0.32.0, torch 2.12.1, NumPy 2.5.0. +- hallu: Linux, 32 cores, NVIDIA RTX 4090, torch 2.12.1+cu130; shared, with the reference binary kept to 8-12 threads in total. + +"Before" figures are those the documents quoted before this phase. +Where a before figure was re-measured in this phase, it used e38aa11 (Phase 6, the last commit before the epic's changes to the fit), run from a separate tree. +Paths are relative to `.context/issue-351/`. +Log-likelihood is abbreviated LL; correlations are Hungarian-matched absolute correlations of unmixing rows. + +## Old and new figures + +| Figure | Before | Now | Command | Commit | Host | Raw record | +|---|---|---|---|---|---|---| +| Harness, 100 iterations, seed 42, independent starts: LL gap PyTorch / NumPy / MLX | 2.9e-5 / 2.9e-5 / 3.2e-5 | 2.71e-4 / 2.72e-4 / 2.76e-4 | `validate_implementations.py --backend all` | 09b8247 (before: e38aa11) | Mac | `raw/harness_run1`, `raw/harness_run2`, `raw/harness_pre_epic_e38aa11` | +| Harness: mean / min correlation, Amari distance (PyTorch) | 0.9992 / 0.9935, 0.0037 | 0.9991 / 0.9918, 0.0038 (NumPy 0.9991 / 0.9917) | same | same | Mac | `raw/harness_run1` | +| Harness seed spread over 8 seeds: reference LL standard deviation (SD); cross-pair LL gap median (range) | not measured | 2.6e-4 (pamica 2.7e-4); 3.5e-4 (1.7e-5 to 8.2e-4) | `harness_gap.py ROOT OUT.json --spread ...` | 09b8247 | Mac | `raw/harness_gap_head.json` | +| Harness from a shared start: LL gap, correlation, Amari | 2.35e-4, 0.99999, 5.8e-4 (e38aa11) | 1.6e-6, 0.99999993, 3.9e-5 | `harness_gap.py` | 09b8247, e38aa11 | Mac | `raw/harness_gap_head.json`, `raw/harness_gap_pre_epic_e38aa11.json` | +| Harness runtimes, reference / PyTorch / NumPy / MLX (s) | 10.1 / 17.9 / 32.5 / 3.2 (same session) | 10.0 / 18.1 / 32.6 / 3.0 | harness | 09b8247, e38aa11 | Mac | `raw/harness_run1`, `raw/harness_pre_epic_e38aa11` | +| 200-iteration `amicaout` fixture: LL gap PyTorch / NumPy / MLX; correlation (min); Amari | 2.2-2.3e-4; 0.9973; 6.3e-3 (before Phase 11) | 1.42e-4 / 1.32e-4 / 1.44e-4; 0.9983 (0.982-0.983); 4.8e-3 | `fixture_parity.py ROOT BACKEND` | 09b8247 | Mac | `raw/fixture_parity_head.txt` | +| MLX float32 vs PyTorch float64 from a shared start, 100 / 200 iterations: LL gap, correlation, Amari | not characterized | 5.0e-6, 0.99999991, 5.0e-5 / 2.4e-6, 0.9999998, 6.3e-5 | `precision_agreement.py` | 09b8247 | Mac | `raw/precision_agreement.json` | +| Table 1, bundled single model: Amari over 5 run pairs | 0.006 | 0.0109 (per seed 0.0031, 0.0037, 0.0380, 0.0029, 0.0069); reference vs itself 0.0185 | `benchmarks/reproduce_table1.py --tier bundled` | 09b8247 | Mac CPU, 2842 s | `raw/table1_bundled` | +| Bundled single model, 10 seeded reference runs against the 5 pamica fits: Amari (max), correlation | not measured | 0.0044 (0.0083), 0.9988 over 50 pairs; reference vs itself 0.0054 (0.0101), 0.9985 over 45; pamica vs itself 0.0039, 0.9991 over 10 | `bundled_single_basins.py` | 09b8247 | Mac | `raw/bundled_basins` | +| Score functions; sufficient statistics | ~1e-15 | log-density 8.9e-16, score 1.8e-15; 4.5e-13 absolute (3e-16 relative) | `reproduce_table1.py --tier bundled` | 09b8247 | Mac | `raw/table1_bundled/report.json` | +| Multi-model correlation: cross; within-reference; within-pamica | 0.65; 0.64 | 0.632; 0.626; 0.638; difference +0.006, permutation p 0.88, run bootstrap 90% interval -0.002 to 0.014 | `reproduce_table1.py --tier bundled`, `equivalence_check.py` | 09b8247 | Mac | `raw/table1_bundled/report.json`, `raw/multimodel/equivalence_check.json` | +| Multi-model Amari: cross; within-reference; within-pamica | 0.163; 0.174 (p > 0.999) | 0.172; 0.166; 0.176; difference +0.005, p 0.051, interval 0.002 to 0.009 | same | 09b8247 | Mac | same | +| Multi-model ensemble LL: reference; pamica | -3.3539; -3.3629 (Kolmogorov-Smirnov (KS) p 6e-5) | -3.3543 (SD 0.002); -3.3541 (SD 0.003); KS p 0.83. The pre-epic pamica refit against the same reference fits gives -3.3627 (0.006), KS p 1e-5 | same, and `multimodel_pamica_fits.py` at e38aa11 | 09b8247, e38aa11 | Mac | `raw/table1_bundled`, `raw/multimodel` | +| keep_best: pamica/reference LL SD ratio at 100 iterations | 12.7x without, 2.0x with | 1.0x with and without; 1 restore in 20 fits (at 300 iterations, gain 4.2e-6); 0 Newton fallbacks | `keep_best_ensemble.py run`, `verify`, `report` | 09b8247 | Mac, reference seeded 0-19, 1 thread | `raw/keep_best` | +| Mean LL gap (pamica minus reference) at 100 / 200 / 300 iterations | -0.009 / 0 / +0.002 | +8.1e-4 / +2.1e-4 / +1.0e-4 (KS p 0.83 / 0.57 / 0.98) | same | 09b8247 | Mac | `raw/keep_best/ensemble.json` | +| Cross-backend LL after 25 iterations (dimsweep) | maximum pairwise ~0.003 | 1e-5 at 32 and 48 channels; 1.1e-3 at 70 channels (k≈6); NumPy (unseeded) 4.2e-3 | `benchmarks/benchmark_dimsweep.py` | 09b8247 | Mac, hallu | `raw/dimsweep` | +| Dimsweep timing at 70 channels, e38aa11 / 09b8247 (ms per iteration) | MLX 33.3, CPU float64 190.8, MPS 165.1 | MLX 33.1, CPU float64 189.4, MPS 166.7 | same | e38aa11, 09b8247 | Mac (quiet) | `raw/dimsweep/timing70_*.json` | +| Newton, independent seeds, 70 channels, 2000 iterations | seed 42: 10-11 of 70 components below 0.9; other seeds ~0.995 | see the Newton table below | `run_newton_hallu.sh`, `newton_seeds.py compare` | 09b8247 | hallu (CUDA float64; reference 10 threads) | `raw/newton` | +| Newton from a shared start: correlation (min), Amari, LL gap | 0.9974 (0.9475) | 0.9999998 (0.9999964), 3.8e-5, 7.6e-8 | `newton_seeds.py pamica/fortran --fixinit` | 09b8247 | hallu | `raw/newton` | +| `share_comps` end to end (300 iterations, threshold 0.95) | 3 merges, LL -3.3416 | 1 merge at iteration 100 (\|cos\| 0.970), LL -3.3410 (-3.3393 without sharing); 63 of 64 components | `share_comps_counts.py` | 09b8247 | Mac | `raw/share_comps` | +| Early scans at iteration 8 / 20, thresholds 0.95 and 0.99 | 32, 24 / 24, 5 | 30, 17 / 22, 5 | same | 09b8247 | Mac | `raw/share_comps` | +| Reference-formula scan on the reference's own state | 32, 32, 30 | 32, 32, 29 (identical `comp_list`s; 8-iteration states agree to 5.2e-6 in A and 1.6e-7 in LL) | same | 09b8247 | Mac | `raw/share_comps` | +| Table 1 external tier LL (on002718, 5 seeds) | gap ~0.0003 at -3.6993 | reference -3.699346 (SD 6.5e-5), pamica -3.699341 (4.1e-5), gap 5.6e-6 | `reproduce_table1.py --tier external --threads 16` | 09b8247 | hallu, CUDA float64 (lead's run, 26185 s) | `raw/table1_external` | +| Table 1 external correlation; Amari | 0.998 (reference vs itself ~0.999) | 0.99965 (SD 0.00048, min component 0.9602), reference vs itself 0.99827 (min 0.9167); Amari 0.00126 (SD 0.00062), reference vs itself 0.00249 | same | 09b8247 | hallu | `raw/table1_external/report.json` | + +External tier per seed (mean correlation / min correlation / Amari): +201 0.9999 / 0.9996 / 0.0008; 202 0.9987 / 0.9602 / 0.0024; 203 0.9999 / 0.9985 / 0.0012; 204 1.0000 / 0.9998 / 0.0007; 205 0.9998 / 0.9955 / 0.0012. +The reference fits took 1972-2559 s and the pamica fits 1886-5013 s. + +Newton pairs (mean / min correlation / components below 0.9): + +| Pair | Mean | Min | Below 0.9 | +|---|---:|---:|---:| +| pamica 42 vs reference 1 | 0.963 | 0.667 | 8 | +| pamica 42 vs reference 2 | 0.986 | 0.858 | 3 | +| pamica 13 vs reference 1 | 0.996 | 0.946 | 0 | +| pamica 13 vs reference 2 | 0.981 | 0.773 | 3 | +| pamica 7 vs reference 1 | 0.995 | 0.943 | 0 | +| pamica 7 vs reference 2 | 0.982 | 0.786 | 3 | +| reference 1 vs reference 2 | 0.985 | 0.841 | 2 | +| pamica 42 vs pamica 13 | 0.962 | 0.658 | 7 | + +Final LLs: reference seed 1 -3.697804 and seed 2 -3.697709; pamica seed 42 -3.697569, 13 -3.697816 and 7 -3.697812; shared start -3.697812. +The shared-start reference run matches reference seed 1 at 0.996 (min 0.955). +MLX float32 (supplementary, Mac): seed 7 stopped on the `lrate` floor after 952 iterations at LL -3.698091 (CUDA float64 -3.697913 at the same iteration), after 121 decreases; +it matches CUDA seed 7 at 0.985 (min 0.907) and reference seed 1 at 0.983 (min 0.905). +MLX seed 42 (928 iterations) matches CUDA seed 42 at 0.955, with 10 components below 0.9 (`raw/newton_mlx`). + +## Harness: why the independent-start gap grew + +The harness fits pamica and the reference from independent random starts at one seed, +so its LL gap is one draw from the start-to-start spread. +Over 8 seeds the reference's own final LL has SD 2.6e-4 and range 8.0e-4, pamica's SD 2.7e-4 and range 8.0e-4, +and the cross-implementation gaps have median 3.5e-4 (1.7e-5 to 8.2e-4). +Before the epic, seed 42 happened to fall near the low end of that spread (2.9e-5); +the epic changed the initial draw (the normalized initial mixing matrix, #341) and the trajectory, and seed 42 now falls near its middle (2.71e-4). +The lead reproduced the binary's LL at seeds 42, 6 and 3. +From a shared start, the reference loaded with pamica's initial state (`native_oracle.run_seeded_reference`), the gap is 1.6e-6, with correlation 0.99999993 and Amari 3.9e-5; +the same comparison at e38aa11 gives 2.35e-4, 0.99999 and 5.8e-4. +The shared state's orientation was checked by the first-iteration LL, which agrees to 9e-16 as loaded and differs by 1.3e-5 when transposed (`raw/orientation_check.txt`). +The documents now give the independent-start figure with the reference's spread beside it, and the shared-start figure. + +## 70-channel dimsweep: round-off sensitivity + +At 32 and 48 channels the backends that share a start agree to 1e-5 in LL after 25 iterations. +At 70 channels on the 30,000-frame excerpt, k = frames / channels² ≈ 6, the five seeded backends spread over 1.1e-3: +MLX -3.21643, CPU float64 -3.21746, MPS -3.21638, CUDA float64 -3.21723, CUDA float32 -3.21689. +The lead's perturbation check measured the sensitivity directly: +changing one sample of the 70-channel data by 1e-9 µV changes the CPU float64 LL at iteration 25 by 4.4e-4, +so differences of this size arise from round-off amplification on data this poorly determined. +The NumPy backend is unseeded in this benchmark and differs by 4.2e-3 (-3.22054). + +## Protocol changes and why + +1. Harness: unchanged. + The seed-spread and shared-start diagnostics (`harness_gap.py`) were added because the single-seed independent-start gap moved tenfold and needed an interpretation. +2. `benchmarks/reproduce_table1.py`: every reference setting is spelled out in `REFERENCE_SETTINGS`. + These are the bundled `input.param` values, which `AMICANative`'s defaults mirrored when Table 1 was measured, plus `do_approx_sphere 1`. + The ensemble's pamica fit pins `lrate=0.05`. + Phase 17 moved the `AMICANative` and wrapper defaults, and the pins keep Table 1's protocol as it was measured. +3. Bundled single-model tier: the five-pair protocol is unchanged. + The 50-pair basin study was added because one of the five reference runs (seed 303, LL -3.4006 against about -3.3996 for the others) sets the five-pair Amari mean. +4. Multi-model ensemble: the protocol is unchanged (20 fits per implementation, 2 models, 3 mixture components, 100 iterations, bundled sample; the reference draws its own clock-based seeds). + The ±0.05 margin is checked with a run-level bootstrap 90% interval of the difference. + The earlier pairwise two one-sided tests (TOST) treated 190 or 400 pairwise values as independent, although each run appears in about 39 pairs; the #27 record had already retired it in favor of the run-level permutation test. + The multi-model Amari distance takes the better of the two model pairings. + Over the 780 run pairs of the new ensemble that choice lowers the mean by 0.0185 (median 0) and swaps the pairing in 333 pairs (`raw/multimodel/pairing_correction.txt`). + The reference runs with `invsigmin` 0.0 and pamica with 1e-8; `validation.md` states this. +5. keep_best ensemble: the reference is seeded 0-19 and single-threaded, so each run is reproducible (the #51 runs were clock-seeded). + The 100- and 200-iteration budgets are read from prefixes of each 300-iteration run. + Separate 100-iteration runs and pamica histories agree exactly with those prefixes (`raw/keep_best/verify.json`, all differences 0.0). +6. Newton: pamica on CUDA float64 at seeds 42, 13 and 7, against the pinned v0.3.3 binary seeded 1 and 2. + The data are the full 70-channel ds002718 recording, rounded to float32. + The early stops are off on both sides, so both run 2000 iterations. + A shared-start pair (A = I, mu = linspace(-1, 1, 3), sbeta = 1, rho = 1.5, alpha = 1/3) replaces #145's matched-initialization run. + The #145 comparison used the gfortran `amica15_linux` build (SHA 43b9f0e3...), which draws a new start on every unseeded run: + two runs differ after one iteration in LL (-3.51144 against -3.51323) and in A (max 9.6e-3; `raw/seedcheck_issue145_binary`). + Both reference-vs-reference figures are therefore reported. +7. Dimsweep and `share_comps`: unchanged; the counts script re-runs the documented scans. + +## Why the multi-model LL gap closed + +The earlier -0.009 ensemble gap came mostly from the code before the epic. +Refitting the pamica half with e38aa11 against the same 20 reference fits gives -3.3627 (SD 0.006, KS p 1e-5). +7 of those 20 fits stopped early on the pre-#339 `min_dll` check (mean -3.3679). +The 13 full-length fits average -3.3600; the difference that remains is attributed to that code's update rule. +With the epic's code the ensemble gap is +2e-4 (KS p 0.83). +The seeded keep_best ensemble shows the same at matched budgets: +8.1e-4, +2.1e-4 and +1.0e-4 at 100, 200 and 300 iterations, with equal or smaller SD for pamica. +The documents no longer attribute the gap to convergence speed. +On Amari distance, the pre-epic ensemble was tighter (within-pamica 0.151, cross 0.160, p 0.998); the current one is slightly wider than the reference's own (0.176 and 0.172 against 0.166, p 0.051). + +## share_comps details + +End to end, 300 iterations at threshold 0.95: 1 merge at iteration 100 (|cos| 0.970), LL -3.3410; -3.3393 with sharing off; 63 of 64 components kept. +Early scans: at iteration 8, 30 merges (0.95) and 17 (0.99); at iteration 20, 22 and 5; at 0.9, 31 and 30. +The early mass-merge collapse: 28 merges, gm2 0.572 to 2.18e-3 to 9.0e-4, second scan 2.44e-4, a non-finite LL at iteration 23. +The gated freeze-free oracle gives 4.222e-3 on both sides. + +## Pins after Phase 17 + +Before Phase 17, pinned and unpinned calls wrote byte-identical `input.param` files at all 8 native call sites, with a negative control (`pin_check.py`, `raw/pin_check.json`). +The pinned files were saved (`raw/pin_check_pinned_params_pre_phase17.json`). +After the merge of bb22df6: +- The 3 seeded-runner calls are byte-identical. +- The 5 `AMICANative` calls write the same settings in Phase 17's key order, plus `do_approx_sphere 1`, the binary's compiled value (`amica15_header.f90:13`); nothing else is added, removed or changed (`raw/pin_check_post_phase17.json`). +- `pin_run_check.py` ran the binary on the pre- and post-Phase-17 forms of the file for the single-model, multi-model and Newton configurations: bundled sample, seeded, single-threaded, 20 or 60 iterations. + All 13 numeric output files are byte-identical, and `out.txt` matches once the per-iteration wall-clock times are removed (`raw/pin_run_check_post_phase17.json`). +- `REFERENCE_SETTINGS` now pins `do_approx_sphere` as well. +- Without the pins, 15 settings of the native calls would take Phase 17's defaults, among them `lrate` 0.1, `do_newton` 0, `newt_start` 20, `invsigmin` 1e-4 and `max_decs` 5. + +## Gates + +Before and after the Phase 17 merge: +- ruff check and format, `ty check .`, typos and `mkdocs build --strict` are clean. +- pytest (`CI=1`, 8 workers, no coverage): 1955 passed, 40 skipped, 3 xfailed before the merge; 1974 passed, 40 skipped, 3 xfailed after it (`raw/pytest_full.log`, `raw/pytest_full_post_phase17.log`). +- `AMICA_RUN_FORTRAN=1` on `test_fortran_param_forwarding.py` and the two early-merge oracles: 37 passed both times (`raw/gated_tests.log`, `raw/gated_tests_post_phase17.log`). From 6825d4fb3f33d6e19603ff87add70fa6fe51b58a Mon Sep 17 00:00:00 2001 From: Seyed Yahya Shirazi Date: Wed, 23 Sep 2026 23:09:39 -0700 Subject: [PATCH 57/58] Reword two remaining contrast phrasings in the paper --- paper.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/paper.md b/paper.md index 5d613a1..0d10b8a 100644 --- a/paper.md +++ b/paper.md @@ -104,7 +104,7 @@ over 50 run pairs the distance between the implementations (0.004) is close to t A mixture of ICA models is not partition-identifiable, so the implementations are compared by the distributions of solutions they sample, over ensembles of 20 runs each (\autoref{fig:ensemble}). One-sided run-level permutation tests of whether cross-implementation agreement is worse than the reference's own run-to-run agreement -give $p=0.88$ by correlation and $p=0.051$ by Amari distance, by which `pamica`'s ensemble spreads slightly more than the reference's. +give $p=0.88$ by correlation and $p=0.051$ by Amari distance, on which `pamica`'s ensemble spreads slightly more than the reference's. | Regime | Metric (dataset) | Result (mean) | |---|---|---| @@ -132,9 +132,11 @@ Double precision remains the default for parity work, and double-precision CUDA On real 70-channel EEG at `block_size=512`, per-iteration cost is 25 ms for MLX on an Apple GPU, 39 ms for double-precision CUDA on an RTX 4090, and 30 ms for native Fortran on a 24-core i9-13900K, against 193 ms for PyTorch on an Apple-Silicon CPU and 255 ms for PyTorch-Metal. -That comparison is block-size-confounded: PyTorch-Metal is far more block-size-sensitive than the CPU it runs beside, falling from 431 to 30.5 ms/iteration on the bundled 32-channel sample -between `block_size=512` and `pamica`'s current 8192 default, still behind the CPU's 21.7 ms/iteration there, and to 13.5 ms/iteration, below the CPU's 15.8 ms, -at a further-tuned single-block setting that is memory-limited rather than a free win, since peak block memory scales with `block_size`, which is why 8192 stays the shipped default. +That comparison is block-size-confounded: PyTorch-Metal is far more block-size-sensitive than the CPU it runs beside, +falling from 431 to 30.5 ms/iteration on the bundled 32-channel sample between `block_size=512` and `pamica`'s current 8192 default, +still behind the CPU's 21.7 ms/iteration there, +and to 13.5 ms/iteration, below the CPU's 15.8 ms, at a further-tuned single-block setting. +Peak block memory grows with `block_size`, which is why 8192 stays the shipped default. MLX stays the fastest Apple backend throughout the sweep. Full tables, the data-size sweep, and reproduction commands are in the [documentation](https://eeglab.org/pAMICA/guides/validation/); the correctness harness never uses synthetic data. The harness and sample data are in the source repository, and every row of Table 1 but the two on002718 entries re-runs from the bundled sample alone. 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