limnotech_rating_curves

Bayesian stage-discharge rating curves: fit a rating to paired stage and discharge measurements, compare model families, and run cross-validation.

import limnotech_rating_curves as lrc

rating = lrc.fit_rating(measurements)
rating.predict(5.0) # discharge at stage = 5 ft
rating.plot()

Units are feet (stage) and cfs (discharge) throughout. See the examples/getting_started.ipynb for a walkthrough of basic functionality.

Setup

Install Miniconda, then from this folder in the Anaconda PowerShell Prompt:

git clone https://github.com/LimnoTech/limnotech_rating_curves
cd limnotech_rating_curves
conda env create -f environment.yml
conda activate rating_curves
pip install -e .
pytest tests/test_environment.py -q

That installs everything except integration with pagaia, which can optionally be included:

pip install -e ".[pagaia]"

You may have to request access to the private LimnoTech pagaia repostitory. You will also have to set PAGAIA_AUTH_TOKEN in your environment variables to your Freeboard API Key.

VS Code

Ctrl+Shift+P => Python: Select Interpreter => rating_curves. If conda envs don't appear, enter the path directly:

C:\Users\<you>\AppData\Local\miniconda3\envs\rating_curves\python.exe

For terminals that activate conda themselves, run conda init powershell once; if the profile then won't load, it's the execution policy: Set-ExecutionPolicy RemoteSigned -Scope CurrentUser.

Running a notebook against your own kernel

You can optional start a jupyter kernel in the terminal and point VS Code at it.

conda activate rating_curves
jupyter notebook --no-browser

It prints a URL with a token, like http://localhost:8888/lab?token=<long hex>. Copy that whole line, then in VS Code: Ctrl+Shift+P => Notebook: Select Notebook Kernel => Select Another Kernel => Existing Jupyter Server => paste the URL => pick the Python 3 (ipykernel) kernel.

Ctrl+C twice in the terminal to stop the kernel.

Next

examples/getting_started.ipynb — fitting, comparing models, cross-validation, saving a fit. Runs on public USGS data. examples/extras.ipynb — datums, zero flow, diagnostics, the map, many sites at once. docs/ — one page per module. rating-curves --help — the CLI. settings.py — every tunable value, listed with its default and each overridable from the environment as LRC_ + its name; copy .env.example to .env and see examples/settings_from_env.py.