gval
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NOAA-OWP
A high-level Python framework to evaluate the skill of geospatial datasets by comparing candidates to benchmark maps producing agreement maps and metrics.
There needs to be functionality to convert a STAC query in to a catalog. Catalogs will be represented by a DataFrame.
There is repeated code for homogenization and and attribute tracking for all full compare methods in gval_xarray.py. There should be a decorator for these methods to promote code reuse.
It should be explored if a probabilistic class should be implemented. If so it should be created in the statistics module.
Where appropriate, we should consolidate configuration files to `pyproject.toml` unless some other use is required for the file. Some examples include: - `setup.cfg` - `.coveragerc` - `config.py`: this file may...
Nox sessions have low test coverage (~85%) when ran locally and even lower on GH Actions (~67%). Update `.coveragerc` min fail value to 95 when addressed.
Investigate if GH actions should use nox sessions?
Add nox session or ability to publish package to PyPi via GH actions as an optional task.
Add a version bumper such as those listed [here](https://github.com/c4urself/bump2version/blob/master/RELATED.md) to automate version changing. Add a nox session to do this with the new version possibly as a session parameter.
Add a static type checker such as pyright, mypy, etc as a nox session within the current `PLACEHOLDER` within the `noxfile.py`. This will require adding the type checker as a...
Probabilistic compare should have an example notebook preferably with real data. NOAA produces a variety of ensemble forecasts.