Paper figures - #199
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AI-assisted implementation!
This PR adds meteograms for publication, centralises some ploting style
things, uses long names for variables and tries out some colors :)
Any feedback and changes welcome!
To run only plotting:
```
evalml publication config/Varda-Single_paper.yaml -- \
--allowed-rules publication_all publication_meteogram publication_figures \
data_download_eckit_geo_grids \
--forcerun publication_meteogram publication_figures
```
Current version of the plots:
<img width="2957" height="1685" alt="image"
src="https://github.com/user-attachments/assets/218f849e-4bd3-41d2-b19d-124dfe156e50"
/>
<img width="2335" height="2056" alt="image"
src="https://github.com/user-attachments/assets/25d1d544-996a-4adf-869c-54ae054cfcf8"
/>
---------
Co-authored-by: Jonas Bhend <jonas.bhend@meteoswiss.ch>
Co-authored-by: Daniele Nerini <daniele.nerini@meteoswiss.ch>
Co-authored-by: Michele Cattaneo <44707621+MicheleCattaneo@users.noreply.github.com>
Co-authored-by: Jonas Bhend <jonasbhend@users.noreply.github.com>
) AI assisted implementation! - Derive the jretrievedwh obs marker from --station inside the script instead of passing a separate --obs argument. The marker value contains '=' (e.g. jretrievedwh:locations=KLO), which marimo's cli_args drops, so obs silently fell back to the KLO default and any non-KLO station was broken (also via the snakemake rule). The rule no longer passes --obs. - Import `time` in the entry cell and thread it through: the timing log lines used time.perf_counter() but `time` was never imported (NameError at runtime).
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AI assisted implementation! Changes the plotting workflow for publication to be able to generate them from the snakemake workflow as well as interactively rendering through a manifest . A documentation is currently available in `docs/publication_figures.md`
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### Summary of changes * Two-panel scorecard for publication * use the defined publication styles
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The publication target of snakemake now only writes a manifest, figures
are produced by standalone Jupyter notebooks that read that manifest.
### Changes
- `evalml publication <config>` → now runs one cheap rule
(`publication_manifest`) to create the manifests. Deleted the three
figure rules and the `python -m evalml.publication` renderer CLI to
simplify the code.
- Result NC files (verification, scoremaps) come from `evalml
experiment` as before, the publication target no longer pulls them.
- New notebooks
`notebooks/publication/{leadtime,meteogram,scoremaps}.ipynb` load the
manifest via `evalml.publication.resolver.Manifest`, style with the
packaged `evalml.publication.style`, and write to
`output/figures/<truth>/<figure>/`.
- Shared style promoted into the package; `plot_meteogram_region.py`
repointed, old marimo scripts removed.
- Added an opt-in `notebooks` dependency group
(jupyterlab/nbconvert/ipykernel), core deps and
inference/verification/hashing untouched.
### Usage
```
evalml experiment config/varda-single_paper_stations.yaml # produce results
evalml publication config/varda-single_paper_stations.yaml # write manifest
# interactive:
EVALML_MANIFEST=output/publication/<truth>/manifest.json jupyter lab notebooks/publication/
# headless (render without opening the notebook):
EVALML_MANIFEST=output/publication/<truth>/manifest.json \
jupyter nbconvert --to notebook --execute --inplace notebooks/publication/leadtime.ipynb
```
See [docs/publication_figures.md](docs/publication_figures.md) for the
full workflow, config options, and troubleshooting.
---------
Co-authored-by: Francesco Zanetta <62377868+frazane@users.noreply.github.com>
Co-authored-by: Jonas Bhend <jonas.bhend@meteoswiss.ch>
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WIP on figures used for Varda-Single publication