Add feature analysis CLI and learn-weights enhancements

[iankchristie]

The learn_weights CLI tool derives weights for all data layers given a grid and label set. This is a problem because some data layers might be highly correlated or the user might want to manually exclude data layers given priors. This CLI tool allows the user to iteratively analyze and exclude fields from before it goes into the learn_weights procedure.

Changes:
- Add analyze-features CLI command for computing feature correlation
analysis (Spearman/Pearson), hierarchical clustering (Ward's linkage),
and generating exclusion suggestions on normalized grids
- Add reVeal/feature_analysis.py module with correlation matrix, cluster
computation, dendrogram/heatmap plotting, and redundancy detection
- Add configurable attribute selection (explicit list or exclude-based
filtering) for learn_weights CLI.
- Output analysis/ subdirectory with correlation_matrix.csv,
feature_clusters.json, dendrogram.png, correlation_heatmap.png,
and suggested_exclusions.json
- Add matplotlib dependency to pyproject.toml and environment.yml
- Add CLI docs for learn-weights and analyze-features
- Add tests for feature_analysis (17 tests) and analyze_features (12 tests)

Example Correlation Map:

Example Dendrogram:

[Copilot]

Pull request overview

Adds a feature-correlation analysis workflow to the existing learn-weights pipeline/CLI so users can inspect correlated layers (clusters/plots) and optionally include/exclude specific attributes before training.

Changes:

• Introduces reVeal/feature_analysis.py for correlation computation, hierarchical clustering, plotting, and exclusion suggestions.
• Extends LearnWeightsConfig + learn-weights CLI with include/exclude attribute selection and analysis/analyze-only options.
• Wires analysis into run_learn_weights (with progress callbacks) and adds new/updated tests.

Reviewed changes

Copilot reviewed 6 out of 6 changed files in this pull request and generated 5 comments.

Show a summary per file

File	Description
reVeal/feature_analysis.py	New correlation + clustering + plotting utilities and output saving helpers.
reVeal/learn_weights.py	Adds progress callback support and optionally runs feature analysis before training (or analysis-only).
reVeal/config/learn_weights.py	Adds new config fields and validators for attribute selection + analyze-only behavior.
reVeal/cli/learn_weights.py	Adds CLI params, progress printing, and analysis artifact saving to analysis/.
tests/test_feature_analysis.py	New unit tests for correlation, clustering, plotting, and output saving.
tests/test_learn_weights.py	Adds tests for include/exclude validation and analyze/analyze-only behavior.

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[codecov-commenter]

Codecov Report

❌ Patch coverage is 80.97166% with 47 lines in your changes missing coverage. Please review.
✅ Project coverage is 81.84%. Comparing base (f868d47) to head (d4352e1).

Files with missing lines	Patch %	Lines
reVeal/learn_weights.py	32.14%	19 Missing ⚠️
reVeal/cli/analyze_features.py	73.13%	17 Missing and 1 partial ⚠️
reVeal/feature_analysis.py	94.57%	4 Missing and 3 partials ⚠️
reVeal/config/learn_weights.py	71.42%	1 Missing and 1 partial ⚠️
reVeal/cli/learn_weights.py	0.00%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main      #58      +/-   ##
==========================================
+ Coverage   81.62%   81.84%   +0.22%     
==========================================
  Files          20       23       +3     
  Lines        1518     1746     +228     
  Branches      200      219      +19     
==========================================
+ Hits         1239     1429     +190     
- Misses        236      269      +33     
- Partials       43       48       +5     

Flag	Coverage Δ
unittests	81.84% <80.97%> (+0.22%)	⬆️

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[ppinchuk]

Question about progress printing. Everything else looks good