Heterogeneity index update

[gnopik]

Summary

Updates the heterogeneity index implementation to match the generalized
methodology.

• computes heterogeneity for the output and all inputs in one call
• normalizes regional sensitivity profiles before calculating H
• supports continuous and categorical custom partitions
• excludes a categorical input from its own regional sensitivity profile
• skips H_Y for categorical outputs with an explanatory warning
• exposes raw and normalized profiles, regional SI sums, region counts,
  and individual contributions through H.details
• adds plotting from the returned HeterogeneityResult object
• uses a minimum regional sample size of 100 observations
• adds unit tests for the new behavior

API

Basic analysis:

H = simdec.heterogeneity_indices(
    output=y,
    inputs=X
)

Custom partition:

H = simdec.heterogeneity_indices(
    output=y,
    inputs=X,
    custom_partition=Z
)

Results:

H.indices
H.details["X1"]
H.plot("X1")

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[tupui]

All good 👍

[tupui]

This is bad, imports should not be relative.