feat: add mahalanobis_distance.py

[kasc0206]

Description

Add the Mahalanobis distance metric implementation to the maths/ directory.

The Mahalanobis distance measures how many standard deviations away a point is from the mean of a distribution, taking into account the correlations between variables.

60114D_M(x) = \sqrt{(x - \mu)^T \Sigma^{-1} (x - \mu)}60114

Functions added

• mahalanobis_distance(point, mean, covariance) — computes distance from a point to a distribution given a known covariance matrix
• mahalanobis_distance_from_sample(point, sample) — estimates the covariance matrix from sample data and computes the distance

Features

• ✅ Comprehensive doctests (23 tests)
• ✅ Full type hints
• ✅ Error handling for dimension mismatch, non-square/singular covariance matrices, and insufficient sample data
• ✅ NumPy-based implementation

References

• https://en.wikipedia.org/wiki/Mahalanobis_distance

[algorithms-keeper]

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