nispace.stats.coloc.corr

nispace.stats.coloc.corr(x, y, rank=False)[source]

Compute Pearson (or, with rank=True, Spearman) correlation for two 1D arrays.

Parameters:
  • x (np.ndarray, shape (n,), dtype float) – Numba-jitted: must be plain 1D np.ndarray instances of equal length. Does not handle NaN – strip/mask NaN entries before calling.

  • y (np.ndarray, shape (n,), dtype float) – Numba-jitted: must be plain 1D np.ndarray instances of equal length. Does not handle NaN – strip/mask NaN entries before calling.

  • rank (bool, default False) – If True, rank x/y via rank1d first (Spearman); if False, compute Pearson directly on the raw values.

Returns:

r – NaN if either array has zero variance.

Return type:

float

Notes

A more generic rank-optional sibling of pearson; used by nulls.py and stats/autocorr.py for spatial-autocorrelation-null comparisons. core/colocalize.py’s own pearson/spearman colocalization path calls rank2d + plain pearson instead of this function.