spearmanr

mvpy.math.spearmanr(x: ndarray | Tensor, y: ndarray | Tensor, *args: Any) → ndarray | Tensor

Compute Spearman correlation between x and y. Note that correlations are always computed over the final dimension in your inputs.

Parameters:

xUnion[np.ndarray, torch.Tensor]

Matrix to compute correlation with.

yUnion[np.ndarray, torch.Tensor]

Matrix to compute correlation with.

Returns:

Union[np.ndarray, torch.Tensor]

Spearman correlations.

See also

mvpy.math.pearsonr()

mvpy.math.rank()

Notes

Spearman correlations are defined as Pearson correlations between the ranks of x and y.

Examples

>>> import torch
>>> from mvpy.math import spearmanr
>>> x = torch.tensor([1, 5, 9])
>>> y = torch.tensor([1, 50, 60])
>>> spearmanr(x, y)
tensor(1., dtype=torch.float64)