pearsonr_d

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

Computes Pearson distance between x and y. Note that distances are always computed over the final dimension in your inputs.

Parameters:

xUnion[np.ndarray, torch.Tensor]

Vector/Matrix/Tensor

yUnion[np.ndarray, torch.Tensor]

Vector/Matrix/Tensor

Returns:

Union[np.ndarray, torch.Tensor]

Distances

See also

mvpy.math.pearsonr()

Notes

Pearson distance is defined as \(1 - \text{pearsonr}(x, y)\).

Examples

>>> import torch
>>> from mvpy.math import pearsonr_d
>>> x = torch.tensor([1, 2, 3])
>>> y = torch.tensor([-1, -2, -3])
>>> pearsonr_d(x, y)
tensor(2.0, dtype=torch.float64)