qfeval_functions.functions.correl

correl(x, y, dim=(), keepdim=False)[source]

Compute Pearson correlation coefficient between two tensors.

This function calculates the Pearson correlation coefficient between tensors x and y along the specified dimension(s). The correlation coefficient measures the linear relationship between two variables and ranges from -1 (perfect negative correlation) to 1 (perfect positive correlation), with 0 indicating no linear correlation.

Parameters:

  • x (Tensor) – The first input tensor.

  • y (Tensor) – The second input tensor. Must be the same shape as x.

  • dim (Union[int, Tuple[int, ...]]) – The dimension(s) along which to compute the correlation. If not specified (default is empty tuple), computes element-wise correlation and sums the result.

  • keepdim (bool) – Whether the output tensor has dim retained or not. Default is False.

Returns:

The Pearson correlation coefficient(s). The shape depends on the input dimensions and the keepdim parameter.

Return type:

Tensor

Example

>>> x = torch.tensor([1.0, 2.0, 3.0, 4.0, 5.0])
>>> y = torch.tensor([2.0, 4.0, 6.0, 8.0, 10.0])
>>> QF.correl(x, y, dim=0)
tensor(1.)

>>> x = torch.tensor([[1.0, 2.0, 3.0],
...                   [4.0, 5.0, 6.0]])
>>> y = torch.tensor([[2.0, 4.0, 5.0],
...                   [8.0, 10.0, 12.0]])
>>> QF.correl(x, y, dim=1)
tensor([0.9820, 1.0000])

>>> QF.correl(x, y, dim=1, keepdim=True)
tensor([[0.9820],
        [1.0000]])