corrcoef

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corrcoef#

class saiunit.math.corrcoef(x, y=None, rowvar=True, unit_to_scale=None, **kwargs)#

Return Pearson product-moment correlation coefficients.

Please refer to the documentation for cov for more detail. The relationship between the correlation coefficient matrix, R, and the covariance matrix, C, is

\[R_{ij} = \frac{ C_{ij} } { \sqrt{ C_{ii} C_{jj} } }\]

The values of R are between -1 and 1, inclusive.

Parameters:

  • x (Array | ndarray | bool | number | bool | int | float | complex | saiunit.Quantity) – A 1-D or 2-D array containing multiple variables and observations. Each row of x represents a variable, and each column a single observation of all those variables. Also see rowvar below.

  • y (Array | ndarray | bool | number | bool | int | float | complex | saiunit.Quantity) – An additional set of variables and observations. y has the same shape as x.

  • rowvar (bool) – If rowvar is True (default), then each row represents a variable, with observations in the columns. Otherwise, the relationship is transposed: each column represents a variable, while the rows contain observations.

  • unit_to_scale (saiunit.Unit | None) – The unit to scale the x.

Returns:

R – The correlation coefficient matrix of the variables.

Return type:

Array

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