scipy.stats.mstats.zmap(scores, compare, axis=0, ddof=0)[source]

Calculates the relative z-scores.

Returns an array of z-scores, i.e., scores that are standardized to zero mean and unit variance, where mean and variance are calculated from the comparison array.


scores : array_like

The input for which z-scores are calculated.

compare : array_like

The input from which the mean and standard deviation of the normalization are taken; assumed to have the same dimension as scores.

axis : int or None, optional

Axis over which mean and variance of compare are calculated. Default is 0. If None, compute over the whole array scores.

ddof : int, optional

Degrees of freedom correction in the calculation of the standard deviation. Default is 0.


zscore : array_like

Z-scores, in the same shape as scores.


This function preserves ndarray subclasses, and works also with matrices and masked arrays (it uses asanyarray instead of asarray for parameters).


>>> from scipy.stats import zmap
>>> a = [0.5, 2.0, 2.5, 3]
>>> b = [0, 1, 2, 3, 4]
>>> zmap(a, b)
array([-1.06066017,  0.        ,  0.35355339,  0.70710678])