### Navigation

- index
- modules |
- modules |
- next |
- previous |
- SciPy v0.12 Reference Guide (DRAFT) »
- Statistical functions for masked arrays (`scipy.stats.mstats`) »

# scipy.stats.mstats.zmap

`scipy.stats.mstats.``zmap`(scores, compare, axis=0, ddof=0)

  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.

  Parameters : | 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. ddof : int, optional Degrees of freedom correction in the calculation of the standard deviation. Default is 0.
  Returns : | zscore : array_like Z-scores, in the same shape as scores.

  Notes

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

  Examples

      >>> 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])

### Navigation

- index
- modules |
- modules |
- next |
- previous |
- SciPy v0.12 Reference Guide (DRAFT) »
- Statistical functions for masked arrays (`scipy.stats.mstats`) »