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# scipy.stats.threshold

`scipy.stats.``threshold`(a, threshmin=None, threshmax=None, newval=0)

  Clip array to a given value.

  Similar to numpy.clip(), except that values less than threshmin or greater than threshmax are replaced by newval, instead of by threshmin and threshmax respectively.

  Parameters: | a : array_like Data to threshold. threshmin : float, int or None, optional Minimum threshold, defaults to None. threshmax : float, int or None, optional Maximum threshold, defaults to None. newval : float or int, optional Value to put in place of values in a outside of bounds. Defaults to 0.
  Returns: | out : ndarray The clipped input array, with values less than threshmin or greater than threshmax replaced with newval.

  Examples

      >>> a = np.array([9, 9, 6, 3, 1, 6, 1, 0, 0, 8])
      >>> from scipy import stats
      >>> stats.threshold(a, threshmin=2, threshmax=8, newval=-1)
      array([-1, -1,  6,  3, -1,  6, -1, -1, -1,  8])