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# scipy.stats.mstats.tmax

scipy.stats.mstats.tmax(a, upperlimit=None, axis=0, inclusive=True)

  Compute the trimmed maximum

  This function computes the maximum value of an array along a given axis, while ignoring values larger than a specified upper limit.

  Parameters:
    a array_like

      array of values

    upperlimit None or float, optional

      Values in the input array greater than the given limit will be ignored. When upperlimit is None, then all values are used. The default value is None.

    axis int or None, optional

      Axis along which to operate. Default is 0. If None, compute over the whole array a.

    inclusive{True, False}, optional

      This flag determines whether values exactly equal to the upper limit are included. The default value is True.

  Returns:
    tmax float, int or ndarray

  Notes

  For more details on `tmax`, see `scipy.stats.tmax`.

  Examples

      >>> import numpy as np
      >>> from scipy.stats import mstats
      >>> a = np.array([[6, 8, 3, 0],
      ...               [3, 9, 1, 2],
      ...               [8, 7, 8, 2],
      ...               [5, 6, 0, 2],
      ...               [4, 5, 5, 2]])
      ...
      ...
      >>> mstats.tmax(a, 4)
      masked_array(data=[4, --, 3, 2],
                   mask=[False,  True, False, False],
             fill_value=999999)