# scipy.stats.tmin

scipy.stats.tmin(a, lowerlimit=None, axis=0, inclusive=True, nan_policy='propagate')

  Compute the trimmed minimum.

  This function finds the miminum value of an array a along the specified axis, but only considering values greater than a specified lower limit.

  Parameters:
    a array_like

      Array of values.

    lowerlimit None or float, optional

      Values in the input array less than the given limit will be ignored. When lowerlimit 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 lower limit are included. The default value is True.

    nan_policy{‘propagate’, ‘raise’, ‘omit’}, optional

      Defines how to handle when input contains nan. The following options are available (default is ‘propagate’):

      > - ‘propagate’: returns nan

      > - ‘raise’: throws an error

      > - ‘omit’: performs the calculations ignoring nan values

  Returns:
    tmin float, int or ndarray

      Trimmed minimum.

  Examples

      >>> import numpy as np
      >>> from scipy import stats
      >>> x = np.arange(20)
      >>> stats.tmin(x)
      0

      >>> stats.tmin(x, 13)
      13

      >>> stats.tmin(x, 13, inclusive=False)
      14