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. ‘propagate’ returns nan, ‘raise’ throws an error, ‘omit’ performs the calculations ignoring nan values. Default is ‘propagate’.

Returns:

tmin : float, int or ndarray

Examples

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

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

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