scipy.stats.mstats.
tmin#
- scipy.stats.mstats.tmin(a, lowerlimit=None, axis=0, inclusive=True)[source]#
- Compute the trimmed minimum - Parameters:
- aarray_like
- array of values 
- lowerlimitNone 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. 
- axisint 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. 
 
- Returns:
- tminfloat, int or ndarray
 
 - Notes - For more details on - tmin, see- scipy.stats.tmin.- Examples - >>> import numpy as np >>> from scipy.stats import mstats >>> a = np.array([[6, 8, 3, 0], ... [3, 2, 1, 2], ... [8, 1, 8, 2], ... [5, 3, 0, 2], ... [4, 7, 5, 2]]) ... >>> mstats.tmin(a, 5) masked_array(data=[5, 7, 5, --], mask=[False, False, False, True], fill_value=999999)