scipy.stats.tmax¶
- scipy.stats.tmax(a, upperlimit=None, axis=0, inclusive=True, nan_policy='propagate')[source]¶
- 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. - 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: - tmax : float, int or ndarray - Examples - >>> from scipy import stats >>> x = np.arange(20) >>> stats.tmax(x) 19 - >>> stats.tmax(x, 13) 13 - >>> stats.tmax(x, 13, inclusive=False) 12 
