sciPy stats.tmax()函数| Python
原文:https://www.geesforgeks.org/scipy-stats-tmax-function-python/
**scipy.stats.tmax(array, lowerlimit=None, axis=0, inclusive=True)**函数沿指定轴计算数组元素的修剪最大值，同时忽略指定限制之外的值。
参数: 数组:输入数组或对象中具有计算修剪后最大值的元素。 轴:轴，统计数据将沿着该轴计算。默认轴= 0 限制:考虑数组的下限和上限，小于下限或大于上限的值将被忽略。如果限制为无[默认值]，则使用所有值。 包含:决定是包含等于下限还是上限的值，还是在计算时将其排除。
返回:根据设置的参数，修剪数组元素的最大值。
代码#1:
# Trimmed Maximum
from scipy import stats
import numpy as np
# array elements ranging from 0 to 19
x = [1, 3, 27, 56, 2, 4, 13, 3, 6]
print("Trimmed Maximum :", stats.tmax(x))
print("\nTrimmed Maximum by setting limit : ",
stats.tmax(x, (5)))
Output:
Trimmed Maximum : 56
Trimmed Maximum by setting limit : 4
代码#2: 多维数据
# Trimmed Maximum
from scipy import stats
import numpy as np
# array elements ranging from 0 to 19
x = [[1, 3, 27],
[3, 4, 7],
[7, 6, 3],
[3, 6, 8]]
print("Trimmed Maximum :", stats.tmax(x))
# setting axis
print("\nTrimmed Maximum by setting axis : ",
stats.tmax(x, axis = 1))
print("\nTrimmed Maximum by setting axis : ",
stats.tmax(x, axis = 0))
# setting limit
print("\nTrimmed Maximum by setting limit : ",
stats.tmax(x, (5), axis = 1))
print("\nTrimmed Maximum by setting limit : ",
stats.tmax(x, (5), axis = 0))
Output:
Trimmed Maximum : [ 7 6 27]
Trimmed Maximum by setting axis : [27 7 7 8]
Trimmed Maximum by setting axis : [ 7 6 27]
Trimmed Maximum by setting limit : [3 4 3 3]
Trimmed Maximum by setting limit : [3 4 3]
