numpy.MaskedArray.average()函数用于返回给定轴上数组的加权平均值。

用法： numpy.ma.average(arr, axis=None, weights=None, returned=False)

参数：

arr :[数组]输入要对其数据求平均的掩码数组。在计算中不考虑屏蔽的条目。

axis :[int，可选]平均arr的轴。如果为None，则对展平的数组进行平均。

weights :[数组，可选]每个元素在平均值计算中的重要性。如果weights = None，则假定arr中的所有数据的权重等于1。如果权重很复杂，则虚部将被忽略。

returned :[bool，可选]它指示是否应将元组(结果，权重之和)作为输出(真)或仅作为结果(假)返回。默认值为False。

返回：[标量或MaskedArray]沿指定轴的平均值。当返回True时，返回一个以平均值为第一个元素，权重之和为第二个元素的元组。

代码1：

# Python program explaining

# numpy.MaskedArray.average() method

# importing numpy as geek

# and numpy.ma module as ma

import numpy as geek

import numpy.ma as ma

# creating input array

in_arr = geek.array([[1, 2], [ 3, -1], [ 5, -3]])

print ("Input array : ", in_arr)

# Now we are creating a masked array.

# by making  entry as invalid.

mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]])

print ("Masked array : ", mask_arr)

# applying MaskedArray.average

# methods to masked array

out_arr = ma.average(mask_arr)

print ("normal average of masked array : ", out_arr)

输出：

Input array : [[ 1 2]

[ 3 -1]

[ 5 -3]]

Masked array : [[-- 2]

[-- -1]

[5 -3]]

normal average of masked array : 0.75

代码2：

# Python program explaining

# numpy.MaskedArray.average() method

# importing numpy as geek

# and numpy.ma module as ma

import numpy as geek

import numpy.ma as ma

# creating input array

in_arr = geek.array([[1, 2], [ 3, -1], [ 5, -3]])

print ("Input array : ", in_arr)

# Now we are creating a masked array.

# by making  entry as invalid.

mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]])

print ("Masked array : ", mask_arr)

# applying MaskedArray.average

# methods to masked array

out_arr = ma.average(mask_arr, weights =[[0, 1], [ 0, 2], [ 3, 1]])

print ("weighted average of masked array : ", out_arr)

输出：

Input array : [[ 1 2]

[ 3 -1]

[ 5 -3]]

Masked array : [[-- 2]

[-- -1]

[5 -3]]

weighted average of masked array : 1.7142857142857142