numpy.MaskedArray.mean()函数用于返回沿给定轴的被屏蔽数组元素的平均值,此处被屏蔽的条目将被忽略,并且非限定结果元素将被屏蔽。
用法: numpy.ma.mean(axis=None, dtype=None, out=None)
参数:
axis :[int,可选]计算平均值的轴。默认值(无)是计算平坦数组的平均值。
dtype : [dtype,可选]返回数组的类型,以及与元素相乘的累加器的类型。
out : [ndarray,可选]将结果存储到的位置。
->如果提供,则必须具有广播输入的形状。
->如果未提供或没有,则返回新分配的数组。
返回:[mean_along_axis,ndarray]除非指定out,否则将返回保存结果的新数组,在这种情况下,将返回对out的引用。
代码1:
# Python program explaining
# numpy.MaskedArray.mean() 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.mean
# methods to masked array
out_arr = mask_arr.mean()
print ("mean of masked array along default axis : ", out_arr)
输出:
Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [-- -1] [5 -3]] mean of masked array along default axis : 0.75
代码2:
# Python program explaining
# numpy.MaskedArray.mean() 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, 0, 3], [ 4, 1, 6]])
print ("Input array : ", in_arr)
# Now we are creating a masked array.
# by making one entry as invalid.
mask_arr = ma.masked_array(in_arr, mask =[[ 0, 0, 0], [ 0, 0, 1]])
print ("Masked array : ", mask_arr)
# applying MaskedArray.mean methods
# to masked array
out_arr1 = mask_arr.mean(axis = 0)
print ("mean of masked array along 0 axis : ", out_arr1)
out_arr2 = mask_arr.mean(axis = 1)
print ("mean of masked array along 1 axis : ", out_arr2)
输出:
Input array : [[1 0 3] [4 1 6]] Masked array : [[1 0 3] [4 1 --]] mean of masked array along 0 axis : [2.5 0.5 3.0] mean of masked array along 1 axis : [1.3333333333333333 2.5]
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注:本文由纯净天空筛选整理自jana_sayantan大神的英文原创作品 Numpy MaskedArray.mean() function | Python。非经特殊声明,原始代码版权归原作者所有,本译文未经允许或授权,请勿转载或复制。