numpy.MaskedArray.cumprod()返回掩码数组元素在给定轴上的累积乘积。在计算过程中,掩码值在内部设置为1。但是,将保存它们的位置,并且结果将在相同位置被屏蔽。
用法: numpy.ma.cumprod(axis=None, dtype=None, out=None)
参数:
axis :[int,可选]计算累积乘积的轴。默认值(无)是在展平的数组上计算cumprod。
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。如果未指定dtype,则默认为arr的dtype,除非arr的整数dtype的精度小于默认平台整数的精度。在这种情况下,将使用默认平台整数。
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:[cumprod_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.cumprod() 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.cumprod
# methods to masked array
out_arr = mask_arr.cumprod()
print ("cumulative product of masked array along default axis : ", out_arr)
输出:
Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [-- -1] [5 -3]] cumulative sum of masked array along default axis : [-- 2 -- -2 -10 30]
代码2:
# Python program explaining
# numpy.MaskedArray.cumprod() 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.cumprod methods
# to masked array
out_arr1 = mask_arr.cumprod(axis = 0)
print ("cumulative product of masked array along 0 axis : ", out_arr1)
out_arr2 = mask_arr.cumprod(axis = 1)
print ("cumulative product 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 --]] cumulative product of masked array along 0 axis : [[1 0 3] [4 0 --]] cumulative product of masked array along 1 axis : [[1 0 0] [4 4 --]]
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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.cumprod() 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。