numpy.MaskedArray.cumprod()返回掩碼數組元素在給定軸上的累積乘積。在計算過程中,掩碼值在內部設置為1。但是,將保存它們的位置,並且結果將在相同位置被屏蔽。
用法: numpy.ma.cumprod(axis=None, dtype=None, out=None)
參數:
axis :[int,可選]計算累積乘積的軸。默認值(無)是在展平的數組上計算cumprod。
dtype : [dtype,可選]返回數組的類型,以及與元素相乘的累加器的類型。如果未指定dtype,則默認為arr的dtype,除非arr的整數dtype的精度小於默認平台整數的精度。在這種情況下,將使用默認平台整數。
out : [ndarray,可選]將結果存儲到的位置。
->如果提供,則必須具有廣播輸入的形狀。
->如果未提供或沒有,則返回新分配的數組。
返回:[cumprod_along_axis,ndarray]除非指定out,否則將返回保存結果的新數組,在這種情況下,將返回對out的引用。
代碼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)
輸出:
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]
代碼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)
輸出:
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:本文由純淨天空篩選整理自jana_sayantan大神的英文原創作品 Numpy MaskedArray.cumprod() function | Python。非經特殊聲明,原始代碼版權歸原作者所有,本譯文未經允許或授權,請勿轉載或複製。