Numpy MaskedArray.cumprod() function | Python
Last Updated :
18 Oct, 2019
numpy.MaskedArray.cumprod()
Return the cumulative product of the masked array elements over the given axis.Masked values are set to 1 internally during the computation. However, their position is saved, and the result will be masked at the same locations.
Syntax : numpy.ma.cumprod(axis=None, dtype=None, out=None)
Parameters:
axis :[ int, optional] Axis along which the cumulative product is computed. The default (None) is to compute the cumprod over the flattened array.
dtype : [dtype, optional] Type of the returned array, as well as of the accumulator in which the elements are multiplied. If dtype is not specified, it defaults to the dtype of arr, unless arr has an integer dtype with a precision less than that of the default platform integer. In that case, the default platform integer is used instead.
out : [ndarray, optional] A location into which the result is stored.
-> If provided, it must have a shape that the inputs broadcast to.
-> If not provided or None, a freshly-allocated array is returned.
Return : [cumprod_along_axis, ndarray] A new array holding the result is returned unless out is specified, in which case a reference to out is returned.
Code #1 :
import numpy as geek
import numpy.ma as ma
in_arr = geek.array([[ 1 , 2 ], [ 3 , - 1 ], [ 5 , - 3 ]])
print ( "Input array : " , in_arr)
mask_arr = ma.masked_array(in_arr, mask = [[ 1 , 0 ], [ 1 , 0 ], [ 0 , 0 ]])
print ( "Masked array : " , mask_arr)
out_arr = mask_arr.cumprod()
print ( "cumulative product of masked array along default axis : " , out_arr)
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Output:
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]
Code #2 :
import numpy as geek
import numpy.ma as ma
in_arr = geek.array([[ 1 , 0 , 3 ], [ 4 , 1 , 6 ]])
print ( "Input array : " , in_arr)
mask_arr = ma.masked_array(in_arr, mask = [[ 0 , 0 , 0 ], [ 0 , 0 , 1 ]])
print ( "Masked array : " , mask_arr)
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)
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Output:
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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