 # Numpy MaskedArray.cumsum () Function | python

`numpy.MaskedArray.cumsum()` . However, their position is preserved and the result will be masked in the same places.

Syntax: ` numpy.ma.cumsum (axis = None, dtype = None, out = None) `

Parameters:
axis: [int, optional] Axis along which the cumulative sum is computed. The default (None) is to compute the cumsum over the flattened array.
dtype: [dtype, optional] Type of the returned array, as well as of the accumulator in which the elements are multiplied.
out: [ndarray, optional] A location into which the result is stored.
– & gt; If provided, it must have a shape that the inputs broadcast to.
– & gt; If not provided or None, a freshly-allocated array is returned.

Return: [cumsum_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:

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``` # Program Python explaining # numpy.MaskedArray.cumsum () method   # import numy as geek # and numpy.ma module as ma import numpy as geek  import numpy.ma as ma    # create input array in_arr = geek.array ([[ 1 , 2 ], [ 3 , - 1 ], [ 5 , - 3 ]]) print ( "Input array:" , in_arr)    # We now create a masked array. # invalidate the post . mask_arr = ma.masked_array ( in_arr, mask = [[ 1 , 0 ], [ 1 , 0 ], [ 0 , 0 ]])  print ( "Masked array:" , mask_arr)    # apply MaskedArray.cumsum # masked array methods out_arr = mask_arr.cumsum ()  print ( "cumulative sum of masked array along default axis: " , out_arr)  ```

` ` Output:

` Input array: [[1 2] [3 -1] [5 -3]] Masked array: [[- 2] [- -1] [5 -3]] cumulative sum of masked array along default axis: [- 2 - 1 6 3] `

Code # 2:

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``` # Python program explaining # numpy.MaskedArray.cumsum () method    # import numy as geek # and numpy.ma module as ma import numpy as geek  import numpy.ma as ma     # create input array in_arr  = geek.array ([[ 1 , 0 , 3 ], [ 4 , 1 , 6 ]])  print ( "Input array:" , in_arr)    # Now we create a masked array. # invalidating one entry. mask_arr = ma.masked_array (in_arr, mask = [[ 0 , 0 , 0 ], [ 0 , 0 , 1 ]])  print ( "Masked array:" , mask_arr)    # applying MaskedArray.cumsum methods # to the masked array out_arr1 = mask_arr.cumsum (axis = 0 )  print ( " cumulative sum of masked array along 0 axis: "  , out_arr1)   out_arr2 = mask_arr.cumsum (axis = 1 )  print ( "cumulative sum of masked array along 1 axis:" , out_arr2)   ```

` ` Exit :

` Input array: [[1 0 3] [4 1 6]] Masked array: [[1 0 3] [4 1 -]] cumulative sum of masked array along 0 axis: [[1 0 3] [5 1 -]] cumulative sum of masked array along 1 axis: [[1 1 4] `