Numpy recarray.cumsum() function | Python
In numpy, arrays may have a data-types containing fields, analogous to columns in a spreadsheet. An example is [(a, int), (b, float)]
, where each entry in the array is a pair of (int, float). Normally, these attributes are accessed using dictionary lookups such as arr['a'] and arr['b']
. Record arrays allow the fields to be accessed as members of the array, using arr.a and arr.b
.
numpy.recarray.cumsum()
function returns the cumulative sum of array elements over a given axis.
Syntax : numpy.recarray.cumsum(axis=None, dtype=None, out=None)
Parameters:
axis : Axis along which the cumulative sumis computed. The default is to compute the sum of the flattened array.
dtype : 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.
-> If provided, it must have a shape that the inputs broadcast to.
-> If not provided or None, a freshly-allocated array is returned.
Return : A new array holding the result is returned unless out is specified, in which case it is returned.
Code #1 :
import numpy as geek
in_arr = geek.array([[( 5.0 , 2 ), ( 3.0 , - 4 ), ( 6.0 , 9 )],
[( 9.0 , 1 ), ( 5.0 , 4 ), ( - 12.0 , - 7 )]],
dtype = [( 'a' , float ), ( 'b' , int )])
print ( "Input array : " , in_arr)
rec_arr = in_arr.view(geek.recarray)
print ( "Record array of float: " , rec_arr.a)
print ( "Record array of int: " , rec_arr.b)
out_arr = rec_arr.a.cumsum( axis = 1 )
print ( "Output array along axis 1: " , out_arr)
out_arr = rec_arr.b.cumsum()
print ( "Output array along default axis : " , out_arr)
|
Output:
Input array : [[( 5., 2) ( 3., -4) ( 6., 9)]
[( 9., 1) ( 5., 4) (-12., -7)]]
Record array of float: [[ 5. 3. 6.]
[ 9. 5. -12.]]
Record array of int: [[ 2 -4 9]
[ 1 4 -7]]
Output array along axis 1: [[ 5. 8. 14.]
[ 9. 14. 2.]]
Output array along default axis : [ 2 -2 7 8 12 5]
Last Updated :
27 Sep, 2019
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