Numpy recarray.conjugate() function | Python
Last Updated :
27 Sep, 2019
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.conjugate()
function return an array by conjugating the complex number in the array.
Syntax : numpy.recarray.conjugate(out=None)
Parameters:
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 : Output array with same dimensions as Input array, placed with result.
Code #1 :
import numpy as geek
in_arr = geek.array([[( 4.0 + 1j , 1 + 3j ), ( 5.0 , 5 - 1j ),
( 8.0 - 6j , 9 )], [( 9.0 , 1 ),
( 7.0 + 1j , 3 - 1j ), ( - 2.0 + 6j , - 7 + 3j )]],
dtype = [( 'a' , complex ), ( 'b' , complex )])
print ( "Input array : " , in_arr)
rec_arr = in_arr.view(geek.recarray)
print ( "1st Record array of complex : " , rec_arr.a)
out_arr = (rec_arr.a).conjugate()
print ( "Output 1st conjugated array : " , out_arr)
rec_arr = rec_arr.b
print ( "2nd Record array of complex : " , rec_arr)
out_arr = rec_arr.conjugate()
print ( "Output 2nd conjugated array : " , out_arr)
|
Output:
Input array : [[( 4.+1.j, 1.+3.j) ( 5.+0.j, 5.-1.j) ( 8.-6.j, 9.+0.j)]
[( 9.+0.j, 1.+0.j) ( 7.+1.j, 3.-1.j) (-2.+6.j, -7.+3.j)]]
1st Record array of complex : [[ 4.+1.j 5.+0.j 8.-6.j]
[ 9.+0.j 7.+1.j -2.+6.j]]
Output 1st conjugated array : [[ 4.-1.j 5.-0.j 8.+6.j]
[ 9.-0.j 7.-1.j -2.-6.j]]
2nd Record array of complex : [[ 1.+3.j 5.-1.j 9.+0.j]
[ 1.+0.j 3.-1.j -7.+3.j]]
Output 2nd conjugated array : [[ 1.-3.j 5.+1.j 9.-0.j]
[ 1.-0.j 3.+1.j -7.-3.j]]
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