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.conj()
function return an array by conjugating the complex number in the array.
Syntax :
numpy.recarray.conj(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 :
# Python program explaining # numpy.recarray.conj() method # importing numpy as geek import numpy as geek # creating input array in_arr = geek.array([[( 5.0 + 2j , 2 + 1j ), ( 3.0 , - 4 + 6j ), ( 6.0 - 5j , 9 )], [( 9.0 , 1 ), ( 5.0 + 1j , 4 - 1j ), ( - 12.0 + 6j , - 7 + 3j )]], dtype = [( 'a' , complex ), ( 'b' , complex )]) print ( "Input array : " , in_arr) # convert it to a record array, using arr.view(np.recarray) rec_arr = in_arr.view(geek.recarray) # 1st record array print ( "1st Record array of complex : " , rec_arr.a) # applying recarray.conj methods to 1st record array out_arr = (rec_arr.a).conj() print ( "Output 1st conjugated array : " , out_arr) # 2nd record array rec_arr = rec_arr.b print ( "2nd Record array of complex : " , rec_arr) # applying recarray.conj methods to 2nd record array out_arr = rec_arr.conj() print ( "Output 2nd conjugated array : " , out_arr) |
Input array : [[( 5.+2.j, 2.+1.j) ( 3.+0.j, -4.+6.j) ( 6.-5.j, 9.+0.j)] [( 9.+0.j, 1.+0.j) ( 5.+1.j, 4.-1.j) (-12.+6.j, -7.+3.j)]] 1st Record array of complex : [[ 5.+2.j 3.+0.j 6.-5.j] [ 9.+0.j 5.+1.j -12.+6.j]] Output 1st conjugated array : [[ 5.-2.j 3.-0.j 6.+5.j] [ 9.-0.j 5.-1.j -12.-6.j]] 2nd Record array of complex : [[ 2.+1.j -4.+6.j 9.+0.j] [ 1.+0.j 4.-1.j -7.+3.j]] Output 2nd conjugated array : [[ 2.-1.j -4.-6.j 9.-0.j] [ 1.-0.j 4.+1.j -7.-3.j]]
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