Numpy recarray.conj() 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.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]]
