numpy.conj() in Python
Last Updated :
04 Dec, 2020
The numpy.conj() function helps the user to conjugate any complex number.
The conjugate of a complex number is obtained by changing the sign of its imaginary part. If the complex number is 2+5j then its conjugate is 2-5j.
Syntax:numpy.conj(x[, out] = ufunc ‘conjugate’)
Parameters :
x [array_like]: Input value.
out [ndarray, optional] : Output array with same dimensions as Input array, placed with result.
Return :
x : ndarray. The complex conjugate of x, with same dtype as y.
Code #1 :
import numpy as np
in_complx1 = 2 + 4j
out_complx1 = np.conj(in_complx1)
print ( "Output conjugated complex number of 2+4j : " , out_complx1)
in_complx2 = 5 - 8j
out_complx2 = np.conj(in_complx2)
print ( "Output conjugated complex number of 5-8j: " , out_complx2)
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Output :
Output conjugated complex number of 2+4j : (2-4j)
Output conjugated complex number of 5-8j: (5+8j)
Code #2 :
import numpy as np
in_array = np.eye( 2 ) + 3j * np.eye( 2 )
print ( "Input array : " , in_array)
out_array = np.conjugate(in_array)
print ( "Output conjugated array : " , out_array)
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Output :
Input array : [[ 1.+3.j 0.+0.j]
[ 0.+0.j 1.+3.j]]
Output conjugated array : [[ 1.-3.j 0.-0.j]
[ 0.-0.j 1.-3.j]]
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