Numpy MaskedArray.conjugate()函数| Python
numpy.MaskedArray.conjugate()函数用于按元素返回复数共轭。复数的共轭是通过改变其虚部的符号来获得的。
Syntax : numpy.ma.conjugate(arr, out=None, where=True, casting='same_kind', order='K', dtype=None, subok=True)
Parameters:
arr :[ array_like] Input masked array which we want to conjugate.
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.
where : [array_like, optional] Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone.
casting :[ ‘no’, ‘equiv’, ‘safe’, ‘same_kind’, or ‘unsafe’] Provides a policy for what kind of casting is permitted.
order : The elements of a are read using this index order.
dtype :[dtype, optional] Type of the returned array, as well as of the accumulator in which the elements are multiplied.
subok : Defaults to true. If set to false, the output will always be a strict array, not a subtype.
Return : [ ndarray] The complex conjugate of arr.
代码#1：
# Python program explaining
# numpy.MaskedArray.conjugate() method
# importing numpy as geek
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
# creating input array
in_arr = geek.array([[1 + 2j, 2 + 3j], [ 3-2j, -1 + 2j], [ 5-4j, -3-3j]])
print ("Input array : ", in_arr)
# Now we are creating a masked array.
# by making two entry as invalid.
mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]])
print ("Masked array : ", mask_arr)
# applying MaskedArray.conjugate
# methods to masked array
out_arr = ma.conjugate(mask_arr)
print ("conjugate of masked array : ", out_arr)
Input array : [[ 1.+2.j 2.+3.j]
[ 3.-2.j -1.+2.j]
[ 5.-4.j -3.-3.j]]
Masked array : [[-- (2+3j)]
[-- (-1+2j)]
[(5-4j) (-3-3j)]]
conjugate of masked array : [[-- (2-3j)]
[-- (-1-2j)]
[(5+4j) (-3+3j)]