复数可以用使用函数 complex(real, imag) 或者是带有后缀j的浮点数来指定 a=complex(2,4)print(a)#(2+4j)b=2-5j#获取对应的实部、虚部和共轭复数print(b.real,b.imag,b.conjugate())#2.0 -5.0 (2+5j)#数学运算print(a+b)#(4-1j)print(abs(a))#4.47213595499958 复数函数比如正弦、余弦或平方根,使...
复制代码 获取复数数组的实部和虚部: real_part = complex_array.real imaginary_part = complex_array.imag 复制代码 进行复数运算: # 加法 result = complex_array[0] + complex_array[1] # 乘法 result = complex_array[0] * complex_array[1] # 共轭 conjugate = np.conj(complex_array) 复制代码 ...
eigvals : eigenvalues of a non-symmetric array. eigh : eigenvalues and eigenvectors of a real symmetric or complex Hermitian (conjugate symmetric) array. eigvalsh : eigenvalues of a real symmetric or complex Hermitian (conjugate symmetric) array. scipy.linalg.eig : Similar function in SciPy that ...
Python之复数、分数、⼤型数组数学运算（complex、cmath、numpy、fra。。。⼀、复数的数学运算 复数可以⽤使⽤函数 complex(real, imag) 或者是带有后缀j的浮点数来指定 a=complex(2,4)print(a) # (2+4j)b=2-5j # 获取对应的实部、虚部和共轭复数 print(b.real,b.imag,b.conjugate()) # 2...
HReturns the (complex) conjugate transpose of self. IReturns the (multiplicative) inverse of invertible self. 下面是从nadarray继承的属性 矩阵的属性属性说明 TReturns the transpose of the matrix. baseBase object if memory is from some other object. ...
'complex64', 'complex_', 'complexfloating', 'compress', 'concatenate', 'conj', 'conjugate', 'convolve', 'copy', 'copysign', 'copyto', 'core', 'corrcoef', 'correlate', 'cos', 'cosh', 'count_nonzero', 'cov', 'cross', 'csingle', 'ctypeslib', 'cumprod', 'cumproduct', 'cumsum...
numpy.conj(x [, out] = ufunc'conjugate'):此函数可帮助用户对任何复数进行共轭。 复数的共轭可通过更改其虚部的符号来获得。如果复数为2 + 5j, 则其共轭为2-5j。 # Python3 code demonstrate conj() function #importing numpy import numpy as np ...
>>> c = array( [ [1,2], [3,4] ], dtype=complex ) >>> c array([[ 1.+0.j, 2.+0.j], [ 3.+0.j, 4.+0.j]]) 通常,数组的元素开始都是未知的,但是它的大小已知。因此,NumPy提供了一些使用占位符创建数组的函数。这最小化了扩展数组的需要和高昂的运算代价。
axis,argmax, argmin, argsort, average, # bincount, ceil, clip, conj, conjugate, corrcoef...
For complex vectors, the conjugate is taken. These add to the existing numpy.matmul as well as to numpy.vecdot, which was added in numpy 2.0. Note that numpy.matmul never takes a complex conjugate, also not when its left input is a vector, while both numpy.vecdot and numpy.vecmat do...