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This gives the expected result
x = random.rand(1) + random.rand(1)*1j print x.dtype print x, x.real, x.imag and this works
C = zeros((2,2),dtype=complex) C[0,0] = 1+1j print C but if we change it to
C[0,0] = 1+1j + x I get "TypeError: can't convert complex to float".
If we now omit the explicit dtype = complex, I get "ValueError: setting an array element with a sequence".
Can someone explain what's going on, and how to do this without errors? I'm lost.
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NumPy provides the vdot() method that returns the dot product of vectors a and b. This function handles complex numbers differently than dot(a, b). Example 1: Python3.
NumPy supports a much greater variety of numerical types than Python does. This section shows which are available, and how to modify an array's data-type. Platform-defined double precision float: typically sign bit, 11 bits exponent, 52 bits mantissa.
Element Assignment in NumPy Arrays We can assign new values to an element of a NumPy array using the = operator, just like regular python lists.
Actually, none of the proposed solutions worked in my case (Python 2.7.6, NumPy 1.8.2). But I've found out, that change of dtype from complex (standard Python library) to numpy.complex_ may help:
>>> import numpy as np >>> x = 1 + 2 * 1j >>> C = np.zeros((2,2),dtype=np.complex_) >>> C array([[ 0.+0.j, 0.+0.j], [ 0.+0.j, 0.+0.j]]) >>> C[0,0] = 1+1j + x >>> C array([[ 2.+3.j, 0.+0.j], [ 0.+0.j, 0.+0.j]]) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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