Numpy Array to Complex Number in Python

In python I load a file of data from a SDR (Software Defined Radio) using rtl_sdr which is stored as uint8. The data seems to be 0-255 values.

It wants to be 0 centred with min -1 and max 1 and stored as complex.

I have two code blocks that have been provided that convert the array of numbers to complex, but the results are different. Pseudo array in sample code below.

METHOD 1

x = np.array([124, 127, 132, 125, 127, 127, 126, 125, 129, 128])x = x.astype(np.float32)x = (x - 127) / 128x = x.astype(complex)

Outputs:

array([-0.0234375+0.j,  0.       +0.j,  0.0390625+0.j, -0.015625 +0.j,    0.       +0.j,  0.       +0.j, -0.0078125+0.j, -0.015625 +0.j,    0.015625 +0.j,  0.0078125+0.j])

METHOD 2

y = np.array([124, 127, 132, 125, 127, 127, 126, 125, 129, 128])y = y.astype(np.float32).view(np.complex64)y /= 127.5y -= 1 + 1j

Outputs:

array([-0.02745092-0.00392151j,  0.03529418-0.01960778j,   -0.00392151-0.00392151j, ..., -0.02745092-0.05098033j,    0.01176476-0.00392151j,  0.05098045-0.01960778j], dtype=complex64)

Since the output is different at least one method is probably incorrect - but which?