Unexpected result with Numpy ctypes data_as pointer arrays

Question

I am getting an unexpected result with two Numpy arrays when I represent them as Ctypes pointers. I have created a minimal example that reproduces the problem I am running into:

import numpy as np
from ctypes import c_float, POINTER

c_float_p = POINTER(c_float)

a = np.array([1], dtype=c_float).ctypes.data_as(c_float_p)
b = np.array([2], dtype=c_float).ctypes.data_as(c_float_p)

print('a: {}, b: {}'.format(a.contents, b.contents))

When I run this I get the following output:

a: c_float(2.0), b: c_float(2.0)

Clearly the contents of the first array have been overridden with the contents of the second. Hence, it seems that the two pointers point to the same location. How can I avoid this from happening?

Note: I am using Python 3.6, Numpy 1.15.4.

D. de Vries · Accepted Answer · 2019-01-18 19:24:23Z

2

It turns out the above example runs as expected when I updated Numpy to 1.16.0.

answered Jan 18, 2019 at 19:24

D. de Vries

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