ursch...@gmail.com wrote: > I'm using ctypes to interface with a binary which returns a void pointer > (ctypes c_void_p) to a nested 64-bit float array: > [[1.0, 2.0], [3.0, 4.0], … ] > then return the pointer so it can be freed > > I'm using the following code to de-reference it: > > # a 10-element array > shape = (10, 2) > array_size = np.prod(shape) > mem_size = 8 * array_size > array_str = ctypes.string_at(ptr, mem_size) > # convert to NumPy array,and copy to a list > ls = np.frombuffer(array_str, dtype="float64", > count=array_size).reshape(shape).tolist() > # return pointer so it can be freed > drop_array(ptr) > return ls > > This works correctly and consistently on Linux and OSX using NumPy 1.11.0, > but fails on Windows 32 bit and 64-bit about 50% of the time, returning > nonsense values. Am I doing something wrong? Is there a better way to do > this?
I'd verify that the underlying memory has not been freed by the "binary" when you are doing the ctypes/numpy processing. You might get the correct values only when you are "lucky" and the memory has not yet been reused for something else, and you are "lucky" on Linux/OSX more often than on Windows... -- https://mail.python.org/mailman/listinfo/python-list
