PythonNet May 2014

pythonnet@python.org

3 participants
2 discussions

Efficient copy of .NET Array to ctypes or numpy array.
by Dave Cook 23 May '14

23 May '14

(Sorry for screwing up the thread; I messed up my list subscription. This is a response to https://mail.python.org/pipermail/pythondotnet/2014-May/001525.html ) Thanks, Jeffrey, that's awesome. Since the pointer can be directly accessed, np.frombuffer() can be used to avoid a copy. src_hndl = GCHandle.Alloc(src, GCHandleType.Pinned) try: src_ptr = src_hndl.AddrOfPinnedObject().ToInt32() bufType = ctypes.c_double*len(src) cbuf = bufType.from_address(src_ptr) dest = np.frombuffer(cbuf, dtype=cbuf._type_) finally: if src_hndl.IsAllocated: src_hndl.Free() Dave Cook

2 1

Efficient copy of .NET Array to ctypes or numpy array.
by Dave Cook 21 May '14

21 May '14

I need to copy a .NET Array (e.g. Double[] or Byte[]) to a numpy array, but it seems the only way to do so is element by element, which is very slow. Since we are copying a lot of data in real time, it creates a real bottleneck. Alternatively, efficient conversion of the .NET array to a Python style byte string would allow numpy.fromstring() to be used for creating the numpy array. (I see a similar question went unanswered on the list in August 2011, but I was hoping someone may have figured it out by now.) Thanks, Dave Cook

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PythonNet May 2014