I recently started programming macros for a microscope that is controlled by ZEN Blue from Zeiss. The Zeiss macro environment uses IronPython 126.96.36.199. I need to write out a hdf5 file, but unfortunately hdf5 support for IronPython is quite bad.
The data I want to transfer is of type Array[Byte] which seems to be somehow connected to the CLR of .NET:
print "length: %i type: %s" %(len(data), type(data))
length: 4915200 type: <type 'Array[Byte]'>
I can sucessfully transfer a dict containing ints and Strings to a python server using pickle via a socket connection (suggested here). However, when I try to unpickle the
Array[Byte] data, python wants to import the CLR, which of course fails:
ImportError: No module named clr
Question: What is the best (fastest) way to convert the .NET Array[Byte] to a basic python type/object which is not linked to the .NET clr?
After some testing, the most efficient solution that I found works like this:
First, convert Array[Byte] to a python string:
data_str = str(buffer(data))
I'm not entirely sure what
buffer does, but it seems to be necessary for efficient computation, some explanation here.
Then send to cpython (in my case via a socket, cpython runs on a linux box) and convert to a tuple:
#data_str is an RGB image with dims sx and sy format_str = str(sx*sy*3).strip() + 'B' im_data = struct.unpack(format_str, data_str) #conversion to tuple
h5py to write the
#put into np.array im = np.asarray(im_data, dtype=np.uint8) #this is the most Time consuming part newshape = (3, sx, sy) im = np.reshape(im, newshape, order='F') #write out f = h5py.File('zenimage_bgr24.h5', 'w') f.create_dataset('/im', data = im, dtype='uint8') f.close()