Improve performance of converting numpy array to MATLAB double

Passing numpy arrays efficiently

Take a look at the file mlarray_sequence.py in the folder PYTHONPATH\Lib\site-packages\matlab\_internal. There you will find the construction of the MATLAB array object. The performance problem comes from copying data with loops within the generic_flattening function.

To avoid this behavior we will edit the file a bit. This fix should work on complex and non-complex datatypes.

1. Make a backup of the original file in case something goes wrong.

2. Add import numpy as np to the other imports at the beginning of the file

3. In line 38 you should find:

   init_dims = _get_size(initializer)
   

   replace this with:

   try:
       init_dims=initializer.shape
   except:
       init_dims = _get_size(initializer)
   

4. In line 48 you should find:

   if is_complex:
       complex_array = flat(self, initializer,
                            init_dims, typecode)
       self._real = complex_array['real']
       self._imag = complex_array['imag']
   else:
       self._data = flat(self, initializer, init_dims, typecode)
   

   Replace this with:

   if is_complex:
       try:
           self._real = array.array(typecode,np.ravel(initializer, order="F").real)
           self._imag = array.array(typecode,np.ravel(initializer, order="F").imag)
       except:
           complex_array = flat(self, initializer,init_dims, typecode)
           self._real = complex_array['real']
           self._imag = complex_array['imag']
   else:
       try:
           self._data = array.array(typecode,np.ravel(initializer, order="F"))
       except:
           self._data = flat(self, initializer, init_dims, typecode)
   

Now you can pass a numpy array directly to the MATLAB array creation method.

data1 = np.random.uniform(low = 0.0, high = 30000.0, size = (1000000,))
#faster
data1m = matlab.double(data1)
#or slower method
data1m = matlab.double(data1.tolist())

data2 = np.random.uniform(low = 0.0, high = 30000.0, size = (1000000,)).astype(np.complex128)
#faster
data1m = matlab.double(data2,is_complex=True)
#or slower method
data1m = matlab.double(data2.tolist(),is_complex=True)

The performance in MATLAB array creation increases by a factor of 15 and the interface is easier to use now.