# Convert numpy ndarray to matlab mlarray in python

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Gan Lee on 14 Apr 2022
mlarray to ndarray: np.asarray(x._data, dtype=dtype)
but inversely, ndarray to mlarray: matlab.double(x.tolist()), which is extremely slow, is there a more efficient way to do this? Thank u for answering.

Al Danial on 28 Apr 2022
Looks like you're making the data load unnecessarily complicated. The file actually loads cleanly into a NumPy array:
x = data['data']
print(x)
produces
array([[0.00000000e+00, 5.90000000e+01, 5.90000000e+01, 2.25296241e+05],
[1.00000000e+00, 6.20000000e+01, 5.81599120e+01, 5.93159561e+04],
[2.00000000e+00, 1.00000000e+02, 9.47518190e+01, 3.22666379e+04],
...,
[2.04500000e+03, 4.00000000e+00, 4.88991300e+00, 3.01840538e+04],
[2.04600000e+03, 2.00000000e+00, 2.26899200e+00, 6.46032757e+04],
[2.04700000e+03, 1.00000000e+00, 1.00000000e+00, 1.18671912e+05]])
print(data.keys()) if key is None else None
return data[key]
then call it like this

Al Danial on 21 Apr 2022
Which version of MATLAB? 2020a and newer (I don't have easy access to older versions) should just be able to do
>> mx = double(x);
without a conversion to a list.
##### 2 CommentsShowHide 1 older comment
Christopher Wunder on 23 Aug 2022
This is not possible for me either.
The function _is_initializer in matlab._internal.mlarray_utils.py checks for the input to be of type collections.abc.Sequence and a numpy.ndarray fails to be of such a type. The only way (without altering the package) is to convert the array beforehand or pass any kind of Sequence to it instead of an array.

Al Danial on 24 Apr 2022
Now I'm curious what is in your variable x. Can you make a small version of this data, write it to a .mat file, then attach the .mat file?

Gan Lee on 27 Apr 2022
Edited: Gan Lee on 27 Apr 2022
Here is part of my python code:
# -*- coding: utf-8 -*-
import numpy as np
import h5py
import matlab
from matlab import engine
from matlab import mlarray
print(data.keys()) if key is None else None
return data.get(key)[:].astype(np.double)
def mlarray2ndarray(x: mlarray):
return np.asarray(x._data, dtype=np.double)
def ndarray2mlarray(x: np.ndarray):
return matlab.double(x)
if __name__ == "__main__":
eng = engine.start_matlab()
pth_mat = r".\data.mat"
# np to matlab
# mx1: mlarray = ndarray2mlarray(x1) #WRONG
mx1 = matlab.double(x.tolist()) #OK, BUT VERY SLOWLY
# matlab to np
x2: np.ndarray = mlarray2ndarray(mx2) #OK
# ......
eng.exit()
here is errcode:
ValueError
initializer must be a rectangular nested sequence

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