Convert numpy ndarray to matlab mlarray in python

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Gan Lee
Gan Lee 2022-4-14
评论： Christopher Wunder 2022-8-23
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.

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采纳的回答

Al Danial
Al Danial 2022-4-28
Looks like you're making the data load unnecessarily complicated. The file actually loads cleanly into a NumPy array:
from scipy.io import loadmat
data = loadmat('data.mat', squeeze_me=True)
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]])
Simplify your function load_mat to
def load_mat(pth_mat, key=None):
data = loadmat(pth_mat, squeeze_me=True)
print(data.keys()) if key is None else None
return data[key]
then call it like this
x1 = load_mat('data.mat', 'data')

更多回答（3 个）

Al Danial
Al Danial 2022-4-21
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 个评论
Christopher Wunder
Christopher Wunder 2022-8-23
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.

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Al Danial
Al Danial 2022-4-24
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
Gan Lee 2022-4-27
编辑：Gan Lee 2022-4-27
Here is part of my python code:
# -*- coding: utf-8 -*-
import numpy as np
from scipy.io import loadmat
import h5py
import matlab
from matlab import engine
from matlab import mlarray
def load_mat(pth_mat, key=None):
data = loadmat(pth_mat)
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
x1: np.ndarray = load_mat(pth_mat, key="data")
# mx1: mlarray = ndarray2mlarray(x1) #WRONG
mx1 = matlab.double(x.tolist()) #OK, BUT VERY SLOWLY
# matlab to np
mx2: mlarray = eng.load(pth_mat).get("data")
x2: np.ndarray = mlarray2ndarray(mx2) #OK
# ......
eng.exit()
here is errcode:
ValueError
initializer must be a rectangular nested sequence

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