Converting a matrix created with MATLAB to Numpy array with a similar syntax

Question

I'm playing with the code snippets of the course I'm taking which is originally written in MATLAB. I use Python and convert these matrices to Python for the toy examples. For example, for the following MATLAB matrix:

s = [2 3; 4 5];

I use

s = array([[2,3],[4,5]])

It is too time consuming for me to re-write all the toy examples this way because I just want to see how they work. Is there a way to directly give the MATLAB matrix as string to a Numpy array or a better alternative for this?

For example, something like:

s = myMagicalM2ArrayFunction('[2 3; 4 5]')

np.matrix actually supports some strings more similar to matlab (maybe it does yours), but I would try to avoid it personally... also in numpy it is usually better to avoid matrices, so do convert it to an array afterwards. — seberg
– seberg, Commented Apr 3, 2013 at 13:34
Thanks @seberg. I would also prefer array approach instead of Matrix. — petrichor
– petrichor, Commented Apr 3, 2013 at 13:37

root · Accepted Answer · 2013-04-03 14:12:43Z

6

numpy.matrix can take string as an argument.

Docstring:
matrix(data, dtype=None, copy=True)

[...]

Parameters
----------
data : array_like or string
   If `data` is a string, it is interpreted as a matrix with commas
   or spaces separating columns, and semicolons separating rows.

In [1]: import numpy as np

In [2]: s = '[2 3; 4 5]'    

In [3]: def mag_func(s):
   ...:     return np.array(np.matrix(s.strip('[]')))

In [4]: mag_func(s)
Out[4]: 
array([[2, 3],
       [4, 5]])

edited Apr 3, 2013 at 14:12

answered Apr 3, 2013 at 13:52

root

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3 Comments

petrichor Over a year ago

Then, np.array(np.matrix(s.strip('[]'))) will do the same magic. It looks more compact.

JoshAdel Over a year ago

+1 since I hardly ever use np.matrix, I didn't know that it takes a string as an input. Good trick to know. Thanks

root Over a year ago

@petrichor -- added a full example.

JoshAdel · Accepted Answer · 2013-04-03 13:48:38Z

2

How about just saving a set of example matrices in Matlab and load them directly into python:

http://docs.scipy.org/doc/scipy/reference/tutorial/io.html

EDIT:

or not sure how robust this is (just threw together a simple parser which is probably better implemented in some other way), but something like:

import numpy as np

def myMagicalM2ArrayFunction(s):
    tok = []
    for t in s.strip('[]').split(';'):
        tok.append('[' + ','.join(t.strip().split(' ')) + ']')

    b = eval('[' + ','.join(tok) + ']')
    return np.array(b)

For 1D arrays, this will create a numpy array with shape (1,N), so you might want to use np.squeeze to get a (N,) shaped array depending on what you are doing.

edited Apr 3, 2013 at 13:48

answered Apr 3, 2013 at 13:22

JoshAdel

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2 Comments

petrichor Over a year ago

This requires MATLAB I think and it is more time consuming for me.

JoshAdel Over a year ago

@petrichor Ok, see the edit for a simple string parser that works for your example.

Roulbacha · Accepted Answer · 2019-05-12 15:50:49Z

0

If you want a numpy array rather than a numpy matrix

    def str_to_mat(x):
        x = x.strip('[]')
        return np.vstack(list(map(lambda r: np.array(r.split(','), dtype=np.float32), x.split(';'))))

answered May 12, 2019 at 15:50

Roulbacha

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Comments

Ka Wa Yip · Accepted Answer · 2024-06-10 19:49:24Z

One can do the following to translate any format of MATLAB matrix to a numpy array:

def myMagicalM2ArrayFunction(s):
    rule = '[\d]*[.][\d]+|[\d]+'
    s = s[1:-1]
    s = s.split(';')
    nlists = []
    for item in s:
        nlist = []
        if re.search(rule, item) is not None:
            for catch in re.finditer(rule, item):
                nlist.append(int(catch[0])) if catch[0].isdigit() else nlist.append(float(catch[0]))
        nlists.append(nlist)
    return np.array(nlists)

Example 1:

import re
import numpy as np
s = myMagicalM2ArrayFunction('[2 3; 4 5]')

Output 1:

array([[2, 3],
       [4, 5]])

Example 2:

s = myMagicalM2ArrayFunction('[ 0.2 3;4.3 5 ]')

Output 2:

array([[0.2, 3. ],
       [4.3, 5. ]])

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