# Convert python numpy array to double

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The plot call below will throw an error because x is not a matlab type. How do you convert a python numpy array to a regular matlab matrix?

x = py.numpy.random.random([4,4]);

plot(x)

Sincerely, Peter

##### 3 Comments

### Accepted Answer

David Garrison
on 27 Aug 2020

Beginning in MATLAB R2018b, Python functions that accept numpy arrays may also accept MATLAB arrays without explicit conversion. When necessary, a numpy array can be created explicitly from a MATLAB array. For example, if you have a supported version of Python that is installed with the numpy library, you can do the following:

>> x = rand(2,2); % MATLAB array

>> y = py.numpy.array(x); % numpy array

y =

Python ndarray:

0.5943 0.8064

0.6133 0.1372

Use details function to view the properties of the Python object.

Use double function to convert to a MATLAB array.

Also beginning in MATLAB R2018b, it is possible to convert numeric numpy arrays returned from Python into MATLAB arrays. For example:

>> y = py.numpy.random.random([int32(2), int32(2)]) % numpy array

y =

Python ndarray:

0.5943 0.8064

0.6133 0.1372

Use details function to view the properties of the Python object.

Use double function to convert to a MATLAB array.

>> x = 2*double(y) % MATLAB array

x =

1.1885 1.6129

1.2266 0.2744

See the MATLAB documentation on Passing Matrices and Multidimensional Arrays for additional Information.

##### 3 Comments

abraham rodriguez
on 18 Sep 2021

winkmal
on 17 May 2022

y = py.numpy.random.random([int32(2), int32(2)])

gives

Python Error: AttributeError: 'array.array' object has no attribute 'fromstring'

### More Answers (3)

Jim Hokanson
on 4 Nov 2014

Here's another approach. This is alluded to by http://www.mathworks.com/help/matlab/matlab_external/handling-data-returned-from-python.html

data = double(py.array.array('d',py.numpy.nditer(x))); %d is for double, see link below on types

data = reshape(data,[4 4])'; %Could incorporate x.shape here ...

py.array.array is apparently the way Matlab suggests getting data from Python into Matlab (see link above) https://docs.python.org/2/library/array.html

This however requires an iterable over which the array can be constructed, hence the call to nditer()

Once the value is an array, then Matlab has written functionality for casting to a Matlab type, in this case via double.

##### 6 Comments

Dev-iL
on 16 May 2017

Edited: Dev-iL
on 16 May 2017

Hi Christoph,

Thanks for the code! However, it doesn't support the conversion of scalar arrays:

Error using reshape

Size vector must have at least two elements.

Error in matpy.nparray2mat (line 55)

result=reshape(result,fliplr(data_size));

This can be solved by modifying the first `if` statement in nparray2mat to:

if any(numel(data_size) == [0,1])

Cheers!

Eric Cousineau
on 30 May 2017

To build further upon y'all's work, I've made a really rough prototype, using `matpy`, to get `numpy`-friendly proxy that allows more natural referencing, indexing / slicing, etc., via `subsref` and `subsassgn`:

Example code:

pyA = py.numpy.eye(3);

mlA = NumPyProxy(pyA);

mlA(:)

double(mlA(:))

mlA(3, 2)

sub = mlA([2, 1], 3)

double(sub) % 2017-05-30T01:09-04:00 - Presently a bug, wrong order

sub2 = mlA([1, 2], 3)

double(sub2)

mlA([2, 1], 3) = 100 * [1, 2]

mlA(:) = 5

Note that PyProxy also permits casting of >1-D arrays, using `subsref` tricks, whereas MATLAB R2016b presently does not permit passing 2-D matrices (at least, as far as I've tried using other people's examples).

This has only been tested / tinkered with in R2016b, and still needs refinement / robustification.

I will try to see if hacks like this aren't needed in future versions of MATLAB.

Thanks a ton for taking the time to post y'all's stuff!

Shaowu Pan
on 27 Sep 2017

Edited: per isakson
on 27 Sep 2017

Weird discussion...

def npArray2Matlab(x):

return matlab.double(x.tolist())

##### 2 Comments

Jim Hokanson
on 4 Oct 2014

Edited: Jim Hokanson
on 4 Oct 2014

Here's a very ugly solution.

temp = cellfun(@cell,cell(x.tolist),'un',0);

data = cell2mat(vertcat(temp {:}));

A slightly cleaner solution:

data = typecast(uint8(char(x.flat.base.data)),'double');

data = reshape(data,[4 4])'; %Could incorporate x.shape here ...

Then of course:

plot(data)

Sorry I don't have time to explain how you would know that you need to do these things. I have to run!

Jim

##### 4 Comments

Peter
on 6 Oct 2014

Edited: Peter
on 6 Oct 2014

Jim, it's a bit complicated. For example, if I run:

for jj = 1:10

x = py.numpy.random.random([10,10]);

try

data = typecast(uint8(char(x.flat.base.data)),'double');

disp(numel(data))

catch me

warning(me.message)

end

end

I should get 100 doubles, but I end up with something very different:

Warning: The first input must contain a multiple of 8 elements to convert from uint8 (8 bits) to double (64 bits).

29.00

8.00

7.00

10.00

Warning: The first input must contain a multiple of 8 elements to convert from uint8 (8 bits) to double (64 bits).

24.00

20.00

Warning: The first input must contain a multiple of 8 elements to convert from uint8 (8 bits) to double (64 bits).

56.00

Do you have any idea why the typecasting is broken? I would guess that it's something to do with the conversion from the flat.base to char.

Peter.

Jim Hokanson
on 8 Oct 2014

Edited: Jim Hokanson
on 8 Oct 2014

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