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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
Peter
Peter on 4 Oct 2014
>> x
x =
Python ndarray with properties:
T: [1x1 py.numpy.ndarray]
base: [1x1 py.NoneType]
ctypes: [1x1 py.numpy.core._internal._ctypes]
data: [1x1 py.buffer]
dtype: [1x1 py.numpy.dtype]
flags: [1x1 py.numpy.flagsobj]
flat: [1x1 py.numpy.flatiter]
imag: [1x1 py.numpy.ndarray]
itemsize: 8
nbytes: 128
ndim: 2
real: [1x1 py.numpy.ndarray]
shape: [1x1 py.tuple]
size: 16
strides: [1x1 py.tuple]
[[ 0.84501423 0.72129285 0.53197632 0.56672641]
[ 0.353229 0.40170347 0.99848745 0.74374568]
[ 0.15023563 0.72432396 0.05446134 0.00455388]
[ 0.85040029 0.65360657 0.35074251 0.08965406]]
>>

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Accepted Answer

David Garrison
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.
  2 Comments
abraham rodriguez
abraham rodriguez on 18 Sep 2021
@Badr Hisham In latest R2021a, you can pass directly a numpy ndarray to double() and it will convert to a native matlab matrix.

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More Answers (3)

Jim Hokanson
Jim Hokanson on 4 Nov 2014
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
Eric Cousineau
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 is an ongoing effort to test some Drake functionality: GitHub Issue
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!

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Shaowu Pan
Shaowu Pan on 27 Sep 2017
Edited: per isakson on 27 Sep 2017
Weird discussion...
def npArray2Matlab(x):
return matlab.double(x.tolist())

Jim Hokanson
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
Jim Hokanson
Jim Hokanson on 8 Oct 2014
Interesting. The problem occurs when there is a zero in the underlying raw buffer (not a zero value but a 0 byte). I'm not sure if this desired or if it is a bug.

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