pythonmatlabmatlab-engine

Square matrix flattened to row vector upon passing through MATLAB API for Python

I have a dataframe which holds covariance data, hence we have a square matrix. I translate this dataframe into numpy and then to list as below, so that I can use it with the matlab api:

import matlab.engine
eng = matlab.engine.start_matlab()

covdata_list = covdata.values.tolist()
covdata_MATLAB = matlab.double(covdata_list)

Then I create an anonymous function from python using the matlab api as follows, which does the simplest task ever:

eng.eval(f"obj_func = @(x) x;", nargout=0)

All good so far, BUT when I send the covariance data-translated in MATLAB's format- i.e. covdata_MATLAB the following happens:

returns = eng.eval(f'obj_func({covdata_MATLAB})', nargout=1)
eng.size(returns)
>>>> matlab.double([[1.0,15625.0]])

While:

eng.size(covdata_MATLAB)
>>>> matlab.double([[125.0,125.0]])

As we can see it as if it "flattens" the covariance and produces a row vector of 1 X (125*125).

Is there a workaround or is there something I am missing?

Solution

  • It is not an exact solution to the above, but -I would say- rather a workaround which in my case and given my programming goals works.

    So the goal was to pass the variable to MATLAB without the need to reshape/resize the matrix.

    (117649.0 corresponds to 343x343 which the square matrix used for this example; in initial Q I was using 125x125 hence the 15625.0, I hope this is clear)

    If I have a look at the workspace now I can see the following:

    enter image description here

    This is convenient in my case it may not be a solution for others.

    end result when calling:

    returns = eng.eval(f'obj_func(covariance)', nargout=1) #be careful now you have to use the variable name defined in the MATLAB workspace, i.e covariance and not covdata_MATLAB
eng.size(returns)
>>>> matlab.double([[343.0,343.0]])