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‎py2mat.m‎

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%% PY2MAT Convert a native Python variable to an equivalent native MATLAB variable.
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%
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% futher enhanced in 2024 by SciVision
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% {{{ code/matlab_py/py2mat.m v 1.3 2023-09-15
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% This code accompanies the book _Python for MATLAB Development:
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% Extend MATLAB with 300,000+ Modules from the Python Package Index_
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% ISBN 978-1-4842-7222-0 | ISBN 978-1-4842-7223-7 (eBook)
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% DOI 10.1007/978-1-4842-7223-7
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% https://github.com/Apress/python-for-matlab-development
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%
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% Copyright © 2022-2023 Albert Danial
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%
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% Contributions by:
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% - https://github.com/hcommin (performance enhancements)
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%
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% MIT License:
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% Permission is hereby granted, free of charge, to any person obtaining a copy
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% of this software and associated documentation files (the "Software"), to deal
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% in the Software without restriction, including without limitation the rights
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% to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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% copies of the Software, and to permit persons to whom the Software is
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% furnished to do so, subject to the following conditions:
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%
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% The above copyright notice and this permission notice shall be included in
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% all copies or substantial portions of the Software.
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%
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% THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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% IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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% FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
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% THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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% LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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% FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
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% DEALINGS IN THE SOFTWARE.
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% }}}
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function [x_mat] = py2mat(x_py)
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switch class(x_py)
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% MATLAB types
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case {'logical', 'double', 'datetime'}
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x_mat = x_py;
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% Python dictionaries
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case 'py.dict'
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try
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% the obvious dict -> struct conversion only works
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% if the key string can be a MATLAB variable
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x_mat = struct(x_py);
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catch EO
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% A failure most likely means a Python key is not
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% a proper MATLAB variable name. Go through them
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% individually
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key_index = int64(0);
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key_list = cell(py.list(x_py.keys()));
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for key = key_list
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key_index = key_index + 1;
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if class(key) == "cell"
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% key could be a Python number
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v_name = string(py.str(key{1}));
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else
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v_name = string(key);
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end
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if isvarname(v_name)
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x_mat.(v_name) = x_py.get(key_list{key_index});
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else
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x_mat.(matlab.lang.makeValidName(v_name)) = x_py.get(key_list{key_index});
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end
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end
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end
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fields = fieldnames(x_mat);
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for i = 1:length(fields)
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new_var = py2mat(x_mat.(fields{i}));
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x_mat = setfield(x_mat,fields{i}, new_var); %#ok<SFLD>
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end
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% NumPy arrays and typed scalars
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case "py.numpy.ndarray"
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switch string(x_py.dtype.name)
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case "float64"
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x_mat = x_py.double;
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case "float32"
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x_mat = x_py.single;
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case "float16"
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% doesn't exist in matlab, upcast to float32
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x_mat = single(x_py.astype('float32'));
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% only reals and logicals can be cast to arrays so
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% have to cast the rest to either single or double
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case "uint8"
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x_mat = uint8(x_py.astype('float32'));
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case "int8"
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x_mat = int8(x_py.astype('float32'));
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case "uint16"
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x_mat = uint16(x_py.astype('float32'));
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case "int16"
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x_mat = int16(x_py.astype('float32'));
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case "uint32"
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x_mat = uint32(x_py.astype('float32'));
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case "int32"
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x_mat = int32(x_py.astype('float32'));
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case "uint64"
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x_mat = uint64(x_py.astype('float64'));
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case "int64"
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x_mat = int64(x_py.astype('float64'));
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case "bool"
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x_mat = logical(x_py);
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% Complex types require a math operation to coerce the
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% real and imaginary components to contiguous arrays.
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% Use "+0" for minimal performance impact. Without this,
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% complex creation fails with
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% Python Error: ValueError: ndarray is not contiguous
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case "complex64"
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x_mat = complex(single(x_py.real+0), single(x_py.imag+0));
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case "complex128"
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x_mat = complex(double(x_py.real+0), double(x_py.imag+0));
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case "complex256"
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fprintf('py2mat: MATLAB does not support quad precision complex\n')
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x_mat = [];
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return
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otherwise
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% gets here with custom dtypes
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fprintf('py2mat: %s not recognized\n', ...
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string(x_py.dtype.name));
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x_mat = [];
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return
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end
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% Scipy sparse matrices
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case {'py.scipy.sparse.coo.coo_matrix', ...
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'py.scipy.sparse.csr.csr_matrix', ...
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'py.scipy.sparse.csc.csc_matrix', ...
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'py.scipy.sparse.dok.dok_matrix', ...
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'py.scipy.sparse.bsr.bsr_matrix', ...
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'py.scipy.sparse.dia.dia_matrix', ...
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'py.scipy.sparse.lil.lil_matrix', }
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ndims = x_py.get_shape();
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if length(ndims) ~= 2
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fprintf('py2mat: can only convert 2D sparse matrices\n')
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x_mat = [];
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return
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end
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nR = int64(ndims{1});
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nC = int64(ndims{2});
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x_py = x_py.tocoo();
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values = py2mat(x_py.data);
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if isempty(values)
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% gets here if trying to convert a complex256 sparse matrix
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return
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end
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% add 1 to row & col indices to go from 0-based to 1-based
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x_mat = sparse(single(x_py.row)+1, single(x_py.col)+1, values, nR, nC);
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% Python sets, tuples, and lists
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case {'cell', 'py.tuple', 'py.list'}
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[nR, nC] = size(x_py);
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x_mat = cell(nR,nC);
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for r = 1:nR
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for c = 1:nC
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x_mat{r,c} = py2mat(x_py{r,c});
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end
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end
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% Python strings
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case 'py.str'
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x_mat = string(x_py);
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% Python integers
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case 'py.int'
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x_mat = x_py.int64;
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case 'py.float'
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x_mat = x_py.real;
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case 'py.complex'
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x_mat = complex(x_py.real, x_py.imag);
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case 'py.bool'
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x_mat = logical(x_py);
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case 'py.datetime.datetime'
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x_mat = datetime(int64(x_py.year), ...
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int64(x_py.month), ...
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int64(x_py.day), ...
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int64(x_py.hour), ...
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int64(x_py.minute),...
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int64(x_py.second),...
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double(x_py.microsecond)/1000.0);
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case 'py.bytes'
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x_mat = uint8(x_py);
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case 'py.NoneType'
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x_mat = '';
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case 'py.scipy.optimize.optimize.OptimizeResult'
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for k = cell(py.list(x_py.keys))
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x_mat.(string(k{1})) = py2mat(x_py.get(k{1}));
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end
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% punt
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otherwise
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% return the original item? nothing?
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fprintf('py2mat: type "%s" not recognized\n', ...
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string(class(x_py)));
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x_mat = [];
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end
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end

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