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ad44738d01
* Replaced the old SWIG-based wrapper with a python-based one. - `PropsSI.m` is now the entry point. - Added tests. - Documentation updated. * Documentation converted from Markdown to reStructredText Following https://github.com/CoolProp/CoolProp/issues/1497#issuecomment-324845758. * Further fixes to documentation. * Further fixes to documentation #2. Worked around the indentation issue in the numbered list. * Added handling of arrays with zero dimensions to matpy * Added a convenience wrapper for the low-level AbstractState API - Readme updated accordingly. - Tests updated accordingly. * Renamd CoolProps to CoolProp
68 lines
2.9 KiB
Matlab
68 lines
2.9 KiB
Matlab
classdef matpy
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%MATPY A class for converting between MATLAB and numpy (python) ndarrays
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%
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% Based on https://www.mathworks.com/matlabcentral/answers/157347
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% by David Laurenson (2016), Christoph Wiedemann (2017), and Iliya Romm (2017).
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methods (Access = public, Static = true)
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function result = mat2nparray( mtlbArr )
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%mat2nparray Convert a MATLAB array into a numpy nparray
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% Convert an n-dimensional MATLAB array into an equivalent nparray
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data_size = size(mtlbArr);
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switch numel(data_size)
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case {0,1}
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% scalars and 1-D vectors are trivial
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result = py.numpy.array(mtlbArr);
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case 2
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% A transpose operation is required either in MATLAB, or in Python due
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% to the difference between row major and column major ordering
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transposed = mtlbArr.';
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% Pass the array to Python as a vector, and then reshape to the correct
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% size
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result = py.numpy.reshape(transposed(:).', int32(data_size));
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otherwise
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% For an n-dimensional array, transpose the first two dimensions to
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% sort the storage ordering issue
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transposed = permute(mtlbArr, numel(data_size):-1:1);
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% Pass it to python, and then reshape to the python style of matrix
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% sizing
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result = py.numpy.reshape(transposed(:).', int32(fliplr(size(transposed))));
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end
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end
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function result = nparray2mat( npArr )
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%nparray2mat Convert an nparray from numpy to a MATLAB array
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% Convert an n-dimensional nparray into an equivalent MATLAB array
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data_size = cellfun(@int64, cell(npArr.shape));
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if ~all(data_size) % Array with at least one zero dimension
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result = zeros(data_size);
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return
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end
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switch numel(data_size)
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case {0,1}
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% Convert to a double scalar or vector (preserving shape)
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result = double(py.array.array('d', py.numpy.nditer(npArr)));
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case 2
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% order='F' is used to get data in column-major order (as in Fortran
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% 'F' and MATLAB)
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result = reshape(double(py.array.array('d', ...
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py.numpy.nditer(npArr, pyargs('order', 'F')))), ...
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data_size);
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otherwise
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% For multidimensional arrays more manipulation is required
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% First recover in python order (C contiguous order)
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result = double(py.array.array('d', ...
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py.numpy.nditer(npArr, pyargs('order', 'C'))));
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% Switch the order of the dimensions (as Python views this in the
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% opposite order to MATLAB) and reshape to the corresponding C-like
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% array
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result = reshape(result, fliplr(data_size));
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% Now transpose rows and columns of the 2D sub-arrays to arrive at the
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% correct MATLAB structuring
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result = permute(result, numel(data_size):-1:1);
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end
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end
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end
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end
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