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SciPy Reference Guide, Release 0.8.dev Notes Whether to load matlab structs as numpy record arrays, or as old-style numpy arrays with dtype=object. Setting this flag to False replicates the behaviour of scipy version 0.6 (returning numpy object arrays). The preferred setting is True, because it allows easier round-trip load and save of matlab files. In a future version of scipy, we will change the default setting to True, and following versions may remove this flag entirely. For now, we set the default to False, for backwards compatibility, but issue a warning. Returns mat_dict : dict dictionary with variable names as keys, and loaded matrices as values v4 (Level 1.0), v6 and v7 to 7.2 matfiles are supported. You will need an HDF5 python library to read matlab 7.3 format mat files. Because scipy does not supply one, we do not implement the HDF5 / 7.3 interface here. savemat(file_name, mdict, appendmat=True, format=’5’, long_field_names=False, do_compression=False, oned_as=None) Save a dictionary of names and arrays into the MATLAB-style .mat file. This saves the arrayobjects in the given dictionary to a matlab style .mat file. Parameters file_name : {string, file-like object} Name of the mat file (do not need .mat extension if appendmat==True) Can also pass open file-like object m_dict : dict dictionary from which to save matfile variables appendmat : {True, False} optional True to append the .mat extension to the end of the given filename, if not already present format : {‘5’, ‘4’} string, optional ‘5’ for matlab 5 (up to matlab 7.2) ‘4’ for matlab 4 mat files long_field_names : boolean, optional, default=False • False - maximum field name length in a structure is 31 characters which is the documented maximum length • True - maximum field name length in a structure is 63 characters which works for Matlab 7.6 do_compression : {False, True} bool, optional Whether to compress matrices on write. Default is False oned_as : {‘column’, ‘row’} string, optional If ‘column’, write 1D numpy arrays as column vectors If ‘row’, write 1D numpy arrays as row vectors 212 Chapter 3. Reference
3.6.2 Matrix Market files SciPy Reference Guide, Release 0.8.dev mminfo(source) Queries the contents of the Matrix Market file ‘filename’ to mmread(source) Reads the contents of a Matrix Market file ‘filename’ into a mmwrite(target, a[, comment, field, precision]) matrix. Writes the sparse or dense matrix A to a Matrix Market formatted file. mminfo(source) Queries the contents of the Matrix Market file ‘filename’ to extract size and storage information. Inputs: Outputs: source - Matrix Market filename (extension .mtx) or open file object rows,cols - number of matrix rows and columns entries - number of non-zero entries of a sparse matrix or rows*cols for a dense matrix format - ‘coordinate’ | ‘array’ field - ‘real’ | ‘complex’ | ‘pattern’ | ‘integer’ symm - ‘general’ | ‘symmetric’ | ‘skew-symmetric’ | ‘hermitian’ mmread(source) Reads the contents of a Matrix Market file ‘filename’ into a matrix. Inputs: Outputs: source - Matrix Market filename (extensions .mtx, .mtz.gz) or open file object. a - sparse or full matrix mmwrite(target, a, comment=”, field=None, precision=None) Writes the sparse or dense matrix A to a Matrix Market formatted file. Inputs: 3.6.3 Other target - Matrix Market filename (extension .mtx) or open file object a - sparse or full matrix comment - comments to be prepended to the Matrix Market file field - ‘real’ | ‘complex’ | ‘pattern’ | ‘integer’ precision - Number of digits to display for real or complex values. save_as_module([file_name, data]) Save the dictionary “data” into npfile(*args, **kwds) npfile is deprecated! save_as_module(file_name=None, data=None) Save the dictionary “data” into a module and shelf named save npfile(*args, **kwds) npfile is deprecated! You can achieve the same effect as using npfile using numpy.save and numpy.load. You can use memory-mapped arrays and data-types to map out a file format for direct manipulation in NumPy. Class for reading and writing numpy arrays to/from files 3.6. Input and output (scipy.io) 213
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