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SciPy Reference Guide, Release 0.8.dev the buffer parameter, and the number of elements within the footprint through filter_size. The calculated valued should be returned in the return_value argument. The function generic_filter1d (see Generic filter functions) accepts a callback function with the following prototype: The calling function iterates over the lines of the input and output arrays, calling the callback function at each line. The current line is extended according to the border conditions set by the calling function, and the result is copied into the array that is passed through the input_line array. The length of the input line (after extension) is passed through input_length. The callback function should apply the 1D filter and store the result in the array passed through output_line. The length of the output line is passed through output_length. The function geometric_transform (see Interpolation functions) expects a function with the following prototype: The calling function iterates over the elements of the output array, calling the callback function at each element. The coordinates of the current output element are passed through output_coordinates. The callback function must return the coordinates at which the input must be interpolated in input_coordinates. The rank of the input and output arrays are given by input_rank and output_rank respectively. 1.11 File IO (scipy.io) See Also: numpy-reference.routines.io (in numpy) 1.11.1 Matlab files loadmat(file_name, **kwargs[, mdict, Load Matlab(tm) file appendmat]) savemat(file_name, mdict[, appendmat, ...]) Save a dictionary of names and arrays into the MATLAB-style .mat file. Getting started: >>> import scipy.io as sio If you are using IPython, try tab completing on sio. You’ll find: sio.loadmat sio.savemat These are the high-level functions you will most likely use. You’ll also find: sio.matlab This is the package from which loadmat and savemat are imported. Within sio.matlab, you will find the mio module - containing the machinery that loadmat and savemat use. From time to time you may find yourself re-using this machinery. 80 Chapter 1. SciPy Tutorial
How do I start? SciPy Reference Guide, Release 0.8.dev You may have a .mat file that you want to read into Scipy. Or, you want to pass some variables from Scipy / Numpy into Matlab. To save us using a Matlab license, let’s start in Octave. Octave has Matlab-compatible save / load functions. Start Octave (octave at the command line for me): octave:1> a = 1:12 a = 1 2 3 4 5 6 7 8 9 10 11 12 octave:2> a = reshape(a, [1 3 4]) a = ans(:,:,1) = 1 2 3 ans(:,:,2) = 4 5 6 ans(:,:,3) = 7 8 9 ans(:,:,4) = 10 11 12 octave:3> save -6 octave_a.mat a % Matlab 6 compatible octave:4> ls octave_a.mat octave_a.mat Now, to Python: >>> mat_contents = sio.loadmat(’octave_a.mat’) /home/mb312/usr/local/lib/python2.5/site-packages/scipy/io/Matlab/mio.py:84: FutureWarning: Using str return MatFile5Reader(byte_stream, **kwargs) >>> print mat_contents {’a’: array([[[ 1., 4., 7., 10.], [ 2., 5., 8., 11.], [ 3., 6., 9., 12.]]]), ’__version__’: ’1.0’, ’__header__’: ’MATLAB 5.0 MAT-file, writte >>> oct_a = mat_contents[’a’] >>> print oct_a [[[ 1. 4. 7. 10.] [ 2. 5. 8. 11.] [ 3. 6. 9. 12.]]] >>> print oct_a.shape (1, 3, 4) We’ll get to the deprecation warning in a second. Now let’s try the other way round: 1.11. File IO (scipy.io) 81
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