See also
numpy-reference.routines.io (in Numpy)
loadmat(file_name, **kwargs[, mdict, appendmat]) | Load MATLAB file |
savemat(file_name, mdict[, appendmat, ...]) | Save a dictionary of names and arrays into a MATLAB-style .mat file. |
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 matrix. |
mmwrite(target, a[, comment, field, precision]) | Writes the sparse or dense matrix A to a Matrix Market formatted file. |
save_as_module([file_name, data]) | Save the dictionary “data” into a module and shelf named save. |
read(file) | Return the sample rate (in samples/sec) and data from a WAV file |
write(filename, rate, data) | Write a numpy array as a WAV file |
Module to read ARFF files, which are the standard data format for WEKA.
ARFF is a text file format which support numerical, string and data values. The format can also represent missing data and sparse data.
See the WEKA website for more details about arff format and available datasets.
>>> from scipy.io import arff
>>> content = """
... @relation foo
... @attribute width numeric
... @attribute height numeric
... @attribute color {red,green,blue,yellow,black}
... @data
... 5.0,3.25,blue
... 4.5,3.75,green
... 3.0,4.00,red
... """
>>> f = open('testdata.arff', 'w')
>>> f.write(content)
>>> f.close()
>>> data, meta = arff.loadarff('testdata.arff')
>>> data
array([(5.0, 3.25, 'blue'), (4.5, 3.75, 'green'), (3.0, 4.0, 'red')],
dtype=[('width', '<f8'), ('height', '<f8'), ('color', '|S6')])
>>> meta
Dataset: foo
width's type is numeric
height's type is numeric
color's type is nominal, range is ('red', 'green', 'blue', 'yellow', 'black')
loadarff(filename) | Read an arff file. |
netcdf_file(filename[, mode, mmap, version]) | A file object for NetCDF data. |
netcdf_variable(data, typecode, shape, ...) | A data object for the netcdf module. |