sidekit_io¶
Copyright 2014-2019 Anthony Larcher
sidekit_io provides methods to read and write from and to different
formats.
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sidekit_io.h5merge(output_filename, input_filename_list)[source]¶ Merge a list of HDF5 files into a new one.
- Parameters
output_filename – the name of the new file resulting from the merge.
input_filename_list – list of thge input files
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sidekit_io.init_logging(level=20, filename=None)[source]¶ Initialize a logger
- Parameters
level – level of messages to catch
filename – name of the output file
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sidekit_io.read_dict_hdf5(input_filename)[source]¶ Read a dictionary from an HDF5 file.
- Parameters
input_filename – name of the file to read from
- Returns
the dictionary
-
sidekit_io.read_fa_hdf5(input_filename)[source]¶ Read a generic FA model from a HDF5 file
- Parameters
input_filename – the name of the file to read from
- Returns
a tuple of 5 elements: the mean vector, the between class covariance matrix, the within class covariance matrix, the MAP matrix and the residual covariancematrix
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sidekit_io.read_key_hdf5(input_filename, key)[source]¶ Read key value from a HDF5 file.
- Parameters
input_filename – the name of the file to read from
key – the name of the key
- Returns
a value
-
sidekit_io.read_matrix(filename)[source]¶ Read matrix in ALIZE binary format and return a ndarray
- Parameters
filename – name of the file to read from
- Returns
a numpy.ndarray object
-
sidekit_io.read_norm_hdf5(input_filename)[source]¶ Read normalization parameters from a HDF5 file.
- Parameters
input_filename – the name of the file to read from
- Returns
a tuple of two lists. The first list contains mean vectors for each iteration, the second list contains covariance matrices for each iteration
-
sidekit_io.read_pickle(filename)[source]¶ Read a generic pickle file and return the content
- Parameters
filename – name of the pickle file to read
- Returns
the content of the file
-
sidekit_io.read_plda_hdf5(input_filename)[source]¶ Read a PLDA model from a HDF5 file.
- Parameters
input_filename – the name of the file to read from
- Returns
a tuple of 4 elements: the mean vector, the between class covariance matrix, the within class covariance matrix and the residual matrix