extendedMD.sax¶

extendedMD.sax.apply_adaptive_sax(ts, win_size, paa_size, alphabet_size, z_threshold)¶

This function applies the sax transformation to a 1-dim time series using adaptive break-points

Parameters:	ts (1D array) – 1-time series win_size (int) – size fo the sliding window that generated each sax word paa_size (int) – number of characters in a single sax word alphabet_size (int) – number of unique characters to use in the sax representation z_threshold (float) – z_threshold for the znorm method from saxpy
Returns:	the sax sequence, a list of strings, where each string represents a single sax word
Return type:	list of str

extendedMD.sax.apply_non_adaptive_sax(ts, win_size, paa_size, alphabet_size, z_threshold)¶

This function applies the sax transformation to a 1-dim time series using adaptive break-points

Parameters:	ts (1D array) – 1-time series win_size (int) – size fo the sliding window that generated each sax word paa_size (int) – number of characters in a single sax word alphabet_size (int) – number of unique characters to use in the sax representation z_threshold (float) – z_threshold for the znorm method from saxpy
Returns:	the sax sequence, a list of strings, where each string represents a single sax word
Return type:	list of str

extendedMD.sax.extract_sax_sequence(ts, win_size, paa_size, alphabet_size, adaptive_break_points, z_threshold=0.01)¶

This function applies the sax transformation to a 1-dim time series. Based on saxpy package

Parameters:	ts (1D array) – 1-time series win_size (int) – size fo the sliding window that generated each sax word paa_size (int) – number of characters in a single sax word alphabet_size (int) – number of unique characters to use in the sax representation adaptive_break_points (bool) – Whether to use a representation with adaptive break-points z_threshold (float) – z_threshold for the znorm method from saxpy
Returns:	the sax sequence, a list of strings, where each string represents a single sax word
Return type:	list of str