def distance_1d_sax(self, sax1, sax2):
"""Compute distance between 1d-SAX representations as defined in [1]_.
Parameters
----------
sax1 : array-like
1d-SAX representation of a time series
sax2 : array-like
1d-SAX representation of another time series
Returns
-------
float
1d-SAX distance
Notes
-----
Unlike SAX distance, 1d-SAX distance does not lower bound Euclidean
distance between original time series.
References
----------
.. [1] S. Malinowski, T. Guyet, R. Quiniou, R. Tavenard. 1d-SAX: a
Novel Symbolic Representation for Time Series. IDA 2013.
"""
if not self._is_fitted():
raise NotFittedError("Model not fitted yet: cannot be used for " +
"distance computation.")
else:
return cydist_1d_sax(sax1, sax2, self.breakpoints_avg_middle_,
self.breakpoints_slope_middle_,
self.size_fitted_)
def distance_1d_sax(self, sax1, sax2):
"""Compute distance between 1d-SAX representations as defined in [1]_.
Parameters
----------
sax1 : array-like
1d-SAX representation of a time series
sax2 : array-like
1d-SAX representation of another time series
Returns
-------
float
1d-SAX distance
Notes
-----
Unlike SAX distance, 1d-SAX distance does not lower bound Euclidean
distance between original time series.
References
----------
.. [1] S. Malinowski, T. Guyet, R. Quiniou, R. Tavenard. 1d-SAX: a
Novel Symbolic Representation for Time Series. IDA 2013.
"""
self._is_fitted()
return cydist_1d_sax(sax1, sax2, self.breakpoints_avg_middle_,
self.breakpoints_slope_middle_,
self._X_fit_dims_[1])