AlignerDtwDtai

class AlignerDtwDtai(use_c=False, window=None, max_dist=None, max_step=None, max_length_diff=None, penalty=None, psi=None, inner_dist='squared euclidean')[source]

Aligner interface for dtaidistance time warping alignment.

Direct interface to dtaidistance.dtw_ndim.warping_path and dtaidistance.dtw_ndim.warping_path_fast.

This distance is covers multivariate data and arbitrary scalar distances as components.

Parameters:

use_c: bool, optional, default=False

Whether to use the faster C variant: True for C, False for Python. True requires a C compiled installation of dtaidistance.

If False, uses dtaidistance.dtw_ndim.distance_matrix.
If True, uses dtaidistance.dtw_ndim.distance_matrix_fast.

windowinteger, optional, default=infinite

Sakoe Chiba window width, from diagonal to boundary. Only allow for maximal shifts from the two diagonals smaller than this number. The maximally allowed warping, thus difference between indices i in series 1 and j in series 2, is thus |i-j| < 2*window + |len(s1) - len(s2)|. It includes the diagonal, meaning that Euclidean distance is obtained by setting window=1. If the two series are of equal length, this means that the band appearing on the cumulative cost matrix is of width 2*window-1. In other definitions of DTW this number may be referred to as the window instead.

max_dist: float, optional, default=infinite

Stop if the returned values will be larger than this value.

max_step: float, optional, default=infinite

Do not allow steps larger than this value. If the difference between two values in the two series is larger than this, thus if |s1[i]-s2[j]| > max_step, replace that value with infinity.

max_length_diff: int, optional, default=infinite

Return infinity if difference of length of two series is larger than this value.

penalty: float, optional, default=0

Penalty to add if compression or expansion is applied

psi: integer or 4-tuple of integers or none, optional, default=none

Psi relaxation parameter (ignore start and end of matching). If psi is a single integer, it is used for both start and end relaxations for both series in a pair of series. If psi is a 4-tuple, it is used as the psi-relaxation for (begin series1, end series1, begin series2, end series2). Useful for cyclical series.

inner_dist: str, or sktime BasePairwiseTransformer, default=”squared euclidean”

Distance between two points in the time series.

If str, must be one of ‘squared euclidean’ (default), ‘euclidean’.
if estimator, must follow sktime BasePairwiseTransformer API. For a range of distances from scipy, see ScipyDist.

Attributes:

is_fitted: Whether fit has been called.

References

[1]

H. Sakoe, S. Chiba, “Dynamic programming algorithm optimization for spoken word recognition,” IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 26(1), pp. 43–49, 1978.

Methods

`check_is_fitted`([method_name])	Check if the estimator has been fitted.
`clone`()	Obtain a clone of the object with same hyper-parameters and config.
`clone_tags`(estimator[, tag_names])	Clone tags from another object as dynamic override.
`create_test_instance`([parameter_set])	Construct an instance of the class, using first test parameter set.
`create_test_instances_and_names`([parameter_set])	Create list of all test instances and a list of names for them.
`fit`(X[, Z])	Fit alignment given series/sequences to align.
`get_aligned`()	Return aligned version of sequences passed to fit.
`get_alignment`()	Return alignment for sequences/series passed in fit (iloc indices).
`get_alignment_loc`()	Return alignment for sequences/series passed in fit (loc indices).
`get_class_tag`(tag_name[, tag_value_default])	Get class tag value from class, with tag level inheritance from parents.
`get_class_tags`()	Get class tags from class, with tag level inheritance from parent classes.
`get_config`()	Get config flags for self.
`get_distance`()	Return overall distance of alignment.
`get_distance_matrix`()	Return distance matrix of alignment.
`get_fitted_params`([deep])	Get fitted parameters.
`get_param_defaults`()	Get object's parameter defaults.
`get_param_names`([sort])	Get object's parameter names.
`get_params`([deep])	Get a dict of parameters values for this object.
`get_tag`(tag_name[, tag_value_default, ...])	Get tag value from instance, with tag level inheritance and overrides.
`get_tags`()	Get tags from instance, with tag level inheritance and overrides.
`get_test_params`([parameter_set])	Test parameters for aligner.
`is_composite`()	Check if the object is composed of other BaseObjects.
`load_from_path`(serial)	Load object from file location.
`load_from_serial`(serial)	Load object from serialized memory container.
`reset`()	Reset the object to a clean post-init state.
`save`([path, serialization_format])	Save serialized self to bytes-like object or to (.zip) file.
`set_config`(**config_dict)	Set config flags to given values.
`set_params`(**params)	Set the parameters of this object.
`set_random_state`([random_state, deep, ...])	Set random_state pseudo-random seed parameters for self.
`set_tags`(**tag_dict)	Set instance level tag overrides to given values.