giotto.time_series
.PermutationEntropy¶
-
class
giotto.time_series.
PermutationEntropy
(n_jobs=None)¶ Entropies from sets of permutations arg-sorting rows in arrays.
Given a two-dimensional array A, another array A’ of the same size is computed by arg-sorting each row in A. The permutation entropy [1] of A is the Shannon entropy of the probability distribution given by the relative frequencies of each arg-sorting permutation in A’.
- Parameters
- n_jobsint or None, optional, default:
None
The number of jobs to use for the computation.
None
means 1 unless in ajoblib.parallel_backend
context.-1
means using all processors.
- n_jobsint or None, optional, default:
References
- 1
C. Bandt and B. Pompe, “Permutation Entropy: A Natural Complexity Measure for Time Series”; Phys. Rev. Lett., 88.17, 2002; doi: 10.1103/physrevlett.88.174102.
Methods
fit
(self, X[, y])Do nothing and return the estimator unchanged.
fit_transform
(self, X[, y])Fit to data, then transform it.
get_params
(self[, deep])Get parameters for this estimator.
set_params
(self, \*\*params)Set the parameters of this estimator.
transform
(self, X[, y])Calculate the permutation entropy of each two-dimensional array in X.
-
__init__
(self, n_jobs=None)¶ Initialize self. See help(type(self)) for accurate signature.
-
fit
(self, X, y=None)¶ Do nothing and return the estimator unchanged.
This method is there to implement the usual scikit-learn API and hence work in pipelines.
- Parameters
- Xndarray, shape (n_samples, n_points, n_dimensions)
Input data.
- yNone
There is no need for a target in a transformer, yet the pipeline API requires this parameter.
- Returns
- selfobject
-
fit_transform
(self, X, y=None, **fit_params)¶ Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.
- Parameters
- Xnumpy array of shape [n_samples, n_features]
Training set.
- ynumpy array of shape [n_samples]
Target values.
- Returns
- X_newnumpy array of shape [n_samples, n_features_new]
Transformed array.
-
get_params
(self, deep=True)¶ Get parameters for this estimator.
- Parameters
- deepboolean, optional
If True, will return the parameters for this estimator and contained subobjects that are estimators.
- Returns
- paramsmapping of string to any
Parameter names mapped to their values.
-
set_params
(self, **params)¶ Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The latter have parameters of the form
<component>__<parameter>
so that it’s possible to update each component of a nested object.- Returns
- self
-
transform
(self, X, y=None)¶ Calculate the permutation entropy of each two-dimensional array in X.
- Parameters
- Xndarray, shape (n_samples, n_points, n_dimensions)
Input data.
- yNone
There is no need for a target in a transformer, yet the pipeline API requires this parameter.
- Returns
- Xtndarray of int, shape (n_samples, 1)
One permutation entropy per entry in X along axis 0.