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TinaJin0228MatthewMiddlehurstTonyBagnallinclinedadarshkevinzb56
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[ENH] add a difference transformer to series transformations (#2729)
* add difference transformer to series transformations * add myself to .all-contributorsrc * small modification * modify according to reviews * [ENH] add informational tags back to estimator docs (#2652) * feat: add new tags information for anomaly detection * feat: add tag information in given anomaly modles * fix: add new anomaly detector tags in mock anomaly detector class * fix: use anomaly-detector instead of estimator for new tags * update and add basic testing * fixes --------- Co-authored-by: MatthewMiddlehurst <pfm15hbu@gmail.com> * [DOC] Documentation improvement of BaseSeriesEstimator and BaseAeonEstimator (#2612) * Added the docs for base series and base classes * Updated documentation for base classes --------- Co-authored-by: Matthew Middlehurst <pfm15hbu@gmail.com> * [ENH] HydraTransformer Output changed (#2656) * output type added * hydra wflow modified * hydra test file added * pr_pytest reverted * soft dep check added * soft dep corrected * docstring corrected, enhanced test cases * [DOC] Improved Hidalgo Segmentation Notebook (#2616) * Improved Hidalgo Segmentation Notebook * Updated hidalgo notebook --------- Co-authored-by: Matthew Middlehurst <pfm15hbu@gmail.com> * new devs and workflow consolidation (#2797) * all branches (#2809) * Automated `pre-commit` hook update (#2820) Co-authored-by: TonyBagnall <9594042+TonyBagnall@users.noreply.github.com> * [MNT] Bump crs-k/stale-branches in the github-actions group (#2821) Bumps the github-actions group with 1 update: [crs-k/stale-branches](https://github.com/crs-k/stale-branches). Updates `crs-k/stale-branches` from 7.0.1 to 8.1.1 - [Release notes](https://github.com/crs-k/stale-branches/releases) - [Commits](crs-k/stale-branches@v7.0.1...v8.1.1) --- updated-dependencies: - dependency-name: crs-k/stale-branches dependency-version: 8.1.1 dependency-type: direct:production update-type: version-update:semver-major dependency-group: github-actions ... Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * fix: indexing in kdtw (#2826) * [ENH] Added test cases for feature based clustering (#2690) * Added test cases for feature based clustering * Automatic `pre-commit` fixes * added docstring * Automatic `pre-commit` fixes * added . * added . * updated tsfresh * Automatic `pre-commit` fixes * added pytest _check_soft_dependencies for tsfresh * Automatic `pre-commit` fixes * added more testing * Automatic `pre-commit` fixes * added docs * added docs * added pytest * Automatic `pre-commit` fixes * improved docs * Automatic `pre-commit` fixes * improved test cases * changes made as requested by moderators * changes made as requested by moderators * Automatic `pre-commit` fixes * changed "percentiles" to "quantiles" --------- Co-authored-by: Ramana-Raja <ramanarajakesavaraja@gamil.com> Co-authored-by: Matthew Middlehurst <pfm15hbu@gmail.com> Co-authored-by: Tony Bagnall <a.j.bagnall@soton.ac.uk> * [DOC] Fix inconsistent double backticks in updated similarity_search module docstrings (#2618) * delete some descriptions * modification to _maintainer_ --------- Signed-off-by: dependabot[bot] <support@github.com> Co-authored-by: Matthew Middlehurst <pfm15hbu@gmail.com> Co-authored-by: Tony Bagnall <a.j.bagnall@soton.ac.uk> Co-authored-by: Adarsh Dubey <dubeyadarshmain@gmail.com> Co-authored-by: Kevin Shah <161136814+kevinzb56@users.noreply.github.com> Co-authored-by: Balgopal Moharana <99070111+lucifer4073@users.noreply.github.com> Co-authored-by: Kavya Rambhia <161142013+kavya-r30@users.noreply.github.com> Co-authored-by: aeon-actions-bot[bot] <148872591+aeon-actions-bot[bot]@users.noreply.github.com> Co-authored-by: TonyBagnall <9594042+TonyBagnall@users.noreply.github.com> Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> Co-authored-by: Sebastian Schmidl <10573700+SebastianSchmidl@users.noreply.github.com> Co-authored-by: Ramana Raja <83065061+Ramana-Raja@users.noreply.github.com> Co-authored-by: Ramana-Raja <ramanarajakesavaraja@gamil.com> Co-authored-by: Ciph3r <142653450+adityagh006@users.noreply.github.com>
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‎.all-contributorsrc

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"contributions": [
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"doc"
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]
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},
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{
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"login": "TinaJin0228",
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"name": "Tina Jin",
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"avatar_url": "https://avatars.githubusercontent.com/TinaJin0228",
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"profile": "https://github.com/TinaJin0228",
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"contributions": [
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"code",
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"doc"
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]
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}
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],
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"commitType": "docs"

‎aeon/transformations/series/__init__.py

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"SIVSeriesTransformer",
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"PCASeriesTransformer",
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"WarpingSeriesTransformer",
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"DifferenceTransformer",
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]
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from aeon.transformations.series._acf import (
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from aeon.transformations.series._boxcox import BoxCoxTransformer
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from aeon.transformations.series._clasp import ClaSPTransformer
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from aeon.transformations.series._dft import DFTSeriesTransformer
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from aeon.transformations.series._diff import DifferenceTransformer
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from aeon.transformations.series._dobin import Dobin
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from aeon.transformations.series._exp_smoothing import ExpSmoothingSeriesTransformer
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from aeon.transformations.series._gauss import GaussSeriesTransformer

‎aeon/transformations/series/_diff.py

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import numpy as np
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from aeon.transformations.series.base import BaseSeriesTransformer
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__maintainer__ = ["TinaJin0228"]
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__all__ = ["DifferenceTransformer"]
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class DifferenceTransformer(BaseSeriesTransformer):
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"""
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Calculates the n-th order difference of a time series.
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Transforms a time series X into a series Y representing the difference
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calculated `order` times.
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The time series are supposed to be all in rows,
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with shape (n_channels, n_timepoints)
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- Order 1: Y[t] = X[t] - X[t-1]
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- Order 2: Y[t] = (X[t] - X[t-1]) - (X[t-1] - X[t-2]) = X[t] - 2*X[t-1] + X[t-2]
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- ... and so on.
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The transformed series will be shorter than the input series by `order`
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elements along the time axis.
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Parameters
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----------
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order : int, default=1
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The order of differencing. Must be a positive integer.
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Notes
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-----
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This transformer assumes the input series does not contain NaN values where
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the difference needs to be computed.
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Examples
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--------
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>>> import numpy as np
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>>> from aeon.transformations.series._diff import DifferenceTransformer
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>>> X1 = np.array([[1, 3, 2, 5, 4, 7, 6, 9, 8, 10]]) # Shape (1, 10)
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>>> dt = DifferenceTransformer()
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>>> Xt1 = dt.fit_transform(X1)
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>>> print(Xt1) # Shape (1, 9)
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[[ 2 -1 3 -1 3 -1 3 -1 2]]
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>>> X2 = np.array([[1, 3, 2, 5, 4, 7, 6, 9, 8, 10]]) # Shape (1, 10)
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>>> dt2 = DifferenceTransformer(order=2)
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>>> Xt2 = dt2.fit_transform(X2)
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>>> print(Xt2) # Shape (1, 8)
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[[-3 4 -4 4 -4 4 -4 3]]
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>>> X3 = np.array([[1, 2, 3, 4, 5], [5, 4, 3, 2, 1]]) # Shape (2, 5)
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>>> dt = DifferenceTransformer()
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>>> Xt3 = dt.fit_transform(X3)
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>>> print(Xt3) # Shape (2, 4)
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[[ 1 1 1 1]
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[-1 -1 -1 -1]]
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"""
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_tags = {
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"capability:multivariate": True,
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"X_inner_type": "np.ndarray",
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"fit_is_empty": True,
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}
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def __init__(self, order=1):
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self.order = order
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super().__init__(axis=1)
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def _transform(self, X, y=None):
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"""
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Perform the n-th order differencing transformation.
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Parameters
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----------
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X : Time series to transform. With shape (n_channels, n_timepoints).
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y : ignored argument for interface compatibility
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Returns
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-------
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Xt : np.ndarray
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"""
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if not isinstance(self.order, int) or self.order < 1:
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raise ValueError(
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f"`order` must be a positive integer, but got {self.order}"
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)
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diff_X = np.diff(X, n=self.order, axis=1)
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Xt = diff_X
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return Xt

‎aeon/transformations/series/tests/test_diff.py

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"""Tests for Difference transformation."""
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import numpy as np
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from aeon.transformations.series._diff import DifferenceTransformer
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def test_diff():
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"""Tests basic first and second order differencing."""
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X = np.array([[1.0, 4.0, 9.0, 16.0, 25.0, 36.0]])
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dt1 = DifferenceTransformer(order=1)
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Xt1 = dt1.fit_transform(X)
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expected1 = np.array([[3.0, 5.0, 7.0, 9.0, 11.0]])
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np.testing.assert_allclose(
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Xt1, expected1, equal_nan=True, err_msg="Value mismatch for order 1"
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)
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dt2 = DifferenceTransformer(order=2)
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Xt2 = dt2.fit_transform(X)
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expected2 = np.array([[2.0, 2.0, 2.0, 2.0]])
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np.testing.assert_allclose(
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Xt2, expected2, equal_nan=True, err_msg="Value mismatch for order 2"
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)
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Y = np.array([[1, 2, 3, 4], [5, 3, 1, 8]])
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Yt1 = dt1.fit_transform(Y)
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expected3 = np.array([[1, 1, 1], [-2, -2, 7]])
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np.testing.assert_allclose(
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Yt1,
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expected3,
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equal_nan=True,
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err_msg="Value mismatch for order 1,multivariate",
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)

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