Merge branch 'main' into pandas2-diag

.all-contributorsrc

@@ -2156,6 +2156,15 @@
       "contributions": [
         "doc"
       ]
-    }
+    },
+    {
+      "login": "marrov",
+      "name": "Marc Rovira",
+      "avatar_url": "https://avatars.githubusercontent.com/u/54272586?v=4",
+      "profile": "https://github.com/marrov",
+      "contributions": [
+        "doc"
+      ]
+    }    
   ]
 }

.github/workflows/test.yml

@@ -44,6 +44,26 @@ jobs:
         run: build_tools/run_examples.sh
         shell: bash
 
+  test-nodevdeps:
+    needs: code-quality
+    runs-on: ubuntu-20.04
+    steps:
+      - uses: actions/checkout@v3
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: 3.9
+      - name: Display Python version
+        run: python -c "import sys; print(sys.version)"
+
+      - name: Install sktime and dependencies
+        run: |
+          python -m pip install .
+
+      - name: Run pytest-free tests
+        run: |
+          python sktime/_nopytest_tests.py
+
   test-nosoftdeps:
     needs: code-quality
     runs-on: ubuntu-20.04

README.md

@@ -1,10 +1,10 @@
-<a href="https://www.sktime.net"><img src="https://github.com/sktime/sktime/blob/main/docs/source/images/sktime-logo.jpg?raw=true)" width="175" align="right" /></a>
+<a href="https://www.sktime.net"><img src="https://github.com/sktime/sktime/blob/main/docs/source/images/sktime-logo.svg" width="175" align="right" /></a>
 
 # Welcome to sktime
 
 > A unified interface for machine learning with time series
 
-:rocket: **Version 0.17.2 out now!** [Check out the release notes here](https://www.sktime.net/en/latest/changelog.html).
+:rocket: **Version 0.18.0 out now!** [Check out the release notes here](https://www.sktime.net/en/latest/changelog.html).
 
 sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation and forecasting. It comes with [time series algorithms](https://www.sktime.net/en/stable/estimator_overview.html) and [scikit-learn] compatible tools to build, tune and validate time series models.
 

docs/source/about/artwork.rst

@@ -8,5 +8,5 @@ High-quality logos are available in the `docs/source/images/ <https://github.com
 
 The logos were designed by `Miguel Garcia Cabrera <https://www.flickr.com/photos/miguelgarciacabrera/>`_.
 
-.. image:: ../images/sktime-logo-no-text.jpg
+.. image:: ../images/sktime-logo-no-text.png
     :align: center

docs/source/api_reference/classification.rst

@@ -20,8 +20,19 @@ Composition
 
     ClassifierPipeline
     ColumnEnsembleClassifier
-    ComposableTimeSeriesForestClassifier
     SklearnClassifierPipeline
+
+Ensembles
+---------
+
+.. currentmodule:: sktime.classification.ensemble
+
+.. autosummary::
+    :toctree: auto_generated/
+    :template: class.rst
+
+    BaggingClassifier
+    ComposableTimeSeriesForestClassifier
     WeightedEnsembleClassifier
 
 Deep learning

docs/source/api_reference/dists_kernels.rst

@@ -53,6 +53,14 @@ Composition
 
     CombinedDistance
 
+.. currentmodule:: sktime.dists_kernels.indep
+
+.. autosummary::
+    :toctree: auto_generated/
+    :template: class.rst
+
+    IndepDist
+
 .. currentmodule:: sktime.dists_kernels.compose_tab_to_panel
 
 .. autosummary::
@@ -109,6 +117,8 @@ Dynamic Time Warping Distances
 Time warping distances can also be obtained by composing ``DistFromAligner`` with
 a time warping aligner, see docstring of ``DistFromAligner``:
 
+.. currentmodule:: sktime.dists_kernels.compose_from_align
+
 .. autosummary::
     :toctree: auto_generated/
     :template: class.rst

docs/source/api_reference/forecasting.rst

@@ -77,6 +77,7 @@ Use ``make_reduction`` for easy specification.
     RecursiveTimeSeriesRegressionForecaster
     DirRecTabularRegressionForecaster
     DirRecTimeSeriesRegressionForecaster
+    YfromX
 
 Naive forecasters
 -----------------

docs/source/changelog.rst

@@ -13,13 +13,109 @@ All notable changes to this project will be documented in this file. We keep tra
 For upcoming changes and next releases, see our `milestones <https://github.com/sktime/sktime/milestones?direction=asc&sort=due_date&state=open>`_.
 For our long-term plan, see our :ref:`roadmap`.
 
+
+Version 0.18.0 - 2023-04-28
+---------------------------
+
+Maintenance release - scheduled ``numba``, ``scikit-base``, ``pandas`` dependency updates,
+scheduled deprecations.
+
+For last non-maintenance content update, see 0.17.2.
+
+Contents
+~~~~~~~~
+
+* ``numba`` has been changed to be a soft dependency. All ``numba`` based estimators
+  continue working unchanged, but require explicit ``numba`` installation.
+* the base module of ``sktime`` has been factored out to ``scikit-base``,
+  the abstract base layer for ``scikit-learn`` like packages maintained by ``sktime``
+* ``pandas 2`` support continues in testing/experimental period until 0.18.last.
+  All ``sktime`` native functionality is ``pandas 2`` compatible, the transition period
+  allows testing of deployments and custom extensions.
+  See instructions below for upgrading dependenet code to ``pandas 2``, or remaining on ``pandas 1``.
+* scheduled deprecation of ``tensorflow`` based probability interface and ``VectorizedDF`` methods.
+
+Dependency changes
+~~~~~~~~~~~~~~~~~~
+
+* ``numba`` is no longer a core dependency, it has changed to soft dependency
+* ``scikit-base`` is a new core dependency
+
+Deprecations and removals
+~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Dependencies
+^^^^^^^^^^^^
+
+* ``numba`` has changed from core dependency to soft dependency in ``sktime 0.18.0``.
+  To ensure functioning of setups of ``sktime`` code dependent on ``numba`` based estimators
+  going forward, ensure to install ``numba`` in the environment explicitly,
+  or install the ``all_extras`` soft dependency set which will continue to contain ``numba``.
+  Besides this, ``numba`` dependent estimators will function identically as before.
+* ``sktime``'s base module has moved to a new core dependency, ``scikit-base``, from ``sktime 0.18.0``.
+  This will not impact functionality or imports directly from ``sktime``, or any usage.
+* ``tensorflow-probability`` will cease to be a soft dependency from 0.19.0,
+  as the only dependency locus (forecasters' old ``predict_proba`` return type)
+  is being deprecated.
+
+Data types, checks, conversions
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+* ``VectorizedDF.get_iloc_indexer`` was removed.
+  Developers and users should use ``iter``, ``__iter__``, or ``get_iter_indices`` instead.
+
+Forecasting
+^^^^^^^^^^^
+
+* forecasters' ``predict_proba`` now by default returns a ``BaseDistribution``.
+  The old ``tensorflow-probability`` based return from pre-0.17.0 can still be obtained
+  by setting the argument ``legacy_interface=False`` in ``predict_proba``.
+  This is useful for handling deprecation.
+* from 0.19.0, the ``legacy_interface`` argument will be removed from ``predict_proba``,
+  together with the option to return ``tensorflow-probability`` based returns.
+
+``pandas 2`` upgrade and testing
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+* support for ``pandas 2`` is being introduced gradually:
+
+  * experimental support period until 0.19.0 (all 0.17.X and 0.18.X versions)
+  * full support from 0.19.0 (0.19.0, 0.19.X and onwards)
+
+* in the experimental period (0.17.1-0.18.last):
+
+  * ``sktime`` will have a dependency bound of ``pandas<2.0.0``
+  * ``sktime`` will aim to be compatible with ``pandas 2.0.X`` as well as ``pandas 1, >=1.1.0``,
+  * ``sktime`` can be run and tested with ``pandas 2.0.X`` by force-installing ``pandas 2.0.X``
+  * estimators can be tested for ``pandas 2`` compatibility via ``check_estimator`` under force-installed ``pandas 2.0.X``
+  * reports on compatibility issues are appreciated in :issue:`4426` (direct input or link from)
+
+* in the full support period (0.19.0-onwards):
+
+  * ``sktime`` requirements will allow ``pandas 2.0.X`` and extend support with ``pandas`` releases
+  * ``sktime`` will aim to be compatible with ``pandas 2`` (any version), as well as ``pandas 1, >=1.1.0``
+  * users choose their preferred ``pandas`` version by requirements on their downstream environment
+  * the bug and issue trackers should be used as normal
+
+List of PR
+~~~~~~~~~~
+
+* [MNT] 0.18.0 change action - ``numba`` as soft dependency (:pr:`3843`) :user:`fkiraly`
+* [MNT] 0.18.0 deprecation actions (:pr:`4510`) :user:`fkiraly`
+* [MNT] ensure ``predict_proba`` calls in ``mlflow`` forecasting interface explicitly call ``legacy_interface`` (:pr:`4514`) :user:`fkiraly`
+* [MNT] ``skbase`` refactor - part 1: ``BaseObject`` and package dependencies (:pr:`3151`) :user:`fkiraly`
+* [MNT] ``skbase`` refactor - part 2: ``all_estimators`` lookup (:pr:`3777`) :user:`fkiraly`
+* [ENH] ``quantile`` method for distributions, default implementation of forecaster ``predict_quantiles`` if ``predict_proba`` is present (:pr:`4513`) :user:`fkiraly`
+* [ENH] add test for ``all_estimators`` tag filter (:pr:`4512`) :user:`fkiraly`
+
+
 Version 0.17.2 - 2023-04-24
 ---------------------------
 
 Highlights
 ~~~~~~~~~~
 
-* the transformers and pipelines tutorial from pydata global 2022 is now available in ``sktime``, see `examples <https://mybinder.org/v2/gh/sktime/sktime/main?filepath=examples>`_(:pr:`4381`) :user:`dashapetr`
+* the transformers and pipelines tutorial from pydata global 2022 is now available in ``sktime``, see `examples <https://mybinder.org/v2/gh/sktime/sktime/main?filepath=examples>`_ (:pr:`4381`) :user:`dashapetr`
 * probabilistic prediction functionality for ``SARIMAX`` (:pr:`4439`) :user:`yarnabrina`
 * ``InceptionTime`` classifier from ``sktime-dl`` migrated (:pr:`3003`) :user:`tobiasweede`
 * ``SplitterBootstrapTransformer`` for booststrapping based on any splitter (:pr:`4455`) :user:`fkiraly`

docs/source/conf.py

@@ -82,7 +82,7 @@
 #
 # This is also used if you do content translation via gettext catalogs.
 # Usually you set "language" from the command line for these cases.
-language = None
+language = "en"
 
 # List of patterns, relative to source directory, that match files and
 # directories to ignore when looking for source files.