Merge branch 'main' into multivariate-compositor

sktime · Aug 11, 2021 · e9ac82f · e9ac82f
2 parents e2ec24c + 82172b5
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diff --git a/.all-contributorsrc b/.all-contributorsrc
@@ -1053,7 +1053,7 @@
       "contributions": [
         "code",
         "bug",
-        "test",
+        "test"
       ]
     },
     {
@@ -1071,7 +1071,7 @@
       "avatar_url": "https://https://avatars.githubusercontent.com/jambo6",
       "profile": "https://github.com/jambo6",
       "contributions": [
-        "code",
+        "code"
       ]
     },
     {
@@ -1091,7 +1091,7 @@
       "contributions": [
         "code"
       ]
-    }
+    },
     {
       "login": "ltoniazzi",
       "name": "Lorenzo Toniazzi",
@@ -1100,6 +1100,50 @@
       "contributions": [
         "code"
       ]
+    },
+    {
+      "login": "Riyabelle25",
+      "name": "Riya Elizabeth John",
+      "avatar_url": "https://avatars.githubusercontent.com/u/55790848?v=4",
+      "profile": "https://github.com/Riyabelle25",
+      "contributions": [
+        "code",
+        "test",
+        "doc"
+      ]
+    },
+    {
+      "login": "chrisholder",
+      "name": "chrisholder",
+      "avatar_url": "https://avatars.githubusercontent.com/u/4674372?v=4",
+      "profile": "https://github.com/chrisholder",
+      "contributions": [
+        "code",
+        "test",
+        "doc",
+        "design",
+        "example"
+      ]
+    },
+    {
+      "login": "moradabaz",
+      "name": "Morad :)",
+      "avatar_url": "https://avatars.githubusercontent.com/u/29915156?v=4",
+      "profile": "https://moradisten.github.io/",
+      "contributions": [
+        "code",
+        "test",
+        "doc"
+      ]
+    },
+    {
+      "login": "bilal-196",
+      "name": "Ahmed Bilal",
+      "avatar_url": "https://avatars.githubusercontent.com/u/74570044?v=4",
+      "profile": "https://github.com/bilal-196",
+      "contributions": [
+        "doc"
+      ]
     }
   ],
   "projectName": "sktime",

diff --git a/.appveyor.yml b/.appveyor.yml
@@ -26,7 +26,7 @@ environment:
       MINICONDA_VERSION: C:\Miniconda36-x64
     - PYTHON_VERSION: "3.7"
       MINICONDA_VERSION: C:\Miniconda37-x64
-    - PYTHON_VERSION: "3.8"
+    - PYTHON_VERSION: "3.8.10"
       MINICONDA_VERSION: C:\Miniconda38-x64
       # For Python 3.8, we need a different image, check out available pre-installed Python
       # and Visual Studio versions: https://www.appveyor.com/docs/linux-images-software/

diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md
@@ -1,17 +1,17 @@
 ---
 name: "\u2728 Feature request"
 about: Suggest an idea for this project
-title: ''
+title: '[ENH]'
 labels: enhancement
 assignees: ''
 
 ---
 
 **Is your feature request related to a problem? Please describe.**
-A clear and concise description of what the problem is. 
+A clear and concise description of what the problem is.
 
 **Describe the solution you'd like**
-A clear and concise description of what you want to happen, ideally taking into consideration the existing toolbox design, classes and methods. 
+A clear and concise description of what you want to happen, ideally taking into consideration the existing toolbox design, classes and methods.
 
 **Describe alternatives you've considered**
 A clear and concise description of any alternative solutions or features you've considered.

diff --git a/CODEOWNERS b/CODEOWNERS
@@ -6,13 +6,16 @@
 sktime/classification/dictionary_based/ @patrickzib @MatthewMiddlehurst @TonyBagnall
 sktime/classification/dictionary_based/tests/ @patrickzib @MatthewMiddlehurst
 sktime/classification/distance_based/ @jasonlines @goaster @TonyBagnall
+sktime/classification/feature_based/ @MatthewMiddlehurst @TonyBagnall
+sktime/classification/feature_based/tests/ @MatthewMiddlehurst
+sktime/classification/feature_based/_signature_classifier.py @jambo6
 sktime/classification/hybrid/ @MatthewMiddlehurst @TonyBagnall
+sktime/classification/hybrid/tests/ @MatthewMiddlehurst
 sktime/classification/interval_based/ @MatthewMiddlehurst @TonyBagnall
 sktime/classification/interval_based/tests/ @MatthewMiddlehurst
 sktime/classification/kernel_based/ @MatthewMiddlehurst @TonyBagnall
 sktime/classification/kernel_based/tests/ @MatthewMiddlehurst
 sktime/classification/shapelet_based/ @jasonlines @ABostrom @TonyBagnall
-sktime/classification/signature_based/ @jambo6
 
 sktime/transformations/panel/dictionary_based/ @patrickzib @MatthewMiddlehurst
 sktime/transformations/panel/shapelets/ @jasonlines @ABostrom @TonyBagnall

diff --git a/CONTRIBUTORS.md b/CONTRIBUTORS.md
diff --git a/README.md b/README.md
@@ -103,13 +103,25 @@ Using pip, sktime releases are available as source packages and binary wheels. Y
 pip install sktime
 ```
 
+or, with maximum dependencies,
+
+```bash
+pip install sktime[all_extras]
+```
+
 ### conda
 You can also install sktime from `conda` via the `conda-forge` channel. For the feedstock including the build recipe and configuration, check out [this repository](https://github.com/conda-forge/sktime-feedstock).
 
 ```bash
 conda install -c conda-forge sktime
 ```
 
+or, with maximum dependencies,
+
+```bash
+conda install -c conda-forge sktime-all-extras
+```
+
 ## :zap: Quickstart
 
 ### Forecasting

diff --git a/build_tools/azure/check_soft_dependencies.py b/build_tools/azure/check_soft_dependencies.py
@@ -2,27 +2,32 @@
 # -*- coding: utf-8 -*-
 # copyright: sktime developers, BSD-3-Clause License (see LICENSE file)
 
-# sktime supports a number of soft dependencies which are necessary for using
-# a certain module but otherwise not necessary. Here we check if soft
-# dependencies have been properly isolated and are not required to run other
-# modules.
+"""
+sktime checks for soft dependencies.
+
+sktime supports a number of soft dependencies which are necessary for using
+a certain module but otherwise not necessary. Here we check if soft
+dependencies have been properly isolated and are not required to run other
+modules.
+"""
+
 import pkgutil
 import re
 from importlib import import_module
 
 SOFT_DEPENDENCIES = {
     "sktime.benchmarking.evaluation": ["matplotlib"],
+    "sktime.benchmarking.experiments": ["tsfresh", "esig"],
     "sktime.forecasting.all": ["pmdarima", "fbprophet", "tbats"],
     "sktime.forecasting.arima": ["pmdarima"],
     "sktime.forecasting.hcrystalball": ["hcrystalball"],
     "sktime.forecasting.tbats": ["tbats"],
     "sktime.forecasting.bats": ["tbats"],
     "sktime.forecasting.fbprophet": ["fbprophet"],
-    "sktime.classification.all": ["tsfresh"],
-    "sktime.regression.all": ["tsfresh"],
+    "sktime.classification.feature_based": ["tsfresh", "esig"],
+    "sktime.classification.signature_based": ["esig"],
     "sktime.transformations.panel.tsfresh": ["tsfresh"],
     "sktime.transformations.series.matrix_profile": ["stumpy"],
-    "sktime.classification.signature_based": ["esig"],
     "sktime.transformations.panel.signature_based": ["esig"],
     "sktime.clustering.evaluation._plot_clustering": ["matplotlib"],
 }

diff --git a/docs/source/api_reference.rst b/docs/source/api_reference.rst
@@ -15,6 +15,7 @@ This is the class and function reference for ``sktime``.
 .. include:: api_reference/regression.rst
 .. include:: api_reference/series_as_features.rst
 .. include:: api_reference/forecasting.rst
+.. include:: api_reference/annotation.rst
 .. include:: api_reference/transformations.rst
 .. include:: api_reference/performance_metrics.rst
 .. include:: api_reference/datasets.rst

diff --git a/docs/source/api_reference/annotation.rst b/docs/source/api_reference/annotation.rst
@@ -0,0 +1,21 @@
+.. _annotation_ref:
+
+sktime.annotation: Time series annotation
+=========================================
+
+The :mod:`sktime.annotation` module contains algorithms and composition tools
+for time series annotation (for example, anomaly or outlier detection).
+
+.. automodule:: sktime.annotation
+    :no-members:
+
+Adapters
+--------
+
+.. currentmodule:: sktime.annotation.adapters
+
+.. autosummary::
+    :toctree: modules/auto_generated/
+    :template: class.rst
+
+    PyODAnnotator
diff --git a/docs/source/api_reference/classification.rst b/docs/source/api_reference/classification.rst
@@ -74,6 +74,8 @@ Interval-based
     TimeSeriesForestClassifier
     RandomIntervalSpectralForest
     SupervisedTimeSeriesForest
+    CanonicalIntervalForest
+    DrCIF
 
 Shapelet-based
 --------------
@@ -99,13 +101,16 @@ Kernel-based
     ROCKETClassifier
     Arsenal
 
-Signature-based
+Feature-based
 ---------------
 
-.. currentmodule:: sktime.classification.signature_based
+.. currentmodule:: sktime.classification.feature_based
 
 .. autosummary::
     :toctree: modules/auto_generated/
     :template: class.rst
 
+    Catch22Classifier
+    MatrixProfileClassifier
+    TSFreshClassifier
     SignatureClassifier
diff --git a/docs/source/api_reference/utils.rst b/docs/source/api_reference/utils.rst
@@ -20,7 +20,7 @@ Plotting
 Data Processing
 ---------------
 
-.. currentmodule:: sktime.utils.data_processing
+.. currentmodule:: sktime.datatypes._panel._convert
 
 .. autosummary::
     :toctree: modules/auto_generated/

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -224,7 +224,7 @@ def find_source():
 def _make_estimator_overview(app):
     """Make estimator overview table."""
     import pandas as pd
-    from sktime.utils import all_estimators
+    from sktime.registry import all_estimators
 
     def _process_author_info(author_info):
         """

diff --git a/docs/source/developer_guide/add_dataset.rst b/docs/source/developer_guide/add_dataset.rst
@@ -1,13 +1,13 @@
 .. _developer_guide_forecasting:
 
 Adding Datasets to sktime
-===========
+=========================
 Follow these steps to add a new dataset to sktime:
 
 *  Include CSV file or supported other format under :code:`sktime/datasets/data/<dataset-name>`
 *  Add :code:`load_<dataset-name>(...)` function in file :code:`sktime/datasets/base.py`
 *  Add :code:`<dataset-name>` to the list :code:`__all__ = [...` in file :code:`sktime/datasets/__init__.py`
 *  Add :code:`<dataset-name>` as argument to method :code:`included_datasets = (...` in file :code:`sktime/sktime/datasets/setup.py`
-*  Add import statement :code:`from sktime.datasets.base import load_<dataset-name>(...)` in file :code:`sktime/sktime/datasets/setup.py`
+*  Add :code:`<dataset-name>` to the list of included problems in file :code:`sktime/sktime/datasets/setup.py`
 
 Thank you for your contribution!
diff --git a/docs/source/installation.rst b/docs/source/installation.rst
@@ -47,9 +47,15 @@ They can be installed via ``conda`` using:
 
 This will install ``sktime`` with core dependencies, excluding soft dependencies.
 
-Currently, there is no easy route to install ``sktime`` with maximum dependencies via ``conda``.
+To install ``sktime`` with maximum dependencies, including soft dependencies, install with the ``all-extras`` recipe:
 
-Community contributions towards this, e.g., via conda metapackages, would be appreciated.
+.. code-block:: bash
+
+    conda install -c conda-forge sktime-all-extras
+
+Note: currently this does not include dependencies ``catch-22``, ``pmdarima``, and ``tbats``.
+As these packages are not available on ``conda-forge``, they must be installed via ``pip`` if desired.
+Contributions to remedy this situation are appreciated.
 
 
 Release versions - troubleshooting
@@ -277,6 +283,17 @@ Then you need to set the following environment variables:
 
 Finally you can build the package using the standard command.
 
+Troubleshooting - Mac OSX build requirements
+""""""""""""""""""""""""""""""""""""""""""""
+
+After installing the release version following the installation steps above and running a ``pytest`` command, some contributors received the error message below:
+
+``E   ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject``
+
+A possible solution to the problem is reinstalling your C compiler. If it is gcc, run ``brew reinstall gcc`` and then ``pip install -e .``.
+This should be followed by installing the OpenMP library and setting the environment variables using the same commands again as in the section above.
+
+If you found another solution to the problem, please kindly consider contributing to this section.
 
 Unix-like OS
 ~~~~~~~~~~~~