Add ask wiki link and init depth

* Update read the docs config

*Update copyright year in docs

* Update python version

* Change build configuration

* Change version read in config

* Refactor config files

* Refactor api config

.github/workflows/main.yml

@@ -13,12 +13,12 @@ jobs:
     strategy:
       matrix:
         os: [macos-latest, ubuntu-latest, windows-latest]
-        python: [3.8, "3.10"]
+        python: [3.11, 3.12]
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - name: Set up Python ${{ matrix.python }}
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python }}
       - name: Install dependencies
@@ -28,14 +28,14 @@ jobs:
           pip install -q --upgrade codecov coverage black flake8 codacy-coverage
       - name: Lint
         run: |
-          black --check --diff stree
+          # black --check --diff stree
           flake8 --count stree
       - name: Tests
         run: |
           coverage run -m unittest -v stree.tests
           coverage xml
       - name: Upload coverage to Codecov
-        uses: codecov/codecov-action@v3
+        uses: codecov/codecov-action@v4
         with:
           token: ${{ secrets.CODECOV_TOKEN }}
           files: ./coverage.xml

.readthedocs.yaml

@@ -3,8 +3,12 @@ version: 2
 sphinx:
   configuration: docs/source/conf.py
 
+build:
+  os: ubuntu-22.04
+  tools:
+    python: "3.12"
+
 python:
-  version: 3.8
   install:
     - requirements: requirements.txt
     - requirements: docs/requirements.txt

MANIFEST.in

@@ -0,0 +1 @@
+include README.md LICENSE

Makefile

@@ -1,46 +1,36 @@
 SHELL := /bin/bash
 .DEFAULT_GOAL := help
-.PHONY: coverage deps help lint push test doc build
+.PHONY: audit coverage help lint test doc doc-clean build
 
 coverage:  ## Run tests with coverage
-	coverage erase
-	coverage run -m unittest -v stree.tests
-	coverage report -m
+	@coverage erase
+	@coverage run -m unittest -v stree.tests
+	@coverage report -m
 
-deps:  ## Install dependencies
-	pip install -r requirements.txt
-
-devdeps:  ## Install development dependencies
-	pip install black pip-audit flake8 mypy coverage
-
-lint:  ## Lint and static-check
-	black stree
-	flake8 stree
-	mypy stree
-
-push:  ## Push code with tags
-	git push && git push --tags
+lint:  ## Lint source files
+	@black stree
+	@flake8 stree
 
 test:  ## Run tests
-	python -m unittest -v stree.tests
+	@python -m unittest -v stree.tests
 
 doc:  ## Update documentation
-	make -C docs --makefile=Makefile html
+	@make -C docs --makefile=Makefile html
 
 build:  ## Build package
-	rm -fr dist/*
-	rm -fr build/*
-	python setup.py sdist bdist_wheel
+	@rm -fr dist/*
+	@rm -fr build/*
+	@hatch build
 
-doc-clean:  ## Update documentation
-	make -C docs --makefile=Makefile clean
+doc-clean:  ## Clean documentation folders
+	@make -C docs --makefile=Makefile clean
 
 audit: ## Audit pip
-	pip-audit
+	@pip-audit
 
-help: ## Show help message
+help: ## Show this help message
 	@IFS=$$'\n' ; \
-	help_lines=(`fgrep -h "##" $(MAKEFILE_LIST) | fgrep -v fgrep | sed -e 's/\\$$//' | sed -e 's/##/:/'`); \
+	help_lines=(`grep -Fh "##" $(MAKEFILE_LIST) | grep -Fv fgrep | sed -e 's/\\$$//' | sed -e 's/##/:/'`); \
 	printf "%s\n\n" "Usage: make [task]"; \
 	printf "%-20s %s\n" "task" "help" ; \
 	printf "%-20s %s\n" "------" "----" ; \

README.md

@@ -1,16 +1,18 @@
+# STree
+
 ![CI](https://github.com/Doctorado-ML/STree/workflows/CI/badge.svg)
 [![CodeQL](https://github.com/Doctorado-ML/STree/actions/workflows/codeql-analysis.yml/badge.svg)](https://github.com/Doctorado-ML/STree/actions/workflows/codeql-analysis.yml)
 [![codecov](https://codecov.io/gh/doctorado-ml/stree/branch/master/graph/badge.svg)](https://codecov.io/gh/doctorado-ml/stree)
 [![Codacy Badge](https://app.codacy.com/project/badge/Grade/35fa3dfd53a24a339344b33d9f9f2f3d)](https://www.codacy.com/gh/Doctorado-ML/STree?utm_source=github.com&utm_medium=referral&utm_content=Doctorado-ML/STree&utm_campaign=Badge_Grade)
 [![PyPI version](https://badge.fury.io/py/STree.svg)](https://badge.fury.io/py/STree)
-![https://img.shields.io/badge/python-3.8%2B-blue](https://img.shields.io/badge/python-3.8%2B-brightgreen)
+![https://img.shields.io/badge/python-3.11%2B-blue](https://img.shields.io/badge/python-3.11%2B-brightgreen)
+[![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/Doctorado-ML/STree)
 [![DOI](https://zenodo.org/badge/262658230.svg)](https://zenodo.org/badge/latestdoi/262658230)
 
-# STree
+![Stree](https://raw.github.com/doctorado-ml/stree/master/example.png)
 
 Oblique Tree classifier based on SVM nodes. The nodes are built and splitted with sklearn SVC models. Stree is a sklearn estimator and can be integrated in pipelines, grid searches, etc.
 
-![Stree](https://raw.github.com/doctorado-ml/stree/master/example.png)
 
 ## Installation
 

docs/source/api/Siterator.rst

@@ -1,9 +1,10 @@
 Siterator
 =========
 
-.. automodule:: Splitter
+.. automodule:: stree
 .. autoclass:: Siterator
     :members:
     :undoc-members:
     :private-members:
-    :show-inheritance:
+    :show-inheritance:
+    :noindex:

docs/source/api/Snode.rst

@@ -1,9 +1,9 @@
 Snode
 =====
 
-.. automodule:: Splitter
-.. autoclass:: Snode
+.. autoclass:: stree.Splitter.Snode
     :members:
     :undoc-members:
     :private-members:
-    :show-inheritance:
+    :show-inheritance:
+    :noindex:

docs/source/api/Splitter.rst

@@ -1,9 +1,10 @@
 Splitter
 ========
 
-.. automodule:: Splitter
+.. automodule:: stree.Splitter
 .. autoclass:: Splitter
     :members:
     :undoc-members:
     :private-members:
-    :show-inheritance:
+    :show-inheritance:
+    :noindex:

docs/source/api/Stree.rst

@@ -6,4 +6,5 @@ Stree
     :members:
     :undoc-members:
     :private-members:
-    :show-inheritance:
+    :show-inheritance:
+    :noindex:

docs/source/conf.py

@@ -6,26 +6,21 @@
 
 # -- Path setup --------------------------------------------------------------
 
-# If extensions (or modules to document with autodoc) are in another directory,
-# add these directories to sys.path here. If the directory is relative to the
-# documentation root, use os.path.abspath to make it absolute, like shown here.
-#
-import os
 import sys
-from stree._version import __version__
+from pathlib import Path
 
-sys.path.insert(0, os.path.abspath("../../stree/"))
+sys.path.insert(0, str(Path(__file__).parent.parent.parent))
+
+import stree
 
 # -- Project information -----------------------------------------------------
 
 project = "STree"
-copyright = "2020 - 2022, Ricardo Montañana Gómez"
+copyright = "2020 - 2024, Ricardo Montañana Gómez"
 author = "Ricardo Montañana Gómez"
 
 # The full version, including alpha/beta/rc tags
-version = __version__
-release = version
-
+version = release = stree.__version__
 
 # -- General configuration ---------------------------------------------------
 

docs/source/index.rst

@@ -5,7 +5,6 @@ Welcome to STree's documentation!
    :caption: Contents:
    :titlesonly:
 
-
    stree
    install
    hyperparameters

pyproject.toml

@@ -1,5 +1,65 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[project]
+name = "STree"
+dependencies = ["scikit-learn>1.0", "mufs"]
+license = { file = "LICENSE" }
+description = "Oblique decision tree with svm nodes."
+readme = "README.md"
+authors = [
+  { name = "Ricardo Montañana", email = "ricardo.montanana@alu.uclm.es" },
+]
+dynamic = ['version']
+requires-python = ">=3.11"
+keywords = [
+  "scikit-learn",
+  "oblique-classifier",
+  "oblique-decision-tree",
+  "decision-tree",
+  "svm",
+  "svc",
+]
+classifiers = [
+  "Development Status :: 5 - Production/Stable",
+  "Intended Audience :: Science/Research",
+  "Intended Audience :: Developers",
+  "Topic :: Software Development",
+  "Topic :: Scientific/Engineering",
+  "License :: OSI Approved :: MIT License",
+  "Natural Language :: English",
+  "Operating System :: OS Independent",
+  "Programming Language :: Python :: 3.11",
+  "Programming Language :: Python :: 3.12",
+]
+
+[project.optional-dependencies]
+dev = ["black", "flake8", "coverage", "hatch", "pip-audit"]
+doc = ["sphinx", "myst-parser", "sphinx_rtd_theme", "sphinx-autodoc-typehints"]
+
+[project.urls]
+Code = "https://github.com/Doctorado-ML/STree"
+Documentation = "https://stree.readthedocs.io/en/latest/index.html"
+
+[tool.hatch.version]
+path = "stree/_version.py"
+
+[tool.hatch.build.targets.sdist]
+include = ["/stree"]
+
+[tool.coverage.run]
+branch = true
+source = ["stree"]
+command_line = "-m unittest discover -s stree.tests"
+
+[tool.coverage.report]
+show_missing = true
+fail_under = 100
+
 [tool.black]
 line-length = 79
+target-version = ["py311"]
 include = '\.pyi?$'
 exclude = '''
 /(
@@ -13,4 +73,4 @@ exclude = '''
   | build
   | dist
 )/
-'''
+'''

requirements.txt

@@ -1,2 +1,3 @@
-scikit-learn>0.24
-mufs
+scikit-learn==1.5.2
+coverage
+mufs

runtime.txt

@@ -1 +0,0 @@
-python-3.8

setup.py

@@ -1,56 +0,0 @@
-import setuptools
-import os
-
-
-def readme():
-    with open("README.md") as f:
-        return f.read()
-
-
-def get_data(field, file_name="__init__.py"):
-    item = ""
-    with open(os.path.join("stree", file_name)) as f:
-        for line in f.readlines():
-            if line.startswith(f"__{field}__"):
-                delim = '"' if '"' in line else "'"
-                item = line.split(delim)[1]
-                break
-        else:
-            raise RuntimeError(f"Unable to find {field} string.")
-    return item
-
-
-def get_requirements():
-    with open("requirements.txt") as f:
-        return f.read().splitlines()
-
-
-setuptools.setup(
-    name="STree",
-    version=get_data("version", "_version.py"),
-    license=get_data("license"),
-    description="Oblique decision tree with svm nodes",
-    long_description=readme(),
-    long_description_content_type="text/markdown",
-    packages=setuptools.find_packages(),
-    url="https://github.com/Doctorado-ML/STree#stree",
-    project_urls={
-        "Code": "https://github.com/Doctorado-ML/STree",
-        "Documentation": "https://stree.readthedocs.io/en/latest/index.html",
-    },
-    author=get_data("author"),
-    author_email=get_data("author_email"),
-    keywords="scikit-learn oblique-classifier oblique-decision-tree decision-\
-    tree svm svc",
-    classifiers=[
-        "Development Status :: 5 - Production/Stable",
-        "License :: OSI Approved :: " + get_data("license"),
-        "Programming Language :: Python :: 3.8",
-        "Natural Language :: English",
-        "Topic :: Scientific/Engineering :: Artificial Intelligence",
-        "Intended Audience :: Science/Research",
-    ],
-    install_requires=get_requirements(),
-    test_suite="stree.tests",
-    zip_safe=False,
-)

stree/Splitter.py

@@ -414,7 +414,8 @@ class Splitter:
         )
         return tuple(
             sorted(
-                range(len(feature_list)), key=lambda sub: feature_list[sub]
+                range(len(feature_list)),
+                key=lambda sub: feature_list[sub],
             )[-max_features:]
         )
 
@@ -529,7 +530,10 @@ class Splitter:
         return entropy
 
     def information_gain(
-        self, labels: np.array, labels_up: np.array, labels_dn: np.array
+        self,
+        labels: np.array,
+        labels_up: np.array,
+        labels_dn: np.array,
     ) -> float:
         """Compute information gain of a split candidate
 
@@ -742,7 +746,7 @@ class Splitter:
             Train time - True / Test time - False
         """
         # data contains the distances of every sample to every class hyperplane
-        # array of (m, nc) nc = # classes
+        # array of (m, nc) nc = k if ovr, nc = k*(k-1)/2 if ovo
         data = self._distances(node, samples)
         if data.shape[0] < self._min_samples_split:
             # there aren't enough samples to split

stree/Strees.py

@@ -168,12 +168,18 @@ class Stree(BaseEstimator, ClassifierMixin):
         self.splitter = splitter
         self.normalize = normalize
         self.multiclass_strategy = multiclass_strategy
+        self.depth_ = 0
 
     @staticmethod
     def version() -> str:
         """Return the version of the package."""
         return __version__
 
+    def __call__(self) -> None:
+        """Only added to comply with scikit-learn base sestimator for
+        ensembles"""
+        pass
+
     def _more_tags(self) -> dict:
         """Required by sklearn to supply features of the classifier
         make mandatory the labels array
@@ -184,7 +190,10 @@ class Stree(BaseEstimator, ClassifierMixin):
         return {"requires_y": True}
 
     def fit(
-        self, X: np.ndarray, y: np.ndarray, sample_weight: np.array = None
+        self,
+        X: np.ndarray,
+        y: np.ndarray,
+        sample_weight: np.array = None,
     ) -> "Stree":
         """Build the tree based on the dataset of samples and its labels
 
@@ -339,7 +348,11 @@ class Stree(BaseEstimator, ClassifierMixin):
         )
         node.set_down(
             self._train(
-                X_D, y_d, sw_d, depth + 1, title + f" - Down({depth+1})"
+                X_D,
+                y_d,
+                sw_d,
+                depth + 1,
+                title + f" - Down({depth+1})",
             )
         )
         return node

stree/__init__.py

@@ -1,8 +1,9 @@
 from .Strees import Stree, Siterator
+from ._version import __version__
 
 __author__ = "Ricardo Montañana Gómez"
 __copyright__ = "Copyright 2020-2021, Ricardo Montañana Gómez"
 __license__ = "MIT License"
 __author_email__ = "ricardo.montanana@alu.uclm.es"
 
-__all__ = ["Stree", "Siterator"]
+__all__ = ["__version__", "Stree", "Siterator"]

stree/_version.py

@@ -1 +1 @@
-__version__ = "1.3.2"
+__version__ = "1.4.0"

stree/tests/Stree_test.py

@@ -289,12 +289,12 @@ class Stree_test(unittest.TestCase):
                 "impurity sigmoid": 0.824,
             },
             "Iris": {
-                "max_samples liblinear": 0.9550561797752809,
+                "max_samples liblinear": 0.9887640449438202,
                 "max_samples linear": 1.0,
                 "max_samples rbf": 0.6685393258426966,
                 "max_samples poly": 0.6853932584269663,
                 "max_samples sigmoid": 0.6404494382022472,
-                "impurity liblinear": 0.9550561797752809,
+                "impurity liblinear": 0.9887640449438202,
                 "impurity linear": 1.0,
                 "impurity rbf": 0.6685393258426966,
                 "impurity poly": 0.6853932584269663,
@@ -440,10 +440,10 @@ class Stree_test(unittest.TestCase):
         clf.fit(X, y)
         score = clf.score(X, y)
         # Check accuracy of the whole model
-        self.assertAlmostEquals(0.98, score, 5)
+        self.assertAlmostEqual(0.98, score, 5)
         svm = LinearSVC(random_state=0)
         svm.fit(X, y)
-        self.assertAlmostEquals(0.9666666666666667, svm.score(X, y), 5)
+        self.assertAlmostEqual(0.9666666666666667, svm.score(X, y), 5)
         data = svm.decision_function(X)
         expected = [
             0.4444444444444444,
@@ -455,7 +455,7 @@ class Stree_test(unittest.TestCase):
         ty[data > 0] = 1
         ty = ty.astype(int)
         for i in range(3):
-            self.assertAlmostEquals(
+            self.assertAlmostEqual(
                 expected[i],
                 clf.splitter_._gini(ty[:, i]),
             )
@@ -593,7 +593,7 @@ class Stree_test(unittest.TestCase):
         )
         self.assertEqual(0.9526666666666667, clf2.fit(X, y).score(X, y))
         X, y = load_wine(return_X_y=True)
-        self.assertEqual(0.9831460674157303, clf.fit(X, y).score(X, y))
+        self.assertEqual(0.9887640449438202, clf.fit(X, y).score(X, y))
         self.assertEqual(1.0, clf2.fit(X, y).score(X, y))
 
     def test_zero_all_sample_weights(self):
@@ -725,6 +725,11 @@ class Stree_test(unittest.TestCase):
         clf = Stree()
         self.assertEqual(__version__, clf.version())
 
+    def test_call(self) -> None:
+        """Check call method."""
+        clf = Stree()
+        self.assertIsNone(clf())
+
     def test_graph(self):
         """Check graphviz representation of the tree."""
         X, y = load_wine(return_X_y=True)