Merge pull request #20 from lias-laboratory/scikit-learn-contrib

scikit-learn-contrib application guidelines applied. New version 1.3.0.

Author: quentinhaenn

.coverage

@@ -3,7 +3,7 @@ docs/build/
 
 # env and caches
 
-mdsenv/
+mds-env/
 **/__pycache__/
 .pytest_cache/
 .ruff_cache/
@@ -25,5 +25,8 @@ docs/source/modules/generated/
 **/emos.c
 **/mds.cpp
 
+# MAC OS files
+.DS_Store
+
 # Reportings
 reporting/

.gitignore

@@ -0,0 +1,19 @@
+# Changelog
+
+## [1.3.0] - 2025-06-18
+
+### Added
+
+- Full test coverage for the entire codebase.
+- Badge for test coverage in the README.
+- Added `radius` parameter to the `RadiusClustering` class, allowing users to specify the radius for clustering.
+
+### Deprecated
+
+- Deprecated the `threshold` parameter in the `RadiusClustering` class. Use `radius` instead.
+
+### Changed
+
+- Updated all the attributes in the `RadiusClustering` class to fit `scikit-learn` standards and conventions.
+- Updated the tests cases to reflect the changes in the `RadiusClustering` class.
+- Updated README and documentation to reflect the new `radius` parameter and the deprecation of `threshold`.

CHANGELOG.md

@@ -16,7 +16,7 @@
 project = "Radius Clustering"
 copyright = "2024, Haenn Quentin, Chardin Brice, Baron Mickaël"
 author = "Haenn Quentin, Chardin Brice, Baron Mickaël"
-release = "1.0"
+release = "1.3.0"
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

docs/source/conf.py

@@ -12,7 +12,9 @@ Here's a basic example of how to use Radius Clustering:
    X = np.random.rand(100, 2)
 
    # Create an instance of MdsClustering
-   rad = RadiusClustering(manner="approx", threshold=0.5)
+   rad = RadiusClustering(manner="approx", radius=0.5) 
+   # Attention: the 'threshold' parameter is deprecated by version 1.3.0
+   # and will be removed in a future version. Use 'radius' instead.
 
    # Fit the model to the data
    rad.fit(X)

docs/source/usage.rst

@@ -82,7 +82,7 @@
 # We create an instance of the `RadiusClustering` class and fit it to the Iris dataset.
 import time
 
-rad = RadiusClustering(manner="exact", threshold=1.43)
+rad = RadiusClustering(manner="exact", radius=1.43)
 t0 = time.time()
 rad.fit(X)
 t_rad = time.time() - t0
@@ -242,7 +242,7 @@ def get_order_labels(kmeans, rad, data):
 
 # Compute clustering with MDS
 
-rad = RadiusClustering(manner="exact", threshold=232.09)
+rad = RadiusClustering(manner="exact", radius=232.09)
 t0 = time.time()
 rad.fit(X)
 t_rad = time.time() - t0

examples/plot_iris_example.py

@@ -52,6 +52,7 @@ documentation = "https://lias-laboratory.github.io/radius_clustering/"
 [project.optional-dependencies]
 dev = [
     "pytest>=8.3.3",
+    "pytest-cov>=5.0.0",
     "pandas",
     "cython>=3.0",
     "setuptools>= 61.0",
@@ -80,8 +81,22 @@ pythonpath = "src"
 testpaths = ["tests"]
 addopts = [
     "--import-mode=importlib",
+    "--cov=src/radius_clustering",
+    "--cov-report=term-missing",
+    "--cov-report=html:coverage_html_report",
 ]
 
+[tool.coverage.run]
+source = ["src/radius_clustering"]
+branch = true
+
+[tool.coverage.report]
+show_missing = true
+
+[tool.coverage.html]
+directory = "coverage_html_report"
+title = "Coverage Report"
+
 [tool.ruff]
 # Exclude a variety of commonly ignored directories.
 exclude = [
@@ -105,14 +120,14 @@ exclude = [
 
 # Same as Black.
 line-length = 88
-indent-width = 4
+target-version = "py310"
 
 [tool.ruff.lint]
 # Enable Pyflakes (`F`) and a subset of the pycodestyle (`E`)  codes by default.
 # Unlike Flake8, Ruff doesn't enable pycodestyle warnings (`W`) or
 # McCabe complexity (`C901`) by default.
-select = ["E", "F"]
-ignore = []
+select = ["E", "F", "W", "I"]
+ignore = ["E203", "E731", "E741"]
 
 # Allow fix for all enabled rules (when `--fix`) is provided.
 fixable = ["ALL"]

pyproject.toml

@@ -1,7 +1,8 @@
 import platform
-from setuptools import setup, Extension
-from Cython.Build import cythonize
+
 import numpy as np
+from Cython.Build import cythonize
+from setuptools import Extension, setup
 
 SYSTEM = platform.system()
 CPU = platform.processor()
@@ -21,7 +22,10 @@
 extensions = [
     Extension(
         "radius_clustering.utils._emos",
-        ["src/radius_clustering/utils/emos.pyx", "src/radius_clustering/utils/main-emos.c"],
+        [
+            "src/radius_clustering/utils/emos.pyx",
+            "src/radius_clustering/utils/main-emos.c"
+        ],
         include_dirs=[np.get_include(), "src/radius_clustering/utils"],
         extra_compile_args=C_COMPILE_ARGS,
     ),

setup.py

@@ -2,6 +2,4 @@
 from .radius_clustering import RadiusClustering
 
 __all__ = ["RadiusClustering"]
-
-# Optionally, you can set a version number for your package
-__version__ = "1.2.2"
+__version__ = "1.3.0"