updating docs

Author: quentinhaenn

CHANGELOG.md

@@ -1,6 +1,6 @@
 # Changelog
 
-## [1.2.3] - 2025-06-18
+## [1.3.0] - 2025-06-18
 
 ### Added
 

docs/source/conf.py

@@ -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/usage.rst

@@ -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)

examples/plot_iris_example.py

@@ -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

src/radius_clustering/__init__.py

@@ -2,4 +2,4 @@
 from .radius_clustering import RadiusClustering
 
 __all__ = ["RadiusClustering"]
-__version__ = "1.2.3"
+__version__ = "1.3.0"