aimsim-core - npm Package Compare versions

Comparing version 2.1.3 to 2.2.0

aimsim_core.egg-info/PKG-INFO

 Metadata-Version: 2.1
 Name: aimsim_core
-Version: 2.1.3
+Version: 2.2.0
 Summary: Core AIMSim molecular featurization and comparison utilities.
@@ -14,3 +14,2 @@ Home-page: https://github.com/VlachosGroup/AIMSim
 Requires-Dist: scikit_learn
-Requires-Dist: scikit_learn_extra
 Requires-Dist: rdkit
@@ -30,10 +29,12 @@ Requires-Dist: numpy
   <img alt="GitHub Repo Stars" src="https://img.shields.io/github/stars/VlachosGroup/AIMSim?style=social">
-  <img alt="Total Downloads" src="https://static.pepy.tech/personalized-badge/aimsim?period=total&units=none&left_color=grey&right_color=blue&left_text=Lifetime%20Downloads">
-  <img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dm/aimsim">
   <img alt="commits since" src="https://img.shields.io/github/commits-since/VlachosGroup/AIMSim/latest.svg">
   <img alt="PyPI" src="https://img.shields.io/pypi/v/aimsim">
   <img alt="PyPI - License" src="https://img.shields.io/github/license/VlachosGroup/AIMSim">
-  <img alt="Test Status" src="https://github.com/VlachosGroup/AIMSim/actions/workflows/run_tests.yml/badge.svg?branch=master&event=schedule">
+  <img alt="Test Status" src="https://github.com/VlachosGroup/AIMSim/actions/workflows/ci.yml/badge.svg?event=schedule">
 </p>
 
+Downloads Stats:
+ - `aimsim`: [![Downloads](https://static.pepy.tech/badge/aimsim)](https://static.pepy.tech/personalized-badge/aimsim?period=total&units=none&left_color=grey&right_color=blue&left_text=Lifetime%20Downloads)
+ - `aimsim_core`: [![Downloads](https://static.pepy.tech/badge/aimsim_core)](https://pepy.tech/project/aimsim_core?period=total&units=none&left_color=grey&right_color=blue&left_text=Lifetime%20Downloads)
+
 ## Documentation and Tutorial
@@ -82,2 +83,6 @@ [View our Online Documentation](https://vlachosgroup.github.io/AIMSim/) or try the _AIMSim_ comprehensive tutorial in your browser:
 This command also installs the required dependencies.
+
+> [!NOTE]
+> Looking to use AIMSim for descriptor calculation or extend its functionality? `AIMSim`'s core modules for creating molecules, calculating descriptors, and comparing the results are available without support for plotting or visualization in the PyPI package `aimsim_core`.
+
 ### `conda`
@@ -84,0 +89,0 @@ `AIMSim` is also available with the `conda` package manager via:

aimsim_core.egg-info/requires.txt

 psutil
 scikit_learn
-scikit_learn_extra
 rdkit
@@ -5,0 +4,0 @@ numpy

aimsim/chemical_datastructures/molecule_set.py

@@ -68,3 +68,2 @@ """Abstraction of a data set comprising multiple Molecule objects."""
             the molecules of the MoleculeSet. Implemented methods.
-                'kmedoids': for the K-Medoids algorithm.
                 'complete_linkage', 'complete':
@@ -1001,6 +1000,2 @@ Complete linkage agglomerative hierarchical
                 similarity measure in use. Implemented clustering_methods are:
-                'kmedoids': for the K-Medoids algorithm [1].
-                    This method is useful
-                    when the molecular descriptors are continuous / Euclidean
-                    since it relies on the existence of a sensible medoid.
                 'complete_linkage', 'complete':
@@ -1018,3 +1013,2 @@ Complete linkage agglomerative hierarchical clustering [2].
                 listed below for these arguments:
-                'kmedoids': https://scikit-learn-extra.readthedocs.io/en/stable/generated/sklearn_extra.cluster.KMedoids.html
                 'complete_linkage', 'average_linkage', 'single_linkage', 'ward'
@@ -1043,3 +1037,3 @@ : https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html
         if (
-            clustering_method == "kmedoids" or clustering_method == "ward"
+            clustering_method == "ward"
         ) and self.similarity_measure.type_ == "discrete":
@@ -1054,3 +1048,3 @@ print(
             if self.similarity_measure.type_ == "continuous":
-                clustering_method = "kmedoids"
+                clustering_method = "ward"
             else:
@@ -1057,0 +1051,0 @@ clustering_method = "complete_linkage"

aimsim/ops/clustering.py

 """Operation for clustering molecules"""
 import sklearn.exceptions
 from sklearn.cluster import AgglomerativeClustering
-from sklearn_extra.cluster import KMedoids as SklearnExtraKMedoids
 
@@ -13,6 +12,2 @@
             Label for the specific algorithm used.
-            'kmedoids':
-                for the K-Medoids algorithm [1]. This method is useful
-                when the molecular descriptors are continuous / Euclidean
-                since it relies on the existence of a sensible medoid.
             'complete_linkage', 'complete':
@@ -29,3 +24,3 @@ Complete linkage agglomerative hierarchical clustering [2].
             Number of clusters.
-        model_ (sklearn.cluster.AgglomerativeClustering or sklearn_extra.cluster.KMedoids):
+        model_ (sklearn.cluster.AgglomerativeClustering):
             The clustering estimator.
@@ -55,7 +50,2 @@ labels_ (np.ndarray of shape (n_samples,)):
             clustering_method(str): Label for the specific algorithm used.
-                Supported methods are:
-                'kmedoids' for the K-Medoids algorithm [1]. This method is
-                    useful when the molecular descriptors are continuous
-                    / Euclidean since it relies on the existence of a
-                    sensible medoid.
                 'complete_linkage', 'complete' for complete linkage
@@ -71,3 +61,2 @@ agglomerative hierarchical clustering [2].
                 estimators. Refer to the following documentation page for
-                kmedoids: https://scikit-learn-extra.readthedocs.io/en/stable/generated/sklearn_extra.cluster.KMedoids.html
                 agglomerative hierarchical clustering: https://scikit-learn.org/stable/modules/generated/sklearn.cluster.AgglomerativeClustering.html
@@ -85,5 +74,3 @@
         self.n_clusters = n_clusters
-        if self.clustering_method == "kmedoids":
-            self.model_ = self._get_kmedoids_model_(**kwargs)
-        elif clustering_method in ["complete_linkage", "complete"]:
+        if clustering_method in ["complete_linkage", "complete"]:
             self.model_ = self._get_linkage_model(linkage_method="complete",
@@ -103,20 +90,2 @@ **kwargs)
 
-    def _get_kmedoids_model_(self, **kwargs):
-        """
-        Initialize a k-medoids model.
-
-        Args:
-        kwargs (dict): Keyword arguments. These are passed to the
-                estimators. Refer to the following documentation page for
-                kmedoids:
-                [https://scikit-learn-extra.readthedocs.io/en/stable/generated/sklearn_extra.cluster.KMedoids.html]
-
-        """
-        _ = kwargs.pop('metric', None)
-        return SklearnExtraKMedoids(
-            n_clusters=self.n_clusters,
-            metric="precomputed",
-            **kwargs
-        )
-
     def _get_linkage_model(self, linkage_method, **kwargs):
@@ -123,0 +92,0 @@ _ = kwargs.pop('affinity', None)

PKG-INFO

 Metadata-Version: 2.1
 Name: aimsim_core
-Version: 2.1.3
+Version: 2.2.0
 Summary: Core AIMSim molecular featurization and comparison utilities.
@@ -14,3 +14,2 @@ Home-page: https://github.com/VlachosGroup/AIMSim
 Requires-Dist: scikit_learn
-Requires-Dist: scikit_learn_extra
 Requires-Dist: rdkit
@@ -30,10 +29,12 @@ Requires-Dist: numpy
   <img alt="GitHub Repo Stars" src="https://img.shields.io/github/stars/VlachosGroup/AIMSim?style=social">
-  <img alt="Total Downloads" src="https://static.pepy.tech/personalized-badge/aimsim?period=total&units=none&left_color=grey&right_color=blue&left_text=Lifetime%20Downloads">
-  <img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dm/aimsim">
   <img alt="commits since" src="https://img.shields.io/github/commits-since/VlachosGroup/AIMSim/latest.svg">
   <img alt="PyPI" src="https://img.shields.io/pypi/v/aimsim">
   <img alt="PyPI - License" src="https://img.shields.io/github/license/VlachosGroup/AIMSim">
-  <img alt="Test Status" src="https://github.com/VlachosGroup/AIMSim/actions/workflows/run_tests.yml/badge.svg?branch=master&event=schedule">
+  <img alt="Test Status" src="https://github.com/VlachosGroup/AIMSim/actions/workflows/ci.yml/badge.svg?event=schedule">
 </p>
 
+Downloads Stats:
+ - `aimsim`: [![Downloads](https://static.pepy.tech/badge/aimsim)](https://static.pepy.tech/personalized-badge/aimsim?period=total&units=none&left_color=grey&right_color=blue&left_text=Lifetime%20Downloads)
+ - `aimsim_core`: [![Downloads](https://static.pepy.tech/badge/aimsim_core)](https://pepy.tech/project/aimsim_core?period=total&units=none&left_color=grey&right_color=blue&left_text=Lifetime%20Downloads)
+
 ## Documentation and Tutorial
@@ -82,2 +83,6 @@ [View our Online Documentation](https://vlachosgroup.github.io/AIMSim/) or try the _AIMSim_ comprehensive tutorial in your browser:
 This command also installs the required dependencies.
+
+> [!NOTE]
+> Looking to use AIMSim for descriptor calculation or extend its functionality? `AIMSim`'s core modules for creating molecules, calculating descriptors, and comparing the results are available without support for plotting or visualization in the PyPI package `aimsim_core`.
+
 ### `conda`
@@ -84,0 +89,0 @@ `AIMSim` is also available with the `conda` package manager via:

README.md

@@ -7,10 +7,12 @@ <h1 align="center">AIMSim README</h1>
   <img alt="GitHub Repo Stars" src="https://img.shields.io/github/stars/VlachosGroup/AIMSim?style=social">
-  <img alt="Total Downloads" src="https://static.pepy.tech/personalized-badge/aimsim?period=total&units=none&left_color=grey&right_color=blue&left_text=Lifetime%20Downloads">
-  <img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dm/aimsim">
   <img alt="commits since" src="https://img.shields.io/github/commits-since/VlachosGroup/AIMSim/latest.svg">
   <img alt="PyPI" src="https://img.shields.io/pypi/v/aimsim">
   <img alt="PyPI - License" src="https://img.shields.io/github/license/VlachosGroup/AIMSim">
-  <img alt="Test Status" src="https://github.com/VlachosGroup/AIMSim/actions/workflows/run_tests.yml/badge.svg?branch=master&event=schedule">
+  <img alt="Test Status" src="https://github.com/VlachosGroup/AIMSim/actions/workflows/ci.yml/badge.svg?event=schedule">
 </p>
 
+Downloads Stats:
+ - `aimsim`: [![Downloads](https://static.pepy.tech/badge/aimsim)](https://static.pepy.tech/personalized-badge/aimsim?period=total&units=none&left_color=grey&right_color=blue&left_text=Lifetime%20Downloads)
+ - `aimsim_core`: [![Downloads](https://static.pepy.tech/badge/aimsim_core)](https://pepy.tech/project/aimsim_core?period=total&units=none&left_color=grey&right_color=blue&left_text=Lifetime%20Downloads)
+
 ## Documentation and Tutorial
@@ -59,2 +61,6 @@ [View our Online Documentation](https://vlachosgroup.github.io/AIMSim/) or try the _AIMSim_ comprehensive tutorial in your browser:
 This command also installs the required dependencies.
+
+> [!NOTE]
+> Looking to use AIMSim for descriptor calculation or extend its functionality? `AIMSim`'s core modules for creating molecules, calculating descriptors, and comparing the results are available without support for plotting or visualization in the PyPI package `aimsim_core`.
+
 ### `conda`
@@ -61,0 +67,0 @@ `AIMSim` is also available with the `conda` package manager via:

requirements_core.txt

 psutil
 scikit_learn
-scikit_learn_extra
 rdkit
@@ -5,0 +4,0 @@ numpy

requirements.txt

@@ -7,3 +7,2 @@ scipy
 multiprocess>=0.70
-scikit_learn_extra
 pandas
@@ -10,0 +9,0 @@ # force pyyaml away from specific versions: https://github.com/yaml/pyyaml/issues/724

tests/test_MoleculeSet.py

@@ -1264,2 +1264,3 @@ """Test the MoleculeSet class."""
 
+    @unittest.skip(reason="kmedoids was removed, obsoleting this test")
     def test_clustering_fingerprints(self):
@@ -1294,4 +1295,4 @@ """
                             str(molecule_set.clusters_),
-                            "kmedoids",
-                            f"Expected kmedoids clustering for "
+                            "ward",
+                            f"Expected ward clustering for "
                             f"similarity: {similarity_measure}",
@@ -1298,0 +1299,0 @@ )

Alert delta unavailable

Currently unable to show alert delta for PyPI packages.

Worsened metrics

Total package byte prevSize

1283508

-0.05%

Lines of code

10434

-0.32%