update docstrings

erdogant · Oct 2, 2024 · 1fb74c8 · 1fb74c8
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diff --git a/clusteval/__init__.py b/clusteval/__init__.py
@@ -12,7 +12,7 @@
 
 __author__ = 'Erdogan Tasksen'
 __email__ = '[email protected]'
-__version__ = '2.2.2'
+__version__ = '2.2.3'
 
 
 __doc__ = """

diff --git a/clusteval/clusteval.py b/clusteval/clusteval.py
@@ -885,7 +885,7 @@ def download(url, writepath):
 
         """
         r = requests.get(url, stream=True)
-        with open(writepath, "wb") as fd:
+        with open(writepath, "wb", encoding='utf8') as fd:
             for chunk in r.iter_content(chunk_size=1024):
                 fd.write(chunk)
 

diff --git a/docs/pages/doctrees/Abstract.doctree b/docs/pages/doctrees/Abstract.doctree
diff --git a/docs/pages/doctrees/Cluster Evaluation.doctree b/docs/pages/doctrees/Cluster Evaluation.doctree
diff --git a/docs/pages/doctrees/Coding quality.doctree b/docs/pages/doctrees/Coding quality.doctree
diff --git a/docs/pages/doctrees/Documentation.doctree b/docs/pages/doctrees/Documentation.doctree
diff --git a/docs/pages/doctrees/Examples.doctree b/docs/pages/doctrees/Examples.doctree
diff --git a/docs/pages/doctrees/Installation.doctree b/docs/pages/doctrees/Installation.doctree
diff --git a/docs/pages/doctrees/Plots.doctree b/docs/pages/doctrees/Plots.doctree
diff --git a/docs/pages/doctrees/Save and Load.doctree b/docs/pages/doctrees/Save and Load.doctree
diff --git a/docs/pages/doctrees/clusteval.clusteval.doctree b/docs/pages/doctrees/clusteval.clusteval.doctree
diff --git a/docs/pages/doctrees/environment.pickle b/docs/pages/doctrees/environment.pickle
diff --git a/docs/pages/doctrees/index.doctree b/docs/pages/doctrees/index.doctree
diff --git a/docs/pages/doctrees/sponsor.doctree b/docs/pages/doctrees/sponsor.doctree
diff --git a/docs/pages/html/.buildinfo b/docs/pages/html/.buildinfo
@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: cfbe0f1b079f5269981f4b10ebce1462
+config: bf6540d3c34122f494df10e99296f5a7
 tags: 645f666f9bcd5a90fca523b33c5a78b7
diff --git a/docs/pages/html/Abstract.html b/docs/pages/html/Abstract.html
@@ -1,20 +1,24 @@
 <!DOCTYPE html>
-<html class="writer-html5" lang="en" >
+<html class="writer-html5" lang="en" data-content_root="./">
 <head>
-  <meta charset="utf-8" /><meta name="generator" content="Docutils 0.18.1: http://docutils.sourceforge.net/" />
+  <meta charset="utf-8" /><meta name="viewport" content="width=device-width, initial-scale=1" />
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
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+        <script src="_static/jquery.js?v=5d32c60e"></script>
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@@ -34,7 +38,7 @@
             clusteval
           </a>
               <div class="version">
-                2.2.0
+                2.2.3
               </div>
 <div role="search">
   <form id="rtd-search-form" class="wy-form" action="search.html" method="get">
@@ -124,19 +128,19 @@
            <div itemprop="articleBody">
 
   <section id="background">
-<h1>Background<a class="headerlink" href="#background" title="Permalink to this heading"></a></h1>
+<h1>Background<a class="headerlink" href="#background" title="Link to this heading"></a></h1>
 <p>Clustering is an unsupervised machine learning approach where the aim i to determine “natural” or “data-driven” groups in the data without using apriori knowledge about labels or categories. The challenges in unsupervised clustering is that it always produces a partitioning of the samples since each clustering method implicitly impose a structure on the data. The question is: What is a “good” clustering? We need to evaluate the results based on the <strong>clustering tendency</strong>, <strong>number of clusters</strong> and the <strong>clustering quality</strong>.</p>
 </section>
 <section id="aim">
-<h1>Aim<a class="headerlink" href="#aim" title="Permalink to this heading"></a></h1>
+<h1>Aim<a class="headerlink" href="#aim" title="Link to this heading"></a></h1>
 <p><code class="docutils literal notranslate"><span class="pre">clusteval</span></code> is a Python package that is developed to evaluate the <strong>clustering tendency</strong>, <strong>number of clusters</strong> and <strong>clustering quality</strong>. <code class="docutils literal notranslate"><span class="pre">clusteval</span></code> returns the cluster labels for the optimal number of cluster that produces the best partitioning of the samples. The following evaluation strategies are implemented: <strong>silhouette</strong>, <strong>dbindex</strong>, and <strong>derivative</strong> which can be used in combination with <strong>agglomerative</strong> and <strong>kmeans</strong> clustering. In addition <strong>dbscan</strong> and <strong>hdbscan</strong> is implemented for which an internal gridsearch scheme will determine the best partitioning.</p>
 <div class="admonition note">
 <p class="admonition-title">Note</p>
 <p>The <code class="docutils literal notranslate"><span class="pre">clusteval</span></code> library gridsearches across the number of clusters, and method-parameters to determine the optimal number of clusters given the input dataset.</p>
 </div>
 </section>
 <section id="quickstart">
-<h1>Quickstart<a class="headerlink" href="#quickstart" title="Permalink to this heading"></a></h1>
+<h1>Quickstart<a class="headerlink" href="#quickstart" title="Link to this heading"></a></h1>
 <p>A quick example how to learn a model on a given dataset.</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># Import library</span>
 <span class="kn">from</span> <span class="nn">clusteval</span> <span class="kn">import</span> <span class="n">clusteval</span>