[ci skip] Merge pull request #4 from IsolationKernel/develop

fix pip install and readme 46c0587

Author: xhan97

README.md

@@ -7,6 +7,18 @@
 
 <!-- <div style="clear: both;"></div> -->
 
+![Python](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue)
+[![PyPI](https://img.shields.io/pypi/v/pyikt)](https://pypi.org/project/pyikt/)
+[![codecov](https://codecov.io/gh/IsolationKernel/pyikt/branch/master/graph/badge.svg)](https://codecov.io/gh/IsolationKernel/pyikt)
+[![Build status](https://github.com/IsolationKernel/pyikt/actions/workflows/python-app.yml/badge.svg)](https://github.com/IsolationKernel/pyikt/actions/workflows/python-app.yml/badge.svg)
+[![Project Status: Active](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
+[![Maintenance](https://img.shields.io/badge/Maintained%3F-yes-green.svg)](https://github.com/IsolationKernel/pyikt/graphs/commit-activity)
+[![Downloads](https://static.pepy.tech/badge/pyikt)](https://pepy.tech/project/pyikt)
+[![Downloads](https://static.pepy.tech/badge/pyikt/month)](https://pepy.tech/project/pyikt)
+[![License](https://img.shields.io/github/license/IsolationKernel/pyikt)](https://github.com/IsolationKernel/pyikt/blob/master/LICENSE)
+
+
+
 ## About The Project
 
 **PyIKT** (Python for Isolation Kernel Toolkit) is an intuitive Python library designed for a variety of machine learning tasks including kernel similarity calculation, anomaly detection, clustering, and change detection—all powered by the innovative **Isolation Kernel (IK)** . Isolation Kernel is a data-dependent kernel that measures similarity by isolating data points using an isolation mechanism. It uniquely adapts to the data distribution, with the property that points in sparse regions are more similar than those in dense regions. Notably, it requires no learning or closed-form expression, making it efficient and scalable.
@@ -49,6 +61,19 @@ For more installation options, including dependencies and additional features, c
 
 ---
 
+## Example
+
+```py
+# Anomaly Detection using inne.
+import numpy as np
+from pyikt.anomaly import INNE
+X = np.array([[-1.1, 0.2], [0.3, 0.5], [0.5, 1.1], [100, 90]])
+clf = INNE(contamination=0.25).fit(X)
+clf.predict([[0.1, 0.3], [0, 0.7], [90, 85]])
+```
+
+---
+
 ## Implemented Algorithms
 
 #### Summary
@@ -138,7 +163,7 @@ Explore our extensive list of examples and tutorials (English and Spanish) to ge
 
 Primarily, PyIKT development consists of adding and creating new *Forecasters*, new validation strategies, or improving the performance of the current code. However, there are many other ways to contribute:
 
-- Submit a bug report or feature request on [GitHub Issues](https://github.com/pyikt/pyikt/issues).
+- Submit a bug report or feature request on [GitHub Issues](https://github.com/IsolationKernel/pyikt/issues).
 - Contribute a Jupyter notebook to our [examples](./examples/examples_english.html).
 - Write [unit or integration tests](https://docs.pytest.org/en/latest/) for our project.
 - Answer questions on our issues, Stack Overflow, and elsewhere.
@@ -173,4 +198,4 @@ url = {https://github.com/IsolationKernel/pyikt}
 
 ## License
 
-[BSD-3-Clause License](https://github.com/pyikt/pyikt/blob/master/LICENSE)
+[BSD-3-Clause License](https://github.com/IsolationKernel/pyikt/blob/master/LICENSE)

index.html

@@ -573,6 +573,15 @@
     </span>
   </a>
 
+</li>
+      
+        <li class="md-nav__item">
+  <a href="#example" class="md-nav__link">
+    <span class="md-ellipsis">
+      Example
+    </span>
+  </a>
+  
 </li>
 
         <li class="md-nav__item">
@@ -1876,6 +1885,15 @@ <h1>Welcome to PyIKT</h1>
 
 <!-- <div style="clear: both;"></div> -->
 
+<p><img alt="Python" src="https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12-blue" />
+<a href="https://pypi.org/project/pyikt/"><img alt="PyPI" src="https://img.shields.io/pypi/v/pyikt" /></a>
+<a href="https://codecov.io/gh/IsolationKernel/pyikt"><img alt="codecov" src="https://codecov.io/gh/IsolationKernel/pyikt/branch/master/graph/badge.svg" /></a>
+<a href="https://github.com/IsolationKernel/pyikt/actions/workflows/python-app.yml/badge.svg"><img alt="Build status" src="https://github.com/IsolationKernel/pyikt/actions/workflows/python-app.yml/badge.svg" /></a>
+<a href="https://www.repostatus.org/#active"><img alt="Project Status: Active" src="https://www.repostatus.org/badges/latest/active.svg" /></a>
+<a href="https://github.com/IsolationKernel/pyikt/graphs/commit-activity"><img alt="Maintenance" src="https://img.shields.io/badge/Maintained%3F-yes-green.svg" /></a>
+<a href="https://pepy.tech/project/pyikt"><img alt="Downloads" src="https://static.pepy.tech/badge/pyikt" /></a>
+<a href="https://pepy.tech/project/pyikt"><img alt="Downloads" src="https://static.pepy.tech/badge/pyikt/month" /></a>
+<a href="https://github.com/IsolationKernel/pyikt/blob/master/LICENSE"><img alt="License" src="https://img.shields.io/github/license/IsolationKernel/pyikt" /></a></p>
 <h2 id="about-the-project">About The Project<a class="headerlink" href="#about-the-project" title="Permanent link">&para;</a></h2>
 <p><strong>PyIKT</strong> (Python for Isolation Kernel Toolkit) is an intuitive Python library designed for a variety of machine learning tasks including kernel similarity calculation, anomaly detection, clustering, and change detection—all powered by the innovative <strong>Isolation Kernel (IK)</strong> . Isolation Kernel is a data-dependent kernel that measures similarity by isolating data points using an isolation mechanism. It uniquely adapts to the data distribution, with the property that points in sparse regions are more similar than those in dense regions. Notably, it requires no learning or closed-form expression, making it efficient and scalable.</p>
 <hr />
@@ -1905,6 +1923,15 @@ <h2 id="installation-dependencies">Installation &amp; Dependencies<a class="head
 </code></pre></div>
 <p>For more installation options, including dependencies and additional features, check out our <a href="./quick-start/how-to-install.html">Installation Guide</a>.</p>
 <hr />
+<h2 id="example">Example<a class="headerlink" href="#example" title="Permanent link">&para;</a></h2>
+<div class="language-py highlight"><pre><span></span><code><span class="c1"># Anomaly Detection using inne.</span>
+<span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
+<span class="kn">from</span><span class="w"> </span><span class="nn">pyikt.anomaly</span><span class="w"> </span><span class="kn">import</span> <span class="n">INNE</span>
+<span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="o">-</span><span class="mf">1.1</span><span class="p">,</span> <span class="mf">0.2</span><span class="p">],</span> <span class="p">[</span><span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">],</span> <span class="p">[</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">1.1</span><span class="p">],</span> <span class="p">[</span><span class="mi">100</span><span class="p">,</span> <span class="mi">90</span><span class="p">]])</span>
+<span class="n">clf</span> <span class="o">=</span> <span class="n">INNE</span><span class="p">(</span><span class="n">contamination</span><span class="o">=</span><span class="mf">0.25</span><span class="p">)</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
+<span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">([[</span><span class="mf">0.1</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">],</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mf">0.7</span><span class="p">],</span> <span class="p">[</span><span class="mi">90</span><span class="p">,</span> <span class="mi">85</span><span class="p">]])</span>
+</code></pre></div>
+<hr />
 <h2 id="implemented-algorithms">Implemented Algorithms<a class="headerlink" href="#implemented-algorithms" title="Permanent link">&para;</a></h2>
 <h4 id="summary">Summary<a class="headerlink" href="#summary" title="Permanent link">&para;</a></h4>
 <table>
@@ -2186,7 +2213,7 @@ <h2 id="examples-and-tutorials">Examples and tutorials<a class="headerlink" href
 <h2 id="how-to-contribute">How to contribute<a class="headerlink" href="#how-to-contribute" title="Permanent link">&para;</a></h2>
 <p>Primarily, PyIKT development consists of adding and creating new <em>Forecasters</em>, new validation strategies, or improving the performance of the current code. However, there are many other ways to contribute:</p>
 <ul>
-<li>Submit a bug report or feature request on <a href="https://github.com/pyikt/pyikt/issues">GitHub Issues</a>.</li>
+<li>Submit a bug report or feature request on <a href="https://github.com/IsolationKernel/pyikt/issues">GitHub Issues</a>.</li>
 <li>Contribute a Jupyter notebook to our <a href="./examples/examples_english.html">examples</a>.</li>
 <li>Write <a href="https://docs.pytest.org/en/latest/">unit or integration tests</a> for our project.</li>
 <li>Answer questions on our issues, Stack Overflow, and elsewhere.</li>
@@ -2211,7 +2238,7 @@ <h2 id="citation">Citation<a class="headerlink" href="#citation" title="Permanen
 </code></pre></div>
 <hr />
 <h2 id="license">License<a class="headerlink" href="#license" title="Permanent link">&para;</a></h2>
-<p><a href="https://github.com/pyikt/pyikt/blob/master/LICENSE">BSD-3-Clause License</a></p>
+<p><a href="https://github.com/IsolationKernel/pyikt/blob/master/LICENSE">BSD-3-Clause License</a></p>
 
 
 

quick-start/how-to-install.html

@@ -1777,7 +1777,7 @@ <h2 id="basic-installation"><strong>Basic installation</strong><a class="headerl
 <div class="language-bash highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span>pyikt
 </code></pre></div>
 <p>Specific version:</p>
-<div class="language-bash highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span><span class="nv">pyikt</span><span class="o">==</span><span class="m">0</span>.01.0
+<div class="language-bash highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span><span class="nv">pyikt</span><span class="o">==</span><span class="m">0</span>.1.0
 </code></pre></div>
 <p>Latest (unstable):</p>
 <div class="language-bash highlight"><pre><span></span><code>pip<span class="w"> </span>install<span class="w"> </span>git+https://github.com/pyikt/pyikt@master
@@ -1788,7 +1788,6 @@ <h2 id="basic-installation"><strong>Basic installation</strong><a class="headerl
 <li>pandas&gt;=1.5</li>
 <li>tqdm&gt;=4.57</li>
 <li>scikit-learn&gt;=1.2</li>
-<li>optuna&gt;=2.10</li>
 <li>joblib&gt;=1.1</li>
 <li>numba&gt;=0.59</li>
 </ul>

quick-start/how-to-install.md

@@ -15,7 +15,7 @@ pip install pyikt
 Specific version:
 
 ```bash
-pip install pyikt==0.01.0
+pip install pyikt==0.1.0
 ```
 
 Latest (unstable):
@@ -30,6 +30,5 @@ The following dependencies are installed with the default installation:
 + pandas>=1.5
 + tqdm>=4.57
 + scikit-learn>=1.2
-+ optuna>=2.10
 + joblib>=1.1
 + numba>=0.59

search/search_index.json

@@ -2,106 +2,106 @@
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
     <url>
          <loc>https://isolationkernel.github.io/pyikt/index.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/anomaly/idkd.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/anomaly/iforest.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/anomaly/inne.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/cluster/idkc.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/cluster/ikahc.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/cluster/pskc.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/graph/IsoGraphKernel.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/graph/ikgod.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/group/ikgad.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/kernel/isolation_dis_kernel.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/kernel/isolation_kernel.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/stream/icid.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/stream/streakhc.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/time_series/iktod.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/trajectory/ikat.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/trajectory/tidkc.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/api/trajectory/data_loader/sheep_dogs.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/authors/authors.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/contributing/contribution.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/examples/examples_english.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/faq/table-of-contents.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/quick-start/how-to-install.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/releases/releases.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/user_guides/inne.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
     <url>
          <loc>https://isolationkernel.github.io/pyikt/user_guides/table-of-contents.html</loc>
-         <lastmod>2025-03-02</lastmod>
+         <lastmod>2025-03-05</lastmod>
     </url>
 </urlset>