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<div class="sidebar">
<p class="sidebar-title">Downloads</p>
<ul class="simple">
<li><p>Released Versions: <a class="reference external" href="http://pypi.python.org/pypi/astroML/">Python Package Index</a></p></li>
<li><p>Bleeding-edge Source: <a class="reference external" href="https://github.com/astroML/astroML">github</a></p></li>
</ul>
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<p>AstroML is a Python module for machine learning and data mining built on
<a class="reference external" href="http://numpy.scipy.org">numpy</a>,
<a class="reference external" href="http://scipy.org">scipy</a>,
<a class="reference external" href="http://scikit-learn.org">scikit-learn</a>,
<a class="reference external" href="http://matplotlib.org">matplotlib</a>,
and <a class="reference external" href="http://astropy.org">astropy</a>,
and distributed under the 3-clause BSD license.
It contains a growing library of statistical and machine learning
routines for analyzing astronomical data in Python, loaders for several open
astronomical datasets, and a large suite of examples of analyzing and
visualizing astronomical datasets.</p>
<p>The goal of astroML is to provide a community repository for fast Python
implementations of common tools and routines used for statistical
data analysis in astronomy and astrophysics, to provide a uniform and
easy-to-use interface to freely available astronomical datasets.
We hope this package will be useful to researchers and students of
astronomy. If you have an example you’d like to share, we are happy to
accept a contribution via a GitHub
<a class="reference external" href="https://help.github.com/articles/using-pull-requests">Pull Request</a>:
the code repository can be found at
<a class="reference external" href="http://github.com/astroML/astroML">http://github.com/astroML/astroML</a>.</p>
<div class="section" id="textbook">
<h2>Textbook<a class="headerlink" href="#textbook" title="Permalink to this headline">¶</a></h2>
<a class="reference external image-reference" href="https://press.princeton.edu/books/hardcover/9780691198309/statistics-data-mining-and-machine-learning-in-astronomy"><img alt="_images/text_cover_2nd.png" class="align-right" src="_images/text_cover_2nd.png" style="width: 150px;" /></a>
<p>The astroML project was started in 2012 to accompany the book <strong>Statistics,
Data Mining, and Machine Learning in Astronomy</strong>, by Željko Ivezić, Andrew
Connolly, Jacob Vanderplas, and Alex Gray, published by <a class="reference external" href="https://press.princeton.edu/books/hardcover/9780691198309/statistics-data-mining-and-machine-learning-in-astronomy">Princeton University Press</a>. The
table of contents is available <a class="reference download internal" download="" href="_downloads/1270ba6a44f327517e5e322a1ba0845e/DMbookTOC.pdf"><code class="xref download docutils literal notranslate"><span class="pre">here(pdf)</span></code></a>,
or you can preview or purchase the book on
<a class="reference external" href="https://www.amazon.com/Statistics-Mining-Machine-Learning-Astronomy/dp/0691198306/">Amazon</a>.</p>
<p>A second edition is published in December 2019. This updated edition features
new sections on deep learning methods, hierarchical Bayes modeling, and
approximate Bayesian computation. The chapters have been revised throughout
and the astroML code has been brought completely up to date.</p>
<p>Did you find a mistake or typo in the book? We maintain an up-to-date
<a class="reference external" href="https://github.com/astroml/text_errata">listing of errata</a>
in the text which you can view on GitHub. If you find a mistake
which is not yet noted on that page, please let us know via email or GitHub
pull request!</p>
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<div class="section" id="user-guide">
<h2>User Guide<a class="headerlink" href="#user-guide" title="Permalink to this headline">¶</a></h2>
<div class="toctree-wrapper compound">
<ul>
<li class="toctree-l1"><a class="reference internal" href="user_guide/index.html">User Guide</a><ul>
<li class="toctree-l2"><a class="reference internal" href="user_guide/introduction.html">1. Introduction</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/installation.html">2. Installation of astroML</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/datasets.html">3. Data Sets</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/density_estimation.html">4. Unsupervised Learning: Density Estimation</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/clustering.html">5. Unsupervised Learning: Clustering</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/correlation_functions.html">6. Two-point Correlation Functions</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/dimensionality.html">7. Unsupervised Learning: Dimensionality Reduction</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/regression.html">8. Supervised Learning: Regression</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/classification.html">9. Supervised Learning: Classification</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/time_series.html">10. Time Series Analysis</a></li>
<li class="toctree-l2"><a class="reference internal" href="modules/classes.html">11. Class reference</a></li>
<li class="toctree-l2"><a class="reference internal" href="user_guide/resources.html">12. Other Resources</a></li>
</ul>
</li>
</ul>
</div>
</div>
<div class="section" id="example-plot-gallery-and-tutorials">
<h2>Example Plot Gallery and Tutorials<a class="headerlink" href="#example-plot-gallery-and-tutorials" title="Permalink to this headline">¶</a></h2>
<div class="toctree-wrapper compound">
<ul>
<li class="toctree-l1"><a class="reference internal" href="examples/index.html">Examples</a><ul>
<li class="toctree-l2"><a class="reference internal" href="examples/index.html#general-astroml-examples">General astroML Examples</a><ul>
<li class="toctree-l3"><a class="reference internal" href="examples/learning/index.html">Machine Learning and Data Modeling</a></li>
<li class="toctree-l3"><a class="reference internal" href="examples/datasets/index.html">Data set Examples</a></li>
<li class="toctree-l3"><a class="reference internal" href="examples/algorithms/index.html">Data Processing Algorithms</a></li>
</ul>
</li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="notebooks/index.html">Notebooks</a></li>
<li class="toctree-l1"><a class="reference internal" href="book_figures_index.html">Book Figures</a></li>
</ul>
</div>
</div>
<div class="section" id="development">
<h2>Development<a class="headerlink" href="#development" title="Permalink to this headline">¶</a></h2>
<div class="toctree-wrapper compound">
<ul>
<li class="toctree-l1"><a class="reference internal" href="development/index.html">Development</a><ul>
<li class="toctree-l2"><a class="reference internal" href="development/contribution.html">Obtaining the Source Code</a></li>
<li class="toctree-l2"><a class="reference internal" href="development/contribution.html#contribution">Contribution</a></li>
<li class="toctree-l2"><a class="reference internal" href="development/authors.html">Authors</a></li>
</ul>
</li>
</ul>
</div>
</div>
<div class="section" id="citing-astroml">
<span id="id1"></span><h2>Citing astroML<a class="headerlink" href="#citing-astroml" title="Permalink to this headline">¶</a></h2>
<p>If you make use of any of these datasets, tools, or examples in a scientific
publication, please consider citing astroML. You may reference the following
paper:</p>
<ul>
<li><p><a class="reference external" href="http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6382200">Introduction to astroML: Machine learning for astrophysics</a>,
Vanderplas <em>et al</em>, proc. of CIDU, pp. 47-54, 2012.</p>
<p><strong>Recipient of the best paper award for CIDU 2012</strong></p>
<p>Bibtex entry:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="nd">@INPROCEEDINGS</span><span class="p">{</span><span class="n">astroML</span><span class="p">,</span>
<span class="n">author</span><span class="o">=</span><span class="p">{{</span><span class="n">Vanderplas</span><span class="p">},</span> <span class="n">J</span><span class="o">.</span><span class="n">T</span><span class="o">.</span> <span class="ow">and</span> <span class="p">{</span><span class="n">Connolly</span><span class="p">},</span> <span class="n">A</span><span class="o">.</span><span class="n">J</span><span class="o">.</span>
<span class="ow">and</span> <span class="p">{</span><span class="n">Ivezi</span><span class="p">{</span>\<span class="s1">'c}}, {</span><span class="se">\v</span><span class="s1"> Z}. and </span><span class="si">{Gray}</span><span class="s1">, A.},</span>
<span class="n">booktitle</span><span class="o">=</span><span class="p">{</span><span class="n">Conference</span> <span class="n">on</span> <span class="n">Intelligent</span> <span class="n">Data</span> <span class="n">Understanding</span> <span class="p">(</span><span class="n">CIDU</span><span class="p">)},</span>
<span class="n">title</span><span class="o">=</span><span class="p">{</span><span class="n">Introduction</span> <span class="n">to</span> <span class="n">astroML</span><span class="p">:</span> <span class="n">Machine</span> <span class="n">learning</span> <span class="k">for</span> <span class="n">astrophysics</span><span class="p">},</span>
<span class="n">month</span><span class="o">=</span><span class="p">{</span><span class="nb">oct</span><span class="o">.</span><span class="p">},</span>
<span class="n">pages</span><span class="o">=</span><span class="p">{</span><span class="mi">47</span> <span class="o">-</span><span class="mi">54</span><span class="p">},</span>
<span class="n">doi</span><span class="o">=</span><span class="p">{</span><span class="mf">10.1109</span><span class="o">/</span><span class="n">CIDU</span><span class="o">.</span><span class="mf">2012.6382200</span><span class="p">},</span>
<span class="n">year</span><span class="o">=</span><span class="p">{</span><span class="mi">2012</span><span class="p">}</span>
<span class="p">}</span>
</pre></div>
</div>
</li>
</ul>
<p>You may also reference the accompanying textbook:</p>
<ul>
<li><p>Statistics, Data Mining, and Machine Learning for Astronomy,
Ivezic <em>et al</em>, 2014</p>
<p>Bibtex entry:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="nd">@BOOK</span><span class="p">{</span><span class="n">astroMLText</span><span class="p">,</span>
<span class="n">title</span><span class="o">=</span><span class="p">{</span><span class="n">Statistics</span><span class="p">,</span> <span class="n">Data</span> <span class="n">Mining</span> <span class="ow">and</span> <span class="n">Machine</span> <span class="n">Learning</span> <span class="ow">in</span> <span class="n">Astronomy</span><span class="p">},</span>
<span class="n">author</span><span class="o">=</span><span class="p">{{</span><span class="n">Ivezi</span><span class="p">{</span>\<span class="s1">'c}}, {</span><span class="se">\v</span><span class="s1"> Z}. and </span><span class="si">{Connolly}</span><span class="s1">, A.J.</span>
<span class="ow">and</span> <span class="p">{</span><span class="n">Vanderplas</span><span class="p">},</span> <span class="n">J</span><span class="o">.</span><span class="n">T</span><span class="o">.</span> <span class="ow">and</span> <span class="p">{</span><span class="n">Gray</span><span class="p">},</span> <span class="n">A</span><span class="o">.</span><span class="p">},</span>
<span class="n">publisher</span><span class="o">=</span><span class="p">{</span><span class="n">Princeton</span> <span class="n">University</span> <span class="n">Press</span><span class="p">},</span>
<span class="n">location</span><span class="o">=</span><span class="p">{</span><span class="n">Princeton</span><span class="p">,</span> <span class="n">NJ</span><span class="p">},</span>
<span class="n">year</span><span class="o">=</span><span class="p">{</span><span class="mi">2014</span><span class="p">}</span>
<span class="p">}</span>
</pre></div>
</div>
</li>
</ul>
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