rebuilding site Mon 27 Jul 2020 12:15:43 WEST

Author: rgommers

404/index.html

@@ -15,14 +15,14 @@
 <script async src='https://www.google-analytics.com/analytics.js'></script>
 
 
-<meta name="description" content="The fundamental package for scientific computing with Python" />
+<meta name="description" content="Why NumPy? Powerful n-dimensional arrays. Numerical computing tools. Interoperable. Performant. Open source." />
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <meta http-equiv="x-ua-compatible" content="ie=edge">
   <title>NumPy</title>
 
 <link href="https://fonts.googleapis.com/css?family=Lato:400,900" rel="stylesheet">
-<link rel="stylesheet" type="text/css" href="/css/style.min.cf5efcb8a6e49b945af419cd8b208a5ae87eb3015995b9afc61218743a0fed3e.css" integrity="sha256-z178uKbkm5Ra9BnNiyCKWuh&#43;swFZlbmvxhIYdDoP7T4=">
+<link rel="stylesheet" type="text/css" href="/css/style.min.90e79d931dd7cbbc3a657115e4b0d9b131892ce20e05d1f3176a3dfbe94ef1c4.css" integrity="sha256-kOedkx3Xy7w6ZXEV5LDZsTGJLOIOBdHzF2o9&#43;&#43;lO8cQ=">
 <link rel="stylesheet" type="text/css" href="/css/icons.css">
 
 <link rel="icon" type="image/png" href="/images/favicon.png" />
@@ -151,6 +151,7 @@ <h5 class="subtitle is-5 is-muted"></h5>
             </div>
         </div>
         <p>Oops! You&rsquo;ve reached a dead end.</p>
+
 <p>If you think something should be here, you can <a href="https://github.com/numpy/numpy.org/issues">open an issue</a> on GitHub.</p>
 
     </div>

about/index.html

@@ -15,14 +15,14 @@
 <script async src='https://www.google-analytics.com/analytics.js'></script>
 
 
-<meta name="description" content="The fundamental package for scientific computing with Python" />
+<meta name="description" content="Why NumPy? Powerful n-dimensional arrays. Numerical computing tools. Interoperable. Performant. Open source." />
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <meta http-equiv="x-ua-compatible" content="ie=edge">
   <title>NumPy</title>
 
 <link href="https://fonts.googleapis.com/css?family=Lato:400,900" rel="stylesheet">
-<link rel="stylesheet" type="text/css" href="/css/style.min.cf5efcb8a6e49b945af419cd8b208a5ae87eb3015995b9afc61218743a0fed3e.css" integrity="sha256-z178uKbkm5Ra9BnNiyCKWuh&#43;swFZlbmvxhIYdDoP7T4=">
+<link rel="stylesheet" type="text/css" href="/css/style.min.90e79d931dd7cbbc3a657115e4b0d9b131892ce20e05d1f3176a3dfbe94ef1c4.css" integrity="sha256-kOedkx3Xy7w6ZXEV5LDZsTGJLOIOBdHzF2o9&#43;&#43;lO8cQ=">
 <link rel="stylesheet" type="text/css" href="/css/icons.css">
 
 <link rel="icon" type="image/png" href="/images/favicon.png" />
@@ -150,11 +150,18 @@ <h5 class="subtitle is-5 is-muted"></h5>
                 <div class="divider"></div>
             </div>
         </div>
-        <p><em>Some information about the NumPy project and community</em></p>
+        
+
+<p><em>Some information about the NumPy project and community</em></p>
+
 <p>NumPy is an open source project aiming to enable numerical computing with Python. It was created in 2005, building on the early work of the Numerical and Numarray libraries. NumPy will always be 100% open source software, free for all to use and released under the liberal terms of the <a href="https://github.com/numpy/numpy/blob/master/LICENSE.txt">modified BSD license</a>.</p>
+
 <p>NumPy is developed in the open on GitHub, through the consensus of the NumPy and wider scientific Python community. For more information on our governance approach, please see our <a href="https://www.numpy.org/devdocs/dev/governance/index.html">Governance Document</a>.</p>
+
 <h2 id="steering-council">Steering Council</h2>
+
 <p>The role of the NumPy Steering Council is to ensure, through working with and serving the broader NumPy community, the long-term well-being of the project, both technically and as a community. The NumPy Steering Council currently consists of the following members (in alphabetical order):</p>
+
 <ul>
 <li>Sebastian Berg</li>
 <li>Jaime Fernández del Río</li>
@@ -169,14 +176,19 @@ <h2 id="steering-council">Steering Council</h2>
 <li>Stéfan van der Walt</li>
 <li>Eric Wieser</li>
 </ul>
+
 <p>Emeritus:</p>
+
 <ul>
 <li>Travis Oliphant (project founder, 2005-2012)</li>
 <li>Alex Griffing (2015-2017)</li>
 <li>Marten van Kerkwijk (2017-2019)</li>
 </ul>
+
 <h2 id="teams">Teams</h2>
+
 <p>The NumPy project is growing; we have teams for</p>
+
 <ul>
 <li>code</li>
 <li>documentation</li>
@@ -185,8 +197,11 @@ <h2 id="teams">Teams</h2>
 <li>funding and grants</li>
 <li>admin</li>
 </ul>
+
 <p>See the <a href="/gallery/team.html">Team</a> page for individual team members.</p>
+
 <h2 id="sponsors">Sponsors</h2>
+
 <p>NumPy receives direct funding from the following sources:
 <div class="sponsor-images">
     <a href="https://www.moore.org">
@@ -231,7 +246,9 @@ <h2 id="sponsors">Sponsors</h2>
         }
     }
 </style></p>
+
 <h2 id="institutional-partners">Institutional Partners</h2>
+
 <p>Institutional Partners are organizations that support the project by employing people that contribute to NumPy as part of their job. Current Institutional Partners include:
 <div class="partner-images">
     <a href="https://www.berkeley.edu">
@@ -270,10 +287,15 @@ <h2 id="institutional-partners">Institutional Partners</h2>
         }
     }
 </style></p>
+
 <h2 id="donate">Donate</h2>
+
 <p>If you have found NumPy useful in your work, research, or company, please consider a donation to the project commensurate with your resources. Any amount helps! All donations will be used strictly to fund the development of NumPy’s open source software, documentation, and community.</p>
-<p>NumPy is a Sponsored Project of NumFOCUS, a 501(c)(3) nonprofit charity in the United States. NumFOCUS provides NumPy with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit <a href="https://numfocus.org">numfocus.org</a> for more information.</p>
+
+<p>NumPy is a Sponsored Project of NumFOCUS, a 501&copy;(3) nonprofit charity in the United States. NumFOCUS provides NumPy with fiscal, legal, and administrative support to help ensure the health and sustainability of the project. Visit <a href="https://numfocus.org">numfocus.org</a> for more information.</p>
+
 <p>Donations to NumPy are managed by <a href="https://numfocus.org">NumFOCUS</a>. For donors in the United States, your gift is tax-deductible to the extent provided by law. As with any donation, you should consult with your tax advisor about your particular tax situation.</p>
+
 <p>NumPy&rsquo;s Steering Council will make the decisions on how to best use any funds received. Technical and infrastructure priorities are documented on the <a href="https://www.numpy.org/neps/index.html#roadmap">NumPy Roadmap</a>.
 <div class="numfocus">
     <a href="https://numfocus.org/donate-to-numpy">

arraycomputing/index.html

@@ -15,14 +15,14 @@
 <script async src='https://www.google-analytics.com/analytics.js'></script>
 
 
-<meta name="description" content="The fundamental package for scientific computing with Python" />
+<meta name="description" content="Why NumPy? Powerful n-dimensional arrays. Numerical computing tools. Interoperable. Performant. Open source." />
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <meta http-equiv="x-ua-compatible" content="ie=edge">
   <title>NumPy</title>
 
 <link href="https://fonts.googleapis.com/css?family=Lato:400,900" rel="stylesheet">
-<link rel="stylesheet" type="text/css" href="/css/style.min.cf5efcb8a6e49b945af419cd8b208a5ae87eb3015995b9afc61218743a0fed3e.css" integrity="sha256-z178uKbkm5Ra9BnNiyCKWuh&#43;swFZlbmvxhIYdDoP7T4=">
+<link rel="stylesheet" type="text/css" href="/css/style.min.90e79d931dd7cbbc3a657115e4b0d9b131892ce20e05d1f3176a3dfbe94ef1c4.css" integrity="sha256-kOedkx3Xy7w6ZXEV5LDZsTGJLOIOBdHzF2o9&#43;&#43;lO8cQ=">
 <link rel="stylesheet" type="text/css" href="/css/icons.css">
 
 <link rel="icon" type="image/png" href="/images/favicon.png" />
@@ -154,25 +154,31 @@ <h5 class="subtitle is-5 is-muted"></h5>
 in various contemporary data science and analytics applications such as data
 visualization, digital signal processing, image processing, bioinformatics,
 machine learning, AI, and several others.</em></p>
+
 <p>Large scale data manipulation and transformation depends on efficient,
 high-performance array computing. The language of choice for data analytics,
 machine learning, and productive numerical computing is <strong>Python.</strong></p>
+
 <p><strong>Num</strong>erical <strong>Py</strong>thon or NumPy is its de-facto standard Python programming
 language library that supports large, multi-dimensional arrays and matrices,
 and comes with a vast collection of high-level mathematical functions to
 operate on these arrays.</p>
+
 <p>Since the launch of NumPy in 2006, Pandas appeared on the landscape in 2008,
 and it was not until a couple of years ago that several array computing
 libraries showed up in succession, crowding the array computing landscape.
 Many of these newer libraries mimic NumPy-like features and capabilities, and
 pack newer algorithms and features geared towards machine learning and artificial intelligence applications.</p>
+
 <p><img
-src="/images/content_images/array_c_landscape.png"
-alt="arraycl"
-title="Array Computing Landscape"></p>
+  src="/images/content_images/array_c_landscape.png"
+  alt="arraycl"
+  title="Array Computing Landscape"></p>
+
 <p><strong>Array computing</strong> is based on <strong>arrays</strong> data structures. <em>Arrays</em> are used
 to organize vast amounts of data such that a related set of values can be easily
 sorted, searched, mathematically manipulated, and transformed easily and quickly.</p>
+
 <p>Array computing is <em>unique</em> as it involves operating on the data array <em>at
 once</em>. What this means is that any array operation applies to an entire set of
 values in one shot. This vectorized approach provides speed and simplicity by

case-studies/blackhole-image/index.html

@@ -15,14 +15,14 @@
 <script async src='https://www.google-analytics.com/analytics.js'></script>
 
 
-<meta name="description" content="The fundamental package for scientific computing with Python" />
+<meta name="description" content="Why NumPy? Powerful n-dimensional arrays. Numerical computing tools. Interoperable. Performant. Open source." />
 <meta charset="utf-8">
 <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
 <meta http-equiv="x-ua-compatible" content="ie=edge">
   <title>NumPy</title>
 
 <link href="https://fonts.googleapis.com/css?family=Lato:400,900" rel="stylesheet">
-<link rel="stylesheet" type="text/css" href="/css/style.min.cf5efcb8a6e49b945af419cd8b208a5ae87eb3015995b9afc61218743a0fed3e.css" integrity="sha256-z178uKbkm5Ra9BnNiyCKWuh&#43;swFZlbmvxhIYdDoP7T4=">
+<link rel="stylesheet" type="text/css" href="/css/style.min.90e79d931dd7cbbc3a657115e4b0d9b131892ce20e05d1f3176a3dfbe94ef1c4.css" integrity="sha256-kOedkx3Xy7w6ZXEV5LDZsTGJLOIOBdHzF2o9&#43;&#43;lO8cQ=">
 <link rel="stylesheet" type="text/css" href="/css/icons.css">
 
 <link rel="icon" type="image/png" href="/images/favicon.png" />
@@ -150,19 +150,24 @@ <h5 class="subtitle is-5 is-muted"></h5>
                 <div class="divider"></div>
             </div>
         </div>
-        <figure>
+        
+
+<figure>
     <img src="/images/content_images/cs/blackhole.jpg"
          alt="black hole image"/> <figcaption>
             <p><strong>Black Hole M87</strong>
                     <a href="https://www.jpl.nasa.gov/images/universe/20190410/blackhole20190410.jpg"><em>(Image Credits: Event Horizon Telescope Collaboration)</em></a></p>
         </figcaption>
 </figure>
 
+
 <blockquote cite="https://www.youtube.com/watch?v=BIvezCVcsYs">
     <p>Imaging the M87 Black Hole is like trying to see something that is by definition impossible to see.</p>
     <footer align="right">—Katie Bouman, <cite>Assistant Professor, Computing & Mathematical Sciences, Caltech</cite></footer>
 </blockquote>
+
 <h2 id="about-the-event-horizon-telescope">About The Event Horizon Telescope</h2>
+
 <p>The <a href="https://eventhorizontelescope.org">Event Horizon telescope (EHT)</a>, is an
 array of eight ground-based radio telescopes forming a computational telescope
 the size of the earth, designed to study extreme objects in the
@@ -172,59 +177,59 @@ <h2 id="about-the-event-horizon-telescope">About The Event Horizon Telescope</h2
 Using this technique, the EHT is able to achieve an angular resolution of
 <a href="https://eventhorizontelescope.org/press-release-april-10-2019-astronomers-capture-first-image-black-hole">20 micro-arcseconds</a> — enough to read a newspaper in New York
 from a sidewalk café in Paris!</p>
+
 <h3 id="key-goals-and-results">Key Goals and Results</h3>
+
 <ul>
-<li>
-<p><strong>A New View of the Universe:</strong>
+<li><p><strong>A New View of the Universe:</strong>
 The EHT is an exciting new tool for studying the most extreme objects in the
 universe. The EHT&rsquo;s groundbreaking image was published 100 years
 after <a href="https://en.wikipedia.org/wiki/Eddington_experiment">Sir Arthur Eddington&rsquo;s experiment</a> yielded the first
-observational evidence in support of Einstein&rsquo;s theory of general relativity.</p>
-</li>
-<li>
-<p><strong>Investigating Black Holes:</strong>
+observational evidence in support of Einstein&rsquo;s theory of general relativity.</p></li>
+
+<li><p><strong>Investigating Black Holes:</strong>
 The EHT&rsquo;s first image focuses on the supermassive black hole at the center
 of the galaxy Messier 87 (M87), located in the Virgo galaxy cluster.
 This black hole resides approximately 55 million light-years from Earth and
 has a mass equal  to 6.5 billion times that of the Sun. It has been a
 subject of astronomical study for
 <a href="https://www.jpl.nasa.gov/news/news.php?feature=7385">over a 100 years</a>.
 Black holes have long been the object of intense study but the EHT provides
-the first direct visual evidence of these extreme phenomena.</p>
-</li>
-<li>
-<p><strong>Comparing Observations to Theory:</strong>
+the first direct visual evidence of these extreme phenomena.</p></li>
+
+<li><p><strong>Comparing Observations to Theory:</strong>
 Based on Einstein’s general theory of relativity, scientists expected
 to see a dark region similar to a shadow, caused by the gravitational bending
 and capture of light by the event horizon. By studying this shadow
 scientists could measure the enormous mass of M87’s central supermassive
-black hole.</p>
-</li>
+black hole.</p></li>
 </ul>
+
 <h3 id="the-challenges">The Challenges</h3>
+
 <ul>
-<li>
-<p><strong>Scale</strong></p>
+<li><p><strong>Scale</strong></p>
+
 <p>The observations from Event Horizon Telescope (EHT) present challenges for
 existing data processing tools, arising from the rapid atmospheric phase
-fluctuations, wide recording bandwidth, and highly heterogeneous array.</p>
-</li>
-<li>
-<p><strong>Calibration and Correlation</strong></p>
+fluctuations, wide recording bandwidth, and highly heterogeneous array.</p></li>
+
+<li><p><strong>Calibration and Correlation</strong></p>
+
 <p>Besides scheduling all of these coordinated observations of EHT, reducing
 the overall volume and complexity of data to aid analysis is a really hard
 problem to solve. To put things in perspective, EHT generates over 350
 Terabytes worth of observed data per day, stored on high-performance
-helium filled hard drives.</p>
-</li>
-<li>
-<p><strong>Image Reconstruction</strong></p>
+helium filled hard drives.</p></li>
+
+<li><p><strong>Image Reconstruction</strong></p>
+
 <p>How are the calibrated data processed to produce an image of something that
 has never before been directly imaged? How can scientists be confident
 that the image is correct? These are some of the challenges overcome in
-the analysis to produce the image.</p>
-</li>
+the analysis to produce the image.</p></li>
 </ul>
+
 <figure class="csfigcaption">
     <img src="/images/content_images/cs/dataprocessbh.png"
          alt="data pipeline"/> <figcaption>
@@ -233,7 +238,9 @@ <h3 id="the-challenges">The Challenges</h3>
         </figcaption>
 </figure>
 
-<h2 id="numpys-role-in-black-hole-imaging">NumPy’s Role in Black Hole Imaging</h2>
+
+<h2 id="numpy-s-role-in-black-hole-imaging">NumPy’s Role in Black Hole Imaging</h2>
+
 <p>While collecting, curating, and processing the data from the EHT facilities
 represents a monumental challenge, it is only the first step in generating
 an image from the data.
@@ -253,33 +260,39 @@ <h2 id="numpys-role-in-black-hole-imaging">NumPy’s Role in Black Hole Imaging<
 collaboration to modern scientific discovery and illustrates the role that
 the scientific Python ecosystem plays in supporting scientific advancement
 through collaborative data analysis.</p>
+
 <figure class="fig-center">
     <img src="/images/content_images/cs/bh_numpy_role.png"
          alt="role of numpy"/> <figcaption>
             <p><strong>The role of NumPy in Black Hole imaging</strong></p>
         </figcaption>
 </figure>
 
+
 <p>For example, the <a href="https://github.com/achael/eht-imaging"><code>eht-imaging</code></a> Python package provides tools for
 simulating and performing image reconstruction on VLBI data.
 NumPy is at the core of array data processing used
 in this package as illustrated by the partial software
 dependency chart below.</p>
+
 <figure class="fig-center">
     <img src="/images/content_images/cs/ehtim_numpy.png"
          alt="ehtim dependency map highlighting numpy"/> <figcaption>
             <p><strong>Software dependency chart of ehtim package highlighting NumPy</strong></p>
         </figcaption>
 </figure>
 
+
 <p>Besides NumPy, many other packages such as
 <a href="https://www.scipy.org">SciPy</a> and <a href="https://pandas.io">Pandas</a> were used in the
 data processing pipeline for imaging the black hole.
 The standard astronomical file formats and time/coordinate transformations
 were handled by <a href="https://www.astropy.org/">Astropy</a> while <a href="https://matplotlib.org/">Matplotlib</a> was used
 in visualizing data throughout the analysis pipeline, including the generation
 of the final image of the black hole.</p>
+
 <h2 id="summary">Summary</h2>
+
 <p>NumPy enabled researchers to manipulate large numerical datasets through its
 efficient and generic n-dimensional array, providing a foundation for the
 software used to generate the first ever image of
@@ -291,6 +304,7 @@ <h2 id="summary">Summary</h2>
 They used
 innovative algorithms and data processing techniques improving upon existing
 astronomical models to help unfold some of the mysteries of the universe.</p>
+
 <figure class="fig-center">
     <img src="/images/content_images/cs/numpy_bh_benefits.png"
          alt="numpy benefits"/> <figcaption>