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<?xml version="1.0" encoding="utf-8"?>
<?xml-stylesheet type="text/xsl" href="assets/xml/rss.xsl" media="all"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Biophysics and Beer</title><link>https://mglerner.github.io/</link><description>Just what it sounds like.</description><atom:link href="https://mglerner.github.io/rss.xml" rel="self" type="application/rss+xml"></atom:link><language>en</language><copyright>Contents © 2020 <a href="mailto:mglerner@protonmail.com">Michael G. Lerner</a> </copyright><lastBuildDate>Fri, 20 Mar 2020 22:21:37 GMT</lastBuildDate><generator>Nikola (getnikola.com)</generator><docs>http://blogs.law.harvard.edu/tech/rss</docs><item><title>Social Distancing and Hospital Capacity for Coronavirus</title><link>https://mglerner.github.io/posts/social-distancing-and-hospital-capacity-for-coronavirus.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
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<h2 id="Social-Distancing-and-Hospital-Capacity-for-coronavirus">Social Distancing and Hospital Capacity for coronavirus<a class="anchor-link" href="https://mglerner.github.io/posts/social-distancing-and-hospital-capacity-for-coronavirus.html#Social-Distancing-and-Hospital-Capacity-for-coronavirus">¶</a></h2><p>There was a <strong>great</strong> Washington Post <a href="https://www.washingtonpost.com/graphics/2020/world/corona-simulator/">article</a> on social distancing. It comes with simulations to show you the effect of different measures, and I think it's fantastic #SciCom. I want to talk it over with my kids, but I want to be ready for them to ask questions like "what if we did (some cool other idea) for social distancing?" I also <a href="https://twitter.com/mglerner/status/1239740748062511106">thought this would be useful for classes</a> like intro physics, data science, computational modeling, etc., especially if those classes can team up with humanities, arts, etc. So, I want to have some Python code to replicate it and play with.</p>
<p>I put the Python code on <a href="https://github.com/mglerner/covid">github</a> so that it's easy to grab and play with. I like having notebooks as standalone things, so all of the relevant code from when I wrote this up is also at the end of the notebook. I tried to make the code basic enough that it's easy to add different models yourself; please do so!</p>
<p>After poking at this, my main thought is that we'd be best off flattening the curve for as long as society can stand, <em>while pushing hard at capacity and cures</em>.</p>
<p>I'm no epidemiologist, but I think the results below make sense. The b</p>
<p><a href="https://mglerner.github.io/posts/social-distancing-and-hospital-capacity-for-coronavirus.html">Read more…</a> (21 min remaining to read)</p></div></div></div></description><guid>https://mglerner.github.io/posts/social-distancing-and-hospital-capacity-for-coronavirus.html</guid><pubDate>Fri, 20 Mar 2020 20:12:03 GMT</pubDate></item><item><title>Starting my sabbatical</title><link>https://mglerner.github.io/posts/starting-my-sabbatical.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div><p>Super exciting news: I'm starting my sabbatical. Through a combination of luck, timing, and hard work on the setup, I'll be spending the time working on computational oncology. Specifically, I'll be joining an existing collaboration between two fantastic labs at Johns Hopkins. It turns out that my statistical physics, computer science/programming, mathematics, and biophysics backgrounds are an excellent fit.</p>
<p>So now it's time to catch up on the science from a different field. I'm starting with a few Coursera courses.</p>
<p><a href="https://mglerner.github.io/posts/starting-my-sabbatical.html">Read more…</a> (3 min remaining to read)</p></div></description><guid>https://mglerner.github.io/posts/starting-my-sabbatical.html</guid><pubDate>Wed, 14 Aug 2019 13:45:35 GMT</pubDate></item><item><title>Orienting</title><link>https://mglerner.github.io/posts/orienting.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div><div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
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<p>(You can download this post as a notebook <a href="https://github.com/mglerner/mglerner.github.io/blob/master/posts/orienting.ipynb">here</a>.)</p>
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<h2 id="Orienting">Orienting<a class="anchor-link" href="https://mglerner.github.io/posts/orienting.html#Orienting">¶</a></h2><p>We're in New Zealand for a semester. Recently, <a href="http://www.whanganuirivertours.co.nz/ki-tai-team/">Ash Patea</a> was telling us some Māori lore about local mountains. We're based in Whanganui, learning about the mountains Tongariro, Taranaki, and Ruapehu, all of which are to our north. Ash starts all of these sessions off by telling us that we're learning <em>his</em> <a href="https://maoridictionary.co.nz/search?&amp;keywords=iwi">iwi</a>'s stories, but that they're not the only stories. That other stories are different, and none is "right." We then get to the part where we learn that the name "Tongariro" tells you it's a mountain to the south, and Ash says that's how they know the story we're learning isn't <em>their</em> story, and all of a sudden I have to write a little math post.</p>
<p>I don't want to spoil the punchline too much (yes I do), but there's a really neat connection between Ash's language and mathematics, about how you orient yourself in the world, and about how things <em>can't</em> always be consistent.</p>
<p><a href="https://mglerner.github.io/posts/orienting.html">Read more…</a> (9 min remaining to read)</p></div></div></div></div></description><guid>https://mglerner.github.io/posts/orienting.html</guid><pubDate>Sun, 10 Feb 2019 05:09:33 GMT</pubDate></item><item><title>Chromebooks for the kids</title><link>https://mglerner.github.io/posts/chromebooks-for-the-kids.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div><h2>Chromebook for the kids</h2>
<p>My oldest daughter is 9, and the twins are 6, so it's probably time to get them involved in computer things. I could have done this earlier, but I definitely screwed up with the kids by introducing tech/books/etc. before they were ready, so I decided to wait. The kids are definitely ready, so here are the goals:</p>
<ul>
<li>Programming<ul>
<li>Minecraft seems to be the best for this, but I want more than 2GB of RAM. Preferably 8GB.</li>
<li><a href="https://scratch.mit.edu">Scratch</a> also seems to get a ton of great recs.</li>
</ul>
</li>
<li>Access to the internet</li>
<li>Having an office suite around. The 9yo will be writing papers at school next year, etc.</li>
</ul>
<p>My original thought was that I'd get a cheap desktop: either a Windows box or a refurbished Mac. I was leaning against Linux because I'm old and it seems like there's a big barrier to entry for Linux. I want this to just work for the kids. Then someone pointed out that we'll be traveling out of the country next year, so a desktop is a bad idea. The cheapo version of a laptop is a Chromebook, but I wanted one capable of running Minecraft. I find a really nice <a href="https://platypusplatypus.com/chromebooks/play-minecraft-chromebook/">guide to setting up Minecraft on a Chromebook</a>. Of all things, the answer is to install Linux via <a href="https://github.com/dnschneid/crouton">crouton</a>. Who knew. So, I'll give that a try. The site also has a nice guide to Minecraft-capable Chromebooks. On the high end, the Pixel has all of the stats I could want ... but $1k seems like quite a bit to spend on a "cheapo" laptop. There were some nice $200 models, but I settled on the Asus Flip 2 (Intel Core m3, 4GB of RAM ... not quite the 8GB I wanted). I think the kids will really like the touchscreen and flipscreen. Hopefully they won't fight too much over the single computer.</p>
<p>So, as per the <a href="https://platypusplatypus.com/chromebooks/play-minecraft-chromebook/">guide</a>,</p>
<ul>
<li>Be prepared to <a href="https://platypusplatypus.com/chromebooks/powerwash-chromebook-full-recovery/">Powerwash</a>/revert to factory settings. (In fact, I had to do this because apparently I screwed up a root password in the next step.)</li>
<li>Enable <a href="https://platypusplatypus.com/chromebooks/enable-developer-mode-chromebook/">Developer Mode</a>.</li>
<li>Install <a href="https://github.com/dnschneid/crouton">crouton</a> and the crouton Chrome extension (link on crouton page).</li>
<li>
<p>Install Linux</p>
<ul>
<li>"Ctrl + Alt + T" gives you a command terminal in Chrome</li>
<li><code>shell</code> gives you a shell</li>
<li><code>sudo sh -e ~/Downloads/crouton -t touch,kde-desktop</code></li>
</ul>
</li>
<li>
<p>Switch back to the Chromebook side (shift+ctrl+alt+left arrow at the top of the keyboard).</p>
</li>
<li>Download the Linux Java version of Minecraft from minecraft.net</li>
<li>Switch back to the linux side (shift+ctrl+alt+right arrow at the top of the keyboard).</li>
<li>Put Minecraft in a stable place<ul>
<li><code>mkdir ~/Games</code></li>
<li><code>mv ~/Downloads/Minecraft.jar ~/Games</code></li>
</ul>
</li>
<li>You can launch via the command line: <code>java -jar ~/Games/Minecraft.jar</code></li>
<li>You can make a KDE shortcut to launch it. It's very particular.<ul>
<li>Open up <code>kmenuedit</code> and make a new item under Games.</li>
<li>Call it Minecraft.</li>
<li>Make the command <code>java -jar ./Minecraft.jar</code></li>
<li>Under Advanced, make the Work path <code>~/Games</code> and select <code>Run in terminal</code></li>
</ul>
</li>
<li>You can also go into <code>~/Games</code>, open it up in the file browser via <code>xdg-open .</code> then drag the Minecraft jar file onto the desktop. That gives you an icon which, when double-clicked, will launch Minecraft.</li>
</ul>
<p>Be aware that exiting developer mode will erase all of the Linux setup from above. Reinstalling it takes about 5 minutes of typing and 45 minutes of letting the computer churn.</p>
<p>So far, the kids seem more than happy with this setup. The crouton Linux install seems to be shared no matter who logs in on the Chromebook, so they can all log in individually on the ChromeOS side, but share the same Linux side. They don't seem to have a problem opening up a command terminal and sudo-launching kde, which is either cool or disturbing. Not sure which :).</p></div></description><guid>https://mglerner.github.io/posts/chromebooks-for-the-kids.html</guid><pubDate>Sun, 31 Dec 2017 17:58:37 GMT</pubDate></item><item><title>Coin Flipping and Entropy</title><link>https://mglerner.github.io/posts/coin-flipping-and-entropy.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
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<p>You can download this whole post as a Jupyter notebook <a href="https://mglerner.github.io/posts/coin-flipping-and-entropy.ipynb">here</a></p>
<h2 id="Some-useful-interactive-bits-for-coin-flipping-and-entropy.">Some useful interactive bits for coin flipping and entropy.<a class="anchor-link" href="https://mglerner.github.io/posts/coin-flipping-and-entropy.html#Some-useful-interactive-bits-for-coin-flipping-and-entropy.">¶</a></h2><p>I made this post for my 1st semester intro physics class, as a lead in to the standard discussion of entropy (sue me, I can't make myself dive into this without starting from stat mech).</p>
<h3 id="Say-you're-going-to-flip-4-coins.-What's-the-most-likely-outcome?-How-likely-is-it?">Say you're going to flip 4 coins. What's the most likely outcome? How likely is it?<a class="anchor-link" href="https://mglerner.github.io/posts/coin-flipping-and-entropy.html#Say-you're-going-to-flip-4-coins.-What's-the-most-likely-outcome?-How-likely-is-it?">¶</a></h3><p>How should we keep track of outcomes? One easy way is to ask "how many heads did we get?"</p>
<p><a href="https://mglerner.github.io/posts/coin-flipping-and-entropy.html">Read more…</a> (29 min remaining to read)</p></div></div></div></description><guid>https://mglerner.github.io/posts/coin-flipping-and-entropy.html</guid><pubDate>Thu, 16 Nov 2017 17:35:56 GMT</pubDate></item><item><title>Post-tenure job stress, part 1/N</title><link>https://mglerner.github.io/posts/post-tenure-job-stress-part-1n.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div><p>I'm feeling a little down job-wise, and perhaps looking for some advice.</p>
<p>I got into this job for several reasons, and I can't shake the feeling that I'm set up never to be excellent at any of them. Some are below, not in order.</p>
<p><strong>Super-brief context:</strong> I'm likely teaching a 3-3 load (none of these are likely to be research classes) and chairing my department for the foreseeable future. This is in addition to broader campus service, which becomes more relevant the more senior I become.</p>
<p><a href="https://mglerner.github.io/posts/post-tenure-job-stress-part-1n.html">Read more…</a> (5 min remaining to read)</p></div></description><guid>https://mglerner.github.io/posts/post-tenure-job-stress-part-1n.html</guid><pubDate>Mon, 06 Nov 2017 03:15:34 GMT</pubDate></item><item><title>Visualizing differential geometry in Jupyter notebooks</title><link>https://mglerner.github.io/posts/visualizing-differential-geometry-in-jupyter-notebooks.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div tabindex="-1" id="notebook" class="border-box-sizing">
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<p>(you can download this post as a notebook <a href="https://github.com/mglerner/mglerner.github.io/blob/master/posts/visualizing-differential-geometry-in-jupyter-notebooks.ipynb">here</a>)</p>
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<h2 id="Visualizing-differential-geometry-in-Jupyter-notebooks">Visualizing differential geometry in Jupyter notebooks<a class="anchor-link" href="https://mglerner.github.io/posts/visualizing-differential-geometry-in-jupyter-notebooks.html#Visualizing-differential-geometry-in-Jupyter-notebooks">¶</a></h2>
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/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%0AOQ4zQTEF+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C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%0AAAAAAABAAAAAoAB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<p>I taught a senior seminar on differential geometry last year. I'll be honest: it was a selfish course. <a href="https://www.cmu.edu/physics/people/faculty/deserno.html">Markus Deserno</a> writes all of these cool papers about membranes, and I didn't know enough math to follow them. So, the goal of our course was basically to learn enough differential geometry to read several of his papers. It was fantastic. We used several of his papers, as well as Kreyszig's textbook, as our core materials.</p>
<p>Here's the thing: a lot of this was pretty foreign to my physics students. In particular, the discussion of surfaces and mappings was new. So, we wrote some tools in Jupyter Notebooks to help us visualize and solve problems. I particularly like the stuff we wrote to visualize a mapping, and I don't know of a comparable resource elsewhere.</p>
<p>As a teaser, the above movies show you how to interpolate between a surface and a curve in the first case, and how the Monge gauge works for a membrane in the second case.</p>
<p>Let's jump in.
</p><p><a href="https://mglerner.github.io/posts/visualizing-differential-geometry-in-jupyter-notebooks.html">Read more…</a> (534 min remaining to read)</p></div></div></div></div></div></description><guid>https://mglerner.github.io/posts/visualizing-differential-geometry-in-jupyter-notebooks.html</guid><pubDate>Sun, 15 Oct 2017 21:15:56 GMT</pubDate></item><item><title>Switching to Nikloa for Jupyter Notebooks and a static site</title><link>https://mglerner.github.io/posts/switching-to-nikloa-for-jupyter-notebooks-and-a-static-site.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div><p>I've been using WordPress for quite a while, almost entirely because
it's an out-of-the-box blog setup that just works. But it kind of
sucks for what I mostly want to do, which is stick some code into blog
posts. In fact, what usually happens is that I do something in a
Jupyter notebook, and want to stick it up as a blog post. That's a
real pain in WordPress. The best I found was converting the notebooks
to html and then including them as a static block, but those
invariably are brittle and ugly.</p>
<p>So, smart people like <a href="http://jakevdp.github.io">Jake Vanderplas</a> and
<a href="http://themodernscientist.com">themodernscientist</a> switched over to
something that deals natively with Jupyter notebooks a long time ago
(so long ago they were called IPython Notebooks!). I'm a slow pony,
but I'm switching to Nikola. It seems to be the easiest one at the
moment. It's a static page generator, which is more than fine for my
purposes, and it deals natively with Jupyter notebooks. Sweet. I
thought it would be useful to document the process for future-me. I
leaned heavily on the Nikola site (including the
<a href="https://getnikola.com/handbook.html#importing-your-wordpress-site-into-nikola">documentation for import_wordpress</a>). The
process wasn't completely trivial, but that's because I did some hacky
stuff to get Jupyter Notebooks included in my WordPress posts
anyway. This seems like a lot of work for like 13 posts, but nobody
ever claimed I was wise.</p>
<p><strong>[UPDATE: I ended up switching all of my old IPython/Jupyter posts over to notebooks rather than HTML. If you read an earlier version of this, basically everything else is the same]</strong></p>
<p><a href="https://mglerner.github.io/posts/switching-to-nikloa-for-jupyter-notebooks-and-a-static-site.html">Read more…</a> (8 min remaining to read)</p></div></description><guid>https://mglerner.github.io/posts/switching-to-nikloa-for-jupyter-notebooks-and-a-static-site.html</guid><pubDate>Thu, 12 Oct 2017 13:52:49 GMT</pubDate></item><item><title>Can I be smarter about late policies?</title><link>https://mglerner.github.io/posts/can-i-be-smarter-about-late-policies.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div><p><strong>Questions</strong>: Is my late policy reasonable? Are there diversity implications for smart late policies?</p>
<p><a href="https://twitter.com/actualham" target="_blank">Robin DeRosa</a> had an interesting <a href="https://twitter.com/actualham/status/777620707186475008" target="_blank">tweet</a> about late policies recently, and I posted my late policy in reply. Here’s a slightly expanded version:</p>
<p>In most of my classes, late work happens because students are really busy, not because they’re slackers. That means a late policy with percentage deductions kind of sucks, because my students will also be really busy the next week. Instead, I combine “no late work accepted” with dropping the equivalent of one week’s worth of each assignment time. E.g. in a class that meets three times a week, I throw out three of the daily assignments.</p>
<p>I make sure to frame this in a discussion with the students, where I explain that the policy is an explicit recognition of the fact that they’re busy. If you’re too busy to get the work done on time, JUST SKIP it, and get your life caught up.</p>
<p>So far, it has been working out really well. The students appreciate the extra lever for managing their schedules, and it’s clear from the beginning that there won’t need to be any exceptions. Note: every semester so far, students have managed to get confused early on … luckily, this comes up in terms of one of those low-weight daily assignments, so we clear it up before a high-stakes situation shows up).</p>
<p><a href="https://mglerner.github.io/posts/can-i-be-smarter-about-late-policies.html">Read more…</a> (3 min remaining to read)</p></div></description><guid>https://mglerner.github.io/posts/can-i-be-smarter-about-late-policies.html</guid><pubDate>Sun, 18 Sep 2016 22:56:07 GMT</pubDate></item><item><title>Using numba to speed up mean-squared displacement calculations</title><link>https://mglerner.github.io/posts/using-numba-to-speed-up-mean-squared-displacement-calculations.html</link><dc:creator>Michael G. Lerner</dc:creator><description><div tabindex="-1" id="notebook" class="border-box-sizing">
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<p>You can download this whole thing as a Jupyter notebook <a href="https://mglerner.github.io/posts/using-numba-to-speed-up-mean-squared-displacement-calculations.ipynb">here</a></p>
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<h2 id="Writing-a-faster-mean-squared-displacement-function">Writing a faster mean-squared-displacement function<a class="anchor-link" href="https://mglerner.github.io/posts/using-numba-to-speed-up-mean-squared-displacement-calculations.html#Writing-a-faster-mean-squared-displacement-function">¶</a></h2><p>I'm trying to calculate the Mean Squared Displacement (MSD) of a particle trajectory. In reality, I have an array of positions for <code>numtrj</code> particles and <code>numpts</code> timepoints and <code>dim</code> dimensions: <code>pos[numtrj, numpts, dim]</code>. I think my question has the same answer if I just have the <code>x</code> trajectory of a single particle, though.</p>
<p>In case you haven't done MSD calculations before, there's one cute way in which you get extra information out of a trajectory. Say I have just five time points, and my positions are</p>
<div class="highlight"><pre><span></span><span class="n">In</span> <span class="p">[</span><span class="mi">83</span><span class="p">]:</span> <span class="n">x</span>
<span class="n">Out</span><span class="p">[</span><span class="mi">83</span><span class="p">]:</span> <span class="n">array</span><span class="p">([</span> <span class="mf">0.</span> <span class="p">,</span> <span class="mf">1.74528704</span><span class="p">,</span> <span class="mf">1.59639865</span><span class="p">,</span> <span class="mf">2.59976219</span><span class="p">,</span> <span class="mf">3.70852457</span><span class="p">])</span>
</pre></div>
<p>You could just get squared displacement by looking at x**2. However, you could also say that you have 4 different values for the displacement at one timestep:</p>
<div class="highlight"><pre><span></span><span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">x</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="n">x</span><span class="p">[</span><span class="mi">4</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span>
</pre></div>
<p>Similarly, three values for displacement at two timesteps: x[2:] - x[:-2]. Etc. So, the way I'm calculating MSD at the moment is:</p>
<div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">msd_1d</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros_like</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">)):</span>
<span class="n">result</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">average</span><span class="p">((</span><span class="n">x</span><span class="p">[</span><span class="n">i</span><span class="p">:]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[:</span><span class="o">-</span><span class="n">i</span><span class="p">])</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
<span class="k">return</span> <span class="n">result</span>
</pre></div>
<p>or</p>
<div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">get_msd_traj</span><span class="p">(</span><span class="n">pos</span><span class="p">):</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros_like</span><span class="p">(</span><span class="n">pos</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="n">pos</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]):</span>
<span class="n">result</span><span class="p">[:,</span><span class="n">i</span><span class="p">,:]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">average</span><span class="p">((</span><span class="n">pos</span><span class="p">[:,</span><span class="n">i</span><span class="p">:,:]</span> <span class="o">-</span> <span class="n">pos</span><span class="p">[:,:</span><span class="o">-</span><span class="n">i</span><span class="p">,:])</span><span class="o">**</span><span class="mi">2</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="k">return</span> <span class="n">result</span>
</pre></div>
<p>(side note: often the data comes indexed like <code>pos[numpts, numtrj, dim]</code> for molecular dynamics trajectories, but that doesn't change anything here)</p>
<p>So, I asked <a href="https://twitter.com/synapticarbors">Joshua Adelman</a> if he had any quick thoughts.
</p><p><a href="https://mglerner.github.io/posts/using-numba-to-speed-up-mean-squared-displacement-calculations.html">Read more…</a> (5 min remaining to read)</p></div></div></div></div></div></description><guid>https://mglerner.github.io/posts/using-numba-to-speed-up-mean-squared-displacement-calculations.html</guid><pubDate>Thu, 02 Jul 2015 14:35:00 GMT</pubDate></item></channel></rss>