Archive for August, 2016

(Slightly) Faster way to compute number of unique elements in matlab matrix

Wednesday, August 31st, 2016

The standard way to compute the number of unique entries in a matlab matrix A is:


If our entries are positive integers, we can try to do the same thing using sparse with:


but actually this is slower.

I don’t see a way to avoid a sort. I came up with this,


As far as I can tell, this will work for matrices that don’t have infs and nans. It’s slightly faster than number(unique(A)). I have a feeling I’m only winning anything here because I’m avoiding overhead within unique

Eitan Grinspun’s “How to host a visit”

Thursday, August 25th, 2016

Eitan has prepared a google doc on hosting visitors to the lab that I find very useful. It contains a detailed list (some unique to Columbia) of things you should do to host a visitor and when you should do them.

Real-time LaTeX in browser

Tuesday, August 23rd, 2016

A long time ago, I made a little web app that allowed you to submit Latex code to a server, the server would run pdflatex and then send back the pdf to be rendered on the page.

Nowadays MathJax can render LaTeX equations in the browser. I found that let’s you interactively write formulae, but it’s restricted to a single equation. There’s also the LaTeXit standalone app, but you have to keep hitting “typeset”. This isn’t so useful if you’re trying to quickly type math during a Skype call.

So I wrote a little program to run in the browser:

You can also fork the git gist

option click on volume menu bar item to change sound devices

Friday, August 19th, 2016

I find myself often switching the microphone and speaker devices on my mac. I usually go all the way through System Preferences > Sound, but I stumbled upon a much faster route.

Normally if you click on the volume menu item at the top of the screen you get a little volume slider:

volume menu bar

If you hold OPTION while you click you see a device selection menu:

volume menu bar option click

Energy optimization, calculus of variations, Euler Lagrange equations in Maple

Tuesday, August 16th, 2016

Here’s a simple demonstration of how to solve an energy functional optimization symbolically using Maple.

Suppose we’d like to minimize the 1D Dirichlet energy over the unit line segment:

min  1/2 * f'(t)^2
subject to: f(0) = 0, f(1) = 1

we know that the solution is given by solving the differential equation:

f''(t) = 0, f(0) = 0, f(1) = 1

and we know that solution to be

f(t) = t

How do we go about verifying this in Maple:

E := diff(f(t),t)^2:
L := EulerLagrange(E,t,f(t)):

so far this will output:

        L := {-2*diff(diff(x(t),t),t), -diff(x(t),t)^2 = K[2], 2*diff(x(t),t) = K[1]}

Finally solve with the boundary conditions using:


which will output

         t(t) = t

Are you using libigl?

Wednesday, August 3rd, 2016

I would love to gather up some information about who out there is using libigl. Drop me a line if you or your university/institution/company is.