## Archive for the ‘code’ Category

### Accessing Free Guangzhou Airport Wi-Fi on MacBook Pro

Saturday, December 2nd, 2017

Guangzhou airport has a crazy way of providing free wifi. If you have a Chinese phone you can receive a login account via text, but if you don’t have a Chinese number, then you have to go to a physical ticket machine, scan your passport, and quickly jot down (or photograph) the code that flashes on the screen for 15 seconds.

Once you have this code, you have to click “Ticket Cert” on the login page and enter the info.

This worked fine for me on my iPhone.

But when I tried to follow the same steps on my laptop, the “Ticket Cert” option did not appear on my browser login prompt. I saw a slightly different page that only had the SMS option (and a bunch of half-loaded CSS and javascript errors).

I tried many things including spoofing the UserAgent on my browser. Nothing seemed to work.

Finally, I changed the MAC address on my laptop to match my already-online iphone’s

ifconfig en0 ether [iphone's "Wi-Fi Address"]

This worked.

PS: So far, I have not managed to get any sort of vpn, proxy or ssh tunnelling to work.

### Convincing maple to solve an ODE with Neumann conditions at a symbolic valued location

Friday, November 17th, 2017

I can use maple to solve a 1D second-order ODE with Dirichlet boundary conditions at symbolic-valued locations:

# Z'' = 0, Z(a)=0, Z(b) = 1
dsolve({diff(Z(r),r,r) = 0,Z(a)=0,Z(b)=1});

This correctly returns

r       a
Z(r) = - ----- + -----
a - b   a - b

I can also easily convince maple to solve this ODE with some Neumann (normal derivative) boundary conditions at at fixed-value, numeric location:

# Z'' = 0, Z(a) = 1, Z'(0) = 0
dsolve({diff(Z(r),r,r) = 0,Z(a)=1,eval(diff(Z(r),r),r=0)=0});

produces

Z(r) = 1

But if I try naively to use a Neumann condition at a symbolic value location

# Z'' = 0, Z(a) = 1, Z'(b) = 0
dsolve({diff(Z(r),r,r) = 0,Z(a)=1,eval(diff(Z(r),r),r=b)=0});

then I get an error:

Error, (in dsolve) found differentiated functions with same name but depending on different arguments in the given DE system: {Z(b), Z(r)}

After a long hunt, I found the solution. dsolve takes an optional second argument that can tell it what the dependent variable actually is. So the correct call is:

# Z'' = 0, Z(a) = 1, Z'(b) = 0
dsolve({diff(Z(r),r,r) = 0,Z(a)=1,eval(diff(Z(r),r),r=b)=0});

and this gives the correct answer

Z(r) = 1

### MATLAB gotcha inverting a (sparse) diagonal matrix

Thursday, November 2nd, 2017

Just got burned by a silly Matlab gotcha. Suppose you have a diagonal matrix D and you want to compute the inverse square root matrix:

Disqrt = diag(1./sqrt(diag(D))

But this will be dense!

Disqrt = diag(sqrt(diag(D).^-1)

Or maybe

Disqrt = diag(diag(D).^-0.5)

Not sure if there’s an accuracy difference (hopefully not).

### Eigen performance gotcha calling non-templated function from templated one

Tuesday, July 25th, 2017

I just spent a while tracking down a rather surprising performance bug in my code.

Here’s a minimal example:

#include <Eigen/Dense>
#include <iostream>

int simple_size(const Eigen::MatrixXi & Z)
{
return Z.size();
}

template <typename T> int templated_size(const Eigen::MatrixBase<T> & Y)
{
return simple_size(Y);
}

int main(int argc, const char * argv[])
{
const int s = 40000;
Eigen::MatrixXi X = Eigen::MatrixXi::Zero(40000,40000);
std::cout<<"Compare:"<<std::endl;
std::cout<<(X.size()         ?"done":"")<<std::endl;
std::cout<<(simple_size(X)          ?"done":"")<<std::endl;
std::cout<<(templated_size(X)?"done":"")<<std::endl;

}

Running this, it will show that the last call to templated_size is taking way too long. Inspection will show that a copy of Y is being created to create a Eigen::MatrixXi & reference.

Now, clearly it’s poor design to call a function expecting a Eigen::MatrixXi & reference with a generic templated type Eigen::MatrixBase<T> &, but unfortunately this happens quite often with legacy libigl functions. My expectation was that since T is Eigen::MatrixXi in this case a simple reference would be passed.

It’s worth noting that const is actually creating/hiding the problem. Because simple_size takes a const reference, the compiler is happy to construct a Eigen::MatrixXi on the fly to create a valid reference. Without the consts the compiler stops at an error.

### Inflate Wire Mesh in libigl C++ or gptoolbox MATLAB

Wednesday, July 12th, 2017

For a visualization and 3D printing, it’s often useful to “inflate” a edge-network into a thickened surface mesh. One method to do this is described “Sculptural Forms from Hyperbolic Tessellations” by George C Hart. This method works by adding rotated polygons at the ends of each edge offset a bit from the vertices. Then for each vertex the convex hull of incident edges’ polygons is computed and unioned with the convex hull of the polygons at either end of each edge. Hart writes that polygons shared by “edge hulls” and “vertex hulls” can simply be discarded. This is unfortunately not true, in general. It’s not super easier to categorize which faces can be discarded (even in general position) since the answer depends on the thickness, the number of sides of the polygons, their rotations, their offsets, and the angle between neighbouring edges. Fortunately, libigl is very good at conducting unions. We can just conduct the union explicitly and exactly using libigl.

I’ve written a new function for libigl igl::wire_mesh that takes in a wire network and spits out a solid (i.e., closed, watertight, manifold) mesh of a the inflated surface.

I’ve also wrapped this up in a Matlab Mex function in gptooolbox wire_mesh.

### Project page for “Generalized Matryoshka: Computational Design of Nesting Objects”

Wednesday, June 14th, 2017

This April I had fun working on a little project that’s been tickling my mind for a while. Can you make any shape into a Matryoshka doll?

I’ll be presenting my paper on this at SGP 2017. It’s entitled
Generalized Matryoshka: Computational Design of Nesting Objects.

### Pause (and then resume) Battery-Guzzling programs

Wednesday, June 7th, 2017

My laptop battery dies quickly these days. Certain apps (cough, cough, Slack), have very high idle CPU-usage. You can pause these programs with

killall -STOP Slack

And later you can resume the application with

killall -CONT Slack

### Convincing LatexIt and Illustrator to use the new SIGGRAPH fonts

Saturday, May 20th, 2017

The SIGGRAPH Latex style changed to the Libertine font. Here’re the steps to convince Latexit to use the new stylesheet and then to convince Illustrator to use the libertine font for drag and drop math.

mkdir ~/Library/texmf/tex/latex/local/acmart.cls/
cp ~/Dropbox/boundary/Paper/acmart.cls ~/Library/texmf/tex/latex/local/acmart.cls

In Latexit, open up Preferences, add a new SIGGRAPH “Template” containing:

\documentclass[sigconf, review]{acmart}
\pagenumbering{gobble}

If you try to drag and drop these into illustrator you’ll see that illustrator has replaced the nice math font with Myriad or something silly.

Drag this into FontBook.app

Update: I also had to issue:

If you see boxes with X’s replacing symbols after dragging and dropping from LaTeXit, then drag into Finder instead (to create a .pdf file), then open this directly and Illustrator will give a warning and tell you which font it’s (still) missing.

### Mex wrapper for graph segmentation

Thursday, May 4th, 2017

I wrote a small mex wrapper for the graph segmentation part of the “Graph Based Image Segmentation” code. Most of the previously matlab implementations/wrappers worked on images. I want to apply this to geometry so I needed access to the graph segmentation directly. Here’s the wrapper (soon to be part of gptoolbox):

// mexopts = gptoolbox_mexopts('Static',false,'Debug',true);
// mex('segment_graph.cpp',mexopts{:});
#ifdef MEX
#  include <mex.h>
#  include <igl/C_STR.h>
#  include <igl/matlab/mexErrMsgTxt.h>
#  undef assert
#  define assert( isOK ) ( (isOK) ? (void)0 : (void) ::mexErrMsgTxt(C_STR(__FILE__<<":"<<__LINE__<<": failed assertion `"<<#isOK<<"'"<<std::endl) ) )
#endif
#include "segment-graph.h"
#include <igl/matlab/mexErrMsgTxt.h>
#include <igl/matlab/parse_rhs.h>
#include <igl/unique.h>
#include <igl/matlab/prepare_lhs.h>
#include <igl/matlab/requires_arg.h>
#include <igl/matlab/validate_arg.h>
#include <igl/matlab/MexStream.h>
#include <Eigen/Sparse>
void mexFunction(
int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
using namespace igl::matlab;
using namespace Eigen;
using namespace std;
igl::matlab::MexStream mout;
std::streambuf *outbuf = std::cout.rdbuf(&mout);

mexErrMsgTxt(nrhs>0,"Too few inputs");
mexErrMsgTxt(mxIsSparse(prhs[0]),"Matrix should be sparse");
const mxArray * mx_data = prhs[0];
const int m = mxGetM(mx_data);
const int n = mxGetN(mx_data);
mexErrMsgTxt(n == mxGetM(prhs[0]), "Matrix should be square");
assert(mxIsSparse(mx_data));
assert(mxGetNumberOfDimensions(mx_data) == 2);
// TODO: It should be possible to directly load the data into the sparse
// matrix without going through the triplets
// Copy data immediately
double * pr = mxGetPr(mx_data);
mwIndex * ir = mxGetIr(mx_data);
mwIndex * jc = mxGetJc(mx_data);
const int num_edges = mxGetNzmax(mx_data);
edge * edges = new edge[num_edges];
int k = 0;
for(int j=0; j<n;j++)
{
// Iterate over inside
while(k<(int)jc[j+1])
{
//cout<<ir[k]<<" "<<j<<" "<<pr[k]<<endl;
assert((int)ir[k]<m);
assert((int)j<n);
edges[k].a = ir[k];
edges[k].b = j;
edges[k].w = pr[k];
k++;
}
}

// defaults
int min_size = 0;
// Threshold
int c = sqrt((double)n);
{
int i = 1;
while(i<nrhs)
{
mexErrMsgTxt(mxIsChar(prhs[i]),"Parameter names should be strings");
// Cast to char
const char * name = mxArrayToString(prhs[i]);
if(strcmp("Threshold",name) == 0)
{
requires_arg(i,nrhs,name);
validate_arg_scalar(i,nrhs,prhs,name);
validate_arg_double(i,nrhs,prhs,name);
c = (double)*mxGetPr(prhs[++i]);
}else if(strcmp("MinSize",name) == 0)
{
requires_arg(i,nrhs,name);
validate_arg_scalar(i,nrhs,prhs,name);
validate_arg_double(i,nrhs,prhs,name);
min_size = (int)((double)*mxGetPr(prhs[++i]));
}
i++;
}
}

universe *u = segment_graph(n, num_edges, edges, c);

// post process small components
for (int i = 0; i < num_edges; i++) {
int a = u->find(edges[i].a);
int b = u->find(edges[i].b);
if ((a != b) && ((u->size(a) < min_size) || (u->size(b) < min_size)))
u->join(a, b);
}

switch(nlhs)
{
case 1:
{
plhs[0] = mxCreateDoubleMatrix(m,1, mxREAL);
Eigen::VectorXi C(m);
for(int i = 0;i<m;i++)
{
C(i) = u->find(i);
}
Eigen::VectorXi uC,I,J;
igl::unique(C,uC,I,J);
prepare_lhs_index(J,plhs);
}
default: break;
}

delete[] edges;
delete u;
std::cout.rdbuf(outbuf);
}

It takes the graph as a sparse matrix and outputs the component ids:

C = segment_graph(A);

### Using glfw background window in matlab mex thread

Monday, April 3rd, 2017

A while ago, I tried to get glfw playing nicely with matlab’s mex files. I didn’t quite succeed.

My current project requires “GP-GPU” programming. I’m currently using glfw’s “background window” feature to create an OpenGL context. My first tests show that matlab’s mex will play nicely if glfwTerminate() is never called:

#include <igl/opengl/glfw/background_window.h>
#include <mex.h>
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
GLFWwindow * window;
igl::opengl::glfw::background_window(window);
glfwDestroyWindow(window);
//glfwTerminate();
}

You can compile this (on mac os x) with:

mex( ...
'-largeArrayDims','-DMEX','CXXFLAGS=$CXXFLAGS -std=c++11', ... 'LDFLAGS=\$LDFLAGS -framework Foundation -framework AppKit -framework Accelerate -framework OpenGL -framework AppKit -framework Carbon -framework QuartzCore -framework IOKit ', ...
'-I/usr/local/igl/libigl//external/nanogui/ext/eigen/', ...
'-I/usr/local/igl/libigl/include', ...
'-I/usr/local/igl/libigl/external/nanogui/ext/glfw/include/', ...
'-L/usr/local/igl/libigl/lib/','-lglfw3', ...
'background_glfw.cpp');

I don’t know why including glfwTerminate() causes matlab to sometimes crash. The error report is impossible to read and seems to have something to do with Quartz.