kohnakagawa

template<typename T>
T pow_n(T x, int n){
  T a = 1.0;
  
  while(n > 0){
    if(n % 2 == 0){
      x = x*x;
      n = n>>1;
    }else{
      a = a*x;

kohnakagawa

#include <sys/time.h>

double time_dif(timeval &tv1, timeval &tv2)
{
  const double dt = tv2.tv_sec - tv1.tv_sec + (tv2.tv_usec - tv1.tv_usec) * 1.0e-6;
  return dt;
}

kohnakagawa

set terminal postscript eps enhanced color lw 2 defaultplex "Helvetica" 16
#set terminal postscript eps enhanced color

set output "dif.eps"
set size 0.65,1.23
set nokey
#set key graph 0.7, graph 0.8
set nogrid
set format y '%g'
set format x '%g'

kohnakagawa

set terminal postscript eps enhanced color lw 2 defaultplex "Helvetica" 16
#set terminal postscript eps enhanced color solid

set output "dif.eps"
set size 0.65,0.62
unset key
#set key graph 0.7, graph 0.9
unset grid
set format y '%g'
set format x '%g'

kohnakagawa

#!/bin/bash

flame_rate=10
output_file="out"
number_of_digit=3

ffmpeg -r ${flame_rate} -i "time%0"${number_of_digit}"d.jpeg" -qscale 0 ${output_file}".mp4"

kohnakagawa

#include <iostream>
#include <cmath>
#include <gsl/gsl_math.h>
#include <gsl/gsl_vector.h>
#include <gsl/gsl_matrix.h>
#include <gsl/gsl_eigen.h>
#include <gsl/gsl_sort_vector.h>

#define DIM 2

kohnakagawa

#include <iostream>
#include "Eigen/Core"
#include "Eigen/Eigenvalues"

int main(void){
  using namespace Eigen;
  Matrix2d A;
  Vector2d a;
  A << 1,-0.5,-0.5,1;
  SelfAdjointEigenSolver<Matrix2d> es(A);

kohnakagawa

#include <iostream>
#include <boost/random.hpp>

int main ()
{
  using namespace boost;
  using namespace std;

  mt19937 gen(100);

kohnakagawa

#small sample for GMM
#install.packages('mclust') #installing Mclust package
library(mclust)
dat <- read.table("./result/")
dat <- data.matrix(dat)
result.dat <- Mclust(dat)
plot(result.dat)
summary(result.dat,parameters=TRUE)

kohnakagawa

#!/bin/bash
R --vanilla --slave < gmm.R
#R --vanilla --slave --args ./infile.txt ./outfile.txt 10000 < gmm.R