stormxuwz

\usepackage[subsection]{algorithm}	% algorithm float, number according to subsection
\usepackage{algpseudocode}	% pseudo-code format



	\begin{algorithm}[htbp]
\caption{Parallel CUDA algorithm for connect component labelling \#1}
\label{alg:imageLabellingGPU1}
\algblockdefx[kernel]{Kernel}{EndKernel}[2][default value]{{\bf kernel} {\footnotesize \uppercase{#1}(#2)}}{\bf end kernel}
\begin{algorithmic}

stormxuwz

# http://stackoverflow.com/questions/19120489/compare-two-files-report-difference-in-python
import difflib
import sys

with open('transect_2_night_1.bin_PB_2013-09-13_151717.dat', 'r') as hosts0:
    with open('transect_3_day_1.bin_PB_2013-09-13_150838.dat', 'r') as hosts1:
        diff = difflib.unified_diff(
            hosts0.readlines(),
            hosts1.readlines(),
            fromfile='hosts0',

stormxuwz

origin='Madison,Chicago,IL';
destination='N+Michigan+Ave,Chicago,IL';

url1=['https://maps.googleapis.com/maps/api/directions/json?origin=' origin '&destination=' destination '&sensor=false&key= XXXX&departure_time=1343641500&mode=driving'];
direction=urlread(url1);
d=parse_json(direction);
steps=d{1}.routes{1}.legs{1}.steps;
[startpoints,endpoints]=cellfun(@parsecoord,steps);

stormxuwz

Sub outputfile_whole()


Dim Infilename, outfilename As String
Dim name As String

Filename = ThisWorkbook.FullName
filename1 = ThisWorkbook.name

filename1 = Left(filename1, Len(filename1) - 5)

stormxuwz

import numpy as np
from scipy.io.wavfile import read,write
import matplotlib.pyplot as plt 
from matplotlib.pylab import *

def omega(N,k,n):
	return np.exp(-2*np.pi/N*k*n*1j)

def hanWindow(N):
	diag=np.array([np.sin(np.pi*i/(N-1))**2 for i in range(N)])

stormxuwz

// This code is from https://www.cac.cornell.edu/VW/OpenMP/whileloop.aspx

#include <omp.h>
#include <stdio.h>
int main(int argc, char **argv)
{
  /* OpenMP does not provide a parallel while loop,
     so we're going to have to make one ourselves... */
  int sj, sstop, tn, tj, tstop;
  int foo(int j);

stormxuwz

# http://stackoverflow.com/questions/10628847/geom-boxplot-with-precomputed-values

library(ggplot2)

DF <- data.frame(x=c("A","B"), min=c(1,2), low=c(2,3), mid=c(3,4), top=c(4,5), max=c(5,6))

ggplot(DF, aes(x=x, ymin = min, lower = low, middle = mid, upper = top, ymax = max)) +
  geom_boxplot(stat = "identity")

stormxuwz

# include <iostream>

using namespace std;

struct person{
	person * previousPerson;
	person * nextPerson;
	int sword;
	int num;
};

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import urllib2;
import numpy as np;
import json;
from pyproj import Geod;

def decode_line(encoded):
    """copied from https://github.com/jconst/Byway-Server/blob/master/polyline.py
    """

    encoded_len = len(encoded)

stormxuwz

 #### LDA,QDA, RDA, naive baye functions ####
 
 lda.model=function(traindata){
 	lda.result=lda(Y~.,data=traindata)
	return(lda.result)
 }
 
 lda.pred=function(model,dataSets.X){
   predresult=lapply(dataSets.X,function(X) predict(model,X)$class) 
	 errorInfo(predresult,"lda")