CerebralMastication

import pandas as pd

## dummy covariance matrix
cov = eye(2) + -.7
fill_diagonal(cov, 1)

# a little bit of non correalted random variates
# also sometimes called the marginal distributions

n = 10000

CerebralMastication

value	Latitude	Longitude
0.7535	49.3387	-124.3272
0.7332	49.3387	-123.9939
0.3963	49.3387	-123.6606
0.1155	49.3387	-123.3272
0.2775	49.3387	-122.9939
0.3157	49.3387	-122.6606
0.4015	49.3387	-122.3272
0.3987	49.3387	-121.9939
0.7647	49.3387	-121.6606

CerebralMastication

## read in the training data
## more lines than it should be because of the https requirement in Github
temporaryFile <- tempfile()
download.file("https://raw.github.com/gist/2061284/44a4dc9b304249e7ab3add86bc245b6be64d2cdd/problem.csv",destfile=temporaryFile, method="curl")
series <- read.csv(temporaryFile)

## munge the data to create a frequency table
freqTable <- as.data.frame( t(apply(series[,1:4], 1, function(X) table(c(X, 0:9))-1)) )
names(freqTable) <- c("zero","one","two","three","four","five","six","seven","eight","nine")

CerebralMastication

> install.packages("sde", lib=libPath)
also installing the dependencies ‘fda’, ‘zoo’

trying URL 'http://cran.r-project.org/src/contrib/fda_2.2.6.tar.gz'
Content type 'application/x-gzip' length 6356938 bytes (6.1 Mb)
opened URL
==================================================
downloaded 6.1 Mb

trying URL 'http://cran.r-project.org/src/contrib/zoo_1.6-5.tar.gz'

CerebralMastication

ip2Int <- function(ip){
  split <- as.numeric(strsplit(ip, "\\.")[[1]])
  out <- (split[1] * 256^3) + (split[2] * 256^2) + (split[3] * 256) + (split[4])
  return(out)
}


int2Ip <- function(int){
  split <- NULL
  split[1] <- as.integer(int/256^3)

CerebralMastication

structure(list(CITY = c("Anqing", "Anqing", "Anqing", "Anqing", 
"Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", 
"Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", 
"Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", 
"Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", 
"Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", 
"Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", 
"Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", 
"Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", 
"Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", "Anqing", 

CerebralMastication

#!/bin/bash

secGroup="sg-50681d39"
ami="ami-1aad5273"
keyName="ec2ApiTools"
keyLocation="/home/jal/Documents/AWS/ec2ApiTools_rsa_id"

instance_id=$(ec2-run-instances -k $keyName -g $secGroup -t m1.large $ami | awk '/INSTANCE/{print $2}') 
echo $instance_id

CerebralMastication

## Joshua Ulrich's pivot function
## This code is alpha and is in development. 
## please test all results to ensure accuracy 

pivot <- function(x, rows, cols, FUN=NULL) {
   clean <- function(xx, dd) {
     cd <- merge(dd,xx,by=0,all=TRUE)
     rownames(cd) <- cd$Row.names
     cd$Row.names <- NULL
     return(cd)

CerebralMastication

# initialize an output data frame 
# with the right columns... I'll assume it's called dfOut

for ( i in 1:(nrow(df)) ) {
   for ( j in 1:(df$endYear - df$startYear + 1 ) ) {
     dfOut[length(dfOut +1), ] <- ## construct a single row data frame here with the write stuff and it will insert into dfOut ##
   }
}

CerebralMastication

#!/bin/sh
#
# Detect displays and move panels to the primary display
#

#15 second pause
sleep 15

PYTHON=python2.6
DISPER=/usr/bin/disper