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#install the packages
install.packages('XML')
require(XML)

#get raw html for Lake Minnetonka
html.raw<-htmlTreeParse(
    'http://www.dnr.state.mn.us/lakefind/showreport.html?downum=27013300',
    useInternalNodes=T
    )

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#import relevant packages
library(gstat)
library(sp)
library(nlme)

#create simulated data, lat and lon from uniformly distributed variable, exp1 and exp2 from random normal
set.seed(2)
samp.sz<-400
lat<-runif(samp.sz,-4,4)
lon<-runif(samp.sz,-4,4)

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catch.fun<-function(dows,fish.str,net.type='Trap',trace=T,clean=F){

  require(XML)

  strt<-Sys.time()

  #create object for output
  fish.out<-data.frame(expand.grid(dows,fish.str),NA,NA)
  names(fish.out)<-c('dows','fish','fish.val','result')

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vif_func<-function(in_frame,thresh=10,trace=T,...){

  library(fmsb)
  
  if(any(!'data.frame' %in% class(in_frame))) in_frame<-data.frame(in_frame)
  
  #get initial vif value for all comparisons of variables
  vif_init<-NULL
  var_names <- names(in_frame)
  for(val in var_names){

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catch.fun.v2<-function(dows,trace=T,rich.out=F){

  require(XML)

  strt<-Sys.time()

  #create object for output
  fish.out<-vector('list',length(dows))
  names(fish.out)<-dows
    

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plot.nnet<-function(mod.in,nid=T,all.out=T,all.in=T,wts.only=F,rel.rsc=5,circle.cex=5,node.labs=T,
  line.stag=NULL,cex.val=1,alpha.val=1,circle.col='lightgrey',pos.col='black',neg.col='grey',...){

  require(scales)
	
  #gets weights for neural network, output is list
  #if rescaled argument is true, weights are returned but rescaled based on abs value
  nnet.vals<-function(mod.in,nid,rel.rsc){

    library(scales)

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shinyServer(function(input, output) {

  myData <- reactive({
  read.csv(input$file$datapath)
    })

  output$summary <- renderPrint({
     if (is.null(input$file)) {

      return(cat('File not uploaded'))

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obs<-100
x<-runif(obs,0,100)
y<-x^2+rnorm(obs,0,800)

require(scales)

#examples with span
par(mfrow=c(2,2),mar=c(4,4,0.5,0.5),family='serif')
span<-round(seq(0.5,0.1,length=4),2)
for(i in span){

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plot.qual<-function(x,x.locs=c(0.01,0.99),y.locs=c(0,1),steps=NULL,sp.names=NULL,dt.tx=T,rsc=T,
	ln.st=NULL,rs.ln=c(3,15),ln.cl='RdYlGn',alpha=0.7,leg=T,rnks=FALSE,...){

	require(RColorBrewer)
	require(scales)
	
	if(length(x.locs) != 2 | length(y.locs) != 2) 
		stop('x and y dimensions must be two-element vectors')
	
	if(x.locs[1]<0 | x.locs[2]>1 | y.locs[1]<0 | y.locs[2]>1) 

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mc.int<-function(mod.in,int=NULL,n=10000,int.base=0,plot=T,plot.pts=T,
  plot.poly=T,cols=list('black','green','blue'),round.val=2,val=F){
	
	require(scales)
	
	#variable names from model
	if(is.null(mod.in$call$formula)){
		x.names<-colnames(eval(mod.in$call$x))
		y.names<-colnames(eval(mod.in$call$y))
		x.range<-range(eval(mod.in$call$x))