library('ggmap')
library('ggplot2')
library('geosphere')
library('curl')
library('stringr')
library('PostcodesioR')
library('qdapTools')

options(width=200)

df=read.csv('mb.csv', header=FALSE)

df=df[!(df$V2>2000),]

match=read.csv('postcodes2.csv',header=TRUE)
match2=read.csv('LSOA2011_AvPTAI2015.csv',header=TRUE)

match=subset(match,select=c(Postcode,LSOA.Code))
match2=subset(match2,select=c(LSOA2011,AvPTAI2015))

#head(match)

df$postcode <- NA 
for (i in c(1:length(df[,1]))){
  lat=df[i,]$V3
  lon= df[i,]$V4
  df[i,]$postcode = reverse_geocoding(lon, lat)[[1]][[1]]   
}

#head(df)

df$lsoa = lookup(df$postcode,match)
#head(df)

df$AvPTAI = lookup(df$lsoa,match2)

df=df[complete.cases(df), ]

df[order(df$AvPTAI, decreasing = FALSE), ]

df=df[- grep("Croydon", df$V1),]

#df$V2
#df$AvPTAI

pdf('go.pdf')

ggplot(df, aes(y=as.numeric(V2), x=as.numeric(AvPTAI)))+geom_point()

dev.off()
#head(df)



#for (i in c(1:length(df[,1]))){
#  df[i,]$diff = df[1,]$diff=distm(c(df[1,]$V4,df[1,]$V3), c(0, 50), fun = distHaversine)
#}


#df=df[!(df$V2>800),]
#df=df[order(df$V2, decreasing = FALSE), ]



#api='c2cacd59df6bacd1c12d0dab637d93b0'
#lon1=toString(df[3,]$V4)
#print(lon1)
#lat1=toString(df[3,]$V3)
#print(lat1)

#lat2='51.5239'
#lon2='0.1097'


#for (i in c(1:length(df[,1]))){
#for (i in c(1,2)){
#   df[1,]$index = 1
#   time=substr(rawToChar(curl_fetch_memory((gsub(" ","",paste("https://developer.citymapper.com/api/1/traveltime/?startcoord=",toString(df[i,]$V3),"%2C",toString(df[i,]$V4),"&endcoord=",lat2,"%2C",lon2,"&time=2014-11-06T19%3A00%3A02-0500&time_type=arrival&key=",api))))$content),1,26)
#   print(time)
#   print(df[1,]$index)
#}
#   call=(gsub(" ", "", call))
#   req = curl_fetch_memory(call)
#   z=rawToChar(req$content)
#   time = substr(z, 25, 26)
#   df[i,]$time = time
#   df[i,]

#df[i,]$pay = as.numeric(paste( unlist(amort.table(Loan=df[i,]$V7,n=df[i,]$rem,i=((df[i,]$V5/100)/12))[1]))[1])

#call=(gsub(" ", "", call))
#print(call)
#req = curl_fetch_memory(call)
#z=rawToChar(req$content)
#time = substr(z, 25, 26)
#print(time)



#length(df[,1])

#head(df,n=100)



#pdf("mb2.pdf", width=10, height=5)
#ggplot(df, aes(x=V2)) + geom_density()
#scale_x_continuous(limits=c(-10,40))
#dev.off()


#on <- c(-38.31,-35.5)
#lat <- c(40.96, 37.5)
#df <- as.data.frame(cbind(lon,lat))
#df = subset(df, select = c(V3, V4))

# getting the map
#mapgilbert <- get_map(location = c(lon = mean(df$V4), lat = mean(df$V3)), 
#                      zoom = 10,
#                      maptype = "roadmap", 
#                      scale = 4)

# plotting the map with some points on it
#pdf('mbmap.pdf')
#ggmap(mapgilbert) +
#  geom_point(data = df, aes(x = V4, y = V3, fill = "red", alpha = 0.8), size = 5, shape = 21) 
##  guides(fill=FALSE, alpha=FALSE, size=FALSE)
#dev.off()