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Area_elig_v4_19.R
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#load libraries--
library(tigris)
library(leaflet)
library(leaflet.extras)
library(rgeos)
library(readxl)
library(RColorBrewer)
library(tidycensus)
library(rgdal)
library(rgeos)
library(htmltools)
library(spatstat)
library(spdep)
library(arrangements)
library(tidyverse)
#------
#ask users to set working directory
setwd(choose.dir())
workdir<-getwd()
#------
#start Stopwatch
Start<-Sys.time()
#------
#Check to see if state data separation has already been done
if(file.exists(paste(workdir,'/Queue/Queue.rds',sep = ""))==TRUE){
print("States already separated: loading Queue")
Queue<-readRDS(paste(workdir,"/Queue/Queue.rds", sep = ""))
} else {
print("Separating States")
#read USDA area eligability file
shapeData <- readOGR(paste(workdir,"/USDA/",list.files(paste(workdir,"/USDA", sep = ""), pattern = ".shp"),sep = "")) #read shapefile
#------
#Separate data into states
StateData<-list() #create emplyt list to hold states
for (i in seq(1,56,1)){ #separate by FIPS code
if (i %in% c(3,7,14,43,52)){
print(paste('Skip non-state:', i))
} else {
print(i)
StateData[[i]]<-subset.data.frame(shapeData,shapeData$STATEFP == str_pad(paste(as.character(i)),2,side='left',pad = "0"))
if(dir.exists(paste(workdir,'/Queue', sep = ""))){
#print("dir exists")
} else{
print("creating queue")
dir.create(paste(workdir,'/Queue', sep = ""))
}
saveRDS(StateData[[i]], paste(workdir,'/Queue/', StateData[[i]]$STATEFP[1],".rds",sep = "")) #save as indivigal states
}
}
#saveRDS(StateData, paste(workdir,"/USDA/StateData.rds", sep = "")) #save RDS to USDA folder
rm(shapeData)
Queue<-list() #create a queue, with name, FIPS, and file location
for (i in seq(1,56,1)){ #separate by FIPS code
if (i %in% c(3,7,14,43,52)){
print(paste('Skip non-state:', i))
} else {
print(paste('Queueing:', i))
st<-data.frame(
FIPS=str_pad(paste(as.character(i)),2,side='left',pad = "0"),
Name=gsub(" ", x=as.character(unique(unlist(StateData[[i]]$State))), replacement = "_"),
File=paste(workdir,'/Queue/', StateData[[i]]$STATEFP[1],".rds",sep = ""),
Done=0
)
Queue[[i]]<-st
rm(st)
}
}
saveRDS(Queue, paste(workdir,'/Queue/Queue.rds',sep = ""))
rm(StateData)
}
#------
calculations<-function(FIPS, state, Threshold){
#generate a list of touching group blocks
neighbor<-poly2nb(state, queen = TRUE)
#------
#Drop polygons and keep data
state<-data.frame(state)
#------
#Embed neighbor index values into Dataframe
state$neighbors<-neighbor
#------
#set threshold value
#Threshold=40
#------
#Create subsets of the dataframe to keep only items that are not eligable and meet the threshold
state_Thresh<-subset.data.frame(state, state$Pct18BG>=Threshold | state$Pct12BG >=Threshold)
state_Thresh_no<-subset.data.frame(state_Thresh, state_Thresh$ELIGFY19=="No")
#------
#Drop neighbors that do not meet the threshold - keep as index values, to change to GEOIDS use FY19_Thresh_no$neighborsGEOID[[i]]
for(i in seq(1, length(state_Thresh_no$neighbors),1)){
print(i)
state_Thresh_no$neighborsThresh[i]<-list(state$GEOID[state_Thresh_no$neighbors[[i]]] %in% state_Thresh$GEOID_1)
if(length(subset(state_Thresh_no$neighbors[[i]], state$GEOID[state_Thresh_no$neighbors[[i]]] %in% state_Thresh$GEOID_1))<1){
state_Thresh_no$neighborsThresh[i]<-0
} else{
state_Thresh_no$neighborsThresh[i]<-list(subset(state_Thresh_no$neighbors[[i]], state$GEOID[state_Thresh_no$neighbors[[i]]] %in% state_Thresh$GEOID_1))
}
}
#------
#Create count of neighbors
for(i in seq(1, length(state_Thresh_no$neighbors),1)){
if(state_Thresh_no$neighborsThresh[[i]][1]==0){
print(0)
state_Thresh_no$Ncount[i]<-0
} else{
print(length(state_Thresh_no$neighborsThresh[[i]]))
state_Thresh_no$Ncount[i]<-length(state_Thresh_no$neighborsThresh[[i]])
}
}
#------
#Subset threshold table to only those that have testable neighbors
state_Thresh_Testable<-subset.data.frame(state_Thresh_no, state_Thresh_no$Ncount>0)
#------
#create list of combinations to test as well as a count for the number of combinations
for( i in seq(1, length(state_Thresh_Testable$Ncount),1)){
#print(i)
if (state_Thresh_Testable$Ncount[i] >=2){
print(state_Thresh_Testable$Ncount[i])
state_Thresh_Testable$test_Combo[i]<-list(arrangements::combinations(state_Thresh_Testable$neighborsThresh[[i]],2, replace = FALSE))
} else{
state_Thresh_Testable$test_Combo[i]<-list(0)
}
state_Thresh_Testable$test_NCombo[i]<-round(length(state_Thresh_Testable$test_Combo[[i]])/2,0)
}
#------
#Preallocate rows to hold results
dt1 <- data.frame(GEOID=rep(0,sum(state_Thresh_Testable$Ncount)),
ID18=rep(0,sum(state_Thresh_Testable$Ncount)),
Pop18=rep(0,sum(state_Thresh_Testable$Ncount)),
Perc18=rep(0,sum(state_Thresh_Testable$Ncount)),
ID12=rep(0,sum(state_Thresh_Testable$Ncount)),
Pop12=rep(0,sum(state_Thresh_Testable$Ncount)),
Perc12=rep(0,sum(state_Thresh_Testable$Ncount)),
firstGEOID=rep(0,sum(state_Thresh_Testable$Ncount)),
firstID18=rep(0,sum(state_Thresh_Testable$Ncount)),
firstPop18=rep(0,sum(state_Thresh_Testable$Ncount)),
firstPerc18=rep(0,sum(state_Thresh_Testable$Ncount)),
firstID12=rep(0,sum(state_Thresh_Testable$Ncount)),
firstPop12=rep(0,sum(state_Thresh_Testable$Ncount)),
firstPerc12=rep(0,sum(state_Thresh_Testable$Ncount)),
secondGEOID=rep(0,sum(state_Thresh_Testable$Ncount)),
secondID18=rep(0,sum(state_Thresh_Testable$Ncount)),
secondPop18=rep(0,sum(state_Thresh_Testable$Ncount)),
secondPerc18=rep(0,sum(state_Thresh_Testable$Ncount)),
secondID12=rep(0,sum(state_Thresh_Testable$Ncount)),
secondPop12=rep(0,sum(state_Thresh_Testable$Ncount)),
secondPerc12=rep(0,sum(state_Thresh_Testable$Ncount))
)
#------
#build list of single neighbor results
for ( i in seq(1,length(state_Thresh_Testable$GEOID_1),1)){
print(i)
for(n in seq(1,state_Thresh_Testable$Ncount[i],1)){
print(n)
row<-which(dt1$GEOID==0)[1] #find first row that has 0 in GEOID
dt1$GEOID[row]<-as.character(state_Thresh_Testable$GEOID[i])
dt1$ID18[row]<-as.numeric(as.character(state_Thresh_Testable$Num18BG[i]))
dt1$Pop18[row]<-as.numeric(as.character(state_Thresh_Testable$TotPovUniv[i]))
dt1$Perc18[row]<-as.numeric(as.character(state_Thresh_Testable$Pct18BG[i]))
dt1$ID12[row]<-as.numeric(as.character(state_Thresh_Testable$Num12BG[i]))
dt1$Pop12[row]<-as.numeric(as.character(state_Thresh_Testable$TotPovUn_1[i]))
dt1$Perc12[row]<-as.numeric(as.character(state_Thresh_Testable$Pct12BG[i]))
dt1$firstGEOID[row]<-as.character(state$GEOID_1[state_Thresh_Testable$neighborsThresh[[i]][n]])
dt1$firstID18[row]<-as.numeric(as.character(state$Num18BG[state_Thresh_Testable$neighborsThresh[[i]][n]]))
dt1$firstPop18[row]<-as.numeric(as.character(state$TotPovUniv[state_Thresh_Testable$neighborsThresh[[i]][n]]))
dt1$firstPerc18[row]<-as.numeric(as.character(state$Pct18BG[state_Thresh_Testable$neighborsThresh[[i]][n]]))
dt1$firstID12[row]<-as.numeric(as.character(state$Num12BG[state_Thresh_Testable$neighborsThresh[[i]][n]]))
dt1$firstPop12[row]<-as.numeric(as.character(state$TotPovUn_1[state_Thresh_Testable$neighborsThresh[[i]][n]]))
dt1$firstPerc12[row]<-as.numeric(as.character(state$Pct12BG[state_Thresh_Testable$neighborsThresh[[i]][n]]))
#dt1$secondGEOID<-0
#dt1$secondID18<-0
#dt1$secondPop18<-0
#dt1$secondPerc18<-0
#dt1$secondNum12<-0
#dt1$secondPop12<-0
#dt1$secondPerc12<-0
}
}
#------
#calculate weighted averages for single neighbors
dt1$weight_ID18<-dt1$ID18+dt1$firstID18
dt1$weight_Pop18<-dt1$Pop18+dt1$firstPop18
dt1$weight_ID12<-dt1$ID12+dt1$firstID12
dt1$weight_Pop12<-dt1$Pop12+dt1$firstPop12
dt1$weight_Perc18<-dt1$weight_ID18/dt1$weight_Pop18
dt1$weight_Perc12<-dt1$weight_ID12/dt1$weight_Pop12
#------
#Filter to only those items that are above 50% with percents above the threshold
Single18<-subset.data.frame(dt1, dt1$weight_Perc18 >=0.5 & dt1$Perc18 >=Threshold & dt1$firstPerc18 >=Threshold)
Single12<-subset.data.frame(dt1, dt1$weight_Perc12 >=0.5 & dt1$Perc12 >=Threshold & dt1$firstPerc12 >=Threshold)
#------
#Combine Single above thresh into one list and remove duplicates
Single<-rbind.data.frame(Single18, Single12)
Single<-Single[!duplicated(Single$GEOID),]
#------
#Create list of areas that were not found to be eligable
'%notin%'<- Negate(`%in%`) #create notin function to negate in operator
secondCalc<- subset.data.frame(state_Thresh_Testable, state_Thresh_Testable$GEOID_1 %notin% Single$GEOID)
#------
#Preallocate rows to hold results
dt2 <- data.frame(GEOID=rep(0,sum(secondCalc$test_NCombo)),
ID18=rep(0,sum(secondCalc$test_NCombo)),
Pop18=rep(0,sum(secondCalc$test_NCombo)),
Perc18=rep(0,sum(secondCalc$test_NCombo)),
ID12=rep(0,sum(secondCalc$test_NCombo)),
Pop12=rep(0,sum(secondCalc$test_NCombo)),
Perc12=rep(0,sum(secondCalc$test_NCombo)),
firstGEOID=rep(0,sum(secondCalc$test_NCombo)),
firstID18=rep(0,sum(secondCalc$test_NCombo)),
firstPop18=rep(0,sum(secondCalc$test_NCombo)),
firstPerc18=rep(0,sum(secondCalc$test_NCombo)),
firstID12=rep(0,sum(secondCalc$test_NCombo)),
firstPop12=rep(0,sum(secondCalc$test_NCombo)),
firstPerc12=rep(0,sum(secondCalc$test_NCombo)),
secondGEOID=rep(0,sum(secondCalc$test_NCombo)),
secondID18=rep(0,sum(secondCalc$test_NCombo)),
secondPop18=rep(0,sum(secondCalc$test_NCombo)),
secondPerc18=rep(0,sum(secondCalc$test_NCombo)),
secondID12=rep(0,sum(secondCalc$test_NCombo)),
secondPop12=rep(0,sum(secondCalc$test_NCombo)),
secondPerc12=rep(0,sum(secondCalc$test_NCombo))
)
#------
#build list of double neighbor results
for ( i in seq(1,length(secondCalc$GEOID),1)){
print(i)
if(secondCalc$test_NCombo[i]==0){
print('skip')
} else{
for(n in seq(1,secondCalc$test_NCombo[i],1)){
print(n)
row<-which(dt2$GEOID==0)[1] #find first row that has 0 in GEOID
dt2$GEOID[row]<-as.character(secondCalc$GEOID[i])
dt2$ID18[row]<-as.numeric(as.character(secondCalc$Num18BG[i]))
dt2$Pop18[row]<-as.numeric(as.character(secondCalc$TotPovUniv[i]))
dt2$Perc18[row]<-as.numeric(as.character(secondCalc$Pct18BG[i]))
dt2$ID12[row]<-as.numeric(as.character(secondCalc$Num12BG[i]))
dt2$Pop12[row]<-as.numeric(as.character(secondCalc$TotPovUn_1[i]))
dt2$Perc12[row]<-as.numeric(as.character(secondCalc$Pct12BG[i]))
dt2$firstGEOID[row]<-as.character(state$GEOID_1[secondCalc$test_Combo[[i]][n,1]])
dt2$firstID18[row]<-as.numeric(as.character(state$Num18BG[secondCalc$test_Combo[[i]][n,1]]))
dt2$firstPop18[row]<-as.numeric(as.character(state$TotPovUniv[secondCalc$test_Combo[[i]][n,1]]))
dt2$firstPerc18[row]<-as.numeric(as.character(state$Pct18BG[secondCalc$test_Combo[[i]][n,1]]))
dt2$firstID12[row]<-as.numeric(as.character(state$Num12BG[secondCalc$test_Combo[[i]][n,1]]))
dt2$firstPop12[row]<-as.numeric(as.character(state$TotPovUn_1[secondCalc$test_Combo[[i]][n,1]]))
dt2$firstPerc12[row]<-as.numeric(as.character(state$Pct12BG[secondCalc$test_Combo[[i]][n,1]]))
dt2$secondGEOID[row]<-as.character(state$GEOID_1[secondCalc$test_Combo[[i]][n,2]])
dt2$secondID18[row]<-as.numeric(as.character(state$Num18BG[secondCalc$test_Combo[[i]][n,2]]))
dt2$secondPop18[row]<-as.numeric(as.character(state$TotPovUniv[secondCalc$test_Combo[[i]][n,2]]))
dt2$secondPerc18[row]<-as.numeric(as.character(state$Pct18BG[secondCalc$test_Combo[[i]][n,2]]))
dt2$secondID12[row]<-as.numeric(as.character(state$Num12BG[secondCalc$test_Combo[[i]][n,2]]))
dt2$secondPop12[row]<-as.numeric(as.character(state$TotPovUn_1[secondCalc$test_Combo[[i]][n,2]]))
dt2$secondPerc12[row]<-as.numeric(as.character(state$Pct12BG[secondCalc$test_Combo[[i]][n,2]]))
}
}
}
#------
#calculate weighted averages for double neighbors
dt2$weight_ID18<-dt2$ID18+dt2$firstID18+dt2$secondID18
dt2$weight_Pop18<-dt2$Pop18+dt2$firstPop18+dt2$secondPop18
dt2$weight_ID12<-dt2$ID12+dt2$firstID12+dt2$secondID12
dt2$weight_Pop12<-dt2$Pop12+dt2$firstPop12+dt2$secondPop12
dt2$weight_Perc18<-dt2$weight_ID18/dt2$weight_Pop18
dt2$weight_Perc12<-dt2$weight_ID12/dt2$weight_Pop12
#------
#Filter to only those items that are above 50% with percents above the threshold
Double18<-subset.data.frame(dt2, dt2$weight_Perc18 >=0.5 & dt2$Perc18 >=Threshold & dt2$firstPerc18 >=Threshold & dt2$secondPerc18 >=Threshold)
Double12<-subset.data.frame(dt2, dt2$weight_Perc12 >=0.5 & dt2$Perc12 >=Threshold & dt2$firstPerc12 >=Threshold & dt2$secondPerc12 >=Threshold)
#------
#Combine double above thresh into one list and remove duplicates
Double<-rbind.data.frame(Double18, Double12)
Double<-Double[!duplicated(Double$GEOID),]
#------
#Combine all calcualted areas above the thresholds into one list
All_calc<-rbind(Single, Double)
#------
#Create Combined data frame of all USDA data and newly calculated fields
Merged<-merge.data.frame(state, All_calc, by.x = 'GEOID_1', by.y = 'GEOID', all.x = TRUE)
Merged[is.na(Merged)] <- 0
#------
#get shapefiles for cartographic boundries
STBlockGCB<-block_groups(FIPS,cb=TRUE)
#------
#Drop extra data
STBlockGCB@data$STATEFP<-NULL
STBlockGCB@data$COUNTYFP<-NULL
STBlockGCB@data$TRACTCE<-NULL
STBlockGCB@data$BLKGRPCE<-NULL
STBlockGCB@data$AFFGEOID<-NULL
STBlockGCB@data$NAME<-NULL
STBlockGCB@data$LSAD<-NULL
STBlockGCB@data$ALAND<-NULL
STBlockGCB@data$AWATER<-NULL
#------
#Join calculated data and polygons
StateCalc<-geo_join(STBlockGCB, Merged, by_sp= 'GEOID', by_df= 'GEOID_1', how='left')
#------
return(StateCalc)
}
BuildMap<-function(BGYes, BGNo, BGCalc){
#build Map
map <- leaflet() %>%
enableTileCaching() %>% addProviderTiles(providers$OpenStreetMap.BlackAndWhite, group = "Grey")
map<- map %>%
addMapPane("plotT", zIndex = 410) %>%
addMapPane("QMi", zIndex = 420) %>%
addMapPane("BlockG", zIndex = 430) %>%
addMapPane("The", zIndex = 480) %>%
addMapPane("top", zIndex = 490)
map<- map %>% addPolygons(data=BGYes,
weight = 1,
fill = TRUE,
fillOpacity = 0.2,
fillColor = "red",#~BlockGYes(Pct18BG),
stroke = TRUE,
color = "black",
label = paste("Est. Eligable: ", as.character(BGYes$Pct18BG),"%", sep=""),
options = leafletOptions(pane = "BlockG"),
popup = paste('<b>Elig</b>: Eligable<br>',
'<b>GEOID:</b>', as.character(BGYes$GEOID), '<br>',
'<b>Identified Under 18:</b>', as.character(BGYes$Num18BG), '<br>',
'<b>Total Under 18:</b>', as.character(BGYes$TotPovUniv), '<br>',
'<b>Under 18 Percent:</b>', as.character(BGYes$Pct18BG), '<br>',
'<b>Identified Under 12:</b>', as.character(BGYes$Num12BG), '<br>',
'<b>Total Under 12:</b>', as.character(BGYes$TotPovUn_1), '<br>',
'<b>Under 12 Percent:</b>', as.character(BGYes$Pct12BG), '<br>'),
# popup = paste("<b>FIPS:</b> ",as.character(BGYes$GEOID),
# "<br><b> Eligable:</b> ", as.character(BGYes$Pct18BG), "%",
# "<br><b> Population:</b> ", BGYes$TotPovUniv,
# "<br><b> Est. Under 18 Eligable:</b> ", BGYes$Num18BG,
# #"<br><b> Coverage:</b> ", round(BGYes$CoverArea*100,2),"%",
# '<br><b> Area elig:</b> ', as.character(BGYes$ELIGFY20), sep=""),
labelOptions = labelOptions(style = list("font-size" = "16px")),
group = 'BlockG',
highlight = highlightOptions(weight = 5,
color = "Red",
bringToFront = TRUE))
map<- map %>% addPolygons(data=BGNo,
weight = 1,
fill = TRUE,
fillOpacity = 0.2,
fillColor = "blue",#~BlockGNo(Pct18BG),
stroke = TRUE,
color = "black",
label = paste("Est. Eligable: ", as.character(BGNo$Pct18BG),"%", sep=""),
options = leafletOptions(pane = "BlockG"),
popup = paste('<b>Elig</b>: Not Eligable<br>',
'<b>GEOID:</b>', as.character(BGNo$GEOID), '<br>',
'<b>Identified Under 18:</b>', as.character(BGNo$Num18BG), '<br>',
'<b>Total Under 18:</b>', as.character(BGNo$TotPovUniv), '<br>',
'<b>Under 18 Percent:</b>', as.character(BGNo$Pct18BG), '<br>',
'<b>Identified Under 12:</b>', as.character(BGNo$Num12BG), '<br>',
'<b>Total Under 12:</b>', as.character(BGNo$TotPovUn_1), '<br>',
'<b>Under 12 Percent:</b>', as.character(BGNo$Pct12BG), '<br>'),
labelOptions = labelOptions(style = list("font-size" = "16px")),
group = 'BlockG',
highlight = highlightOptions(weight = 5,
color = "Red",
bringToFront = TRUE))
map<- map %>% addPolygons(data=BGCalc,
weight = 1,
fill = TRUE,
fillOpacity = 0.3,
fillColor = "orange",
stroke = TRUE,
color = "black",
label = paste("Calc Eligable"),
options = leafletOptions(pane = "BlockG"),
# popup = paste("<b>FIPS:</b> ",as.character(BGCalc$GEOID),
# "<br><b> Self Eligable:</b> ", as.character(BGCalc$Pct18BG), "%",
# "<br><b> Population:</b> ", BGCalc$TotPovUniv,
# "<br><b> Est. Under 18 Eligable:</b> ", BGCalc$Num18BG,
# #"<br><b> Coverage:</b> ", round(BGCalc$CoverArea*100,2),"%",
# '<br><b> Area elig:</b> ', "Calculated Yes",
# '<br><b> Calc Block 1:</b> ', BGCalc$firstGEOID,
# '<br><b> Calc Block 2:</b> ', BGCalc$secondGEOID,
# sep=""),
popup = paste('<b>Elig</b>: Calculation Eligable<br>',
'<b>GEOID:</b>', as.character(BGCalc$GEOID), '<br>',
'<b>Identified Under 18:</b>', as.character(BGCalc$Num18BG), '<br>',
'<b>Total Under 18:</b>', as.character(BGCalc$TotPovUniv), '<br>',
'<b>Under 18 Percent:</b>', as.character(BGCalc$Pct18BG), '<br>',
'<b>Identified Under 12:</b>', as.character(BGCalc$Num12BG), '<br>',
'<b>Total Under 12:</b>', as.character(BGCalc$TotPovUn_1), '<br>',
'<b>Under 12 Percent:</b>', as.character(BGCalc$Pct12BG), '<br><hr>',
'<b><center>Calculation</center></b><hr>',
'<table border="1">
<tr>
<th style="background-color:#c5d9d5;" align="center">GEOID</th>
<th style="background-color:#c5d9d5;" align="center">Under 18</th>
<th style="background-color:#c5d9d5;" align="center">18 pop</th>
<th style="background-color:#c5d9d5;" align="center">18 perc</th>
<th style="background-color:#c5d9d5;" align="center">Under 12</th>
<th style="background-color:#c5d9d5;" align="center">12 pop</th>
<th style="background-color:#c5d9d5;" align="center">12 perc</th>
</tr>
<tbody>
<tr>
<td align="center">',BGCalc$firstGEOID,'</td>
<td align="center">',BGCalc$firstID18,'</td>
<td align="center">',BGCalc$firstPop18,'</td>
<td align="center">',BGCalc$firstPerc18,'</td>
<td align="center">',BGCalc$firstID12,'</td>
<td align="center">',BGCalc$firstPop12,'</td>
<td align="center">',BGCalc$firstPerc12,'</td>
</tr>
<tr>
<td align="center">', BGCalc$secondGEOID, '</td>
<td align="center">', BGCalc$secondID18, '</td>
<td align="center">', BGCalc$secondPop18, '</td>
<td align="center">', BGCalc$secondPerc18, '</td>
<td align="center">', BGCalc$secondID12, '</td>
<td align="center">', BGCalc$secondPop12, '</td>
<td align="center">', BGCalc$secondPerc12, '</td>
</tr>
<tr>
<td style="background-color:#f7daad;" align="center">Totals</td>
<td style="background-color:#f7daad;" align="center">', BGCalc$weight_ID18, '</td>
<td style="background-color:#f7daad;" align="center">', BGCalc$weight_Pop18, '</td>
<td style="background-color:#f7daad;" align="center">', "", '</td>
<td style="background-color:#f7daad;" align="center">', BGCalc$weight_ID12, '</td>
<td style="background-color:#f7daad;" align="center">', BGCalc$weight_Pop12, '</td>
<td style="background-color:#f7daad;" align="center">', "", '</td>
</tr>
</tbody>
</table>',
'<b>Weighted % under 18:</b>', round(BGCalc$weight_Perc18*100,2), '<br>',
'<b>Weighted % under 12:</b>', round(BGCalc$weight_Perc12*100,2), '<br>'),
labelOptions = labelOptions(style = list("font-size" = "16px")),
group = 'BlockG',
highlight = highlightOptions(weight = 5,
color = "Red",
bringToFront = TRUE))
map <- map %>% addLegend(position = "bottomright",
labels = c("USDA Eligible","Calculated Eligible", "Ineligible"),
colors = c('red','yellow','blue'),
opacity = 0.5,
title = 'Color Code',
group = 'BlockG')
map <- map %>% addSearchOSM(options = searchOptions(autoCollapse = TRUE, minLength = 2))
return(map)
}
#Read queue, find next item, load RDS, run calc function, generate output
Data<-data.frame()
for (i in seq(1,56,1)){ #separate by FIPS code
if (i %in% c(3,7,14,43,52)){
print(paste('Skip non-state:', i))
} else {
if(Queue[[i]]$Done[1]==1){
print("Done")
} else{
print("To Be Done")
Start_state<-Sys.time()
state<-readRDS(as.character(Queue[[i]]$File[1]))
FIPS<-as.character(Queue[[i]]$FIPS[1])
Output<-calculations(FIPS, state, 40)
Output$CalcElig<-ifelse(Output$ID18 >0, "1", "0")
CalcAreas<-data.frame(Output[c('GEOID','CalcElig')])
if(dir.exists(paste(workdir,'/Done', sep = ""))){
#print("dir exists")
} else{
print("creating output directory")
dir.create(paste(workdir,'/Done', sep = ""))
}
setwd(paste(workdir,'/done/',sep = ""))
write.csv(CalcAreas, paste(as.character(Queue[[i]]$FIPS[1]),"_",as.character(Queue[[i]]$Name[1]),"_Calc.csv",sep = ""), row.names = FALSE)
setwd(workdir)
print('Saving calculation output')
saveRDS(Output, paste(workdir,'/done/', as.character(Queue[[i]]$FIPS[1]),"_",as.character(Queue[[i]]$Name[1]),"_Calc.rds",sep = "")) #save calc output
print("separating and building map")
BGYes<-subset.data.frame(Output, Output$ELIGFY19=='Yes')
BGNo<-subset.data.frame(Output, Output$ELIGFY19=='No')
BGCalc<-subset.data.frame(BGNo, BGNo$weight_Perc18>=0.5 | BGNo$weight_Perc12>=0.5)
BGNo<-subset.data.frame(BGNo, BGNo$weight_Perc18<0.5 & BGNo$weight_Perc12<0.5)
maps<-BuildMap(BGYes,BGNo,BGCalc)
print('Saving Map')
setwd(paste(workdir,'/done/',sep = ""))
htmlwidgets::saveWidget(maps,file = paste(as.character(Queue[[i]]$FIPS[1]),"_",as.character(Queue[[i]]$Name[1]),"_Calc.html",sep = ""), selfcontained = TRUE)
setwd(workdir)
End_state<-Sys.time()
Queue[[i]]$BG_Yes_Areas[1]<-length(BGYes$Num18BG)
Queue[[i]]$BG_Yes_ID18[1]<-sum(as.numeric(as.character(BGYes$Num18BG)))
Queue[[i]]$BG_No_Areas[1]<-length(BGNo$Num18BG)
Queue[[i]]$BG_No_ID18[1]<-sum(as.numeric(as.character(BGNo$Num18BG)))
Queue[[i]]$BG_Calc_Areas[1]<-length(BGCalc$Num18BG)
Queue[[i]]$BG_Calc_ID18[1]<-sum(as.numeric(as.character(BGCalc$Num18BG)))
Queue[[i]]$ElapsedTime[1]<-as.numeric(difftime(End_state, Start_state, units = "secs"))
rm(Output, BGYes, BGNo, BGCalc, maps)
Queue[[i]]$Done<-1
Data<-rbind(Data, Queue[[i]])
}
}
}
Data<-subset.data.frame(Data, is.na(Data$Name)==FALSE)
write.csv(Data, "Data.csv", row.names = FALSE)
#grep("B", colnames(df)) #ets column undex for match of text
#Stop stopwatch
End<-Sys.time()
print(End-Start)
#------