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global.R
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global.R
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Sys.setenv( ODBCINI="/usr/local/etc/odbc.ini")
Sys.setenv(NZ_ODBC_INI_PATH="/usr/local/etc/")
print(print( R.home()))
## Load Libraries
## Load Libraries
library(shinycssloaders)
library(shiny)
library(shinyjqui)
library(ggmap)
library(dggridR)
library(DBI)
library(dplyr)
library(sf)
#library(shinyBS)
library(leaflet)
#library(leaflet.opacity)
library(leafgl)
#library(mapview)
library(plyr)
#library(geosphere)
library(rgeos)
library(distr)
#library(sp)
#library(rgdal)
library(raster)
library(ggplot2)
library(plotly)
#library(RJSONIO)
library(ggmap)
#library(tmap)
library(tmaptools)
library(dbplyr)
#library(colourvalues)
library(grDevices)
library(hazus)
library(leaflet.extras)
#library(htmlwidgets)
#library(grDevices)
#library(ICSNP)
#library(wicket)
library(leaflet.extras)
library(colourvalues)
## Netezza Connection
con = dbConnect(RNetezza::Netezza(), dsn='NZSQL') ## Already modified for server
#con = dbConnect(RNetezza::Netezza(), dsn='NZSQL_A') ## Mute this when done editing
## Construct
dggs = dgconstruct(res=23, metric=TRUE, resround='nearest', pole_lat_deg = 37,pole_lon_deg =-178)
## Miscellaneous Variables
RPl <- c(1.25,1.5,2.0,2.33,5.0,10.0,25.0,50.0,100.0,200.0,500.0)
RPy <- RPl %>% data.frame()
RPy$RPI <- c(1,2,3,4,5,6,7,8,9,10,11)
names(RPy) <- c("RP", "REPID")
## Load Netezza Tables
riverrp <- tbl(con,"RRP")
catch=tbl(con,"CATCHMENT")
gridf=tbl(con,"GF") %>% filter(RESOLUTION==23)
rivers <- tbl(con,"NETWORK")
hand=tbl(con,"HAND")
rp <- tbl(con,"REP")
stadis <- tbl(con,"STAGEDISCHARGE_GRAND")
## Split tables based on watershed for future use
riverrpG <- filter(riverrp,ZONE=="GrandRiverBasin")
riverrpO <- filter(riverrp,ZONE=="OttawaRiverBasin")
catchG <- filter(catch,ZONE=="GrandRiverBasin")
catchO <- filter(catch,ZONE=="OttawaRiverBasin")
riversG <- filter(rivers,ZONE=="GrandRiverBasin")
riversO <- filter(rivers, ZONE=="OttawaRiverBasin")
handG <- filter(hand,ZONE=="GrandRiverBasin")
handO <- filter(hand,ZONE=="OttawaRiverBasin")
rpG <- filter(rp,ZONE=="GrandRiverBasin")
rpO <- filter(rp,ZONE=="OttawaRiverBasin")
stadisG <- filter(stadis,ZONE=="GrandRiverBasin")
stadisO <- filter(stadis,ZONE=="OttawaRiverBasin")
## catchment polygon
#G <- readOGR("catch.shp") ## Grand River Watershed
#O <- readOGR("OttawaGCS.shp") ## Ottawa River Watershed
#m <- readOGR("mask.shp") ## Global mask
catchGround <- readLines("catchment.geojson") %>% paste(collapse = "\n")
#O <- readOGR("OttawaGCS.shp")
mask <- readLines("mask.geojson") %>% paste(collapse = "\n")
### Function F1: Get discharge bounds, outline, stream network, and midpoint of selected subcatchment
f1 <- function(catidNew,catchment){
catid=catidNew
# Remove selected subcatchment from Grand River watershed polygon
Gnew <- NA
# Gnew <- subset(G,G$cat_id != catid)
if (catchment=="Grand River Watershed"){
### Get discharge bounds based on catchment id
###TODO: check for performance
bounds <- riverrpG %>% filter(CAT_ID==catid)
bounds <- as.data.frame(bounds)
dmin <- mean(bounds$RP1_25,na.rm = TRUE)
dmax <- mean(bounds$RP500,na.rm = TRUE)
### Get rasters for relevant catid
## Catchment polygon
catchmentB <- filter(catchG,CATID==catid) %>% filter(BOUNDARY==1) %>% inner_join(.,gridf,by="DGGID") %>% mutate(.,WKT=inza..ST_AsText(GEOM)) %>% dplyr::select("WKT") %>% collect()
catchmentB <- as.data.frame(catchmentB)
# %>% st_as_sf(., wkt='WKT', crs = 4326)
#catchmentB <- mutate(catchmentP,WKT=inza..ST_AsText(GEOM)) %>% filter(BOUNDARY==1) %>% collect()
#%>% dplyr::select("WKT")
#catchmentB <- catchmentP %>% filter(BOUNDARY==1) ## Catchment boundary only
## River Network lines
rivers2 <- filter(riversG,CATID==catid) %>% inner_join(.,gridf,by="DGGID") %>% mutate(.,WKT=inza..ST_AsText(GEOM)) %>% dplyr::select("WKT") %>% collect()
rivers2 <- as.data.frame(rivers2)
# %>% st_as_sf(., wkt='WKT', crs = 4326)
# Get approximate spatial mean of selected subcatchment to guide map zoom
#i <- mean(catchmentB$I)
#j <- mean(catchmentB$J)
#try <- dgQ2DI_to_GEO(dggs, 5, in_i=i, in_j=j) ##in_quad = 5
lon <- NA
lat <-NA
#bounds <- wkt_bounding(catchmentP$WKT,as_matrix=FALSE)
list <- list("x"=lon, "y"=lat,"catid"=catid,"dmin"=dmin,"dmax"=dmax,"rivers"=rivers2,"boundary"=catchmentB,"Gnew"=Gnew)
return(list)
}
} ## End of F1
### Function F2: Generate flood raster based on discharge input
f2 <- function(con,catid,discharge,catchment){
if (catchment == "Grand River Watershed"){
#name=paste(catid,'.csv', sep = "")
#Data=read.csv(name)
Data <- stadisG %>% filter(CATID==catid) %>% as.data.frame()
RPStage=approx(Data$DISCHARGE, Data$STAGE,discharge, method = "linear")$y
handf=filter(handG,VALUE<RPStage)
catchc=filter(catchG,CATID==catid)
handc=handf%>%inner_join(.,catchc,by="DGGID")%>%inner_join(.,gridf,by="DGGID")
handc=mutate(handc,VALUE1=RPStage-VALUE,WKT=inza..ST_AsText(GEOM))%>%
dplyr::select(DGGID,VALUE=VALUE1,WKT) %>%
collect()
#%>%
print(3)
#chunk=collect(handc)
chunk <<- as.data.frame(handc)
#names(chunk)[2]<-paste("vv")
#names(chunk)[12]<-paste("VALUE")
#chunk <- chunk[,c(1,12,13)]
#FIXME: We need to get rid of the extra columns
#chunk = st_as_sf(chunk, wkt='WKT', crs = 4326)
}
return(chunk)
} ### End of f2
### Function F3: Generate flood raster based on return period input
f3 <- function (con,catid,rps,catchment){
if (catchment == "Grand River Watershed"){
rps <- which(RPl==rps)
#catchc=filter(catch,CATID==catid)
rp2 <- filter(rpG,REPID==rps)%>%filter(CATCHID==catid)
#rp2=rp2%>%inner_join(.,catchc,by="DGGID")%>%inner_join(.,gridf,by="DGGID")
rp2=rp2%>%inner_join(.,gridf,by="DGGID")
rp2=mutate(rp2,WKT=inza..ST_AsText(GEOM)) %>% dplyr::select(DGGID,VALUE,WKT) %>% collect()
#rp2= st_as_sf(rp2, wkt='WKT', crs = 4326)
rp2 <- as.data.frame(rp2)
}
return(rp2)
}
### Function F4: Extract depth value from discharge-based flood raster as clicked-on point
f4 <- function (dggid,catid,discharge,chunk,catchment){
if (catchment == "Grand River Watershed"){
hex <- dggid
rp3 <- filter(rpG,DGGID==hex) %>% collect()
New <- subset(chunk, DGGID==hex)
value <- New$VALUE
rp3 <- arrange(rp3,REPID)
rp3 <- inner_join(rp3,RPy,by="REPID")
if (nrow(rp3) >=2){########## some hexagons in Waterloo catchment only have 1 rp, so I can't interpolate
RetPer <- (approx(rp3$VALUE,rp3$RP,value, method = "linear"))$y
}
else {
RetPer <- rp3$VALUE
}
####
df1 <- data.frame("rp"=rp3$RP,"Depth"=rp3$VALUE) ## Depths for all return periods
df2 <- data.frame("rp"=RetPer,"Depth"=value) ## Depth for the clicked point, selected discharge only
list <- list("value"=value,"df1"=df1,"df2"=df2)
}
return (list)
}
### Function F5: Extract depth value from return period-based flood raster as clicked-on point
f5 <- function(dggid,catid,rpI,catchment){
if (catchment == "Grand River Watershed"){
hex <- dggid
rp4 <- filter(rpG,DGGID==hex) %>% collect()
rp4 <- inner_join(rp4,RPy,by="REPID") %>% arrange(REPID)
rowN <- which(rp4$RP==rpI)
depth <- as.numeric(rp4[rowN,1])
df2 <- data.frame("rp"=rpI,"Depth"=depth) ## Depth for the clicked point, selected RP only
list <- list("value"=depth,"df1"=rp4,"df2"=df2)
}
return (list)
}
## Generate RGB palette for discharge-based flood raster depth values
value_rgbD=function(df,cmin,cmax){
list=c(df$VALUE,cmin,cmax)
cols = colour_values_rgb(list, palette="Reds",include_alpha = FALSE) / 255
cols=cols[1:(dim(cols)[1]-2),]
return(cols)
}
# Generate RGB palette for return period-based flood raster depth values
value_rgbR=function(df,cmin,cmax){
list=c(df$VALUE,cmin,cmax)
cols = colour_values_rgb(list, palette="Reds",include_alpha = FALSE) / 255
cols=cols[1:(dim(cols)[1]-2),]
return(cols)
}
## Get fl_dept (Hazus depth-damage)
fl_dept <- extract_hazus_functions()
haz_fl_occ <- haz_fl_occ
haz_fl_occ$Desc1_2 <- paste(haz_fl_occ$Occ_Desc1,haz_fl_occ$Occ_Desc2)
fl_dept$Depthm <- fl_dept$depth / 3.2808
addGlGeojsonPolygons = function(map,
data,
color = cbind(0, 0.2, 1),
fillColor = color,
opacity = 0.8,
fillOpacity = 0.6,
group = "glpolygons",
popup = NULL,
layerId = NULL,
src = FALSE,
...) {
## currently leaflet.glify only supports single (fill)opacity!
opacity = opacity[1]
fillOpacity = fillOpacity[1]
if (is.null(group)) group = deparse(substitute(data))
#if (inherits(data, "Spatial")) data <- sf::st_as_sf(data)
#stopifnot(inherits(sf::st_geometry(data), c("sfc_POLYGON", "sfc_MULTIPOLYGON")))
# if (inherits(sf::st_geometry(data), "sfc_MULTIPOLYGON"))
# stop("Can only handle POLYGONs, please cast your MULTIPOLYGON to POLYGON using sf::st_cast",
# call. = FALSE)
#bounds = as.numeric(sf::st_bbox(data))
# fillColor
args <- list(...)
palette = "viridis"
if ("palette" %in% names(args)) {
palette <- args$palette
args$palette = NULL
}
fillColor <- leafgl:::makeColorMatrix(fillColor, data, palette = palette)
if (ncol(fillColor) != 3) stop("only 3 column fillColor matrix supported so far")
fillColor = as.data.frame(fillColor, stringsAsFactors = FALSE)
colnames(fillColor) = c("r", "g", "b")
# cols = jsonlite::toJSON(fillColor)
cols = jsonify::to_json(fillColor, digits = 3)
# # popup
# if (is.null(popup)) {
# # geom = sf::st_transform(sf::st_geometry(data), crs = 4326)
# geom = sf::st_geometry(data)
# data = sf::st_sf(id = 1:length(geom), geometry = geom)
# } else if (isTRUE(popup)) {
# data = data[, popup]
# } else {
# htmldeps <- htmltools::htmlDependencies(popup)
# if (length(htmldeps) != 0) {
# map$dependencies = c(
# map$dependencies,
# htmldeps
# )
# }
# popup = makePopup(popup, data)
# popup = jsonify::to_json(popup)
# geom = sf::st_geometry(data)
# data = sf::st_sf(id = 1:length(geom), geometry = geom)
# }
# data
# if (length(args) == 0) {
# geojsonsf_args = NULL
# } else {
# geojsonsf_args = try(
# match.arg(
# names(args)
# , names(as.list(args(geojsonsf::sf_geojson)))
# , several.ok = TRUE
# )
# , silent = TRUE
# )
# if (inherits(geojsonsf_args, "try-error")) geojsonsf_args = NULL
# if (identical(geojsonsf_args, "sf")) geojsonsf_args = NULL
# }
# data = do.call(geojsonsf::sf_geojson, c(list(data), args[geojsonsf_args]))
# data = geojsonsf::sf_geojson(data, ...)
# dependencies
map$dependencies = c(
leafgl:::glifyDependencies()
, map$dependencies
)
map = leaflet::invokeMethod(
map
, leaflet::getMapData(map)
, 'addGlGeojsonPolygons'
, data
, cols
, popup
, fillOpacity
, group
, layerId
)
}
addGeoJSONv3 = function(
map, geojson, layerId = NULL, group = NULL,
markerType = NULL, markerIcons = NULL,
markerIconProperty = NULL, markerOptions = leaflet::markerOptions(),
clusterOptions = NULL, clusterId = NULL,
labelProperty = NULL, labelOptions = leaflet::labelOptions(),
popupProperty = NULL, popupOptions = leaflet::popupOptions(),
stroke = TRUE,
color = "#03F",
weight = 5,
opacity = 0.5,
fill = TRUE,
fillColor = color,
fillOpacity = 0.2,
dashArray = NULL,
smoothFactor = 1.0,
noClip = FALSE,
pathOptions = leaflet::pathOptions(),
highlightOptions = NULL
) {
leaflet.extras:::invokeJSAddMethod("addGeoJSONv3",
map, geojson, layerId, group,
markerType, markerIcons,
markerIconProperty, markerOptions,
clusterOptions, clusterId,
labelProperty, labelOptions, popupProperty, popupOptions,
stroke,
color,
weight,
opacity,
fill,
fillColor,
fillOpacity,
dashArray,
smoothFactor,
noClip,
pathOptions, highlightOptions)
}
setCatID = function(
map, catid
) {
leaflet.extras:::invokeJSAddMethod("setCatID",
map, catid)
}