Merge pull request #178 from ldecicco-USGS/master

Cleaned up map

NAMESPACE

@@ -46,6 +46,7 @@ importFrom(dplyr,group_by_)
 importFrom(dplyr,left_join)
 importFrom(dplyr,mutate)
 importFrom(dplyr,mutate_)
+importFrom(dplyr,n)
 importFrom(dplyr,rename)
 importFrom(dplyr,rename_)
 importFrom(dplyr,right_join)

R/makeMap.R

@@ -6,10 +6,10 @@
 #' @param category either "Biological", "Chemical Class", or "Chemical"
 #' @param chem_site data frame with at least columns SiteID, site_grouping, and Short Name
 #' @param mean_logic logical \code{TRUE} is mean, \code{FALSE} is maximum
-#' @param hit_threshold numeric threshold defining a "hit"
 #' @export
 #' @import ggplot2
 #' @importFrom stats median
+#' @importFrom dplyr n
 #' @importFrom grDevices colorRampPalette
 #' @importFrom leaflet colorBin
 #' @importFrom dplyr full_join filter mutate select left_join right_join
@@ -37,12 +37,11 @@
 getMapInfo <- function(chemicalSummary,
                     chem_site,
                     category = "Biological",
-                    mean_logic = FALSE,
-                    hit_threshold = 0.1){
+                    mean_logic = FALSE){
 
   match.arg(category, c("Biological","Chemical Class","Chemical"))
 
-  site <- nSamples <- `Short Name` <- Fullname <- dec_lat <- dec_lon <- ".dplyr"
+  site <- meanEAR <- nSamples <- `Short Name` <- Fullname <- dec_lat <- dec_lon <- ".dplyr"
 
   siteToFind <- chem_site$`Short Name`
 
@@ -54,42 +53,34 @@ getMapInfo <- function(chemicalSummary,
     typeWords <- "chemical classes"
   }
 
-  statsOfGroupOrdered <- statsOfGroup(chemicalSummary = chemicalSummary,
-                                      category = category,
-                                      hit_threshold = hit_threshold)
-  sumStat <- statsOfColumns(chemicalSummary = chemicalSummary,
-                            category = category,
-                            hit_threshold = hit_threshold,
-                            mean_logic = mean_logic)
+  mapData <- chem_site[,c("Short Name", "dec_lat", "dec_lon", "SiteID")]
 
-  mapData <- left_join(sumStat, distinct(select(statsOfGroupOrdered, site, nSamples)), by="site")
-  mapData <- left_join(mapData, chem_site[,c("Short Name", "dec_lat", "dec_lon")], by=c("site"="Short Name"))
+  nSamples <- select(chemicalSummary,site,date) %>%
+    distinct() %>%
+    group_by(site) %>%
+    summarize(count = n())
 
-  col_types <- c("darkblue","dodgerblue","green4","gold1","orange","brown","red")
+  meanStuff <- graphData(chemicalSummary = chemicalSummary, 
+            category = category, mean_logic = mean_logic) %>%
+    group_by(site) %>%
+    summarize(meanMax = max(meanEAR)) %>%
+    left_join(nSamples, by="site")
 
-  earCols <- grep("EAR", names(mapData))
+  mapData <- left_join(mapData, meanStuff, by=c("SiteID"="site"))
 
-  if(length(earCols) > 1){
-    if(mean_logic){
-      mapData$meanMax <- rowMeans(mapData[,earCols], na.rm = TRUE)
-    } else {
-      mapData$meanMax <- apply(mapData[,earCols], 1, function(x) max(x, na.rm = TRUE))
-    }    
-  } else {
-    mapData$meanMax <- mapData[,earCols]
-  }
+  col_types <- c("darkblue","dodgerblue","green4","gold1","orange","brown","red")
 
-  counts <- mapData$nSamples       
+  counts <- mapData$count       
 
   if(length(siteToFind) > 1){
     leg_vals <- unique(as.numeric(quantile(mapData$meanMax, probs=c(0,0.01,0.1,0.25,0.5,0.75,0.9,.99,1), na.rm=TRUE)))
     pal = colorBin(col_types, mapData$meanMax, bins = leg_vals)
     rad <-3*seq(1,4,length.out = 16)
 
-    if(sum(mapData$nSamples) == 0){
+    if(sum(mapData$count, na.rm = TRUE) == 0){
       mapData$sizes <- rad[1]
     } else {
-      mapData$sizes <- rad[as.numeric(cut(mapData$nSamples, breaks=16))]
+      mapData$sizes <- rad[as.numeric(cut(mapData$count, breaks=16))]
     }
 
   } else {
@@ -100,4 +91,4 @@ getMapInfo <- function(chemicalSummary,
 
   return(list(mapData=mapData, pal=pal))
 
-}
+}

inst/shiny/mapStuff.R

@@ -15,29 +15,15 @@ output$mapFooter <- renderUI({
   )
 
   chemicalSummary <- chemicalSummary()
-  catType = as.numeric(input$radioMaxGroup)
-  meanEARlogic <- as.logical(input$meanEAR)  
-  hit_threshold <- hitThresValue()
 
-  statsOfGroupOrdered <- statsOfGroup(chemicalSummary = chemicalSummary,
-                                      category = c("Biological","Chemical","Chemical Class")[catType],
-                                      hit_threshold = hit_threshold)
-  statsOfGroupOrdered <- statsOfGroupOrdered %>%
+  nSamples <- select(chemicalSummary,site,date) %>%
+    distinct() %>%
     group_by(site) %>%
-    summarize(nSamples = median(nSamples, na.rm = TRUE))
-
-  if(input$radioMaxGroup == "1"){
-    word <- "groups"
-  } else if (input$radioMaxGroup == "2"){
-    word <- "chemicals"
-  } else {
-    word <- "classes"
-  }
+    summarize(count = n())
 
-  HTML(paste0("<h5>Size range represents number of ",word,
-              " with hits. Ranges from ", min(statsOfGroupOrdered$nSamples,na.rm = TRUE),
+  HTML(paste0("<h5>Size range represents number of samples. Ranges from ", min(nSamples$count,na.rm = TRUE),
               " - ", 
-              max(statsOfGroupOrdered$nSamples,na.rm = TRUE),"</h5>"))
+              max(nSamples$count,na.rm = TRUE),"</h5>"))
 
 })
 
@@ -62,27 +48,32 @@ observe({
   mapDataList <- getMapInfo(chemicalSummary, 
                      chem_site = chem_site, 
                      category = c("Biological","Chemical","Chemical Class")[catType],
-                     mean_logic = meanEARlogic,
-                     hit_threshold = hitThresValue())
+                     mean_logic = meanEARlogic)
 
   mapData <- mapDataList$mapData
   pal <- mapDataList$pal
 
   if(length(siteToFind) == 1){
 
     mapData <- filter(chem_site, SiteID == siteToFind) %>%
-      mutate(nSamples = median(mapData$nSamples),
+      mutate(nSamples = median(mapData$count),
              meanMax = median(mapData$meanMax),
              sizes = median(mapData$sizes))
   }
 
   map <- leafletProxy("mymap", data=mapData) %>%
     clearMarkers() %>%
     clearControls() %>%
+    setView(lng = mean(mapData$dec_lon, na.rm = TRUE), 
+            lat = mean(mapData$dec_lat, na.rm = TRUE), zoom=6) %>%
+    fitBounds(lng1 = min(mapData$dec_lon, na.rm = TRUE), 
+              lat1 = min(mapData$dec_lat, na.rm = TRUE), 
+              lng2 = max(mapData$dec_lon, na.rm = TRUE), 
+              lat2 = max(mapData$dec_lat, na.rm = TRUE)) %>%
     addCircleMarkers(lat=~dec_lat, lng=~dec_lon,
                      popup=paste0('<b>',mapData$site,"</b><br/><table>",
                                   "<tr><td>",maxEARWords,": </td><td>",sprintf("%.1f",mapData$meanMax),'</td></tr>',
-                                  "<tr><td>Number of Samples: </td><td>",mapData$nSamples,'</td></tr>',
+                                  "<tr><td>Number of Samples: </td><td>",mapData$count,'</td></tr>',
                                   # "<tr><td>Frequency: </td><td>",sprintf("%.1f",mapData$freq),'</td></tr>',
                                   # "<tr><td>Number of ",typeWords," with hits: </td><td>",counts,'</td></tr>',
                                   '</table>') ,