summariseRSUs, fixed with dplyr::summarise

R/plotSummarisedRSUs.R

@@ -0,0 +1,57 @@
+plotSummarisedRSUs<-function(longSf, workflows = c("osm", "bdt", "iau", "wudapt"), plot = TRUE, locations = NULL, graphPath = ""){
+  print(locations)
+  colorMap<-c("#8b0101","#cc0200","#fc0001","#be4c03","#ff6602","#ff9856",
+              "#fbed08","#bcbcba","#ffcca7","#57555a","#006700","#05aa05",
+              "#648423","#bbdb7a","#010101","#fdf6ae","#6d67fd", NA)
+  names(colorMap)<-as.character(c(1:10,101:107, NA))
+  etiquettes<-c("LCZ 1: Compact high-rise","LCZ 2: Compact mid-rise","LCZ 3: Compact low-rise",
+                "LCZ 4: Open high-rise","LCZ 5: Open mid-rise","LCZ 6: Open low-rise",
+                "LCZ 7: Lightweight low-rise","LCZ 8: Large low-rise",
+                "LCZ 9: Sparsely built","LCZ 10: Heavy industry",
+                "LCZ A: Dense trees", "LCZ B: Scattered trees",
+                "LCZ C: Bush,scrub","LCZ D: Low plants",
+                "LCZ E: Bare rock or paved","LCZ F: Bare soil or sand","LCZ G: Water", "ghostwhite")
+
+
+  summarisedRSUs<-matrix(ncol=6, nrow=0) %>% as.data.frame
+  names(summarisedRSUs)<-c("lcz",   "numberRSUs", "meanArea", "numberRSUsClust", "meanAreaClust", "wf")
+  if(is.null(locations) | length(locations)==0){
+    locations<-unique(longSf$location)
+  }
+
+  for (wfi in workflows){
+    print(wfi)
+    sfIn<-longSf[longSf$location%in%locations & longSf$wf==wfi,]
+    dfOut<-summariseRSUs(sfIn, column = "lcz_primary" )
+    dfOut$wf<-wfi
+    summarisedRSUs<-rbind(summarisedRSUs, dfOut)
+  }
+
+  summarisedRSUs$lcz<-factor(summarisedRSUs$lcz,
+                                   levels = c(as.character(1:10),as.character(101:107)))
+
+  summarisedRSUs$meanArea<-round(summarisedRSUs$meanArea)
+  summarisedRSUs$meanAreaClust<-round(summarisedRSUs$meanAreaClust)
+  summarisedRSUs<-summarisedRSUs %>% arrange(wf,lcz)
+
+
+  # 
+  outPlot<-ggplot() +
+    # geom_point(data = summarisedRSUs, aes(x=numberRSUs, y = meanArea, color = lcz), size = 2) +
+    geom_point(data = summarisedRSUs, aes(x=numberRSUsClust, y = meanAreaClust, color = lcz), size = 2) +
+    scale_color_manual(values=colorMap, breaks = names(colorMap), labels = etiquettes, na.value = "ghostwhite")+
+    facet_wrap(vars(wf))
+  if(plot){print(outPlot)}
+
+  if(!is.null(graphPath) && length(graphPath)==1 && nchar(graphPath)>1){
+    if(substr(graphPath, nchar(graphPath), nchar(graphPath))!="/"){graphPath<-paste0(graphPath, "/")}
+    graphName<-paste0(graphPath, paste0(locations, collapse = "_"), ".png")
+    ggsave(graphName, outPlot)
+  }
+
+  output<-list(outPlot=outPlot, summarisedRSUs=summarisedRSUs)
+  return(output)
+
+}
+
+# plotSummarisedRSUs(longSf = allLocAllWfs)

R/summariseRSUs.R

@@ -8,13 +8,13 @@
 #' with same level of LCZ which touch each other
 #' @export
 #' @examples
-summariseRSUs<-function(sf, column ){
+summariseRSUs<-function(sf, column = "lcz_primary" ){
   # sf<-sf %>% mutate(area=st_area(geometry)) %>% st_drop_geometry() %>% as.data.frame
 
   unClustered <-sf %>% group_by(.data[[column]])  %>%
     summarise(numberRSUs=n(), meanArea = round(mean(st_area(geometry)), digits = 0)) %>% st_drop_geometry()
 
-  clustered <-sf %>% group_by(.data[[column]]) %>%  summarise() %>% ungroup %>% 
+  clustered <-sf %>% group_by(.data[[column]]) %>%  summarize() %>% ungroup %>% 
     st_cast("MULTIPOLYGON") %>% st_cast("POLYGON") %>%  group_by(.data[[column]]) %>% 
     summarise(numberRSUsClust=n(), meanAreaClust = round(mean(st_area(geometry)), digits = 0)) %>% st_drop_geometry
   output <- full_join(unClustered,clustered, by = column)
@@ -23,4 +23,17 @@ summariseRSUs<-function(sf, column ){
 }
 
 
-
+summariseRSUs<-function (sf, column)
+{
+  unClustered <- sf %>% group_by(.data[[column]]) %>% dplyr::summarise(numberRSUs = n(),
+                                                                meanArea = round(mean(st_area(geometry)), digits = 0)) %>%
+    st_drop_geometry()
+  clustered <- sf %>% group_by(.data[[column]]) %>% dplyr::summarise() %>%
+    ungroup %>% st_cast("MULTIPOLYGON") %>% st_cast("POLYGON") %>%
+    group_by(.data[[column]]) %>% dplyr::summarise(numberRSUsClust = n(),
+                                            meanAreaClust = round(mean(st_area(geometry)), digits = 0)) %>%
+    st_drop_geometry
+  output <- full_join(unClustered, clustered, by = column)
+  names(output)[1] <- "lcz"
+  return(output)
+}

inst/tinytest/test_summariseRSUs.R

@@ -20,7 +20,7 @@ showLCZ(test, column="lcz_primary")+geom_sf_text(aes(label = round(drop_units(ar
 
 
 library(sf)
-allLocAllWfs<-read_sf("/home/gousseff/Documents/3_data/data_article_LCZ_diff_algos/newDataTree/AllLocAllWorkflows.fgb")
+allLocAllWfs<-read_sf("/home/gousseff/Documents/3_data/data_article_LCZ_diff_algos/newDataTree/allLocAllWfs.fgb")
 # summary(allLocAllWfs)
 RSUsSummarisedAllLoc<-matrix(ncol=6, nrow=0) %>% as.data.frame
 names(RSUsSummarisedAllLoc)<-c("lcz",   "numberRSUs", "meanArea", "numberRSUsClust", "meanAreaClust", "wf")