Start of editing of points on the map

jumpingrivers · Feb 9, 2023 · fed2877 · fed2877
1 parent 319e277
commit fed2877
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Showing 4 changed files with 150 additions and 44 deletions.
diff --git a/JM_notes b/JM_notes
@@ -4,25 +4,32 @@ WORK DONE
 
 #udpated POWO search to trap when you have no results, ugly but works
 #tweak map size to be same as left panel
-
-WORK NEEDED
-HIGH
-# User editable, moveable, delete point etc
+#180 date line delt with for EOO, AOO not that useful
+#Suggest Rating for EOO and AOO added
+#Projection details stored for use later
+#updated so that data progresses through to map
+#updated so default fields are build etc as below
 # a.	geocat_id = an internal ID which is populated on import (ie 1:nrow), new points will be added to this with a nrow + _leaflet_id (_leaflet_id is a unique number from leaflet) this should allow me to use this id to query all on map edits/delete. The reason for odd allocation is that leaflet assigns its own unique values and I can’t find a way to update (read only), there is a possibility of a clash if,  I just increment ID and I may have get back out the leaflet ID as some point (not sure I do). I may simplify this later.
 #b.	geo_status = a record of what has happen to a point ie “new point”, “moved point”, “deleted point”
 #c.	geocat_use = Flag to false it point is deleted (could query on above, but I feel this is quicker)?
 #d.	geocat_analysis = Flag for any queries (ie GBIF only etc), which we can switch on or off depending on reactive # elements (ie your switches for GBIF/user)
 
-#GBIF query
+
+WORK NEEDED
+HIGH
+# User editable, moveable, delete point etc
+# GBIF query
 
 MEDIUM
-#Split polygon when over date line
-# add suggestted IUCN ratings linked to EOO and AOO values
-# return the projection used to the user?
-#colour points by data_source
+#report Projection
+#report metadata (ie projection, GBIF query and citations etc)
+# colour points by data_source
+# TDWG maps from species name
 
 LOW
 # POWO search which returns nothing, need to inform user in the information box to the left (where steve reports missing values)
 # POWO search clear off old searches (maybe a button)
 # Map to reproduce over date line (ie not say map data not available)
+# split aoo over dateline (not going to happen very often)
+# allow data with long 180++
 
diff --git a/R/app.R b/R/app.R
@@ -4,7 +4,7 @@ geocatApp <- function(...) {
   ui <- fluidPage(
 
     shinyjs::useShinyjs(),
-    
+
     tags$html(lang = "en"),
 
     # title
@@ -80,7 +80,7 @@ geocatApp <- function(...) {
         column(
           12,
           align = "centre",
-          shiny::helpText("Upload a CSV with a unique 'id' and 'longitude', 'latitude' fields "),
+          shiny::helpText("Upload a CSV with at least 'longitude', 'latitude' fields "),
           shiny::fileInput(
             "csv_in",
             NULL,
@@ -152,9 +152,12 @@ geocatApp <- function(...) {
 
 ##### server #####
 server <- function(input, output, session) {
+  #JM builds an empty df to populate later
+  ################################
   values <- reactiveValues(
     analysis_data=empty_tbl_()
   )
+  values$analysis_data <- buildspdf()
 
   observeEvent(input$reset, {
       session$reload()
@@ -168,21 +171,27 @@ server <- function(input, output, session) {
     } else {
       shiny::validate("Invalid file; please upload a .csv file")
     }
-
-    shiny::validate(check_fields_(data, c("longitude", "latitude", "id")))
+    ###########################################################
+    #ID not needed any more
+    #shiny::validate(check_fields_(data, c("longitude", "latitude","id")))
     shiny::validate(check_numeric_(data, c("longitude", "latitude")))
-
-    values$analysis_data <-
-      dplyr::bind_rows(
-        values$analysis_data,
-        data %>%
+
+    csv_imported <- data %>%
           dplyr::select(longitude,latitude, id) %>%
           dplyr::filter(if_all(everything(), ~!is.na(.))) %>%
           dplyr::filter(longitude < 180, longitude > -180,
                         latitude < 90, latitude > -90) %>%
-          dplyr::mutate(group="csv")
+          dplyr::mutate(
+            geocat_id=seq.int(nrow(values$analysis_data)),
+            geocat_source="csv import",
+          )
+
+    values$analysis_data <-
+      dplyr::bind_rows(
+        values$analysis_data,
+        csv_imported
       )
-    
+
     data
   })
 
@@ -210,7 +219,7 @@ server <- function(input, output, session) {
 
       leaflet::setView(lng = 0,
                        lat = 0,
-                       zoom = 2) %>%
+                       zoom = 3) %>%
 
       leaflet.extras::addSearchOSM(options = leaflet.extras::searchOptions(
         autoCollapse = F,
@@ -220,7 +229,28 @@ server <- function(input, output, session) {
       )) %>%
 
       leaflet::addScaleBar(position = "bottomright") %>%
-
+      ######################################################
+      #JM
+      #df <- values$analysis_data
+      leaflet.extras::addDrawToolbar(editOptions = editToolbarOptions(edit=TRUE),
+                                     targetGroup = 'mappoints',
+                                     circleMarkerOptions=FALSE,
+                                     rectangleOptions=FALSE,
+                                     circleOptions=FALSE,
+                                     polygonOptions=FALSE,
+                                     polylineOptions=FALSE) %>%
+
+      leaflet::addCircleMarkers(data = values$analysis_data[values$analysis_data$geocat_use==TRUE,],
+                 popup = "popup",#~thetext,
+                 layerId = ~geocat_id,
+                 group="mappoints",
+                 radius = 7,
+                 color="#FFFFFF",
+                 stroke = T,
+                 fillColor = "#FF0000",
+                 fillOpacity = 1,
+                 options = markerOptions(draggable = FALSE)) %>%
+      #####################################################
       leaflet::addMeasure(
         position = "bottomleft",
         primaryLengthUnit = "meters",
@@ -236,12 +266,6 @@ server <- function(input, output, session) {
         options = leaflet::providerTileOptions(noWrap = TRUE)
       )  %>%
 
-      leaflet::addProviderTiles(
-        provider = "Esri.WorldStreetMap",
-        group = "ESRI Open Street map",
-        options = leaflet::providerTileOptions(noWrap = TRUE)
-      )  %>%
-
       leaflet::addProviderTiles(
         provider = "OpenStreetMap.Mapnik",
         group = "Open Street Map",
@@ -258,33 +282,32 @@ server <- function(input, output, session) {
         baseGroups = c(
           "ESRI World Imagery",
           "Open Street Map",
-          "Open Topo Map",
-          "ESRI Open Street map"
+          "Open Topo Map"
         ),
         options = leaflet::layersControlOptions(collapsed = FALSE)
       )
     })
-
-  output$csvValidation <- shiny::renderPrint({
+
+  shiny::observeEvent(input$leafmap_draw_new_feature, {
+    print("New Feature added")
+  })
+
+  output$validation <- shiny::renderPrint({
     data <- csvpointsInput()
     if (! is.data.frame(data)) {
       data
     }
     msg <- c(
-      check_complete_(data, c("longitude", "latitude", "id")),
-      check_range_(data, "longitude", -180, 180),
-      check_range_(data, "latitude", -90, 90),
+      #check_complete_(data, c("longitude", "latitude", "id")),
+      #check_range_(data, "longitude", -180, 180),
+      #check_range_(data, "latitude", -90, 90),
       check_rounded_(data, "longitude"),
-      check_rounded_(data, "latitude"),
-      check_zeros_(data, "longitude"),
-      check_zeros_(data, "latitude")
     )
-
     if (! is.null(msg)) {
       msg
     }
   })
-  
+
   output$gbifValidation <- shiny::renderPrint({
     data <- gbifPointsInput()
     if (nrow(data) == 0) {
@@ -325,7 +348,9 @@ server <- function(input, output, session) {
 
   shiny::observeEvent(input$csv_in, {
 
-    df <- csvpointsInput()
+    df <- values$analysis_data
+    #needs cleaning up with formating and maybe more information
+    popuptext <- paste(df$geocat_id,df$sci_name,df$latitude,df$longitude)
 
     leaflet::leafletProxy("mymap", data=df) %>%
 
@@ -341,7 +366,7 @@ server <- function(input, output, session) {
                                 fillOpacity = 1,
                                 fill = T,
                                 fillColor = "#0070ff",
-                                popup = as.character(df$id))
+                                popup = as.character(popuptext))
   })
 
   shiny::observeEvent(input$queryGBIF, {
@@ -444,8 +469,33 @@ server <- function(input, output, session) {
 
   shiny::observeEvent(list(input$Analysis, values$eoo_polygon, values$aoo_polygon), {
     if (input$Analysis){
-        leaflet::leafletProxy("mymap", data=values$aoo_polygon) %>%
-        leaflet::clearGroup("AOOpolys") %>%
+      #analysis here
+      #print(values$analysis_data)
+      d  <- data.frame(long=values$analysis_data$longitude,lat=values$analysis_data$latitude)
+      # if (!input$gbif_onoff) {
+      #   d <- dplyr::filter(d, source != "gbif")
+      # }
+      #if (!input$csv_onoff) {
+      #  d <- dplyr::filter(d, source != "csv")
+      #}
+      if (nrow(d) == 0)  {
+        return()
+      }
+      #d <- dplyr::select(d, -source)#is this needed or is it the above needed, I think they are doing the same thing
+      #JMJJMJMJMJM
+      #project the data so we can work on it in a sensible space for areas and distance
+      projp <- simProjWiz(d)
+      #reports projection need to sent this to validate
+      #
+      print (projp$crs)
+      EOO <- eoosh(projp$p)
+      AOO <- aoosh(projp$p)
+      values$eooarea <- EOO$area
+      values$aooarea <- AOO$area
+      values$eoo_rat <- ratingEoo(EOO$area,abb=TRUE)
+      values$aoo_rat <- ratingAoo(AOO$area,abb=TRUE)
+      #JMJMJMMJ
+      leaflet::leafletProxy("mymap",data = AOO$polysf) %>%
         leaflet::addPolygons(
           color = "#000000",
           stroke = T,

diff --git a/R/validate-data.R b/R/validate-data.R
@@ -1,3 +1,51 @@
+#Function to setup empty dataframe for geoCAT to work with
+#JM
+#notes
+#geocat_source = where the data has come from (ie gbif, csv import, user defined)
+#geocat_id = an internal ID which is populated on import (ie 1:nrow), new points will be added to this with a nrow + _leaflet_id (_leaflet_id is a unique number from leaflet) this should allow me to use this id to query all on map edits/delete. The reason for odd allocation is that leaflet assigns its own unique values and I can’t find a way to update (read only), there is a possibility of a clash if,  I just increment ID and I may have get back out the leaflet ID as some point (not sure I do). I may simplify this later.
+#geocat_status = a record of what has happen to a point ie “new point”, “moved point”, “deleted point”
+#geocat_use = Flag to false it point is deleted (could query on above, but I feel this is quicker)?
+#geocat_analysis = Flag for any queries (ie GBIF only etc), which we can switch on or off depending on reactive # elements (ie your switches for GBIF/user)
+#geocat_notes = records what has happened the points when moved (ie moved from x,y to p,q)
+#note at this point #geocat_analysis is not used
+buildspdf <- function(){
+  df <- data.frame(BasisOfRec = as.character(),
+             EVENT_YEAR = as.integer(),
+             latitude = as.numeric(),
+             longitude = as.numeric(),
+             sci_name = as.character(),
+             PRESENCE = as.integer(),
+             ORIGIN = as.integer(),
+             SEASONAL = as.integer(),
+             CATALOG_NO = as.character(),
+             SPATIALREF = as.character(),
+             CITATION = as.character(),
+             COMPILER = as.character(),
+             recordno = as.character(),
+             recordedBy = as.character(),
+             yrcompiled = as.integer(),
+             DATA_SENS = as.logical(),
+             SOURCE = as.logical(),
+             dist_comm = as.logical(),
+             tax_comm = as.logical(),
+             #user specific
+             id = as.integer(),
+             #geocat specific fields
+             geocat_source = as.character(),
+             geocat_id = as.integer(),
+             geocat_status = as.character(),
+             geocat_use = as.logical(),
+             geocat_analysis = as.logical(),
+             geocat_notes = as.character()
+  )
+  #add some dummy data
+  mypoints <- data.frame(longitude = rnorm(4) + 46, latitude = rnorm(4) + -21, geocat_id = c(1:4),geocat_use=TRUE)
+  merge(df,mypoints, all=TRUE)
+
+
+}
+
+
 # Functions to validate occurrences and occurrence files
 
 check_fields_ <- function(df, required_fields) {

diff --git a/app.R b/app.R
@@ -1,3 +1,4 @@
 library(shiny)
+library(leaflet.extras)
 pkgload::load_all(".")
 geocatApp()