In jsubei/IRDTunaAtlas: IRD (www.ird.fr) - UMR EME - Tuna atlas

library(flexdashboard)
library(shiny)
library(dplyr)
library(XML)
library(DBI)
library(RPostgres)
library(RPostgreSQL)
library(dplyr)
library(leaflet)
library(leaflet.extras)
library(leafpm)
library(mapedit)
library(pacman)
library(sf)
library(sp)
library(ggplot2)
library(plotly)
library(plyr)
library(streamgraph)

#######################
##Database Identifiers: tunaatlas / db-tunaatlas
# source(file = "~/Desktop/CODES/IRDTunaAtlas/credentials.R")
source(file = "~/Bureau/CODES/IRDTunaAtlas/credentials.R")

codes_github_repository <- "https://raw.githubusercontent.com/juldebar/IRDTunaAtlas/master/R/"
codes_directory=codes_github_repository
# query <- paste(readLines(paste0(codes_directory,"SQL/select_annotated_images_attributes.sql")), collapse=" ")

####################################################################################################################################################################################################################################
source("https://raw.githubusercontent.com/juldebar/IRDTunaAtlas/master/R/TunaAtlas_i1_SpeciesByOcean.R")
source("https://raw.githubusercontent.com/juldebar/IRDTunaAtlas/master/R/TunaAtlas_i2_SpeciesByGear.R")

Column {data-width=350}

Select parameters to customize plots 1, 2, 3 and 4 (see Github wiki)

new_wkt <- 'POLYGON((-180 -90, 180 -90, 180 90, -180 90, -180 -90))'
wkt <- reactiveVal(new_wkt) 

query_i1i2 <- ("select * from i1i2 ;")
df_nominal <- st_read(con, query = query_i1i2)
species = unique(df_nominal$species)
gear_group = unique(df_nominal$gear_group)
ocean = unique(df_nominal$ocean)

# selectInput widget

selectInput("species_choice", label = h3("Select species for i1, i2 and i3 "), choices = species,  selected = c("SKJ","BET","BFT", "YFT"),multiple = TRUE)
selectInput("ocean_choice", label = h3("Select ocean for i1"), choices = ocean, selected = c("ICCAT","IOTC","IATTC", "CCSBT"),multiple = TRUE)
selectInput("gear_choice", label = h3("Select gear(s) for i2"), choices = gear_group, selected = c("PS","BB"),multiple = TRUE)


# textOutput(wkt())

renderPrint({ 
  paste0("Your current selection for i1 and i2: ", input$species_choice," and ", input$gear_choice," and ", input$ocean_choice)
  paste0("The area you have selected is (WKT format): ", wkt())
  query_i1i2 <- paste0("SELECT sum(value) as value, unit, ocean, gear_group, year, species, st_collect(geom) FROM public.i1i2_spatial WHERE ST_Within(geom,ST_GeomFromText('",wkt(),"',4326)) GROUP BY  unit, ocean, gear_group, year, species ;")
})

Select WKT on the map

To be done : add all WMS layers of input datasets

output$mymap <- renderLeaflet(
leaflet() %>%
addTiles() %>%
addPmToolbar(
  toolbarOptions = pmToolbarOptions(drawMarker = FALSE, position = "topright"),
  drawOptions = pmDrawOptions(snappable = FALSE, allowSelfIntersection = FALSE),
  editOptions = pmEditOptions(preventMarkerRemoval = TRUE, draggable = FALSE),
  cutOptions = pmCutOptions(snappable = FALSE, allowSelfIntersection = FALSE)
) %>%
    addDrawToolbar(
        targetGroup = "draw",
        editOptions = editToolbarOptions(
            selectedPathOptions = selectedPathOptions()
        )
    )   %>% setView(lng =48, lat =-8, zoom = 5
        ) %>% addWMSTiles(
    # "http://thredds.oreme.org:8080/thredds/wms/MARBEC/Seychelles/global-reanalysis-phy-001-030-monthly_SEY_t55_199301-201906.nc",
    "https://geoserver-sdi-lab.d4science.org/geoserver/sdilab_geoflow/ows?service=WMS",
    layers = "global_catch_5deg_1m_ird_level0",
        # layers = "thetao",
        options = WMSTileOptions(format = "image/png", transparent = TRUE), group ="Seatizen", attribution = "Seatizen WMS"
  )  %>%
    addLayersControl(
        overlayGroups = c("draw"),
        options = layersControlOptions(collapsed = FALSE)
    ) 

)
    leafletOutput('mymap')  


        observe({
              #use the draw_stop event to detect when users finished drawing
            feature <- input$mymap_draw_new_feature
            req(input$mymap_draw_stop)
            print(feature)
            polygon_coordinates <- input$mymap_draw_new_feature$geometry$coordinates[[1]]
            # see  https://rstudio.github.io/leaflet/shiny.html
            bb <- input$mymap_bounds 
            geom_polygon <- input$mymap_draw_new_feature$geometry
            # drawn_polygon <- Polygon(do.call(rbind,lapply(polygon_coordinates,function(x){c(x[[1]][1],x[[2]][1])})))
            geoJson <- geojsonio::as.json(feature)
            # spdf <- geojsonio::geojson_sp(feature)
            geom <- st_read(geoJson)
            wkt(st_as_text(st_geometry(geom[1,])))
            new_wkt <- st_as_text(st_geometry(geom[1,]))

            north <- polygon_coordinates[[1]][[1]]
            south <- polygon_coordinates[[2]][[1]]
            east <- polygon_coordinates[[1]][[2]]
            west <- polygon_coordinates[[2]][[2]]


            if(is.null(polygon_coordinates))
                return()
            text<-paste("North ", north, "South ", east)

            mymap_proxy = leafletProxy("mymap") %>% clearPopups() %>% addPopups(south,west,new_wkt)
            textOutput("wkt")
        })

Column {data-width=650}

Plot 1 Indicator I1 : Annual catches by ocean

output$plot1 <- renderPlotly({ 
#unique(df_nominal$species)
# nrow(df_nominal)
# colnames(df_nominal)
# unique(df_nominal$ocean)

# Setting parameters (hard coded here) with selectInput widget

if(wkt()!=new_wkt){
  df_nominal = st_read(con, query = paste0("SELECT sum(value) as value, unit, ocean, gear_group, year, species, st_collect(geom) FROM public.i1i2_spatial WHERE ST_Within(geom,ST_GeomFromText('",wkt(),"',4326)) GROUP BY  unit, ocean, gear_group, year, species ;"))
}
  #Filtering input dataset with selected parameters

df_i1 <- df_nominal %>% filter(species %in% input$species_choice,ocean %in% input$ocean_choice) 


i1 <- Atlas_i1_SpeciesByOcean(as.data.frame(df_i1), 
                         yearAttributeName="year", 
                         oceanAttributeName="ocean", 
                         speciesAttributeName="species", 
                         valueAttributeName="value")
})

plotlyOutput("plot1")

Plot 2 Indicator I2 : Annual catches by gear

output$plot2 <- renderPlotly({ 

# target_species <- c("SKJ")
# target_gear <- c("PS")

#Filtering input dataset with selected parameters
# df_i2 <- df_nominal %>% filter(gear_group %in% target_gear,species %in% target_species) %>% dplyr::rename(gear_type=gear_group)


if(wkt()!=new_wkt){
  df_nominal = st_read(con, query = paste0("SELECT sum(value) as value, unit, ocean, gear_group, year, species, st_collect(geom) FROM public.i1i2_spatial WHERE ST_Within(geom,ST_GeomFromText('",wkt(),"',4326)) GROUP BY  unit, ocean, gear_group, year, species ;"))
}
  #Filtering input dataset with selected parameters

df_i2 <- df_nominal %>% filter(gear_group %in% input$gear_choice,species %in% input$species_choice) %>% dplyr::rename(gear_type=gear_group)

i2 <- Atlas_i2_SpeciesByGear(as.data.frame(df_i2),
                             yearAttributeName="year",
                                    speciesAttributeName="species",
                                    valueAttributeName="value",
                                   gearTypeAttributeName="gear_type",
                                    withSparql=FALSE)
})

plotlyOutput("plot2")