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server.R
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server.R
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##################################
# MeadoWatch WTA Analysis
# Adapted by Aji John #
# original by Alessio Benedetti #
# server.R file #
##################################
library(shiny)
library(tidyverse)
library(leaflet.extras)
library(rvest)
#####################
# SUPPORT FUNCTIONS #
#####################
##################
# DATA WRANGLING #
##################
PhenoSite_clean <- read.csv("cleandata/PhenoSite_Clean.csv", header=TRUE)
MW_PhenoSite_2013_2018 <- read_csv("data/MW_SiteDat_2013_2018.csv")
AllSites_2018 <- MW_PhenoSite_2013_2018 %>%
filter(Year == 2018 & Transect %in% c( "Reflection Lakes","Glacier Basin")) %>%
as.data.frame()
fp <- read_csv('output/FloweringProbabilities.csv')
meadow_species <- unique(PhenoSite_clean$Species)
fr <- read_csv('output/FloweringRichness.csv')
years <- unique(fp$year)
# tidy & enrich datafram
# support structures
################
# SERVER LOGIC #
################
shinyServer(function(input, output) {
# trails map
output$trailsMap <- renderLeaflet({
leaflet(data=AllSites_2018) %>% addProviderTiles(providers$Stamen.Watercolor, group = "Stamen Watercolor", options = providerTileOptions(noWrap = TRUE)) %>%#, minZoom = 4)) %>%
addProviderTiles(providers$OpenStreetMap.Mapnik, group = "Open Street Map", options = providerTileOptions(noWrap = TRUE)) %>%
addProviderTiles(providers$NASAGIBS.ViirsEarthAtNight2012, group = "Nasa Earth at Night", options = providerTileOptions(noWrap = TRUE)) %>%
addProviderTiles(providers$Stamen.TerrainBackground, group = "Stamen Terrain Background", options = providerTileOptions(noWrap = TRUE)) %>%
addProviderTiles(providers$Esri.WorldImagery, group = "Esri World Imagery", options = providerTileOptions(noWrap = TRUE)) %>%
addFullscreenControl() %>%
setView( -121.7203,46.8523, zoom = 10) %>%
addMarkers(
~longitude,
~latitude,
icon = makeIcon(
iconUrl = "flowers_1.png",
#shadowUrl = "flowers.png",
shadowAnchorX = -1, shadowAnchorY = -2
),
clusterOptions = markerClusterOptions()
) %>%
addLayersControl(
baseGroups = c("Stamen Watercolor","Open Street Map","Nasa Earth at Night","Stamen Terrain Background","Esri World Imagery"),
position = c("topleft"),
options = layersControlOptions(collapsed = TRUE)
)
})
# DT table
output$phenoSiteDataTable <- renderDataTable(
PhenoSite_clean,
filter = "top"
)
# ggplot2 charts
output$categorySelectComboChart <- renderUI({
selectInput("selectedCategoryChart","Select a species:", meadow_species)
})
speciesGgplot1 <- reactive(fp[,c('year','trail','DOY',input$selectedCategoryChart)])
speciesGgplot2 <- reactive(fp[,c('year','trail','DOY',input$selectedCategoryChart)])
speciesGgplot3 <- reactive(fr)
speciesGgplot4 <- reactive(fr)
output$ggplot2Group1 <- renderPlot({
g1 <- speciesGgplot1() %>%
filter(trail=='RL') %>%
mutate(yearf = as.factor(year)) %>%
ggplot() + geom_point(aes_string(x="DOY",y=input$selectedCategoryChart,color="yearf")) + labs(color='Year' , title="Species - [Refections Lakes Trail]", x ="Day of the year (DOY)", y = paste0("P (flowering ) of ", input$selectedCategoryChart)) +theme_classic()
print(g1)
})
output$ggplot2Group2 <- renderPlot({
g2 <- speciesGgplot2() %>%
filter(trail=='GB') %>%
mutate(yearf = as.factor(year)) %>%
ggplot() + geom_point(aes_string(x="DOY",y=input$selectedCategoryChart,color="yearf")) + labs(color='Year',title="Species - [Glacier Basin]", x ="Day of the year (DOY)", y = paste0("P (flowering ) of ", input$selectedCategoryChart)) +theme_classic()
print(g2)
})
# selections for richness
output$yearSelectCombo <- renderUI({
selectInput("yearsCombo","Select a year:", years)
})
output$speciesCombo <- renderUI({
selectInput("speciesCombo","Select a species:", meadow_species)
})
output$ggplot2Group3 <- renderPlot({
g3 <- speciesGgplot3() %>%
filter(trail=='RL') %>%
mutate(yearf = as.factor(year)) %>%
ggplot() + geom_smooth(aes_string(x="DOY",y="rich",color="yearf")) + labs(color='Year' , title="Richness - [Refections Lakes Trail]", x ="Day of the year (DOY)", y = paste0(" ", "")) +theme_classic()
print(g3)
})
output$ggplot2Group4 <- renderPlot({
g4 <- speciesGgplot4() %>%
filter(trail=='GB') %>%
mutate(yearf = as.factor(year)) %>%
ggplot() + geom_smooth(aes_string(x="DOY",y="rich",color="yearf")) + labs(color='Year',title="Richness - [Glacier Basin]", x ="Day of the year (DOY)", y = paste0("", "")) +theme_classic()
print(g4)
})
})