R/Atlas_i1_SpeciesByOcean_julien.R
In juldebar/IRDTunaAtlas: IRD (www.ird.fr) - UMR EME - Tuna atlas
Defines functions
Atlas_i1_SpeciesByOcean_julien
# Atlas_i1_SpeciesByOcean_julien.R
#Tuna Atlas - IRD / MR EME
#
#This indicator produce a graph of annual catches by ocean for each species present in the input data. An associated RDF file is also produced.
##################################################################
#Norbert Billet - IRD
#2014/03/28: add the possibility to desactivate ecoscope sparql query
#2013/11/04: V2 version: add RDF export and allow production of multiple graph (i.e. species)
#2013/09/03: Norbert - Add attributes names as parameters
#2013/08/30: Norbert - Modifications to use with IRDTunaAtlas package
#2013/03/15: Norbert - Initial version
##################################################################
#Use example:
# library(IRDTunaAtlas)
# csv.df <- read.csv("/home/norbert/Boulot/iMarine/WPS/Atlas/CSV/i1i2.csv", stringsAsFactors=FALSE)
# Atlas_i1_SpeciesByOcean_julien(csv.df,
# yearAttributeName="year",
# oceanAttributeName="ocean",
# speciesAttributeName="species",
# valueAttributeName="value")
#
# OTHER EXAMPLE with WFS
#
# require(IndicatorsForFisheries)
# df <- readData(connectionType="remote", dataType="WFS",
# url="http://mdst-macroes.ird.fr:8080/constellation/WS/wfs/tuna_atlas",
# layer="ns11:i1i2_mv",
# ogcFilter='')
# result <- Atlas_i1_SpeciesByOcean_julien(df=df, yearAttributeName="year",
# oceanAttributeName="ocean",
# speciesAttributeName="species",
# valueAttributeName="value")
##################################################################
# a decommenter (rCharts)
# library(rCharts)
# library(jsonlite)
# library(rjson)
# library(dplyr)
# source("/home/tomcat7/temp/IRDTunaAtlas_OLD.R")
# source("/home/julien/SVNs/GIT/IRDTunaAtlas/R/IRDTunaAtlas_julien.R")
Atlas_i1_SpeciesByOcean_julien <- function(df,
yearAttributeName="year",
oceanAttributeName="ocean",
speciesAttributeName="species",
valueAttributeName="value",
withSparql=TRUE)
{
if (! require(XML) | ! require(ggplot2) | ! require(RColorBrewer)) {
stop("Missing library")
}
if (missing(df)) {
stop("Input data frame not specified")
}
#check for input attributes
if(sum(names(df) == yearAttributeName) == 0) {
stop("Cannot found year attribute")
}
if(sum(names(df) == oceanAttributeName) == 0) {
stop("Cannot found ocean attribute")
}
if(sum(names(df) == speciesAttributeName) == 0) {
stop("Cannot found species attribute")
}
if(sum(names(df) == valueAttributeName) == 0) {
stop("Cannot found value attribute")
}
#format columns
df[, yearAttributeName] <- as.numeric(df[, yearAttributeName])
df[, oceanAttributeName] <- as.factor(df[, oceanAttributeName])
df[, speciesAttributeName] <- as.factor(df[, speciesAttributeName])
df[, valueAttributeName] <- as.numeric(df[, valueAttributeName])
#aggregate to cut other columns
df <- aggregate(x=df[, valueAttributeName],
by=list(df[, yearAttributeName], df[, oceanAttributeName], df[, speciesAttributeName]),
FUN=sum)
#rename columns
names(df) <- c("year", "ocean", "species", "value")
#define the result df
result.df <- c()
#test if FAO usual ocean codes are used
if (length(intersect(levels(df$ocean), c("ATL", "IND", "PAC_E", "PAC_W"))) == length(levels(df$ocean))) {
df$ocean <- factor(df$ocean, levels=c("ATL", "IND", "PAC_E", "PAC_W"), labels=c("Atlantic O.", "Indian O.", "East Pacific O.", "West Pacific O."))
}
#setup the palette
my.colors <- brewer.pal(length(levels(df$ocean)), "Set1")
names(my.colors) <- levels(df$ocean)
#
# store = new.rdf(ontology=FALSE)
# add.prefix(store,
# prefix="resources_def",
# namespace="http://www.ecoscope.org/ontologies/resources_def/")
# add.prefix(store,
# prefix="ical",
# namespace="http://www.w3.org/2002/12/cal/ical/")
# add.prefix(store,
# prefix="dct",
# namespace="http://purl.org/dc/terms/")
#
# tableauResult <- data.frame(result=character())
tableauResults <- data.frame(type="plot||download||map||..",
description="Rapport d'exécution du traitement i1",
stringsAsFactors=FALSE)
# tableauResult$results <- data.frame(titre=character(),
tableauResult <- data.frame(titre=character(),
Description=character(),
uri=character(),
start=character(),
Metadata=character(),
image=character(),
radarPlots=character(),
dataTable=character(),
download=character(),
stringsAsFactors=FALSE)
listeResult <- list()
# URL<-"http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/"
URL<-"http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/default/"
repository<-paste(mywd,"outputs/www/html/tmp/SpeciesByOcean/default/",sep="")
# repository<-"/data/www/html/tmp/SpeciesByOcean/"
#TODO : mcforeach ?
for (species.current in unique(df$species)) {
current.df <- df[df$species == species.current,]
#aggregate values by years and ocean
aggData <- aggregate(value ~ ocean + year, data=current.df, sum)
#keep only common time extent
max_year <- min(unlist(lapply(levels(aggData$ocean), function(o) {return(if(length(subset(aggData, ocean==o)$year) > 0) max(subset(aggData, ocean==o)$year) else NA)})), na.rm=TRUE)
min_year <- max(unlist(lapply(levels(aggData$ocean), function(o) {return(if(length(subset(aggData, ocean==o)$year) > 0) min(subset(aggData, ocean==o)$year) else NA)})), na.rm=TRUE)
aggData <- subset(aggData, year >= min_year & year <= max_year)
#convert values from tons to thousand tons
aggData$value <- aggData$value / 1000
# if (withSparql) {
# #get species scientific name from ecoscope sparql
# sparqlResult <- getSpeciesFromEcoscope(as.character(species.current))
# if (length(sparqlResult) > 0) {
# species.label <- sparqlResult[1,"scientific_name"]
# species.URI <- sparqlResult[1,"uri"]
# } else {
# species.label <- species.current
# species.URI <- species.current
# }
# } else {
# species.label <- species.current
# species.URI <- species.current
# }
species.label <- species.current
species.URI <- species.current
#build the plot
resultPlot <- ggplot(aggData, aes(x=year, y=value, group=ocean)) +
geom_area(aes(fill=ocean), position="stack") +
geom_line(position="stack", color="grey20") +
scale_fill_manual(name="Ocean", values=my.colors) +
xlab("Year") + ylab("Catches in thousand tons") +
ggtitle(paste(species.label, "catches by Ocean")) +
theme(legend.position="bottom")
#draw the plot
#tempfile.base <- tempfile(pattern=paste("I1_", gsub(" ", "_", species.label), "_", sep=""),tmpdir="/data/www/html/tmp/SpeciesByOcean")
filename <- paste("I1", gsub(" ", "_", species.label), sep="_")
tempfile.base <- paste(repository,filename, sep="")
plot.filepath <- paste(tempfile.base, ".png", sep="")
plot.URLpng <- paste(URL,filename, ".png", sep="")
ggsave(filename=plot.filepath, plot=resultPlot, dpi=300)
## AJOUT Julien RChart NVD3
#plotRchartsNVD3 <- nPlot(value ~ year, group = 'ocean', data = aggData, type = 'line')
plotRchartsNVD3 <- nPlot(value ~ year, group = 'ocean', data = aggData, type = 'stackedAreaChart', id = 'chart')
#plotRchartsNVD3$addFilters("East Pacific O.", "Atlantic O.")
#plotRchartsNVD3$addControls("group", value = "ocean", values = names(aggData$ocean[1:3]))
plotRchartsNVD3$xAxis(axisLabel = 'Year')
plotRchartsNVD3$yAxis(axisLabel = 'Catches')
plotRchartsNVD3$chart(width = 800, height = 400, useInteractiveGuideline=TRUE)
plotRchartsNVD3bis <- nPlot(value ~ year, group = 'ocean', data = aggData, type = 'lineChart')
# plotRchartsNVD3bis$xAxis(axisLabel = 'Year')
# plotRchartsNVD3bis$yAxis(axisLabel = 'Catches')
# plotRchartsNVD3bis$chart(width = 800, height = 400)
#plotRchartsNVD3$addFilters("East Pacific O.", "Atlantic O.")
#plotRchartsNVD3$addControls("group", value = "ocean", values = names(aggData$ocean[1:3]))
## AJOUT Julien RChart Highcharts
plotRchartsHighcharts <- hPlot(value ~ year, data = aggData, type = c("line","scatter", "bubble"), group = "ocean", title = "Captures par espèce et par océan", subtitle = "species.label", size = "value", width = "100%")
# plotRchartsHighcharts$chart(width = 800, height = 400, zoomType = "xy")
plotRchartsHighcharts$chart(zoomType = "xy")
plotRchartsHighcharts$yAxis(title = list(text = "Captures"))
plotRchartsHighcharts$exporting(enabled = T)
plotRchartsHighcharts$legend(align = 'center', verticalAlign = 'top', y = 30, margin = 20)
plotRchartsHighcharts$xAxis(labels = list(rotation = -45, align = 'right', style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif')), replace = F)
plotRchartsHighcharts$plotOptions(column = list(stacking = "normal", dataLabels = list(enabled = T, rotation = -90, align = 'right', color = '#FFFFFF', x = 4, y = 10, style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif'))))
#plotRchartsHighcharts$addFilters("East Pacific O.", "Atlantic O.")
#plotRchartsHighcharts$addControls("x", value = "value", values = names(aggData$ocean))
#plotRchartsHighcharts$addControls("group", value = "FacVar1", values = names(simoriginal[, 1:3]))
#plotRchartsHighcharts$addControls("y", value = "year", values = names(aggData$year[1:3]))
#Display Plots
# plotRchartsHighcharts
## AJOUT Julien RChart Highcharts
plotRchartsRickshaw <- Rickshaw$new()
plotRchartsRickshaw$layer(value ~ year, data = aggData, group='ocean', type = 'area', title = "C'est de la balle")#, colors = 'steelblue', , subtitle = species.label
#plotRchartsRickshaw$xAxis(type = 'Time')
plotRchartsRickshaw$yAxis(orientation = 'right')
#plotRchartsRickshaw$legend("De la bonne grosse légende")
plotRchartsRickshaw$set(width = 800, height = 400, legend = TRUE, slider = TRUE)
#Rickshaw.Graph.JSONP
#plotRchartsRickshaw$chart(zoomType = "xy")
#plotRchartsHighcharts$show('iframe', cdn = TRUE)
#Datatable in HTML to be browsed online
Datatable <- dTable(
aggData,
sPaginationType= "full_numbers"
)
plot.filepathtml <- paste(tempfile.base, ".html", sep="")
#{plotRchartsHighcharts results = "asis", comment = NA}
#plotRchartsHighcharts$save(plot.filepathtml,include_assets = TRUE,cdn=TRUE)
plotRchartsHighcharts$save(plot.filepathtml,standalone=TRUE)
# plotRchartsHighcharts$save(plot.filepathtml,chartId="julien", cdn=TRUE)
plot.URLhtml <- paste(URL,filename, ".html", sep="")
plot.filepathtmlNVD3 <- paste(tempfile.base, "NVD3.html", sep="_")
plotRchartsNVD3$save(plot.filepathtmlNVD3,standalone=TRUE)
# plotRchartsNVD3$save(plot.filepathtmlNVD3,chartId="julien", cdn=TRUE)
plot.URLhtmlNVD3 <- paste(URL,filename, "_NVD3.html", sep="")
plot.filepathtmlNVD3bis <- paste(tempfile.base, "NVD3bis.html", sep="_")
plotRchartsNVD3bis$save(plot.filepathtmlNVD3bis,standalone=TRUE)
# plotRchartsNVD3bis$save(plot.filepathtmlNVD3bis,chartId="julien", cdn=TRUE)
plot.URLhtmlNVD3bis <- paste(URL,filename, "_NVD3bis.html", sep="")
plot.filepathtmlRickshaw <- paste(tempfile.base, "Rickshaw.html", sep="_")
plotRchartsRickshaw$save(plot.filepathtmlRickshaw,standalone=TRUE)
# plotRchartsRickshaw$save(plot.filepathtmlRickshaw,chartId="julien", cdn=TRUE)
plot.URLhtmlRickshaw <- paste(URL,filename, "_Rickshaw.html", sep="")
plot.filepathtmltable <- paste(tempfile.base, "table.html", sep="_")
Datatable$save(plot.filepathtmltable,standalone=TRUE)
# Datatable$save(plot.filepathtmltable,chartId="julien", cdn=TRUE)
plot.URLhtmlTable <- paste(URL,filename, "_table.html", sep="")
# # Display Plots
# Datatable
#
# #Metadata elements (in addition to OGC WPS metadata) to describe the current indicator which will be used by other applications (Ecoscope and Tuna Atlas Websites)
# titles=c(paste("IRD Tuna Atlas: indicator #1 - catches for",species.label, "species by ocean", sep=" "),
# paste("IRD Atlas thonier : indicateur #1 - captures par océan pour l'espèce ",species.label, sep=" "))
# titre=paste("Espèce:",species.label, sep=" ")
# descriptions=c(paste(species.label, "catches by ocean"),
# paste("Captures de", species.label, "par océan"))
# Description=paste("IRD Tuna Atlas: indicator #1 - catches of species",species.label,"by ocean", sep=" ")
# subjects=c(as.character(species.current))
# #Collect the URIs of related Topics from Ecoscope SPARQL endpoint
# URI <- FAO2URIFromEcoscope(as.character(species.current))
# tabURIs<- data.frame(type="speciesJulien",URI=URI,stringsAsFactors=FALSE)
#
# #TODO julien => A ADAPTER AVEC LA CONVEX HULL / ou la collection DE TOUTES LES GEOMETRIES CONCERNEES
# spatial_extent="POLYGON((-180 -90,-180 90,180 90,180 -90,-180 -90))"
# temporal_extent_begin=as.character(min(aggData$year))
# temporal_extent_end=as.character(max(aggData$year))
#
# rdf.filepath <- paste(repository, "La_totale.rdf", sep="")
# rdf.URL <- paste(URL,filename, ".rdf", sep="")
# # il faudrait ajouter un attribut qui précise le type de visualisation: carte, chart...
#
# data_output_identifiers=data.frame(titre="2 en fait y a pas besoin de cet attribut",type="stackedArea",year=temporal_extent_begin, fileURL=plot.URLhtml,stringsAsFactors=FALSE)
# ligne <- c(titre="3 en fait y a pas besoin de cet attribut",type="stackedArea",year=temporal_extent_begin,fileURL=plot.URLhtmlNVD3)
# data_output_identifiers <- rbind(data_output_identifiers, ligne)
# ligne <- c(titre="4 en fait y a pas besoin de cet attribut",type="stackedArea",year=temporal_extent_begin,fileURL=plot.URLhtmlNVD3bis)
# data_output_identifiers <- rbind(data_output_identifiers, ligne)
# ligne <- c(titre="5 en fait y a pas besoin de cet attribut",type="stackedArea",year=temporal_extent_begin,fileURL=plot.URLhtmlRickshaw)
# data_output_identifiers <- rbind(data_output_identifiers, ligne)
# ligne <- c(titre="6 en fait y a pas besoin de cet attribut",type="dataTable",year=temporal_extent_begin,fileURL=plot.URLhtmlTable)
# data_output_identifiers <- rbind(data_output_identifiers, ligne)
# # map|lines|pies|radarPlots
# # ligneTableauResult$uri=list(data.frame(typeURI="Species",URI=URI))
#
# download=data.frame(format="csv",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/XXX.csv", stringsAsFactors=FALSE)
# ligne <- c(format="shp",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/XXX.shp")
# download <- rbind(download, ligne)
# ligne <- c(format="GML|WKT|shp|netCDF",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/XXX.nc....")
# download <- rbind(download, ligne)
#
# #Write the RDF metadata describing the current indicator in the RDF model of the whole execution: used by Ecoscope and Tuna Atlas
# #Write the Json metadata used by the SIP
# # tableauResult <- buildRdf(store=store, tableauResult = tableauResult,
# RDFMetadata=rdf.URL,
# rdf_file_path=rdf.filepath,
# rdf_subject=paste("http://www.ecoscope.org/ontologies/resources", tempfile.base, sep=""),
# #rdf_subject="http://ecoscope.org/indicatorI1",
# titles=titles,
# descriptions=descriptions,
# subjects=subjects,
# tabURIs=tabURIs,
# processes="http://www.ecoscope.org/ontologies/resources/processI1",
# image=plot.URLpng,
# data_output_identifiers=data_output_identifiers,
# download=download,
# start=temporal_extent_begin,
# end=temporal_extent_end,
# spatial=spatial_extent,
# withSparql)
#
# # result.df <- rbind(result.df, c(plot.file.path=plot.filepath, rdf.file.path=rdf.filepath))
#
}
# julien<-buildJson(type="plot||download||map||..",
# description="Rapport d'exécution du traitement i1",
# processSourceCode="http://mdst-macroes.ird.fr:8084/wps//R/scripts/toto_wps.R",
# results=tableauResult)
listeResult<-list("data"=aggData,"species"=species.label, "colors"=my.colors)
return(listeResult)
}
juldebar/IRDTunaAtlas documentation built on March 9, 2024, 3:40 a.m.
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Defines functions Atlas_i1_SpeciesByOcean_julien
# Atlas_i1_SpeciesByOcean_julien.R
#Tuna Atlas - IRD / MR EME
#
#This indicator produce a graph of annual catches by ocean for each species present in the input data. An associated RDF file is also produced.
##################################################################
#Norbert Billet - IRD
#2014/03/28: add the possibility to desactivate ecoscope sparql query
#2013/11/04: V2 version: add RDF export and allow production of multiple graph (i.e. species)
#2013/09/03: Norbert - Add attributes names as parameters
#2013/08/30: Norbert - Modifications to use with IRDTunaAtlas package
#2013/03/15: Norbert - Initial version
##################################################################
#Use example:
# library(IRDTunaAtlas)
# csv.df <- read.csv("/home/norbert/Boulot/iMarine/WPS/Atlas/CSV/i1i2.csv", stringsAsFactors=FALSE)
# Atlas_i1_SpeciesByOcean_julien(csv.df,
# yearAttributeName="year",
# oceanAttributeName="ocean",
# speciesAttributeName="species",
# valueAttributeName="value")
#
# OTHER EXAMPLE with WFS
#
# require(IndicatorsForFisheries)
# df <- readData(connectionType="remote", dataType="WFS",
# url="http://mdst-macroes.ird.fr:8080/constellation/WS/wfs/tuna_atlas",
# layer="ns11:i1i2_mv",
# ogcFilter='')
# result <- Atlas_i1_SpeciesByOcean_julien(df=df, yearAttributeName="year",
# oceanAttributeName="ocean",
# speciesAttributeName="species",
# valueAttributeName="value")
##################################################################
# a decommenter (rCharts)
# library(rCharts)
# library(jsonlite)
# library(rjson)
# library(dplyr)
# source("/home/tomcat7/temp/IRDTunaAtlas_OLD.R")
# source("/home/julien/SVNs/GIT/IRDTunaAtlas/R/IRDTunaAtlas_julien.R")
Atlas_i1_SpeciesByOcean_julien <- function(df,
yearAttributeName="year",
oceanAttributeName="ocean",
speciesAttributeName="species",
valueAttributeName="value",
withSparql=TRUE)
{
if (! require(XML) | ! require(ggplot2) | ! require(RColorBrewer)) {
stop("Missing library")
}
if (missing(df)) {
stop("Input data frame not specified")
}
#check for input attributes
if(sum(names(df) == yearAttributeName) == 0) {
stop("Cannot found year attribute")
}
if(sum(names(df) == oceanAttributeName) == 0) {
stop("Cannot found ocean attribute")
}
if(sum(names(df) == speciesAttributeName) == 0) {
stop("Cannot found species attribute")
}
if(sum(names(df) == valueAttributeName) == 0) {
stop("Cannot found value attribute")
}
#format columns
df[, yearAttributeName] <- as.numeric(df[, yearAttributeName])
df[, oceanAttributeName] <- as.factor(df[, oceanAttributeName])
df[, speciesAttributeName] <- as.factor(df[, speciesAttributeName])
df[, valueAttributeName] <- as.numeric(df[, valueAttributeName])
#aggregate to cut other columns
df <- aggregate(x=df[, valueAttributeName],
by=list(df[, yearAttributeName], df[, oceanAttributeName], df[, speciesAttributeName]),
FUN=sum)
#rename columns
names(df) <- c("year", "ocean", "species", "value")
#define the result df
result.df <- c()
#test if FAO usual ocean codes are used
if (length(intersect(levels(df$ocean), c("ATL", "IND", "PAC_E", "PAC_W"))) == length(levels(df$ocean))) {
df$ocean <- factor(df$ocean, levels=c("ATL", "IND", "PAC_E", "PAC_W"), labels=c("Atlantic O.", "Indian O.", "East Pacific O.", "West Pacific O."))
}
#setup the palette
my.colors <- brewer.pal(length(levels(df$ocean)), "Set1")
names(my.colors) <- levels(df$ocean)
#
# store = new.rdf(ontology=FALSE)
# add.prefix(store,
# prefix="resources_def",
# namespace="http://www.ecoscope.org/ontologies/resources_def/")
# add.prefix(store,
# prefix="ical",
# namespace="http://www.w3.org/2002/12/cal/ical/")
# add.prefix(store,
# prefix="dct",
# namespace="http://purl.org/dc/terms/")
#
# tableauResult <- data.frame(result=character())
tableauResults <- data.frame(type="plot||download||map||..",
description="Rapport d'exécution du traitement i1",
stringsAsFactors=FALSE)
# tableauResult$results <- data.frame(titre=character(),
tableauResult <- data.frame(titre=character(),
Description=character(),
uri=character(),
start=character(),
Metadata=character(),
image=character(),
radarPlots=character(),
dataTable=character(),
download=character(),
stringsAsFactors=FALSE)
listeResult <- list()
# URL<-"http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/"
URL<-"http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/default/"
repository<-paste(mywd,"outputs/www/html/tmp/SpeciesByOcean/default/",sep="")
# repository<-"/data/www/html/tmp/SpeciesByOcean/"
#TODO : mcforeach ?
for (species.current in unique(df$species)) {
current.df <- df[df$species == species.current,]
#aggregate values by years and ocean
aggData <- aggregate(value ~ ocean + year, data=current.df, sum)
#keep only common time extent
max_year <- min(unlist(lapply(levels(aggData$ocean), function(o) {return(if(length(subset(aggData, ocean==o)$year) > 0) max(subset(aggData, ocean==o)$year) else NA)})), na.rm=TRUE)
min_year <- max(unlist(lapply(levels(aggData$ocean), function(o) {return(if(length(subset(aggData, ocean==o)$year) > 0) min(subset(aggData, ocean==o)$year) else NA)})), na.rm=TRUE)
aggData <- subset(aggData, year >= min_year & year <= max_year)
#convert values from tons to thousand tons
aggData$value <- aggData$value / 1000
# if (withSparql) {
# #get species scientific name from ecoscope sparql
# sparqlResult <- getSpeciesFromEcoscope(as.character(species.current))
# if (length(sparqlResult) > 0) {
# species.label <- sparqlResult[1,"scientific_name"]
# species.URI <- sparqlResult[1,"uri"]
# } else {
# species.label <- species.current
# species.URI <- species.current
# }
# } else {
# species.label <- species.current
# species.URI <- species.current
# }
species.label <- species.current
species.URI <- species.current
#build the plot
resultPlot <- ggplot(aggData, aes(x=year, y=value, group=ocean)) +
geom_area(aes(fill=ocean), position="stack") +
geom_line(position="stack", color="grey20") +
scale_fill_manual(name="Ocean", values=my.colors) +
xlab("Year") + ylab("Catches in thousand tons") +
ggtitle(paste(species.label, "catches by Ocean")) +
theme(legend.position="bottom")
#draw the plot
#tempfile.base <- tempfile(pattern=paste("I1_", gsub(" ", "_", species.label), "_", sep=""),tmpdir="/data/www/html/tmp/SpeciesByOcean")
filename <- paste("I1", gsub(" ", "_", species.label), sep="_")
tempfile.base <- paste(repository,filename, sep="")
plot.filepath <- paste(tempfile.base, ".png", sep="")
plot.URLpng <- paste(URL,filename, ".png", sep="")
ggsave(filename=plot.filepath, plot=resultPlot, dpi=300)
## AJOUT Julien RChart NVD3
#plotRchartsNVD3 <- nPlot(value ~ year, group = 'ocean', data = aggData, type = 'line')
plotRchartsNVD3 <- nPlot(value ~ year, group = 'ocean', data = aggData, type = 'stackedAreaChart', id = 'chart')
#plotRchartsNVD3$addFilters("East Pacific O.", "Atlantic O.")
#plotRchartsNVD3$addControls("group", value = "ocean", values = names(aggData$ocean[1:3]))
plotRchartsNVD3$xAxis(axisLabel = 'Year')
plotRchartsNVD3$yAxis(axisLabel = 'Catches')
plotRchartsNVD3$chart(width = 800, height = 400, useInteractiveGuideline=TRUE)
plotRchartsNVD3bis <- nPlot(value ~ year, group = 'ocean', data = aggData, type = 'lineChart')
# plotRchartsNVD3bis$xAxis(axisLabel = 'Year')
# plotRchartsNVD3bis$yAxis(axisLabel = 'Catches')
# plotRchartsNVD3bis$chart(width = 800, height = 400)
#plotRchartsNVD3$addFilters("East Pacific O.", "Atlantic O.")
#plotRchartsNVD3$addControls("group", value = "ocean", values = names(aggData$ocean[1:3]))
## AJOUT Julien RChart Highcharts
plotRchartsHighcharts <- hPlot(value ~ year, data = aggData, type = c("line","scatter", "bubble"), group = "ocean", title = "Captures par espèce et par océan", subtitle = "species.label", size = "value", width = "100%")
# plotRchartsHighcharts$chart(width = 800, height = 400, zoomType = "xy")
plotRchartsHighcharts$chart(zoomType = "xy")
plotRchartsHighcharts$yAxis(title = list(text = "Captures"))
plotRchartsHighcharts$exporting(enabled = T)
plotRchartsHighcharts$legend(align = 'center', verticalAlign = 'top', y = 30, margin = 20)
plotRchartsHighcharts$xAxis(labels = list(rotation = -45, align = 'right', style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif')), replace = F)
plotRchartsHighcharts$plotOptions(column = list(stacking = "normal", dataLabels = list(enabled = T, rotation = -90, align = 'right', color = '#FFFFFF', x = 4, y = 10, style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif'))))
#plotRchartsHighcharts$addFilters("East Pacific O.", "Atlantic O.")
#plotRchartsHighcharts$addControls("x", value = "value", values = names(aggData$ocean))
#plotRchartsHighcharts$addControls("group", value = "FacVar1", values = names(simoriginal[, 1:3]))
#plotRchartsHighcharts$addControls("y", value = "year", values = names(aggData$year[1:3]))
#Display Plots
# plotRchartsHighcharts
## AJOUT Julien RChart Highcharts
plotRchartsRickshaw <- Rickshaw$new()
plotRchartsRickshaw$layer(value ~ year, data = aggData, group='ocean', type = 'area', title = "C'est de la balle")#, colors = 'steelblue', , subtitle = species.label
#plotRchartsRickshaw$xAxis(type = 'Time')
plotRchartsRickshaw$yAxis(orientation = 'right')
#plotRchartsRickshaw$legend("De la bonne grosse légende")
plotRchartsRickshaw$set(width = 800, height = 400, legend = TRUE, slider = TRUE)
#Rickshaw.Graph.JSONP
#plotRchartsRickshaw$chart(zoomType = "xy")
#plotRchartsHighcharts$show('iframe', cdn = TRUE)
#Datatable in HTML to be browsed online
Datatable <- dTable(
aggData,
sPaginationType= "full_numbers"
)
plot.filepathtml <- paste(tempfile.base, ".html", sep="")
#{plotRchartsHighcharts results = "asis", comment = NA}
#plotRchartsHighcharts$save(plot.filepathtml,include_assets = TRUE,cdn=TRUE)
plotRchartsHighcharts$save(plot.filepathtml,standalone=TRUE)
# plotRchartsHighcharts$save(plot.filepathtml,chartId="julien", cdn=TRUE)
plot.URLhtml <- paste(URL,filename, ".html", sep="")
plot.filepathtmlNVD3 <- paste(tempfile.base, "NVD3.html", sep="_")
plotRchartsNVD3$save(plot.filepathtmlNVD3,standalone=TRUE)
# plotRchartsNVD3$save(plot.filepathtmlNVD3,chartId="julien", cdn=TRUE)
plot.URLhtmlNVD3 <- paste(URL,filename, "_NVD3.html", sep="")
plot.filepathtmlNVD3bis <- paste(tempfile.base, "NVD3bis.html", sep="_")
plotRchartsNVD3bis$save(plot.filepathtmlNVD3bis,standalone=TRUE)
# plotRchartsNVD3bis$save(plot.filepathtmlNVD3bis,chartId="julien", cdn=TRUE)
plot.URLhtmlNVD3bis <- paste(URL,filename, "_NVD3bis.html", sep="")
plot.filepathtmlRickshaw <- paste(tempfile.base, "Rickshaw.html", sep="_")
plotRchartsRickshaw$save(plot.filepathtmlRickshaw,standalone=TRUE)
# plotRchartsRickshaw$save(plot.filepathtmlRickshaw,chartId="julien", cdn=TRUE)
plot.URLhtmlRickshaw <- paste(URL,filename, "_Rickshaw.html", sep="")
plot.filepathtmltable <- paste(tempfile.base, "table.html", sep="_")
Datatable$save(plot.filepathtmltable,standalone=TRUE)
# Datatable$save(plot.filepathtmltable,chartId="julien", cdn=TRUE)
plot.URLhtmlTable <- paste(URL,filename, "_table.html", sep="")
# # Display Plots
# Datatable
#
# #Metadata elements (in addition to OGC WPS metadata) to describe the current indicator which will be used by other applications (Ecoscope and Tuna Atlas Websites)
# titles=c(paste("IRD Tuna Atlas: indicator #1 - catches for",species.label, "species by ocean", sep=" "),
# paste("IRD Atlas thonier : indicateur #1 - captures par océan pour l'espèce ",species.label, sep=" "))
# titre=paste("Espèce:",species.label, sep=" ")
# descriptions=c(paste(species.label, "catches by ocean"),
# paste("Captures de", species.label, "par océan"))
# Description=paste("IRD Tuna Atlas: indicator #1 - catches of species",species.label,"by ocean", sep=" ")
# subjects=c(as.character(species.current))
# #Collect the URIs of related Topics from Ecoscope SPARQL endpoint
# URI <- FAO2URIFromEcoscope(as.character(species.current))
# tabURIs<- data.frame(type="speciesJulien",URI=URI,stringsAsFactors=FALSE)
#
# #TODO julien => A ADAPTER AVEC LA CONVEX HULL / ou la collection DE TOUTES LES GEOMETRIES CONCERNEES
# spatial_extent="POLYGON((-180 -90,-180 90,180 90,180 -90,-180 -90))"
# temporal_extent_begin=as.character(min(aggData$year))
# temporal_extent_end=as.character(max(aggData$year))
#
# rdf.filepath <- paste(repository, "La_totale.rdf", sep="")
# rdf.URL <- paste(URL,filename, ".rdf", sep="")
# # il faudrait ajouter un attribut qui précise le type de visualisation: carte, chart...
#
# data_output_identifiers=data.frame(titre="2 en fait y a pas besoin de cet attribut",type="stackedArea",year=temporal_extent_begin, fileURL=plot.URLhtml,stringsAsFactors=FALSE)
# ligne <- c(titre="3 en fait y a pas besoin de cet attribut",type="stackedArea",year=temporal_extent_begin,fileURL=plot.URLhtmlNVD3)
# data_output_identifiers <- rbind(data_output_identifiers, ligne)
# ligne <- c(titre="4 en fait y a pas besoin de cet attribut",type="stackedArea",year=temporal_extent_begin,fileURL=plot.URLhtmlNVD3bis)
# data_output_identifiers <- rbind(data_output_identifiers, ligne)
# ligne <- c(titre="5 en fait y a pas besoin de cet attribut",type="stackedArea",year=temporal_extent_begin,fileURL=plot.URLhtmlRickshaw)
# data_output_identifiers <- rbind(data_output_identifiers, ligne)
# ligne <- c(titre="6 en fait y a pas besoin de cet attribut",type="dataTable",year=temporal_extent_begin,fileURL=plot.URLhtmlTable)
# data_output_identifiers <- rbind(data_output_identifiers, ligne)
# # map|lines|pies|radarPlots
# # ligneTableauResult$uri=list(data.frame(typeURI="Species",URI=URI))
#
# download=data.frame(format="csv",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/XXX.csv", stringsAsFactors=FALSE)
# ligne <- c(format="shp",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/XXX.shp")
# download <- rbind(download, ligne)
# ligne <- c(format="GML|WKT|shp|netCDF",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByOcean/XXX.nc....")
# download <- rbind(download, ligne)
#
# #Write the RDF metadata describing the current indicator in the RDF model of the whole execution: used by Ecoscope and Tuna Atlas
# #Write the Json metadata used by the SIP
# # tableauResult <- buildRdf(store=store, tableauResult = tableauResult,
# RDFMetadata=rdf.URL,
# rdf_file_path=rdf.filepath,
# rdf_subject=paste("http://www.ecoscope.org/ontologies/resources", tempfile.base, sep=""),
# #rdf_subject="http://ecoscope.org/indicatorI1",
# titles=titles,
# descriptions=descriptions,
# subjects=subjects,
# tabURIs=tabURIs,
# processes="http://www.ecoscope.org/ontologies/resources/processI1",
# image=plot.URLpng,
# data_output_identifiers=data_output_identifiers,
# download=download,
# start=temporal_extent_begin,
# end=temporal_extent_end,
# spatial=spatial_extent,
# withSparql)
#
# # result.df <- rbind(result.df, c(plot.file.path=plot.filepath, rdf.file.path=rdf.filepath))
#
}
# julien<-buildJson(type="plot||download||map||..",
# description="Rapport d'exécution du traitement i1",
# processSourceCode="http://mdst-macroes.ird.fr:8084/wps//R/scripts/toto_wps.R",
# results=tableauResult)
listeResult<-list("data"=aggData,"species"=species.label, "colors"=my.colors)
return(listeResult)
}
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