R/Atlas_i2_SpeciesByGear_julien.R
In jsubei/IRDTunaAtlas: IRD (www.ird.fr) - UMR EME - Tuna atlas
Defines functions
Atlas_i2_SpeciesByGear_julien
#Atlas_i2_SpeciesByGear.R
#Tuna Atlas - IRD / MR EME
#
#This indicator produce a graph of annual catches by gear for each species present in the input data. An associated RDF file is also produced.
##################################################################
#Norbert Billet - IRD
#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(IndicatorsForFisheries)
# csv.df <- read.csv("/home/norbert/Boulot/iMarine/WPS/Atlas/CSV/i1i2.csv", stringsAsFactors=FALSE)
# Atlas_i2_SpeciesByGear(csv.df,
# yearAttributeName="year",
# gearTypeAttributeName="gear_type",
# speciesAttributeName="species",
# valueAttributeName="value")
##################################################################
# library(rCharts)
# library(jsonlite)
# source("/home/tomcat7/temp/IRDTunaAtlas.R")
# source("/home/julien/SVNs/GIT/IRDTunaAtlas/R/IRDTunaAtlas_julien.R")
Atlas_i2_SpeciesByGear_julien <- function(df,
yearAttributeName="year",
speciesAttributeName="species",
gearTypeAttributeName="gear_type",
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) == speciesAttributeName) == 0) {
stop("Cannot found species attribute")
}
if(sum(names(df) == gearTypeAttributeName) == 0) {
stop("Cannot found gear attribute")
}
if(sum(names(df) == valueAttributeName) == 0) {
stop("Cannot found value attribute")
}
#format columns
df[, yearAttributeName] <- as.numeric(df[, yearAttributeName])
df[, speciesAttributeName] <- as.factor(df[, speciesAttributeName])
df[, gearTypeAttributeName] <- as.factor(df[, gearTypeAttributeName])
df[, valueAttributeName] <- as.numeric(df[, valueAttributeName])
#aggregate to cut other columns
df <- aggregate(x=df[, valueAttributeName],
by=list(df[, yearAttributeName], df[, speciesAttributeName], df[, gearTypeAttributeName]),
FUN=sum)
#rename columns
names(df) <- c("year", "species", "gear_type", "value")
#test if FAO usual gear codes are used
#if (length(intersect(levels(df$gear_type), c("BB", "GILL", "LL", "PS", "OTHER_I", "OTHER_A", "TROL", "TRAP"))) == length(levels(df$gear_type))) {
# df$gear_type <- factor(df$gear_type, levels=c("BB", "GILL", "LL", "PS", "OTHER_I", "OTHER_A", "TROL", "TRAP"), labels=c("Baitboat", "Gillnet", "Longline", "Purse seine", "Unclass. art. Indian O.", "Unclass. art. Atl. O.", "Trol.", "Trap"))
#}
#setup the palette
my.colors <- brewer.pal(length(levels(df$gear_type)), "Set1")
names(my.colors) <- levels(df$gear_type)
#define the result
result.df <- c()
#List to store URLs of the set of files generated for each species
liste <- list()
#Julien comment rrdf
# 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$results <- data.frame(titre=character(),
tableauResult <- data.frame(stringsAsFactors=FALSE)
URL<-"http://mdst-macroes.ird.fr/tmp/SpeciesByGear/default/"
repository<-paste(mywd,"outputs/www/html/tmp/SpeciesByGear/default/",sep="")
# URL<-"http://mdst-macroes.ird.fr/tmp/SpeciesByGear/cdn/"
# repository<-"/data/www/html/tmp/SpeciesByGear/cdn/"
#TODO : mcforeach ?
for (species.current in unique(df$species)) {
current.df <- df[df$species == species.current,]
#aggregate values by years and gear type
aggData <- aggregate(value ~ gear_type + year, data=current.df, sum)
#convert values from tons to thousand tons
aggData$value <- aggData$value / 1000
#order factors levels by value
aggData$gear_type <- factor(aggData$gear_type, levels=rev(levels(reorder(aggData$gear_type, aggData$value))))
#Julien comment rrdf
#
# if (withSparql) {
# #get species scientific name from ecoscope sparql
# sparqlResult <- getSpeciesFromEcoscope(as.character(species.current))
# if (length(sparqlResult) > 0) {
# species.label <- sparqlResult[1,"scientific_name"]
# species.URI <- sparqlResult[1,"uri"]
# } else {
# species.label <- species.current
# species.URI <- species.current
# }
# } else {
# species.label <- species.current
# species.URI <- species.current
# }
species.label <- species.current
species.URI <- species.current
#TODO : mcforeach ?
# for (gear_type.current in unique(df$gear_type)) {
# current.df <- df[df$gear_type == gear_type.current,]
#
#
#get getFishingGearId current name and URI from ecoscope sparql
# sparqlResult <- getFishingGearIdFromEcoscope(as.character(gear_type.current))
# if (length(sparqlResult) > 0) {
# gear_type.label <- sparqlResult[1,"label"]
# gear_type.URI <- sparqlResult[1,"uri"]
# } else {
# gear_type.label <- gear_type.current
# gear_type.URI <- gear_type.current
# }
# }
#build the plot
resultPlot <- ggplot(aggData, aes(x=year, y=value, fill=gear_type, order=gear_type)) +
geom_bar(stat="identity", width=0.8) +
geom_bar(stat="identity", width=0.8, colour="grey20", show_guide=FALSE) +
scale_fill_manual(name="Gear type", values=my.colors) +
xlab("Year") + ylab("Catches in thousand tons") +
ggtitle(paste(species.label, "catches by gear type")) +
theme(legend.position="bottom")
#draw the plot
#tempfile.base <- tempfile(pattern=paste("I2", gsub(" ", "_", species.label), as.character(min(aggData$year)), as.character(max(aggData$year)), "_", sep="_"), tmpdir="")
#filename <- tempfile(pattern=paste("I2", gsub(" ", "_", species.label), "_", sep=""),tmpdir="")
filename <- paste("I2", gsub(" ", "_", species.label), sep="_")
tempfile.base <- paste(repository,filename, sep="")
plot.filepath <- paste(tempfile.base, ".png", sep="")
plot.URLpng <- paste(URL,filename, ".png", sep="")
ggsave(filename=plot.filepath, plot=resultPlot, dpi=300)
## AJOUT Julien RChart
#p8 <- nPlot(value ~ year, group = 'gear_type', data = aggData, type = 'multiBarHorizontalChart')
#p8$chart(showControls = F)
#p8 <- nPlot(value ~ year, group = 'gear_type', data = aggData, type = 'multiBarChart')
# plotRchartsHighcharts <- hPlot(value ~ year, group = 'gear_type', data = aggData, type = c("column","line","scatter", "bubble"), radius = 6, size='value')
# plotRchartsHighcharts$plotOptions(column = list(dataLabels = list(enabled = T, rotation = -90, align = 'right', color = '#FFFFFF', x = 4, y = 10, style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif'))))
plotRchartsHighcharts <- hPlot(value ~ year, data = aggData, type = 'column', group = 'gear_type', radius = 6, title = "Catches per month per fishing gear",width = "100%")
plotRchartsHighcharts$xAxis(labels = list(rotation = -45, align = 'right', style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif')), replace = F)
plotRchartsHighcharts$plotOptions(column = list(stacking = "normal", dataLabels = list(enabled = T, rotation = -90, align = 'right', color = '#FFFFFF', x = 4, y = 10, style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif'))))
plotRchartsHighcharts$legend(align = 'center', verticalAlign = 'top', y = 30, margin = 20)
# plotRchartsHighcharts$chart(width = 800,height = 400, zoomType = "xy")
plotRchartsHighcharts$chart(zoomType = "xy")
plotRchartsHighcharts$exporting(enabled = T)
plotRchartsHighcharts
## {title: MultiBar Chart}
plotRchartsNVD3 <- nPlot(value ~ year, group = 'gear_type', data = aggData, type = 'multiBarChart', width = 800, height = 400)
# plotRchartsNVD3 <- nPlot(value ~ year, group = 'gear_type', data = aggData, type = 'multiBarChart', width = "100%")
# plotRchartsNVD3$chart(width = 800, height = 400, color = c('brown', 'blue', '#594c26', 'green'), useInteractiveGuideline=TRUE)
plotRchartsNVD3$xAxis(axisLabel = 'Year')
plotRchartsNVD3$yAxis(axisLabel = 'Catches')
# plotRchartsNVD3$chart(width = 800, height = 400, useInteractiveGuideline=TRUE)
#plotRchartsNVD3$chart(useInteractiveGuideline=TRUE)
plotRchartsNVD3
# plotRchartsNVD3 <- nPlot(value ~ month, group='gear_type', data = current.df, type = 'multiChart')
## Dataset in HTML
Datatable <- dTable(
aggData,
sPaginationType= "full_numbers"
)
Datatable
## Storage of files in a given repository (temporary or permanent)
plot.filepathtml <- paste(tempfile.base, ".html", sep="")
plotRchartsHighcharts$save(plot.filepathtml,standalone=TRUE)
# plotRchartsHighcharts$save(plot.filepathtml,cdn=TRUE)
plot.URLRchartsHighcharts <- paste(URL, filename, ".html", sep="")
plot.filepathtmlNVD3 <- paste(tempfile.base, "NVD3.html", sep="")
plotRchartsNVD3$save(plot.filepathtmlNVD3,standalone=TRUE)
# plotRchartsNVD3$save(plot.filepathtmlNVD3,cdn=TRUE)
plot.URLRchartsNVD3 <- paste(URL, filename, "_NVD3.html", sep="")
plot.filepathtmltable <- paste(tempfile.base, "table.html", sep="_")
Datatable$save(plot.filepathtmltable,standalone=TRUE)
# Datatable$save(plot.filepathtmltable,cdn=TRUE)
plot.URLhtmlTable <- paste(URL,filename, "_table.html", sep="")
################################################################################################
# ligne <- data.frame(TYPE="URI", URL=URI, stringsAsFactors=FALSE)
################################################################################################
#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(species.label, "catches by gear type"),
paste("Captures de", species.label, "par type d'engin"))
descriptions=c(c("en",paste("IRD Tuna Atlas: indicator #2 - catches for",species.label, "species: catches by species and by gear type", sep=" ")),
c("fr",paste("IRD Atlas Thonier: indicator #2 - Captures par type d'engins de pêche pour l'espèce",species.label, sep=" ")))
subjects=c(as.character(species.current), as.character(unique(current.df$gear_type)))
#Collect the URIs of related Topics from Ecoscope SPARQL endpoint
# URI <- FAO2URIFromEcoscope(as.character(species.current))
# tabURIs<- data.frame(type="species",URI=URI,stringsAsFactors=FALSE)
# for (gear_type.current in unique(df$gear_type)) {
# URIGear <- FAO2URIFromEcoscope(as.character(unique(current.df$gear_type)))
# ligne<- c(x="gear",y=URIGear)
# tabURIs<- rbind(tabURIs,ligne)
# }
# EVENTUELLEMENT AJOUTER D'AUTRES SUJETS COMME LA ZONE
#subjects=c(as.character(species.current), as.character(gear_type.current), as.character(unique(current.df$gear_type))),
#subjects=c(as.character(species.current)),
#subjects=c(as.character(species.current), as.character(gear_type.current)),
#data_input=url,
#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, ".rdf", sep="")
#rdf.filepath <- paste(tempfile.base, ".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="1 en fait y a pas besoin de cet attribut",type="image",year=temporal_extent_begin, fileURL=plot.URLpng, stringsAsFactors=FALSE)
ligne <- c(titre="2 en fait y a pas besoin de cet attribut",type="stackedArea", year=temporal_extent_begin, fileURL=plot.URLRchartsHighcharts)
data_output_identifiers <- rbind(data_output_identifiers, ligne)
ligne <- c(titre="3 en fait y a pas besoin de cet attribut",type="map|lines|pies|radarPlots",year=temporal_extent_begin, fileURL=plot.URLRchartsNVD3)
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)
# ligneTableauResult$uri=list(data.frame(typeURI="Species",URI=URI))
download=data.frame(format="csv",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByGear/XXX.csv", stringsAsFactors=FALSE)
ligne <- c(format="shp",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByGear/XXX.shp")
download <- rbind(download, ligne)
ligne <- c(format="GML|WKT|shp|netCDF",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByGear/XXX.nc....")
download <- rbind(download, ligne)
#Write the RDF metadata describing the current indicator in the RDF model of the whole execution: used by Ecoscope and Tuna Atlas
#Write the Json metadata used by the SIP
# tableauResult$results <- data.frame(titre=character(),
# 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/processI2",
# 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="bar Chart", description="Rapport d'exécution du traitement i2",processSourceCode="http://mdst-macroes.ird.fr:8084/wps//R/scripts/Atlas_i2_SpeciesByOcean_HighCharts.R",results=tableauResult)
listeResult<-list("data"=aggData,"species"=species.label, "colors"=my.colors)
return(listeResult)
}
jsubei/IRDTunaAtlas documentation built on March 9, 2024, 3:05 a.m.
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Defines functions Atlas_i2_SpeciesByGear_julien
#Atlas_i2_SpeciesByGear.R
#Tuna Atlas - IRD / MR EME
#
#This indicator produce a graph of annual catches by gear for each species present in the input data. An associated RDF file is also produced.
##################################################################
#Norbert Billet - IRD
#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(IndicatorsForFisheries)
# csv.df <- read.csv("/home/norbert/Boulot/iMarine/WPS/Atlas/CSV/i1i2.csv", stringsAsFactors=FALSE)
# Atlas_i2_SpeciesByGear(csv.df,
# yearAttributeName="year",
# gearTypeAttributeName="gear_type",
# speciesAttributeName="species",
# valueAttributeName="value")
##################################################################
# library(rCharts)
# library(jsonlite)
# source("/home/tomcat7/temp/IRDTunaAtlas.R")
# source("/home/julien/SVNs/GIT/IRDTunaAtlas/R/IRDTunaAtlas_julien.R")
Atlas_i2_SpeciesByGear_julien <- function(df,
yearAttributeName="year",
speciesAttributeName="species",
gearTypeAttributeName="gear_type",
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) == speciesAttributeName) == 0) {
stop("Cannot found species attribute")
}
if(sum(names(df) == gearTypeAttributeName) == 0) {
stop("Cannot found gear attribute")
}
if(sum(names(df) == valueAttributeName) == 0) {
stop("Cannot found value attribute")
}
#format columns
df[, yearAttributeName] <- as.numeric(df[, yearAttributeName])
df[, speciesAttributeName] <- as.factor(df[, speciesAttributeName])
df[, gearTypeAttributeName] <- as.factor(df[, gearTypeAttributeName])
df[, valueAttributeName] <- as.numeric(df[, valueAttributeName])
#aggregate to cut other columns
df <- aggregate(x=df[, valueAttributeName],
by=list(df[, yearAttributeName], df[, speciesAttributeName], df[, gearTypeAttributeName]),
FUN=sum)
#rename columns
names(df) <- c("year", "species", "gear_type", "value")
#test if FAO usual gear codes are used
#if (length(intersect(levels(df$gear_type), c("BB", "GILL", "LL", "PS", "OTHER_I", "OTHER_A", "TROL", "TRAP"))) == length(levels(df$gear_type))) {
# df$gear_type <- factor(df$gear_type, levels=c("BB", "GILL", "LL", "PS", "OTHER_I", "OTHER_A", "TROL", "TRAP"), labels=c("Baitboat", "Gillnet", "Longline", "Purse seine", "Unclass. art. Indian O.", "Unclass. art. Atl. O.", "Trol.", "Trap"))
#}
#setup the palette
my.colors <- brewer.pal(length(levels(df$gear_type)), "Set1")
names(my.colors) <- levels(df$gear_type)
#define the result
result.df <- c()
#List to store URLs of the set of files generated for each species
liste <- list()
#Julien comment rrdf
# 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$results <- data.frame(titre=character(),
tableauResult <- data.frame(stringsAsFactors=FALSE)
URL<-"http://mdst-macroes.ird.fr/tmp/SpeciesByGear/default/"
repository<-paste(mywd,"outputs/www/html/tmp/SpeciesByGear/default/",sep="")
# URL<-"http://mdst-macroes.ird.fr/tmp/SpeciesByGear/cdn/"
# repository<-"/data/www/html/tmp/SpeciesByGear/cdn/"
#TODO : mcforeach ?
for (species.current in unique(df$species)) {
current.df <- df[df$species == species.current,]
#aggregate values by years and gear type
aggData <- aggregate(value ~ gear_type + year, data=current.df, sum)
#convert values from tons to thousand tons
aggData$value <- aggData$value / 1000
#order factors levels by value
aggData$gear_type <- factor(aggData$gear_type, levels=rev(levels(reorder(aggData$gear_type, aggData$value))))
#Julien comment rrdf
#
# if (withSparql) {
# #get species scientific name from ecoscope sparql
# sparqlResult <- getSpeciesFromEcoscope(as.character(species.current))
# if (length(sparqlResult) > 0) {
# species.label <- sparqlResult[1,"scientific_name"]
# species.URI <- sparqlResult[1,"uri"]
# } else {
# species.label <- species.current
# species.URI <- species.current
# }
# } else {
# species.label <- species.current
# species.URI <- species.current
# }
species.label <- species.current
species.URI <- species.current
#TODO : mcforeach ?
# for (gear_type.current in unique(df$gear_type)) {
# current.df <- df[df$gear_type == gear_type.current,]
#
#
#get getFishingGearId current name and URI from ecoscope sparql
# sparqlResult <- getFishingGearIdFromEcoscope(as.character(gear_type.current))
# if (length(sparqlResult) > 0) {
# gear_type.label <- sparqlResult[1,"label"]
# gear_type.URI <- sparqlResult[1,"uri"]
# } else {
# gear_type.label <- gear_type.current
# gear_type.URI <- gear_type.current
# }
# }
#build the plot
resultPlot <- ggplot(aggData, aes(x=year, y=value, fill=gear_type, order=gear_type)) +
geom_bar(stat="identity", width=0.8) +
geom_bar(stat="identity", width=0.8, colour="grey20", show_guide=FALSE) +
scale_fill_manual(name="Gear type", values=my.colors) +
xlab("Year") + ylab("Catches in thousand tons") +
ggtitle(paste(species.label, "catches by gear type")) +
theme(legend.position="bottom")
#draw the plot
#tempfile.base <- tempfile(pattern=paste("I2", gsub(" ", "_", species.label), as.character(min(aggData$year)), as.character(max(aggData$year)), "_", sep="_"), tmpdir="")
#filename <- tempfile(pattern=paste("I2", gsub(" ", "_", species.label), "_", sep=""),tmpdir="")
filename <- paste("I2", gsub(" ", "_", species.label), sep="_")
tempfile.base <- paste(repository,filename, sep="")
plot.filepath <- paste(tempfile.base, ".png", sep="")
plot.URLpng <- paste(URL,filename, ".png", sep="")
ggsave(filename=plot.filepath, plot=resultPlot, dpi=300)
## AJOUT Julien RChart
#p8 <- nPlot(value ~ year, group = 'gear_type', data = aggData, type = 'multiBarHorizontalChart')
#p8$chart(showControls = F)
#p8 <- nPlot(value ~ year, group = 'gear_type', data = aggData, type = 'multiBarChart')
# plotRchartsHighcharts <- hPlot(value ~ year, group = 'gear_type', data = aggData, type = c("column","line","scatter", "bubble"), radius = 6, size='value')
# plotRchartsHighcharts$plotOptions(column = list(dataLabels = list(enabled = T, rotation = -90, align = 'right', color = '#FFFFFF', x = 4, y = 10, style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif'))))
plotRchartsHighcharts <- hPlot(value ~ year, data = aggData, type = 'column', group = 'gear_type', radius = 6, title = "Catches per month per fishing gear",width = "100%")
plotRchartsHighcharts$xAxis(labels = list(rotation = -45, align = 'right', style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif')), replace = F)
plotRchartsHighcharts$plotOptions(column = list(stacking = "normal", dataLabels = list(enabled = T, rotation = -90, align = 'right', color = '#FFFFFF', x = 4, y = 10, style = list(fontSize = '13px', fontFamily = 'Verdana, sans-serif'))))
plotRchartsHighcharts$legend(align = 'center', verticalAlign = 'top', y = 30, margin = 20)
# plotRchartsHighcharts$chart(width = 800,height = 400, zoomType = "xy")
plotRchartsHighcharts$chart(zoomType = "xy")
plotRchartsHighcharts$exporting(enabled = T)
plotRchartsHighcharts
## {title: MultiBar Chart}
plotRchartsNVD3 <- nPlot(value ~ year, group = 'gear_type', data = aggData, type = 'multiBarChart', width = 800, height = 400)
# plotRchartsNVD3 <- nPlot(value ~ year, group = 'gear_type', data = aggData, type = 'multiBarChart', width = "100%")
# plotRchartsNVD3$chart(width = 800, height = 400, color = c('brown', 'blue', '#594c26', 'green'), useInteractiveGuideline=TRUE)
plotRchartsNVD3$xAxis(axisLabel = 'Year')
plotRchartsNVD3$yAxis(axisLabel = 'Catches')
# plotRchartsNVD3$chart(width = 800, height = 400, useInteractiveGuideline=TRUE)
#plotRchartsNVD3$chart(useInteractiveGuideline=TRUE)
plotRchartsNVD3
# plotRchartsNVD3 <- nPlot(value ~ month, group='gear_type', data = current.df, type = 'multiChart')
## Dataset in HTML
Datatable <- dTable(
aggData,
sPaginationType= "full_numbers"
)
Datatable
## Storage of files in a given repository (temporary or permanent)
plot.filepathtml <- paste(tempfile.base, ".html", sep="")
plotRchartsHighcharts$save(plot.filepathtml,standalone=TRUE)
# plotRchartsHighcharts$save(plot.filepathtml,cdn=TRUE)
plot.URLRchartsHighcharts <- paste(URL, filename, ".html", sep="")
plot.filepathtmlNVD3 <- paste(tempfile.base, "NVD3.html", sep="")
plotRchartsNVD3$save(plot.filepathtmlNVD3,standalone=TRUE)
# plotRchartsNVD3$save(plot.filepathtmlNVD3,cdn=TRUE)
plot.URLRchartsNVD3 <- paste(URL, filename, "_NVD3.html", sep="")
plot.filepathtmltable <- paste(tempfile.base, "table.html", sep="_")
Datatable$save(plot.filepathtmltable,standalone=TRUE)
# Datatable$save(plot.filepathtmltable,cdn=TRUE)
plot.URLhtmlTable <- paste(URL,filename, "_table.html", sep="")
################################################################################################
# ligne <- data.frame(TYPE="URI", URL=URI, stringsAsFactors=FALSE)
################################################################################################
#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(species.label, "catches by gear type"),
paste("Captures de", species.label, "par type d'engin"))
descriptions=c(c("en",paste("IRD Tuna Atlas: indicator #2 - catches for",species.label, "species: catches by species and by gear type", sep=" ")),
c("fr",paste("IRD Atlas Thonier: indicator #2 - Captures par type d'engins de pêche pour l'espèce",species.label, sep=" ")))
subjects=c(as.character(species.current), as.character(unique(current.df$gear_type)))
#Collect the URIs of related Topics from Ecoscope SPARQL endpoint
# URI <- FAO2URIFromEcoscope(as.character(species.current))
# tabURIs<- data.frame(type="species",URI=URI,stringsAsFactors=FALSE)
# for (gear_type.current in unique(df$gear_type)) {
# URIGear <- FAO2URIFromEcoscope(as.character(unique(current.df$gear_type)))
# ligne<- c(x="gear",y=URIGear)
# tabURIs<- rbind(tabURIs,ligne)
# }
# EVENTUELLEMENT AJOUTER D'AUTRES SUJETS COMME LA ZONE
#subjects=c(as.character(species.current), as.character(gear_type.current), as.character(unique(current.df$gear_type))),
#subjects=c(as.character(species.current)),
#subjects=c(as.character(species.current), as.character(gear_type.current)),
#data_input=url,
#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, ".rdf", sep="")
#rdf.filepath <- paste(tempfile.base, ".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="1 en fait y a pas besoin de cet attribut",type="image",year=temporal_extent_begin, fileURL=plot.URLpng, stringsAsFactors=FALSE)
ligne <- c(titre="2 en fait y a pas besoin de cet attribut",type="stackedArea", year=temporal_extent_begin, fileURL=plot.URLRchartsHighcharts)
data_output_identifiers <- rbind(data_output_identifiers, ligne)
ligne <- c(titre="3 en fait y a pas besoin de cet attribut",type="map|lines|pies|radarPlots",year=temporal_extent_begin, fileURL=plot.URLRchartsNVD3)
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)
# ligneTableauResult$uri=list(data.frame(typeURI="Species",URI=URI))
download=data.frame(format="csv",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByGear/XXX.csv", stringsAsFactors=FALSE)
ligne <- c(format="shp",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByGear/XXX.shp")
download <- rbind(download, ligne)
ligne <- c(format="GML|WKT|shp|netCDF",URL="http://mdst-macroes.ird.fr/tmp/SpeciesByGear/XXX.nc....")
download <- rbind(download, ligne)
#Write the RDF metadata describing the current indicator in the RDF model of the whole execution: used by Ecoscope and Tuna Atlas
#Write the Json metadata used by the SIP
# tableauResult$results <- data.frame(titre=character(),
# 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/processI2",
# 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="bar Chart", description="Rapport d'exécution du traitement i2",processSourceCode="http://mdst-macroes.ird.fr:8084/wps//R/scripts/Atlas_i2_SpeciesByOcean_HighCharts.R",results=tableauResult)
listeResult<-list("data"=aggData,"species"=species.label, "colors"=my.colors)
return(listeResult)
}
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