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plots.R
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require(ncdf4)
require(stringr)
require(ggplot2)
require(gridExtra)
require(parallel)
require(tidyr)
require(dplyr)
#require(RColorBrewer)
#require(jsonlite)
#require(networkD3)
#require(tibble)
#require(htmlwidgets)
plot_QC <- function(filename, with_corr=FALSE, do_plot=TRUE, logscale=TRUE) {
filenc = nc_open(filename)
STATION_PARAMETERS = ncvar_get(filenc, "STATION_PARAMETERS")
param_name = "DOWNWELLING_PAR"
id_param = grep(str_pad(param_name, 64, side="right"), STATION_PARAMETERS)
id_prof = arrayInd(id_param, dim(STATION_PARAMETERS))[2]
if (length(id_param)!=1) {
nc_close(filenc)
return(NULL)
}
IRR380_NAME = c("DOWN_IRRADIANCE380", "DOWN_IRRADIANCE380_ADJUSTED")
IRR412_NAME = c("DOWN_IRRADIANCE412", "DOWN_IRRADIANCE412_ADJUSTED")
IRR490_NAME = c("DOWN_IRRADIANCE490", "DOWN_IRRADIANCE490_ADJUSTED")
PAR_NAME = c("DOWNWELLING_PAR", "DOWNWELLING_PAR_ADJUSTED")
if (with_corr) {
max_i = 2
} else {
max_i = 1
}
for (i in 1:max_i) {
PRES = ncvar_get(filenc, "PRES")[,id_prof]
IRR_380 = ncvar_get(filenc, IRR380_NAME[i])[,id_prof]
IRR_412 = ncvar_get(filenc, IRR412_NAME[i])[,id_prof]
IRR_490 = ncvar_get(filenc, IRR490_NAME[i])[,id_prof]
PAR = ncvar_get(filenc, PAR_NAME[i])[,id_prof]
if (length(which(!is.na(IRR_380))) < 5) {
nc_close(filenc)
return(list("type380"="0", "type412"="0", "type490"="0", "typePAR"="0"))
}
QC_flags = RT_QC_radiometry(PRES, IRR_380, IRR_412, IRR_490, PAR)
dataf = data.frame(QC_flags)
dataf$PRES = PRES
dataf$IRR_380 = IRR_380
dataf$IRR_412 = IRR_412
dataf$IRR_490 = IRR_490
dataf$PAR = PAR
dataf$FLAG_380[which(dataf$FLAG_380 == "NA")] = NA
dataf$FLAG_412[which(dataf$FLAG_412 == "NA")] = NA
dataf$FLAG_490[which(dataf$FLAG_490 == "NA")] = NA
dataf$FLAG_PAR[which(dataf$FLAG_PAR == "NA")] = NA
dataf$FLAG_380 = factor(dataf$FLAG_380 , levels=c("1", "2", "3", "4", NA))
dataf$FLAG_412 = factor(dataf$FLAG_412 , levels=c("1", "2", "3", "4", NA))
dataf$FLAG_490 = factor(dataf$FLAG_490 , levels=c("1", "2", "3", "4", NA))
dataf$FLAG_PAR = factor(dataf$FLAG_PAR , levels=c("1", "2", "3", "4", NA))
if (do_plot) {
col_1 = "#869C66"
col_2 = "#FFCA0B"
col_3 = "#FF9502"
col_4 = "#D43501"
type_col = c(col_1, col_2, col_3)
g1 = ggplot(dataf, aes(y=PRES, x=PAR, color=FLAG_PAR)) +
geom_point() +
scale_y_reverse() +
scale_color_manual(values=c(col_1, col_2, col_3, col_4), breaks=c("1", "2", "3", "4"), drop=FALSE) +
geom_label(
label=paste("Profile type :", dataf$typePAR),
x=log10(max(dataf$PAR, na.rm=T)),
y=-max(dataf$PRES, na.rm=T),
vjust="bottom",
hjust="right",
label.padding = unit(0.55, "lines"), # Rectangle size around label
#label.size = 0.35,
color = "black",
fill = type_col[as.numeric(as.character(dataf$typePAR[1]))]
) +
theme_bw() +
theme(legend.justification=c("right", "bottom"), legend.position=c(0.95,0.15))
g2 = ggplot(dataf, aes(y=PRES, x=IRR_380, color=FLAG_380)) +
geom_point() +
scale_y_reverse() +
scale_color_manual(values=c(col_1, col_2, col_3, col_4), breaks=c("1", "2", "3", "4"), drop=FALSE) +
geom_label(
label=paste("Profile type :", dataf$type380),
x=log10(max(dataf$IRR_380, na.rm=T)),
y=-max(dataf$PRES, na.rm=T),
vjust="bottom",
hjust="right",
label.padding = unit(0.55, "lines"), # Rectangle size around label
#label.size = 0.35,
color = "black",
fill=type_col[as.numeric(as.character(dataf$type380[1]))]
) +
theme_bw() +
theme(legend.justification=c("right", "bottom"), legend.position=c(0.95,0.15))
g3 = ggplot(dataf, aes(y=PRES, x=IRR_412, color=FLAG_412)) +
geom_point() +
scale_y_reverse() +
scale_color_manual(values=c(col_1, col_2, col_3, col_4), breaks=c("1", "2", "3", "4"), drop=FALSE) +
geom_label(
label=paste("Profile type :", dataf$type412),
x=log10(max(dataf$IRR_412, na.rm=T)),
y=-max(dataf$PRES, na.rm=T),
vjust="bottom",
hjust="right",
label.padding = unit(0.55, "lines"), # Rectangle size around label
#label.size = 0.35,
color = "black",
fill=type_col[as.numeric(as.character(dataf$type412[1]))]
) +
theme_bw() +
theme(legend.justification=c("right", "bottom"), legend.position=c(0.95,0.15))
g4 = ggplot(dataf, aes(y=PRES, x=IRR_490, color=FLAG_490)) +
geom_point() +
scale_y_reverse() +
scale_color_manual(values=c(col_1, col_2, col_3, col_4), breaks=c("1", "2", "3", "4"), drop=FALSE) +
geom_label(
label=paste("Profile type :", dataf$type490),
x=log10(max(dataf$IRR_490, na.rm=T)),
y=-max(dataf$PRES, na.rm=T),
vjust="bottom",
hjust="right",
label.padding = unit(0.55, "lines"), # Rectangle size around label
#label.size = 0.35,
color = "black",
fill=type_col[as.numeric(as.character(dataf$type490[1]))]
) +
theme_bw() +
theme(legend.justification=c("right", "bottom"), legend.position=c(0.95,0.15))
if (logscale) {
g1 = g1 + scale_x_log10()
g2 = g2 + scale_x_log10()
g3 = g3 + scale_x_log10()
g4 = g4 + scale_x_log10()
} else {
g1 = g1 + scale_x_continuous(limits=c(-1,1))
g2 = g2 + scale_x_continuous(limits=c(-1e-4,1e-4))
g3 = g3 + scale_x_continuous(limits=c(-1e-4,1e-4))
g4 = g4 + scale_x_continuous(limits=c(-1e-4,1e-4))
}
if (i == 1) {
gg5 = arrangeGrob(g1, g2, g3, g4, nrow=1)
} else {
gg5_adjusted = arrangeGrob(g1, g2, g3, g4, nrow=1)
}
}
}
if (str_sub(filename,-4,-4) == "D") {
plot_name = paste("radiometry_QC_", str_sub(filename, -15, -4), "_xing.png", sep="")
} else {
plot_name = paste("radiometry_QC_", str_sub(filename, -14, -4), "_xing.png", sep="")
}
if (do_plot) {
if (with_corr){
png(plot_name, width = 800, height = 800)
plot(grid.arrange(gg5, gg5_adjusted, nrow=2))
dev.off()
} else {
png(plot_name, width = 800, height = 400)
plot(gg5)
dev.off()
}
}
nc_close(filenc)
return(list("type380"=QC_flags$type380, "type412"=QC_flags$type412, "type490"=QC_flags$type490, "typePAR"=QC_flags$typePAR))
}
plot_corr <- function(filename, pres_zoom=FALSE) {
filenc = nc_open(filename)
STATION_PARAMETERS = ncvar_get(filenc, "STATION_PARAMETERS")
param_name = "DOWNWELLING_PAR"
id_param = grep(str_pad(param_name, 64, side="right"), STATION_PARAMETERS)
id_prof = arrayInd(id_param, dim(STATION_PARAMETERS))[2]
if (length(id_param)!=1) {
nc_close(filenc)
return(NULL)
}
PRES = ncvar_get(filenc, "PRES")[,id_prof]
IRR_380 = ncvar_get(filenc, "DOWN_IRRADIANCE380")[,id_prof]
IRR_412 = ncvar_get(filenc, "DOWN_IRRADIANCE412")[,id_prof]
IRR_490 = ncvar_get(filenc, "DOWN_IRRADIANCE490")[,id_prof]
PAR = ncvar_get(filenc, "DOWNWELLING_PAR")[,id_prof]
IRR_380_ADJUSTED = ncvar_get(filenc, "DOWN_IRRADIANCE380_ADJUSTED")[,id_prof]
IRR_412_ADJUSTED = ncvar_get(filenc, "DOWN_IRRADIANCE412_ADJUSTED")[,id_prof]
IRR_490_ADJUSTED = ncvar_get(filenc, "DOWN_IRRADIANCE490_ADJUSTED")[,id_prof]
PAR_ADJUSTED = ncvar_get(filenc, "DOWNWELLING_PAR_ADJUSTED")[,id_prof]
nc_close(filenc)
ggdata = data.frame(PRES, IRR_380, IRR_412, IRR_490, PAR,
IRR_380_ADJUSTED, IRR_412_ADJUSTED, IRR_490_ADJUSTED, PAR_ADJUSTED)
y_limits = NULL
if (pres_zoom) {
y_limits = c(250, 0)
}
x_limits = NULL
x_limits[[1]] = c(
min(min(PAR,na.rm=T), min(PAR_ADJUSTED, na.rm=T)),
max(2*quantile(PAR, 1/4, na.rm=T) - min(PAR,na.rm=T),
2*quantile(PAR_ADJUSTED, 1/4, na.rm=T) - min(PAR_ADJUSTED, na.rm=T)))
x_limits[[2]] = c(
min(min(IRR_380,na.rm=T), min(IRR_380_ADJUSTED, na.rm=T)),
max(2*quantile(IRR_380, 1/4, na.rm=T) - min(IRR_380, na.rm=T),
2*quantile(IRR_380_ADJUSTED, 1/4, na.rm=T) - min(IRR_380_ADJUSTED, na.rm=T)))
x_limits[[3]] = c(
min(min(IRR_412,na.rm=T), min(IRR_412_ADJUSTED, na.rm=T)),
max(2*quantile(IRR_412, 1/4, na.rm=T) - min(IRR_412,na.rm=T),
2*quantile(IRR_412_ADJUSTED, 1/4, na.rm=T) - min(IRR_412_ADJUSTED, na.rm=T)))
x_limits[[4]] = c(
min(min(IRR_490,na.rm=T), min(IRR_490_ADJUSTED, na.rm=T)),
max(2*quantile(IRR_490, 1/4, na.rm=T) - min(IRR_490,na.rm=T),
2*quantile(IRR_490_ADJUSTED, 1/4, na.rm=T) - min(IRR_490_ADJUSTED, na.rm=T)))
g1 = ggplot(ggdata, aes(x=PAR, y=PRES)) +
geom_point() +
geom_path(mapping = aes(x=PAR_ADJUSTED, y=PRES, color="red")) +
scale_y_reverse(limits=y_limits) +
theme_bw() +
theme(legend.position="none")
g2 = ggplot(ggdata, aes(x=IRR_380, y=PRES)) +
geom_point() +
geom_path(mapping = aes(x=IRR_380_ADJUSTED, y=PRES, color="red")) +
scale_y_reverse(limits=y_limits) +
theme_bw() +
theme(legend.position="none")
g3 = ggplot(ggdata, aes(x=IRR_412, y=PRES)) +
geom_point() +
geom_path(mapping = aes(x=IRR_412_ADJUSTED, y=PRES, color="red")) +
scale_y_reverse(limits=y_limits) +
theme_bw() +
theme(legend.position="none")
g4 = ggplot(ggdata, aes(x=IRR_490, y=PRES)) +
geom_point() +
geom_path(mapping = aes(x=IRR_490_ADJUSTED, y=PRES, color="red")) +
scale_y_reverse(limits=y_limits) +
theme_bw() +
theme(legend.position="none")
g1_log = g1 + scale_x_log10()
g2_log = g2 + scale_x_log10()
g3_log = g3 + scale_x_log10()
g4_log = g4 + scale_x_log10()
#g1_lin = g1 + scale_x_continuous(limits=1*c(-1,1))
#g2_lin = g2 + scale_x_continuous(limits=2*c(-1e-4,1e-4))
#g3_lin = g3 + scale_x_continuous(limits=3*c(-1e-4,1e-4))
#g4_lin = g4 + scale_x_continuous(limits=4*c(-1e-4,1e-4))
g1_lin = g1 + scale_x_continuous(limits=x_limits[[1]])
g2_lin = g2 + scale_x_continuous(limits=x_limits[[2]])
g3_lin = g3 + scale_x_continuous(limits=x_limits[[3]])
g4_lin = g4 + scale_x_continuous(limits=x_limits[[4]])
if (str_sub(filename,-4,-4) == "D") {
plot_name = paste0("radiometry_with_corr_", str_sub(filename, -15, -4), ".png")
} else {
plot_name = paste0("radiometry_with_corr_", str_sub(filename, -14, -4), ".png")
}
png(plot_name, width = 800, height = 800)
grid.arrange(g1_log, g2_log, g3_log, g4_log, g1_lin, g2_lin, g3_lin, g4_lin, nrow=2)
dev.off()
return(0)
}
plot_corr_wrapper <- function(WMO, index_ifremer, path_to_netcdf, n_cores=detectCores(), pres_zoom=FALSE) {
files = as.character(index_ifremer$file) #retrieve the path of each netcfd file
ident = strsplit(files,"/") #separate the different roots of the files paths
ident = matrix(unlist(ident), ncol=4, byrow=TRUE)
wod = ident[,2] #retrieve the WMO of all profiles as a vector
prof_id = ident[,4] #retrieve all profiles name as a vector
#profile_list = paste(path_to_netcdf, files[which(substr(prof_id,3,9)==WMO)], sep="")
files_corr = files[which(substr(prof_id,3,9)==WMO & substr(prof_id,14,14)==".")]
for (i in 1:length(files_corr)) {
path = unlist(strsplit(files_corr[i], "/"))
str_sub(path[4], 2, 2) = "D"
files_corr[i] = paste(path[1], path[2], path[3], "RADM/RADM_profiles", path[4], sep="/")
}
files_corr = paste(path_to_netcdf, files_corr, sep="")
check_file_exists = unlist(mclapply(files_corr, function(file_ls){is.null(attr(try(system2("ls", file_ls, stdout = T), silent=T), "status"))}))
C = mcmapply(plot_corr, files_corr[which(check_file_exists)], mc.cores=n_cores, SIMPLIFY=FALSE, MoreArgs=list(pres_zoom=pres_zoom))
return(C)
}
plot_QC_wrapper <- function(WMO, index_ifremer, path_to_netcdf, n_cores=detectCores(), with_corr=FALSE, do_plot=TRUE, logscale=TRUE) {
files = as.character(index_ifremer$file) #retrieve the path of each netcfd file
ident = strsplit(files,"/") #separate the different roots of the files paths
ident = matrix(unlist(ident), ncol=4, byrow=TRUE)
wod = ident[,2] #retrieve the WMO of all profiles as a vector
prof_id = ident[,4] #retrieve all profiles name as a vector
#profile_list = paste(path_to_netcdf, files[which(substr(prof_id,3,9)==WMO)], sep="")
files_corr = files[which(substr(prof_id,3,9)==WMO & substr(prof_id,14,14)==".")]
for (i in 1:length(files_corr)) {
path = unlist(strsplit(files_corr[i], "/"))
files_corr[i] = paste(path[1], path[2], path[3], "RADM/RADM_profiles", path[4], sep="/")
}
files_corr = paste(path_to_netcdf, files_corr, sep="")
#M = mcmapply(plot_QC, files_corr, mc.cores=num_cores, SIMPLIFY=FALSE, MoreArgs=list(with_corr=FALSE, do_plot=FALSE))
#Mcorr = mcmapply(plot_QC, files_corr, mc.cores=num_cores, SIMPLIFY=FALSE, MoreArgs=list(with_corr=TRUE, do_plot=FALSE))
Mcorr = mcmapply(plot_QC, files_corr, mc.cores=n_cores, SIMPLIFY=FALSE, MoreArgs=list(with_corr=with_corr, do_plot=do_plot, logscale=logscale))
return(Mcorr)
A = t(array(unlist(M, use.names=FALSE), dim=c(4,length(M))))
Acorr = t(array(unlist(Mcorr, use.names=FALSE), dim=c(4,length(M))))
param_name = c("IRR380", "IRR412", "IRR490", "PAR")
sankey_names = paste0("sankey_day_", WMO, "_", param_name, ".html")
for (n in 1:4) {
type = A[,n]
type_corr = Acorr[,n]
change = matrix(0, 4, 4)
rownames(change) = c("1", "2", "3", "4")
colnames(change) = c("corr_1", "corr_2", "corr_3", "corr_4")
for (i in 1:4) {
for (j in 1:4) {
change[i,j] = length(which(type==as.character(i) & type_corr==as.character(j)))
}
}
links = change %>%
as.data.frame() %>%
rownames_to_column(var="source") %>%
gather(key="target", value="value", -1) %>%
filter(value != 0)
nodes = data.frame(
name = c(as.character(links$source), as.character(links$target)) %>%
unique()
)
links$IDsource = match(links$source, nodes$name) -1
links$IDtarget = match(links$target, nodes$name) -1
my_color = 'd3.scaleOrdinal() .domain(["1", "2", "3", "4", "corr_1", "corr_2", "corr_3", "corr_4"]) .range(["#869C66", "#FFCA0B", "#FF9502", "#D43501", "#869C66", "#FFCA0B", "#FF9502", "#D43501"])'
p1 = sankeyNetwork(Links = links, Nodes = nodes,
Source = "IDsource", Target = "IDtarget",
Value = "value", NodeID = "name",
colourScale = my_color)
saveWidget(p1, file=sankey_names[n], selfcontained=FALSE)
}
#write_json(M, path="profile_types.json", auto_unbox=T, pretty=T, null="list")
}
#for (file_i in files_corr[260:length(files_corr)]) {
# apply_plot = plot_QC(file_i, with_corr=TRUE, do_plot=TRUE)
#}
#for (file_i in profile_list[250:270]) {
# apply_plot = plot_QC(file_i, with_corr=FALSE, do_plot=TRUE)
#}