sos4R_wps.R

# wps.des: sos4R_wps_gwl_horo, title = interp mean gw levels per Foi per year via SOS,
# abstract = A Simple and useless demo WPS Process just summing the meaausrements for a given Foi;

# wps.in: year, string;

# calculate something... variable "input" don't has to be initialized
library(sos4R)
library(akima)
library(fields)

c("soe_352007",
  "soe_352051",
  "soe_352111",
  "soe_352131",
  "soe_352271",
  "soe_352311",
  "soe_353291",
  "soe_361003",
  "soe_361041",
  "soe_362003",
  "soe_362005",
  "soe_362017",
  "soe_362033",
  "soe_362331",
  "soe_362541",
  "soe_362551",
  "soe_362661",
  "soe_362711",
  "soe_362951",
  "soe_362511",
  "soe_362521",
  "soe_363251",
  "soe_372061")

myopts <- curlOptions(ssl.verifyhost=FALSE, ssl.verifypeer=FALSE, followlocation=TRUE)
handle <- getCurlHandle( .opts= myopts)

gwl.converters <- SosDataFieldConvertingFunctions(
  "http://resources.smart-project.info/gemet/groundwaterlevel" = sosConvertDouble,
  "http://www.opengis.net/def/property/OGC/0/SamplingTime" = sosConvertTime,
  "http://www.opengis.net/def/property/OGC/0/FeatureOfInterest" = sosConvertString)
gwl <- SOS(url = "http://portal.smart-project.info/52nSOSv3.5.0/sos",
           dataFieldConverters = gwl.converters, curlHandle=handle)


yearString = paste(c(year, '/01/01::', year, '/12/31'), collapse='')
yearTP = sosCreateTime(sos = gwl, time = yearString)

gwl_offerings <- sosOfferings(gwl)
gwl_off_no2 <- gwl_offerings[[2]]

observ<-getObservation(sos = gwl, offering=gwl_off_no2, saveOriginal = FALSE, eventTime = yearTP)
result<-sosResult(observ, coordinates = TRUE)
measLevel <- colnames(result)[[2]]
obs.crs<-sosGetCRS(observ)

gwl_spdf<-SpatialPointsDataFrame(coords = result[,c("lon", "lat")],data = result[,c("SamplingTime", "feature", measLevel)],proj4string = obs.crs)
gwl_spdf_sc <- as(observ, "SpatialPointsDataFrame")

x <- result[["lat"]]
y <- result[["lon"]]
z <- result[[measLevel]]
matr <- interp(x,y,z, duplicate = "mean", linear = TRUE)

zr<-range(result[[measLevel]])
# zr<-range(c(0, 50))

image.plot(matr, zlim = zr )
points(gwl_spdf_sc, pch = 19)

randnum <- sample(10000:99999, 1)
image = paste(c('tmp-sos-interp-',randnum ,'.png'), collapse='')
png(file = image)
titletext = paste(c('interpolated groundwater levels in the Horowhenua area'), collapse='')
subtitletext = paste(c('gwl/masl ', year, '/01/01 - ', year, '/12/31'), collapse='')
image.plot(matr, zlim = zr)
title(main = titletext, sub = subtitletext )
# dev.off()
graphics.off()

# wps.out: image, png;