#Reading NetCDF-files
library(ncdf4)
library(ggplot2)
library(reshape2)

#setwd("Dropbox/karine/fraGunhild/OneDrive_4_2-8-2019/")
ncname <- "INDORSE-Franfjorden-Scenario1_modified-2018.10.10_concentration.nc"
my_data <- nc_open("INDORSE-Franfjorden-Scenario1_modified-2018.10.09_concentration.nc")

# Printer info om datasettet. Alle variabler og dimensjoner. 
print(my_data)

# Henter ut variabler.
total_concentration <- ncvar_get(my_data, "total_concentration")  # [lon, lat, depth, time]
lat <- ncvar_get(my_data, "latitude")
lon <- ncvar_get(my_data, "longitude")
depth <- ncvar_get(my_data, "depth")
time <- ncvar_get(my_data, "time")

#Just some bit of the area:
relevant_lon_pos = which(lon>7.11 & lon<7.13)
relevant_lat_pos = which(lat<62.85 & lat>62.84)


rel_lon = lon[relevant_lon_pos]
rel_lat = lat[relevant_lat_pos]
#Making one large vector for plotting
lonVec = rep(rel_lon, length(rel_lat))
latVec = rep(rel_lat, each = length(rel_lon))

#If we want the whole area:
relevant_lon_pos = 1:length(lon)
relevant_lat_pos = 1:length(lat)

#Making one large vector for plotting
lonVec = rep(relevant_lon_pos, length(relevant_lat_pos))
latVec = rep(relevant_lat_pos, each = length(relevant_lon_pos))

################################################
#Testing for one (high tide) time and one depth:
#total_concentration[longitude, latitude, depth, time]
snapshot = total_concentration[relevant_lon_pos,relevant_lat_pos,which(depth==15),211]

consVec = melt(snapshot, value.name = 'cons')

ggplot(data.frame(consVec), aes(x=lonVec, y=latVec))+ 
  geom_raster(aes(fill = cons)) + 
  scale_fill_gradientn(colors =c('blue4','red'))+
  ggtitle("") +
  theme(plot.title = element_text(hjust = 0.5))


# Gj??r om til fornuftig tidspunkt. Origin blir hentet fra my_data$dim$time$units.
date = as.POSIXct(time,origin = "2018-10-07",tz = "GMT")