library('pacman')
p_load('ggplot2')
p_load('solaR')
p_load('stringr')
p_load('lubridate')

sol = readRDS(file="sol.Rda")

irradiance <- function(lat,alfa) {
  g = calcGef(
	      lat,		# latitude argument
	      modeTrk='fixed',  # does not track the sun
	      modeRad='bdI',    # daily irradiance
	      dfI2Meteo(sol, time.col = 'timestamp', lat=lat, format='%Y-%m-%d %H:%M:%S'),
	      keep.night=TRUE,
	      sunGeometry='michalsky',
	      beta=90, 
	      alfa=alfa,
	      corr='none',
	      iS=2, 
	      alb=0.0)
   
   g = as.data.frameI(g)[c('Gef')]
   g =tail(head(g,n=6000),n=24)
   g = data.frame(time=as.numeric(ymd_hms(rownames(g))),G=g$Gef, Z = paste("g",abs(alfa),sep=""))
   assign(paste("g",abs(alfa), sep=""), g, envir= .GlobalEnv)
}


R = c(-138,-48,42,132)
L = c(1,1)
H = 2.5
A = L*H
G = c(0.5,0.5)


for (i in R){
  irradiance(i)
}

#rm(sol)

#df = cbind(names(which(unlist(eapply(.GlobalEnv,is.data.frame)))))
gval=0.92
g138$G=g138$G*35*gval
g48$G=g48$G*15*gval
g42$G=g42$G*21*gval
g132$G=g132$G*15*gval

df = rbind(g138,g48,g42,g132)


pdf('stack3.pdf')

ggplot(df, aes(x = time, y = G, fill = Z,)) + 
geom_area(position = 'stack') 

#xlim(1486960000, 1486971200)

dev.off()

#df2 = df*A*G

#df2$time = as.numeric(ymd_hms(rownames(df2)))

#df2$time = as.numeric(df2$time)