fogDec: Fog Classification

## script: compute image features

## Load Libraries
library(data.table)
library(fogDec)
library(visDec)
library(ggplot2)
library(doParallel)
library(imager)
library(changepoint) # functionality should be included in imager
library(maptools)



cl<-makePSOCKcluster(4)
#primary<-'127.0.0.1'
#user<-'andrea'
#machineAddresses <- list(
 #    list(host=primary,user=user,
  #      ncore=2)
 # )

## make cluster
#registerDoParallel(cores=4)


# i<-0
# machines<-list()
# ## the users and addresses are based on the AWS configuration
# user    <- 'ubuntu'
# primary <- '172.31.45.30'
# 
# #IPs contains a list of slaves that will run the computations
# IPs<-paste0("172.31.46.", seq(from = 24, to = 33))
# #IPs<-c(IPs, "172.31.38.73") ##slave gold master machine
# #IPs<-c("172.31.38.73")
# for (ip in IPs){
#   i<-i+1
#   machines[[i]]<-list(host=ip, user = user, ncore=4)
# }
# 
# machineAddresses <- list(
#   list(host=primary,user=user,
#        ncore=1)
# )
# machineAddresses<-c(machineAddresses,machines)
# 
# #characteristics of the cluster are assigned (e.g., IPs, hosts, users, IPs)
# spec <- lapply(machineAddresses,
#                function(machine) {
#                   rep(list(list(host=machine$host,
#                                user=machine$user)),
#                      machine$ncore)
#                 })
# spec <- unlist(spec,recursive=FALSE)
# 
# #cluster is created (the communication between master and slaves takes place on the port 11000 and is a SSH-like session)
# parallelCluster <- parallel::makeCluster(type='PSOCK',
#                                          master=primary,
#                                          spec=spec,
#                                          port=11000, outfile="")
# print(parallelCluster)

#source("./R/CoreFeatureCompute.R")# we might export those functions


##some libraries and functions are explicitly exported
#clusterEvalQ(parallelCluster, library(imager), FileNameParser())
parallelCluster <- cl
clusterEvalQ(parallelCluster, c(library(imager),library(data.table)))
clusterEvalQ(parallelCluster, c(library(fogDec)))
clusterExport(parallelCluster,"FileNameParser")
registerDoParallel(parallelCluster)


## get configuration

propertiesLoc <- fread("properties.csv") #, stringsAsFactors = FALSE)

#print(propertiesLocations)

## extract features save the data.table (do not print anything / besides progress)


apply(propertiesLoc, 1, fogDec:::featureExtraction)


##stop the cluster
stopImplicitCluster()