#!R -f
library(ggplot2)
library(ggthemes)
library(scales)
library(xtable)
library(grid)
library(dplyr)

all <- read.csv("results.tsv",sep="\t",header=F, stringsAsFactors=F)
names(all) <- c("exp", "sys", "conf", "s", "r", "timesec")

ybreaks <- c(.01,.1,1,10,60,600)
ylabels <- c("10ms","100ms","1s", "10s","1min", "10min")

xbreaks <- 10^(5:9)
xlabels <- c(expression(10^5),expression(10^6),expression(10^7),expression(10^8),expression(10^9))

theme <- theme_few(base_size = 24) + 
theme(axis.title.y=element_text(vjust=0.9), 
	  axis.title.x=element_text(vjust=-0.1),
	  text=element_text(family="serif"),
	legend.position = "none"
    )


se <- function(x) sqrt(var(x)/length(x))






# parallel


d <- all %>% filter(exp=="parallel", s  == 8) %>% group_by(exp, sys, conf) %>% 
	summarize(meant=mean(timesec), se=se(timesec)) %>% 
	mutate(threads=ifelse(conf=="none", 1L, as.integer(conf))) %>% mutate(tool=paste(sys,threads)) %>% filter(threads < 32)

print(d)


limits <- aes(ymax = meant + se, ymin=meant - se, width=2)

pdf("parallel.pdf",width=10,height=7)
p <- ggplot(d,aes(threads,meant,group=sys)) + 
  geom_point(size=4) + geom_line(size=1.5, aes(group=sys, linetype=sys)) +
  geom_pointrange(limits) +
  scale_y_continuous(limits=c(0,NA)) +
   scale_x_continuous(breaks=unique(d$threads)) +
 geom_vline(xintercept = 10) +
	xlab("Number of Threads") + ylab("Execution Time (s)") + theme +
		annotate("text", x=13.1, y=1.5, label="Problem parallelism", family="serif", size=10) +

	annotate("text", x=2, y=0.4, label="Laptop", family="serif", size=10)+
	annotate("text", x=3, y=1, label="Server", family="serif", size=10)

print(p)
dev.off()


# f <- d %>% group_by(exp, sys, s) %>% summarize(maxmt=max(meant))

# d <- d %>% left_join(f) %>% mutate(speedup = maxmt/meant) %>% select(s,threads,speedup)


# print(d)

# pdf("speedup.pdf",width=10,height=7)
# p <- ggplot(d,aes(threads,speedup,group=s)) + 
#   geom_point(size=4) + geom_line(size=1.5, aes(group=s, linetype=sys)) +
#   scale_y_continuous(limits=c(0,NA)) +
#    scale_x_continuous(breaks=unique(d$threads)) +
# 	xlab("Number of Threads") + ylab("Speedup") + theme #+
# #	annotate("text", x=10, y=6, label="Problem parallelism", family="serif", size=10) #+
# 	# annotate("text", x=3.5, y=20, label="Renjin ", family="serif", size=10)

# print(p)
# dev.off()


stop()
# recycling
d <- all %>% filter(exp=="recycling", s > 5) %>% group_by(exp, sys, s, conf) %>% 
	summarize(meant=mean(timesec), se=se(timesec)) %>% 
	mutate(datasize=10^as.integer(s), tool=paste(sys, conf))

print(d)

limits <- aes(ymax = meant + se, ymin=meant - se, width=2)

pdf("recycling.pdf",width=10,height=7)
p <- ggplot(d,aes(datasize,meant,group=tool)) + 
  geom_point(size=4) + geom_line(size=1.5, aes(group=tool, linetype=tool)) +
  geom_pointrange(limits) +
#  scale_y_log10(breaks=ybreaks, labels=ylabels) +
    scale_x_log10(breaks=xbreaks, labels=xlabels) +

	xlab("Dataset Size (elements, log scale)") + ylab("Execution Time (s)") + theme +
	annotate("text", x=10^7.7, y=65, label="Renjin", family="serif", size=10)+
	annotate("text", x=10^7.7, y=2, label="Renjin + R.", family="serif", size=10)+
	annotate("text", x=10^7.8, y=21, label="GNU R", family="serif", size=10)


print(p)
dev.off()

# survey
d <- all %>% filter(exp=="survey") %>% group_by(sys, s, conf) %>% 
	summarize(meant=mean(timesec), se=se(timesec)) %>% 
	mutate(tool=paste(sys,conf), 
		datasize=sapply(s, switch, alabama=47512, california=1060060, acs3yr=9093077)) %>% 
	filter(tool == "Renjin jitopt" | sys != "Renjin")

print(d)

limits <- aes(ymax = meant + se, ymin=meant - se, width=2)

pdf("survey.pdf",width=10,height=7)
ggplot(d,aes(datasize,meant,group=tool)) + 
  geom_point(size=4) + geom_line(size=1.5, aes(group=tool, linetype=tool)) +
  geom_pointrange(limits) +
  #scale_y_log10(breaks=ybreaks, labels=ylabels) +
    scale_x_log10(breaks=c(47512,1060060,9093077)) +

	xlab("Dataset Size (elements, log scale)") + ylab("Execution Time (s)") + theme +
	annotate("text", x=10^6.6, y=45, label="GNU R", family="serif", size=10)+
	annotate("text", x=10^6.4, y=100, label="sqlsurvey", family="serif", size=10)+
	annotate("text", x=10^6.8, y=15, label="Renjin", family="serif", size=10)

	#scale_color_brewer(palette=cBrwPl) +
 #guides(colour=guide_legend(keywidth=3.5))

dev.off()


# # identity
d <- all %>% filter(exp=="identity", s > 5) %>% group_by(exp, sys, conf, s) %>% 
	summarize(meant=mean(timesec), se=se(timesec)) %>% 
	mutate(tool=ifelse(conf=="none", sys, paste(sys,conf)), datasize=10^as.integer(s))

print(d)

limits <- aes(ymax = meant + se, ymin=meant - se, width=2)

pdf("identity.pdf",width=10,height=7)
ggplot(d,aes(datasize,meant,group=tool)) + 
  geom_point(size=4) + geom_line(size=1.5, aes(group=tool, linetype=tool)) +
  geom_pointrange(limits) +
  #scale_y_log10(breaks=ybreaks, labels=ylabels) +
    scale_x_log10(breaks=xbreaks, labels=xlabels) +

	xlab("Dataset Size (elements, log scale)") + ylab("Execution Time (s)") + theme +
	annotate("text", x=60000000, y=4, label="GNU R", family="serif", size=10)+
	annotate("text", x=40000000, y=8.1, label="Renjin ", family="serif", size=10)+
	annotate("text", x=40000000, y=.6, label="Renjin + Identity", family="serif", size=10)

	#scale_color_brewer(palette=cBrwPl) +
 # guides(colour=guide_legend(keywidth=3.5))

dev.off()


# pushdown

d <- all %>% filter(exp=="pushdown", s > 4) %>% group_by(exp, sys, s) %>% 
	summarize(meant=mean(timesec), se=se(timesec)) %>% 
	mutate(tool=sys, datasize=10^as.integer(s))

print(d)

limits <- aes(ymax = meant + se, ymin=meant - se, width=2)

pdf("pushdown.pdf",width=10,height=7)
p <- ggplot(d,aes(datasize,meant,group=tool)) + 
  geom_point(size=4) + geom_line(size=1.5, aes(group=tool, linetype=tool)) +
  geom_pointrange(limits) +
 # scale_y_log10(breaks=ybreaks, labels=ylabels) +
    scale_x_log10(breaks=xbreaks, labels=xlabels) +

	xlab("Dataset Size (elements, log scale)") + ylab("Execution Time (s)") + theme +
	annotate("text", x=10^7.5, y=5, label="GNU R", family="serif", size=10)+
	annotate("text", x=10^7.6, y=.4, label="Renjin ", family="serif", size=10)

print(p)
dev.off()




# operators
d <- all %>% filter(exp=="operators", s > 5) %>% group_by(exp, sys, s, conf) %>% 
	summarize(meant=mean(timesec), se=se(timesec)) %>% 
	mutate(conf=ifelse(conf=="opt"," + Vectorization",""), tool=paste(sys,conf,sep=""), datasize=10^as.integer(s))

print(d)

limits <- aes(ymax = meant + se, ymin=meant - se, width=2)

pdf("operators.pdf",width=10,height=7)
p <- ggplot(d,aes(datasize,meant,group=tool)) + 
  geom_point(size=4) + geom_line(size=1.5, aes(group=tool, linetype=tool)) +
  geom_pointrange(limits) +
   # scale_y_log10(breaks=ybreaks, labels=ylabels) +
    scale_x_log10(breaks=xbreaks, labels=xlabels, limits=c(NA, 10^8.1)) +

	xlab("Dataset Size (elements, log scale)") + ylab("Execution Time (log)") + theme +

	annotate("text", x=10^7.8, y=4, label="GNU R", family="serif", size=10)+
	annotate("text", x=40000000, y=19, label="Renjin ", family="serif", size=10)+
	annotate("text", x=10^7.95, y=14, label="Renjin + V.", family="serif", size=10)

	#annotate("text", x=700000, y=6, label="Renjin", family="serif", size=10)+
	#annotate("text", x=20000000, y=2, label="Renjin + Recycling", family="serif", size=10)


print(p)
dev.off()


# # print some latex for the paper
# selection$timesec <- selection$timesec/1000
# selproj$timesec <- selproj$timesec/1000
# grouping$timesec <- grouping$timesec/1000
# joins$timesec <- joins$timesec/1000

# selection <- cast(selection,datasetn+oparg ~ tool)
# selproj <- cast(selproj,datasetn+oparg ~ tool)
# joins <- cast(joins,datasetn+oparg ~ tool)
# grouping <- cast(grouping,datasetn+opargn ~ tool)

# selection[1] <- ""
# print(xtable(selection),include.rownames=FALSE)

# selproj[1] <- ""
# print(xtable(selproj),include.rownames=FALSE)

# grouping[1] <- ""
# print(xtable(grouping),include.rownames=FALSE)

# joins[1] <- ""
# print(xtable(joins),include.rownames=FALSE)