#!/usr/bin/env Rscript
# Copyright (c) 2018-2019 Intel Corporation
#
# SPDX-License-Identifier: Apache-2.0

# Show effects of parallel container launch on boot and deletion times by
# launching and killing off a deployment whilst ramping the number of pods requested.

suppressMessages(suppressWarnings(library(ggplot2)))	# ability to plot nicely.
							# So we can plot multiple graphs
library(gridExtra)					# together.
suppressMessages(suppressWarnings(library(ggpubr)))	# for ggtexttable.
suppressMessages(library(jsonlite))			# to load the data.
suppressMessages(library(scales))			# For de-science notation of axis

render_parallel <- function()
{
	testnames=c(
		"k8s-parallel*"
	)

	data=c()
	stats=c()
	rstats=c()
	rstats_names=c()
	cstats=c()
	cstats_names=c()

	skip_points_enable_smooth=0	# Should we draw the points as well as lines on the graphs.

	for (currentdir in resultdirs) {
		dirstats=c()
		for (testname in testnames) {
			matchdir=paste(inputdir, currentdir, sep="")
			matchfile=paste(testname, '\\.json', sep="")
			files=list.files(matchdir, pattern=matchfile)
			if ( length(files) == 0 ) {
				#warning(paste("Pattern [", matchdir, "/", matchfile, "] matched nothing"))
			}
			for (ffound in files) {
				fname=paste(inputdir, currentdir, ffound, sep="")
				if ( !file.exists(fname)) {
					warning(paste("Skipping non-existent file: ", fname))
					next
				}

				# Derive the name from the test result dirname
				datasetname=basename(currentdir)

				# Import the data
				fdata=fromJSON(fname)
				# De-nest the test name specific data
				shortname=substr(ffound, 1, nchar(ffound)-nchar(".json"))
				fdata=fdata[[shortname]]

				testname=datasetname

				# convert ms to seconds
				cdata=data.frame(boot_time=as.numeric(fdata$BootResults$launch_time$Result)/1000)
				cdata=cbind(cdata, delete_time=as.numeric(fdata$BootResults$delete_time$Result)/1000)
				cdata=cbind(cdata, npod=as.numeric(fdata$BootResults$n_pods$Result))

				# If we have more than 20 items to draw, then do not draw the points on
				# the graphs, as they are then too noisy to read.
				# But, do draw the smoothed lines to help read the now dense and potentially
				# noisy graphs.
				if (length(cdata[, "boot_time"]) > 20) {
					skip_points_enable_smooth=1
				}

				cdata=cbind(cdata, testname=rep(testname, length(cdata[, "boot_time"]) ))
				cdata=cbind(cdata, dataset=rep(datasetname, length(cdata[, "boot_time"]) ))

				# Store away as a single set
				data=rbind(data, cdata)
			}
		}
	}

	# If we found nothing to process, quit early and nicely
	if ( length(data) == 0 ) {
		cat("No results files found for parallel tests\n\n")
		return()
	}

	# Show how boot time changed
	boot_line_plot <- ggplot( data=data, aes(npod, boot_time, colour=testname, group=dataset)) +
		geom_line( alpha=0.2) +
		xlab("parallel pods") +
		ylab("Boot time (s)") +
		ggtitle("Deployment boot time (detail)") +
		#ylim(0, NA) + # For big machines, better to not 0-index
		theme(axis.text.x=element_text(angle=90))

		if ( skip_points_enable_smooth == 0 ) {
			boot_line_plot = boot_line_plot + geom_point(alpha=0.3)
		} else {
			boot_line_plot = bool_line_plot + geom_smooth(se=FALSE, method="loess", size=0.3)
		}

		# And get a zero Y index plot.
		boot_line_plot_zero = boot_line_plot + ylim(0, NA) +
			ggtitle("Deployment boot time (0 index)")

	# Show how boot time changed
	delete_line_plot <- ggplot( data=data, aes(npod, delete_time, colour=testname, group=dataset)) +
		geom_line(alpha=0.2) +
		xlab("parallel pods") +
		ylab("Delete time (s)") +
		ggtitle("Deployment deletion time (detail)") +
		#ylim(0, NA) + # For big machines, better to not 0-index
		theme(axis.text.x=element_text(angle=90))

		if ( skip_points_enable_smooth == 0 ) {
			delete_line_plot = delete_line_plot + geom_point(alpha=0.3)
		} else {
			delete_line_plot = delete_line_plot + geom_smooth(se=FALSE, method="loess", size=0.3)
		}

		# And get a 0 indexed Y axis plot
		delete_line_plot_zero = delete_line_plot + ylim(0, NA) +
			ggtitle("Deployment deletion time (0 index)")

	# See https://www.r-bloggers.com/ggplot2-easy-way-to-mix-multiple-graphs-on-the-same-page/ for
	# excellent examples
	master_plot = grid.arrange(
		boot_line_plot_zero,
		delete_line_plot_zero,
		boot_line_plot,
		delete_line_plot,
		nrow=2,
		ncol=2 )
}

render_parallel()