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# Copyright 2017 Open Networking Foundation (ONF)
#
# Please refer questions to either the onos test mailing list at <onos-test@onosproject.org>,
# the System Testing Plans and Results wiki page at <https://wiki.onosproject.org/x/voMg>,
# or the System Testing Guide page at <https://wiki.onosproject.org/x/WYQg>
#
# TestON is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# TestON is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with TestON. If not, see <http://www.gnu.org/licenses/>.
#
# If you have any questions, or if you don't understand R,
# please contact Jeremy Ronquillo: j_ronquillo@u.pacific.edu
# **********************************************************
# STEP 1: File management.
# **********************************************************
print( "STEP 1: File management." )
print( "Reading commmand-line args." )
args <- commandArgs( trailingOnly=TRUE )
# Import libraries to be used for graphing and organizing data, respectively.
# Find out more about ggplot2: https://github.com/tidyverse/ggplot2
# reshape2: https://github.com/hadley/reshape
print( "Importing libraries." )
library( ggplot2 )
library( reshape2 )
library( RPostgreSQL ) # For databases
# Normal usage
# Check if sufficient args are provided.
if ( is.na( args[ 8 ] ) ){
print( "Usage: Rscript SCPFInstalledIntentsFlows <has-flowObj> <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
q() # basically exit(), but in R
}
# paste() is used to concatenate strings.
outputFile <- paste( args[ 8 ], args[ 6 ], sep="" )
if ( args[ 1 ] == "y" ){
outputFile <- paste( outputFile, "flowObj", sep="_" )
}
outputFile <- paste( outputFile, args[ 7 ], sep="_" )
outputFile <- paste( outputFile, "_errGraph.jpg", sep="" )
print( "Reading from databases." )
con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 2 ], port=strtoi( args[ 3 ] ), user=args[ 4 ],password=args[ 5 ] )
command <- "SELECT * FROM max_intents_"
if ( args[ 1 ] == "y" ){
command <- paste( command, "fobj_", sep="" )
}
command <- paste( command, "tests WHERE branch = '", sep = "" )
command <- paste( command, args[ 7 ], sep="" )
command <- paste( command, "' AND date IN ( SELECT MAX( date ) FROM max_intents_", sep="" )
if ( args[ 1 ] == "y" ){
command <- paste( command, "fobj_", sep="" )
}
command <- paste( command, "tests WHERE branch = '", sep = "" )
command <- paste( command, args[ 7 ], sep = "" )
command <- paste( command, "' ) ", sep="" )
print( paste( "Sending SQL command:", command ) )
fileData <- dbGetQuery( con, command )
if ( args[ 1 ] == "y" ){
chartTitle <- "Number of Installed Intents & Flows\n with Flow Objectives"
} else {
chartTitle <- "Number of Installed Intents & Flows"
}
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
fileDataNames <- names( fileData )
avgs <- c()
print( "Sorting data." )
avgs <- c( fileData[ 'max_intents_ovs' ], fileData[ 'max_flows_ovs' ] )
dataFrame <- melt( avgs )
dataFrame$scale <- fileData$scale
colnames( dataFrame ) <- c( "ms", "type", "scale" )
dataFrame$type <- as.character( dataFrame$type )
dataFrame$type <- factor( dataFrame$type, levels=unique( dataFrame$type ) )
dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
print( "Data Frame Results:" )
print( dataFrame )
# **********************************************************
# STEP 3: Generate graphs.
# **********************************************************
print( "Generating fundamental graph data." )
theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
mainPlot <- ggplot( data = dataFrame, aes( x = scale, y = ms, fill = type ) )
xScaleConfig <- scale_x_continuous( breaks=c( 1, 3, 5, 7, 9) )
xLabel <- xlab( "Scale" )
yLabel <- ylab( "Max Number of Intents/Flow Rules" )
fillLabel <- labs( fill="Type" )
theme <- theme( plot.title=element_text( hjust = 0.5, size = 32, face='bold' ), legend.position="bottom", legend.text=element_text( size=22 ), legend.title = element_blank(), legend.key.size = unit( 1.5, 'lines' ) )
colors <- scale_fill_manual( values=c( "#F77670", "#619DFA" ) )
wrapLegend <- guides( fill=guide_legend( nrow=1, byrow=TRUE ) )
fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme + wrapLegend
print( "Generating bar graph bars." )
width <- 1.3
barGraphFormat <- geom_bar( stat="identity", position=position_dodge( ), width = width )
values <- geom_text( aes( x=dataFrame$scale, y=dataFrame$ms + 0.015 * max( dataFrame$ms ), label = format( dataFrame$ms, digits=3, big.mark = ",", scientific = FALSE ) ), size = 5.2, fontface = "bold", position=position_dodge( width=1.25 ) )
title <- ggtitle( chartTitle )
result <- fundamentalGraphData + barGraphFormat + colors + title + values
print( paste( "Saving bar chart to", outputFile ) )
ggsave( outputFile, width = 15, height = 10, dpi = 200 )
print( paste( "Successfully wrote bar chart out to", outputFile ) )