| # 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." ) |
| |
| # Command line arguments are read. |
| 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 |
| |
| |
| # Check if sufficient args are provided. |
| if ( is.na( args[ 7 ] ) ){ |
| print( "Usage: Rscript SCPFhostLat <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 |
| errBarOutputFile <- paste( args[ 7 ], args[ 5 ], sep="" ) |
| errBarOutputFile <- paste( errBarOutputFile, args[ 6 ], sep="_" ) |
| errBarOutputFile <- paste( errBarOutputFile, "_errGraph.jpg", sep="" ) |
| |
| print( "Reading from databases." ) |
| |
| con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 1 ], port=strtoi( args[ 2 ] ), user=args[ 3 ],password=args[ 4 ] ) |
| |
| command <- paste( "SELECT * FROM host_latency_tests WHERE branch = '", args[ 6 ], sep = "" ) |
| command <- paste( command, "' AND date IN ( SELECT MAX( date ) FROM host_latency_tests WHERE branch = '", sep = "" ) |
| command <- paste( command, args[ 6 ], sep = "" ) |
| command <- paste( command, "' ) ", sep="" ) |
| |
| print( paste( "Sending SQL command:", command ) ) |
| |
| fileData <- dbGetQuery( con, command ) |
| |
| chartTitle <- "Host Latency" |
| |
| |
| # ********************************************************** |
| # STEP 2: Organize data. |
| # ********************************************************** |
| |
| print( "STEP 2: Organize data." ) |
| |
| avgs <- c() |
| |
| print( "Sorting data." ) |
| avgs <- c( fileData[ 'avg' ] ) |
| |
| dataFrame <- melt( avgs ) |
| dataFrame$scale <- fileData$scale |
| dataFrame$std <- fileData$std |
| |
| colnames( dataFrame ) <- c( "ms", "type", "scale", "std" ) |
| |
| 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 = 20 ) ) # set the default text size of the graph. |
| mainPlot <- ggplot( data = dataFrame, aes( x = scale, y = ms, ymin = ms - std, ymax = ms + std ) ) |
| xScaleConfig <- scale_x_continuous( breaks=c( 1, 3, 5, 7, 9) ) |
| xLabel <- xlab( "Scale" ) |
| yLabel <- ylab( "Latency (ms)" ) |
| fillLabel <- labs( fill="Type" ) |
| theme <- theme( plot.title=element_text( hjust = 0.5, size = 28, face='bold' ) ) |
| |
| fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme |
| |
| |
| print( "Generating bar graph with error bars." ) |
| width <- 0.9 |
| barGraphFormat <- geom_bar( stat="identity", position=position_dodge( ), width = width, fill="#E8BD00" ) |
| errorBarFormat <- geom_errorbar( position=position_dodge(), width = width, color=rgb( 140, 140, 140, maxColorValue=255 ) ) |
| values <- geom_text( aes( x=dataFrame$scale, y=dataFrame$ms + 0.08 * max( dataFrame$ms ), label = format( dataFrame$ms, digits=3, big.mark = ",", scientific = FALSE ) ), size = 5, fontface = "bold" ) |
| title <- ggtitle( paste( chartTitle, "with Standard Error Bars" ) ) |
| result <- fundamentalGraphData + barGraphFormat + errorBarFormat + title + values |
| |
| |
| print( paste( "Saving bar chart with error bars to", errBarOutputFile ) ) |
| ggsave( errBarOutputFile, width = 10, height = 6, dpi = 200 ) |
| |
| print( paste( "Successfully wrote bar chart out to", errBarOutputFile ) ) |