| # 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: jeremyr@opennetworking.org |
| |
| # This is the R script that generates the SCPF front page graphs. |
| |
| # ********************************************************** |
| # STEP 1: Data management. |
| # ********************************************************** |
| |
| print( "STEP 1: Data management." ) |
| |
| # 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 |
| # RPostgreSQL: https://code.google.com/archive/p/rpostgresql/ |
| print( "Importing libraries." ) |
| library( ggplot2 ) |
| library( reshape2 ) |
| library( RPostgreSQL ) |
| |
| # Command line arguments are read. Args include the database credentials, test name, branch name, and the directory to output files. |
| print( "Reading commmand-line args." ) |
| args <- commandArgs( trailingOnly=TRUE ) |
| |
| # Check if sufficient args are provided. |
| if ( is.na( args[ 10 ] ) ){ |
| print( "Usage: Rscript testresultgraph.R <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <#-dates> <SQL-command> <y-axis> <directory-to-save-graph>" ) |
| q() # basically exit(), but in R |
| } |
| |
| # Filenames for the output graph include the testname, branch, and the graph type. |
| |
| outputFile <- paste( args[ 10 ], "SCPF_Front_Page" , sep="" ) |
| outputFile <- paste( outputFile, gsub( " ", "_", args[ 5 ] ), sep="_" ) |
| outputFile <- paste( outputFile, args[ 6 ], sep="_" ) |
| outputFile <- paste( outputFile, args[ 7 ], sep="_" ) |
| outputFile <- paste( outputFile, "dates", sep="-" ) |
| outputFile <- paste( outputFile, "_graph.jpg", sep="" ) |
| |
| # From RPostgreSQL |
| print( "Reading from databases." ) |
| con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 1 ], port=strtoi( args[ 2 ] ), user=args[ 3 ],password=args[ 4 ] ) |
| |
| print( "Sending SQL command." ) |
| fileData <- dbGetQuery( con, args[ 8 ] ) |
| |
| # Title of graph based on command line args. |
| title <- args[ 5 ] |
| |
| # ********************************************************** |
| # STEP 2: Organize data. |
| # ********************************************************** |
| |
| print( "STEP 2: Organize data." ) |
| |
| # Create lists c() and organize data into their corresponding list. |
| print( "Sorting data into new data frame." ) |
| |
| if ( ncol( fileData ) > 1 ){ |
| for ( i in 2:ncol( fileData ) ){ |
| fileData[ i ] <- fileData[ i - 1 ] + fileData[ i ] |
| } |
| } |
| |
| # Parse lists into data frames. |
| # This is where reshape2 comes in. Avgs list is converted to data frame. |
| dataFrame <- melt( fileData ) |
| |
| dataFrame$date <- fileData$date |
| |
| colnames( dataFrame ) <- c( "Legend", "Values" ) |
| |
| # Format data frame so that the data is in the same order as it appeared in the file. |
| dataFrame$Legend <- as.character( dataFrame$Legend ) |
| dataFrame$Legend <- factor( dataFrame$Legend, levels=unique( dataFrame$Legend ) ) |
| |
| # Adding a temporary iterative list to the dataFrame so that there are no gaps in-between date numbers. |
| dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) ) |
| |
| dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist |
| |
| print( "Data Frame Results:" ) |
| print( dataFrame ) |
| |
| # ********************************************************** |
| # STEP 3: Generate graphs. |
| # ********************************************************** |
| |
| print( "STEP 3: Generate graphs." ) |
| |
| print( "Creating main plot." ) |
| # Create the primary plot here. |
| # ggplot contains the following arguments: |
| # - data: the data frame that the graph will be based off of |
| # - aes: the asthetics of the graph which require: |
| # - x: x-axis values (usually iterative, but it will become date # later) |
| # - y: y-axis values (usually tests) |
| # - color: the category of the colored lines (usually legend of test) |
| theme_set( theme_grey( base_size = 20 ) ) # set the default text size of the graph. |
| mainPlot <- ggplot( data = dataFrame, aes( x = iterative, y = Values, color = Legend ) ) |
| |
| print( "Formatting main plot." ) |
| |
| # Store plot configurations as 1 variable |
| fundamentalGraphData <- mainPlot + expand_limits( y = 0 ) |
| |
| yScaleConfig <- scale_y_continuous( breaks = seq( 0, max( dataFrame$Values ) * 1.05, by = ceiling( max( dataFrame$Values ) / 10 ) ) ) |
| |
| xLabel <- xlab( "Date" ) |
| yLabel <- ylab( args[ 9 ] ) |
| fillLabel <- labs( fill="Type" ) |
| legendLabels <- scale_colour_discrete( labels = names( fileData ) ) |
| centerTitle <- theme( plot.title=element_text( hjust = 0.5 ) ) # To center the title text |
| theme <- theme( axis.text.x = element_blank(), axis.ticks.x = element_blank(), plot.title = element_text( size = 28, face='bold' ) ) |
| |
| fundamentalGraphData <- fundamentalGraphData + yScaleConfig + xLabel + yLabel + fillLabel + legendLabels + centerTitle + theme |
| print( "Generating line graph." ) |
| |
| lineGraphFormat <- geom_line() |
| pointFormat <- geom_point( size = 0.2 ) |
| title <- ggtitle( title ) |
| |
| result <- fundamentalGraphData + lineGraphFormat + pointFormat + title |
| |
| # Save graph to file |
| print( paste( "Saving result graph to", outputFile ) ) |
| ggsave( outputFile, width = 10, height = 6, dpi = 200 ) |
| print( paste( "Successfully wrote result graph out to", outputFile ) ) |