| # 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: Data management. |
| # ********************************************************** |
| has_flow_obj = 1 |
| database_host = 2 |
| database_port = 3 |
| database_u_id = 4 |
| database_pw = 5 |
| test_name = 6 |
| branch_name = 7 |
| has_neighbors = 8 |
| old_flow = 9 |
| save_directory = 10 |
| |
| print( "**********************************************************" ) |
| print( "STEP 1: Data management." ) |
| print( "**********************************************************" ) |
| |
| # Command line arguments are read. |
| print( "Reading commmand-line args." ) |
| args <- commandArgs( trailingOnly=TRUE ) |
| |
| # ---------------- |
| # Import Libraries |
| # ---------------- |
| |
| print( "Importing libraries." ) |
| library( ggplot2 ) |
| library( reshape2 ) |
| library( RPostgreSQL ) # For databases |
| |
| # ------------------- |
| # Check CLI Arguments |
| # ------------------- |
| |
| print( "Verifying CLI args." ) |
| |
| if ( is.na( args[ save_directory ] ) ){ |
| |
| print( paste( "Usage: Rscript SCPFflowTp1g.R", |
| "<has-flow-obj>", |
| "<database-host>", |
| "<database-port>", |
| "<database-user-id>", |
| "<database-password>", |
| "<test-name>", |
| "<branch-name>", |
| "<has-neighbors>", |
| "<using-old-flow>", |
| "<directory-to-save-graphs>", |
| sep=" " ) ) |
| |
| q() # basically exit(), but in R |
| } |
| |
| # ----------------- |
| # Create File Names |
| # ----------------- |
| |
| print( "Creating filenames and title of graph." ) |
| |
| chartTitle <- "Flow Throughput Test" |
| fileNeighborsModifier <- "no" |
| commandNeighborModifier <- "" |
| fileFlowObjModifier <- "" |
| sqlFlowObjModifier <- "" |
| if ( args[ has_flow_obj ] == 'y' ){ |
| fileFlowObjModifier <- "_flowObj" |
| sqlFlowObjModifier <- "_fobj" |
| chartTitle <- paste( chartTitle, " with Flow Objectives", sep="" ) |
| } |
| |
| chartTitle <- paste( chartTitle, "\nNeighbors =", sep="" ) |
| |
| fileOldFlowModifier <- "" |
| if ( args[ has_neighbors ] == 'y' ){ |
| fileNeighborsModifier <- "all" |
| commandNeighborModifier <- "scale=1 OR NOT " |
| chartTitle <- paste( chartTitle, "Cluster Size - 1" ) |
| } else { |
| chartTitle <- paste( chartTitle, "0" ) |
| } |
| if ( args[ old_flow ] == 'y' ){ |
| fileOldFlowModifier <- "_OldFlow" |
| chartTitle <- paste( chartTitle, "With Old Flow", sep="\n" ) |
| } |
| errBarOutputFile <- paste( args[ save_directory ], |
| args[ test_name ], |
| "_", |
| args[ branch_name ], |
| "_", |
| fileNeighborsModifier, |
| "-neighbors", |
| fileFlowObjModifier, |
| fileOldFlowModifier, |
| "_graph.jpg", |
| sep="" ) |
| # ------------------ |
| # SQL Initialization |
| # ------------------ |
| |
| print( "Initializing SQL" ) |
| |
| con <- dbConnect( dbDriver( "PostgreSQL" ), |
| dbname = "onostest", |
| host = args[ database_host ], |
| port = strtoi( args[ database_port ] ), |
| user = args[ database_u_id ], |
| password = args[ database_pw ] ) |
| |
| # --------------------------- |
| # Flow Throughput SQL Command |
| # --------------------------- |
| |
| print( "Generating Flow Throughput SQL command." ) |
| |
| command <- paste( "SELECT scale, avg( avg ), avg( std ) FROM flow_tp", |
| sqlFlowObjModifier, |
| "_tests WHERE (", |
| commandNeighborModifier, |
| "neighbors = 0 ) AND branch = '", |
| args[ branch_name ], |
| "' AND date IN ( SELECT max( date ) FROM flow_tp", |
| sqlFlowObjModifier, |
| "_tests WHERE branch='", |
| args[ branch_name ], |
| "' AND ", |
| ( if( args[ old_flow ] == 'y' ) "" else "NOT " ), |
| "is_old_flow", |
| " ) GROUP BY scale ORDER BY scale", |
| sep="" ) |
| |
| print( "Sending SQL command:" ) |
| print( command ) |
| |
| fileData <- dbGetQuery( con, command ) |
| |
| # ********************************************************** |
| # STEP 2: Organize data. |
| # ********************************************************** |
| |
| print( "**********************************************************" ) |
| print( "STEP 2: Organize Data." ) |
| print( "**********************************************************" ) |
| |
| # ------------ |
| # Data Sorting |
| # ------------ |
| |
| print( "Sorting data for Flow Throughput." ) |
| |
| colnames( fileData ) <- c( "scale", |
| "avg", |
| "std" ) |
| |
| avgs <- c( fileData[ 'avg' ] ) |
| |
| |
| # ---------------------------- |
| # Flow TP Construct Data Frame |
| # ---------------------------- |
| |
| print( "Constructing Flow TP data frame." ) |
| |
| dataFrame <- melt( avgs ) # This is where reshape2 comes in. Avgs list is converted to data frame |
| dataFrame$scale <- fileData$scale # Add node scaling to the data frame. |
| dataFrame$std <- fileData$std |
| |
| colnames( dataFrame ) <- c( "throughput", |
| "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( "**********************************************************" ) |
| print( "STEP 3: Generate Graph." ) |
| print( "**********************************************************" ) |
| |
| # ------------------ |
| # Generate Main Plot |
| # ------------------ |
| |
| print( "Generating 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 node scaling) |
| # - y: y-axis values (usually time in milliseconds) |
| # - fill: the category of the colored side-by-side bars (usually type) |
| |
| mainPlot <- ggplot( data = dataFrame, aes( x = scale, |
| y = throughput, |
| ymin = throughput, |
| ymax = throughput + std, |
| fill = type ) ) |
| # ------------------------------ |
| # Fundamental Variables Assigned |
| # ------------------------------ |
| |
| print( "Generating fundamental graph data." ) |
| |
| # Formatting the plot |
| theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph. |
| width <- 0.7 # Width of the bars. |
| xScaleConfig <- scale_x_continuous( breaks = dataFrame$scale, |
| label = dataFrame$scale ) |
| xLabel <- xlab( "Scale" ) |
| yLabel <- ylab( "Throughput (,000 Flows/sec)" ) |
| fillLabel <- labs( fill="Type" ) |
| imageWidth <- 15 |
| imageHeight <- 10 |
| imageDPI <- 200 |
| errorBarColor <- rgb( 140, 140, 140, maxColorValue=255 ) |
| |
| theme <- theme( plot.title = element_text( hjust = 0.5, |
| size = 32, |
| face = 'bold' ) ) |
| title <- ggtitle( chartTitle ) |
| |
| # Store plot configurations as 1 variable |
| fundamentalGraphData <- mainPlot + |
| xScaleConfig + |
| xLabel + |
| yLabel + |
| fillLabel + |
| theme + |
| title |
| |
| # --------------------------- |
| # Generating Bar Graph Format |
| # --------------------------- |
| |
| # Create the stacked bar graph with error bars. |
| # geom_bar contains: |
| # - stat: data formatting (usually "identity") |
| # - width: the width of the bar types (declared above) |
| # geom_errorbar contains similar arguments as geom_bar. |
| print( "Generating bar graph with error bars." ) |
| barGraphFormat <- geom_bar( stat = "identity", |
| width = width, |
| fill = "#FFAA3C" ) |
| |
| errorBarFormat <- geom_errorbar( width = width, |
| position = position_dodge(), |
| color = errorBarColor ) |
| |
| values <- geom_text( aes( x = dataFrame$scale, |
| y = dataFrame$throughput + 0.03 * max( dataFrame$throughput ), |
| label = format( dataFrame$throughput, |
| digits=3, |
| big.mark = ",", |
| scientific = FALSE ) ), |
| size = 7.0, |
| fontface = "bold" ) |
| |
| result <- fundamentalGraphData + |
| barGraphFormat + |
| errorBarFormat + |
| values |
| |
| # ----------------------- |
| # Exporting Graph to File |
| # ----------------------- |
| |
| print( paste( "Saving bar chart with error bars to", errBarOutputFile ) ) |
| |
| ggsave( errBarOutputFile, |
| width = imageWidth, |
| height = imageHeight, |
| dpi = imageDPI ) |
| |
| print( paste( "[SUCCESS] Successfully wrote bar chart with error bars out to", errBarOutputFile ) ) |