[ONOS-7175]: Refractor R Scripts that generate wiki result graphs in TestON.
- Code is "chunked"; blocks of code are sectioned into sub-steps.
- Many comments have been added and updated.
- Many console messages have been added and updated.
Change-Id: I86853b4a3917d807e634311b672ab6d6d57b1194
diff --git a/TestON/JenkinsFile/scripts/SCPFflowTp1g.R b/TestON/JenkinsFile/scripts/SCPFflowTp1g.R
index 26584ad..9c79ac8 100644
--- a/TestON/JenkinsFile/scripts/SCPFflowTp1g.R
+++ b/TestON/JenkinsFile/scripts/SCPFflowTp1g.R
@@ -21,89 +21,158 @@
# please contact Jeremy Ronquillo: j_ronquillo@u.pacific.edu
# **********************************************************
-# STEP 1: File management.
+# STEP 1: Data management.
# **********************************************************
-print( "STEP 1: File management." )
+print( "**********************************************************" )
+print( "STEP 1: Data management." )
+print( "**********************************************************" )
# 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
+# ----------------
+# Import Libraries
+# ----------------
+
print( "Importing libraries." )
library( ggplot2 )
library( reshape2 )
library( RPostgreSQL ) # For databases
-# Normal usage
-# Check if sufficient args are provided.
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
if ( is.na( args[ 9 ] ) ){
- print( "Usage: Rscript SCPFflowTp1g.R <has-flow-obj> <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <has-neighbors> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript SCPFflowTp1g.R",
+ "<has-flow-obj>",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<has-neighbors>",
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
q() # basically exit(), but in R
}
-# paste() is used to concatenate strings.
-errBarOutputFile <- paste( args[ 9 ], args[ 6 ], sep="" )
-errBarOutputFile <- paste( errBarOutputFile, args[ 7 ], sep="_" )
-if ( args[ 8 ] == 'y' ){
- errBarOutputFile <- paste( errBarOutputFile, "all-neighbors", sep="_" )
-} else {
- errBarOutputFile <- paste( errBarOutputFile, "no-neighbors", sep="_" )
-}
-if ( args[ 1 ] == 'y' ){
- errBarOutputFile <- paste( errBarOutputFile, "flowObj", sep="_")
-}
-errBarOutputFile <- paste( errBarOutputFile, "_graph.jpg", sep="" )
+# -----------------
+# Create File Names
+# -----------------
-print( "Reading from databases." )
-con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 2 ], port=strtoi( args[ 3 ] ), user=args[ 4 ],password=args[ 5 ] )
+print( "Creating filenames and title of graph." )
+chartTitle <- "Flow Throughput Test"
+fileNeighborsModifier <- "no"
commandNeighborModifier <- ""
-flowObjModifier <- ""
+fileFlowObjModifier <- ""
+sqlFlowObjModifier <- ""
if ( args[ 1 ] == 'y' ){
- flowObjModifier <- "_fobj"
+ fileFlowObjModifier <- "_flowObj"
+ sqlFlowObjModifier <- "_fobj"
+ chartTitle <- paste( chartTitle, " with Flow Objectives", sep="" )
}
+
+chartTitle <- paste( chartTitle, "\nNeighbors =", sep="" )
+
if ( args[ 8 ] == 'y' ){
+ fileNeighborsModifier <- "all"
commandNeighborModifier <- "scale=1 OR NOT "
+ chartTitle <- paste( chartTitle, "Cluster Size - 1" )
+} else {
+ chartTitle <- paste( chartTitle, "0" )
}
-command <- paste( "SELECT scale, avg( avg ), avg( std ) FROM flow_tp", flowObjModifier, sep="" )
-command <- paste( command, "_tests WHERE (", sep="" )
-command <- paste( command, commandNeighborModifier, sep="" )
-command <- paste( command, "neighbors = 0 ) AND branch = '", sep="" )
-command <- paste( command, args[ 7 ], sep="" )
-command <- paste( command, "' AND date IN ( SELECT max( date ) FROM flow_tp", sep="" )
-command <- paste( command, flowObjModifier, sep="" )
-command <- paste( command, "_tests WHERE branch='", sep="" )
-command <- paste( command, args[ 7 ], sep="" )
-command <- paste( command, "' ) GROUP BY scale ORDER BY scale", sep="" )
+errBarOutputFile <- paste( args[ 9 ],
+ args[ 6 ],
+ "_",
+ args[ 7 ],
+ "_",
+ fileNeighborsModifier,
+ "-neighbors",
+ fileFlowObjModifier,
+ "_graph.jpg",
+ sep="" )
+# ------------------
+# SQL Initialization
+# ------------------
-print( paste( "Sending SQL command:", command ) )
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 2 ],
+ port = strtoi( args[ 3 ] ),
+ user = args[ 4 ],
+ password = args[ 5 ] )
+
+# ---------------------------
+# 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[ 7 ],
+ "' AND date IN ( SELECT max( date ) FROM flow_tp",
+ sqlFlowObjModifier,
+ "_tests WHERE branch='",
+ args[ 7 ],
+ "' ) GROUP BY scale ORDER BY scale",
+ sep="" )
+
+print( "Sending SQL command:" )
+print( command )
fileData <- dbGetQuery( con, command )
-title <- paste( args[ 6 ], args[ 7 ], sep="_" )
-
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
-print( "STEP 2: Organize data." )
+print( "**********************************************************" )
+print( "STEP 2: Organize Data." )
+print( "**********************************************************" )
-# Create lists c() and organize data into their corresponding list.
-print( "Sorting data." )
-colnames( fileData ) <- c( "scale", "avg", "std" )
+# ------------
+# Data Sorting
+# ------------
+
+print( "Sorting data for Flow Throughput." )
+
+colnames( fileData ) <- c( "scale",
+ "avg",
+ "std" )
+
avgs <- c( fileData[ 'avg' ] )
-# Parse lists into data frames.
+
+# ----------------------------
+# 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$scale <- fileData$scale # Add node scaling to the data frame.
dataFrame$std <- fileData$std
-colnames( dataFrame ) <- c( "throughput", "type", "scale", "std" )
+colnames( dataFrame ) <- c( "throughput",
+ "type",
+ "scale",
+ "std" )
dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
@@ -114,19 +183,15 @@
# STEP 3: Generate graphs.
# **********************************************************
-print( "STEP 3: Generate graphs." )
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
-# 1. Graph fundamental data is generated first.
-# These are variables that apply to all of the graphs being generated, regardless of type.
-#
-# 2. Type specific graph data is generated.
-# Data specific for the error bar and stacked bar graphs are generated.
-#
-# 3. Generate and save the graphs.
-# Graphs are saved to the filename above, in the directory provided in command line args
+# ------------------
+# Generate Main Plot
+# ------------------
-print( "Generating fundamental graph data." )
-
+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
@@ -135,33 +200,47 @@
# - y: y-axis values (usually time in milliseconds)
# - fill: the category of the colored side-by-side bars (usually type)
-theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
+mainPlot <- ggplot( data = dataFrame, aes( x = scale,
+ y = throughput,
+ ymin = throughput,
+ ymax = throughput + std,
+ fill = type ) )
+# ------------------------------
+# Fundamental Variables Assigned
+# ------------------------------
-mainPlot <- ggplot( data = dataFrame, aes( x = scale, y = throughput, ymin = throughput, ymax = throughput + std, fill = type ) )
+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 )
+xScaleConfig <- scale_x_continuous( breaks = dataFrame$scale,
+ label = dataFrame$scale )
xLabel <- xlab( "Scale" )
yLabel <- ylab( "Throughput (,000 Flows/sec)" )
fillLabel <- labs( fill="Type" )
-chartTitle <- "Flow Throughput Test"
-if ( args[ 1 ] == 'y' ){
- chartTitle <- paste( chartTitle, " with Flow Objectives", sep="" )
-}
-chartTitle <- paste( chartTitle, "\nNeighbors =", sep="" )
-if ( args[ 8 ] == 'y' ){
- chartTitle <- paste( chartTitle, "Cluster Size - 1" )
-} else {
- chartTitle <- paste( chartTitle, "0" )
-}
+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' ) )
-
+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
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ title
+# ---------------------------
+# Generating Bar Graph Format
+# ---------------------------
# Create the stacked bar graph with error bars.
# geom_bar contains:
@@ -169,13 +248,37 @@
# - 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=rgb( 140,140,140, maxColorValue=255 ) )
-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" )
-title <- ggtitle( paste( chartTitle, "" ) )
-result <- fundamentalGraphData + barGraphFormat + errorBarFormat + title + values
+barGraphFormat <- geom_bar( stat = "identity",
+ width = width,
+ fill = "#FFAA3C" )
-# Save graph to file
+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 = 15, height = 10, dpi = 200 )
-print( paste( "Successfully wrote bar chart with error bars out to", errBarOutputFile ) )
+
+ggsave( errBarOutputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
+
+print( paste( "[SUCCESS] Successfully wrote bar chart with error bars out to", errBarOutputFile ) )