[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/README.md b/TestON/JenkinsFile/scripts/README.md
new file mode 100644
index 0000000..dab3f68
--- /dev/null
+++ b/TestON/JenkinsFile/scripts/README.md
@@ -0,0 +1,23 @@
+<h1>Wiki Graph Scripts</h1>
+
+The scripts that generate the graphs are written in the R programming language.
+
+The scripts are structured in the following format:
+1. Data Management
+ * Data is obtained from the databases through SQL. CLI arguments, filename, and titles are also handled here.
+ 1. Importing libraries
+ 2. Command line arguments
+ 3. Title of the graph
+ 4. Filename
+ 5. SQL Initialization and Data Gathering
+2. Organize Data
+ * Raw data is sorted into a data frame. The data frame is used in generating the graph.
+ 1. Combining data into a single list.
+ 2. Using the list to construct a data frame
+ 3. Adding data as columns to the data frame
+3. Generate Graphs
+ * The graphs are formatted and constructed here.
+ 1. Main plot generated
+ 2. Fundamental variables assigned
+ 3. Generate specific graph format
+ 4. Exporting graph to file
diff --git a/TestON/JenkinsFile/scripts/SCPFIntentInstallWithdrawRerouteLat.R b/TestON/JenkinsFile/scripts/SCPFIntentInstallWithdrawRerouteLat.R
index 76352e8..93e9e00 100644
--- a/TestON/JenkinsFile/scripts/SCPFIntentInstallWithdrawRerouteLat.R
+++ b/TestON/JenkinsFile/scripts/SCPFIntentInstallWithdrawRerouteLat.R
@@ -21,172 +21,308 @@
# 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
-# Check if sufficient args are provided.
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
if ( is.na( args[ 9 ] ) ){
- print( "Usage: Rscript SCPFIntentInstallWithdrawRerouteLat.R <isFlowObj> <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <batch-size> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript SCPFIntentInstallWithdrawRerouteLat.R",
+ "<isFlowObj>" ,
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<batch-size>",
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
q() # basically exit(), but in R
}
-flowObjFileModifier <- ""
-if ( args[ 1 ] == "y" ){
- flowObjFileModifier <- "fobj_"
-}
+# -----------------------------------
+# Create File Name and Title of Graph
+# -----------------------------------
-# paste() is used to concatenate strings
-errBarOutputFile <- paste( args[ 9 ], "SCPFIntentInstallWithdrawRerouteLat", sep="" )
-errBarOutputFile <- paste( errBarOutputFile, args[ 7 ], sep="_" )
+print( "Creating filename and title of graph." )
+
+chartTitle <- "Intent Install, Withdraw, & Reroute Latencies"
+flowObjFileModifier <- ""
+errBarOutputFile <- paste( args[ 9 ],
+ "SCPFIntentInstallWithdrawRerouteLat_",
+ args[ 7 ],
+ sep="" )
+
if ( args[ 1 ] == "y" ){
errBarOutputFile <- paste( errBarOutputFile, "_fobj", sep="" )
+ flowObjFileModifier <- "fobj_"
+ chartTitle <- paste( chartTitle, "w/ FlowObj" )
}
-errBarOutputFile <- paste( errBarOutputFile, "_", sep="" )
-errBarOutputFile <- paste( errBarOutputFile, args[ 8 ], sep="" )
-errBarOutputFile <- paste( errBarOutputFile, "-batchSize", sep="" )
-errBarOutputFile <- paste( errBarOutputFile, "_graph.jpg", sep="" )
-print( "Reading from databases." )
+errBarOutputFile <- paste( errBarOutputFile,
+ "_",
+ args[ 8 ],
+ "-batchSize_graph.jpg",
+ sep="" )
-con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 2 ], port=strtoi( args[ 3 ] ), user=args[ 4 ],password=args[ 5 ] )
+chartTitle <- paste( chartTitle,
+ "\nBatch Size =",
+ args[ 8 ],
+ sep=" " )
-command1 <- paste( "SELECT * FROM intent_latency_", flowObjFileModifier, sep="" )
-command1 <- paste( command1, "tests WHERE batch_size=", sep="" )
-command1 <- paste( command1, args[ 8 ], sep="" )
-command1 <- paste( command1, " AND branch = '", sep="" )
-command1 <- paste( command1, args[ 7 ], sep="" )
-command1 <- paste( command1, "' AND date IN ( SELECT MAX( date ) FROM intent_latency_", sep="" )
-command1 <- paste( command1, flowObjFileModifier, sep="" )
-command1 <- paste( command1, "tests WHERE branch='", sep="" )
-command1 <- paste( command1, args[ 7 ], sep="" )
-command1 <- paste( command1, "')", sep="" )
+# ------------------
+# SQL Initialization
+# ------------------
-print( paste( "Sending SQL command:", command1 ) )
+print( "Initializing SQL" )
-fileData1 <- dbGetQuery( con, command1 )
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 2 ],
+ port = strtoi( args[ 3 ] ),
+ user = args[ 4 ],
+ password = args[ 5 ] )
-command2 <- paste( "SELECT * FROM intent_reroute_latency_", flowObjFileModifier, sep="" )
-command2 <- paste( command2, "tests WHERE batch_size=", sep="" )
-command2 <- paste( command2, args[ 8 ], sep="" )
-command2 <- paste( command2, " AND branch = '", sep="" )
-command2 <- paste( command2, args[ 7 ], sep="" )
-command2 <- paste( command2, "' AND date IN ( SELECT MAX( date ) FROM intent_reroute_latency_", sep="" )
-command2 <- paste( command2, flowObjFileModifier, sep="" )
-command2 <- paste( command2, "tests WHERE branch='", sep="" )
-command2 <- paste( command2, args[ 7 ], sep="" )
-command2 <- paste( command2, "')", sep="" )
+# ---------------------------------------
+# Intent Install and Withdraw SQL Command
+# ---------------------------------------
+print( "Generating Intent Install and Withdraw SQL Command" )
-print( paste( "Sending SQL command:", command2 ) )
+installWithdrawSQLCommand <- paste( "SELECT * FROM intent_latency_",
+ flowObjFileModifier,
+ "tests WHERE batch_size=",
+ args[ 8 ],
+ " AND branch = '",
+ args[ 7 ],
+ "' AND date IN ( SELECT MAX( date ) FROM intent_latency_",
+ flowObjFileModifier,
+ "tests WHERE branch='",
+ args[ 7 ],
+ "')",
+ sep="" )
-fileData2 <- dbGetQuery( con, command2 )
+print( "Sending Intent Install and Withdraw SQL command:" )
+print( installWithdrawSQLCommand )
+installWithdrawData <- dbGetQuery( con, installWithdrawSQLCommand )
+
+# --------------------------
+# Intent Reroute SQL Command
+# --------------------------
+
+print( "Generating Intent Reroute SQL Command" )
+
+rerouteSQLCommand <- paste( "SELECT * FROM intent_reroute_latency_",
+ flowObjFileModifier,
+ "tests WHERE batch_size=",
+ args[ 8 ],
+ " AND branch = '",
+ args[ 7 ],
+ "' AND date IN ( SELECT MAX( date ) FROM intent_reroute_latency_",
+ flowObjFileModifier,
+ "tests WHERE branch='",
+ args[ 7 ],
+ "')",
+ sep="" )
+
+print( "Sending Intent Reroute SQL command:" )
+print( rerouteSQLCommand )
+rerouteData <- dbGetQuery( con, rerouteSQLCommand )
# **********************************************************
-# STEP 2: Organize data.
+# 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." )
-if ( ncol( fileData2 ) == 0 ){
- avgs <- c( fileData1[ 'install_avg' ], fileData1[ 'withdraw_avg' ] )
+# -------------------------------------------------------
+# Combining Install, Withdraw, and Reroute Latencies Data
+# -------------------------------------------------------
+
+print( "Combining Install, Withdraw, and Reroute Latencies Data" )
+
+if ( ncol( rerouteData ) == 0 ){ # Checks if rerouteData exists, so we can exclude it if necessary
+ avgs <- c( installWithdrawData[ 'install_avg' ],
+ installWithdrawData[ 'withdraw_avg' ] )
} else{
- colnames( fileData2 ) <- c( "date", "name", "date", "branch", "commit", "scale", "batch_size", "reroute_avg", "reroute_std" )
- avgs <- c( fileData1[ 'install_avg' ], fileData1[ 'withdraw_avg' ], fileData2[ 'reroute_avg' ] )
+ colnames( rerouteData ) <- c( "date",
+ "name",
+ "date",
+ "branch",
+ "commit",
+ "scale",
+ "batch_size",
+ "reroute_avg",
+ "reroute_std" )
+
+ avgs <- c( installWithdrawData[ 'install_avg' ],
+ installWithdrawData[ 'withdraw_avg' ],
+ rerouteData[ 'reroute_avg' ] )
}
-# Parse lists into data frames.
-dataFrame <- melt( avgs ) # This is where reshape2 comes in. Avgs list is converted to data frame
+# Combine lists into data frames.
+dataFrame <- melt( avgs )
-if ( ncol( fileData2 ) == 0 ){
- dataFrame$scale <- c( fileData1$scale, fileData1$scale ) # Add node scaling to the data frame.
- dataFrame$stds <- c( fileData1$install_std, fileData1$withdraw_std )
+# --------------------
+# Construct Data Frame
+# --------------------
+
+print( "Constructing data frame." )
+
+if ( ncol( rerouteData ) == 0 ){ # Checks if rerouteData exists (due to batch size) for the dataFrame this time
+ dataFrame$scale <- c( installWithdrawData$scale,
+ installWithdrawData$scale )
+
+ dataFrame$stds <- c( installWithdrawData$install_std,
+ installWithdrawData$withdraw_std )
} else{
- dataFrame$scale <- c( fileData1$scale, fileData1$scale, fileData2$scale ) # Add node scaling to the data frame.
- dataFrame$stds <- c( fileData1$install_std, fileData1$withdraw_std, fileData2$reroute_std )
+ dataFrame$scale <- c( installWithdrawData$scale,
+ installWithdrawData$scale,
+ rerouteData$scale )
+
+ dataFrame$stds <- c( installWithdrawData$install_std,
+ installWithdrawData$withdraw_std,
+ rerouteData$reroute_std )
}
-colnames( dataFrame ) <- c( "ms", "type", "scale", "stds" )
+
+colnames( dataFrame ) <- c( "ms",
+ "type",
+ "scale",
+ "stds" )
# Format data frame so that the data is in the same order as it appeared in the file.
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
-
-
+dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
print( "Data Frame Results:" )
print( dataFrame )
# **********************************************************
-# STEP 3: Generate graphs.
+# STEP 3: Generate graph.
# **********************************************************
-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
+# -------------------
+# Main Plot Generated
+# -------------------
+
+print( "Creating the main plot." )
+
+mainPlot <- ggplot( data = dataFrame, aes( x = scale,
+ y = ms,
+ ymin = ms,
+ ymax = ms + stds,
+ fill = type ) )
+
+# ------------------------------
+# Fundamental Variables Assigned
+# ------------------------------
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, ymin = ms, ymax = ms + stds, fill = type ) )
-
-# Formatting the plot
-width <- 1.3 # Width of the bars.
-xScaleConfig <- scale_x_continuous( breaks=c( 1, 3, 5, 7, 9) )
+theme_set( theme_grey( base_size = 22 ) )
+barWidth <- 1.3
+xScaleConfig <- scale_x_continuous( breaks = c( 1, 3, 5, 7, 9) )
xLabel <- xlab( "Scale" )
yLabel <- ylab( "Latency (ms)" )
fillLabel <- labs( fill="Type" )
-chartTitle <- "Intent Install, Withdraw, & Reroute Latencies"
-if ( args[ 1 ] == "y" ){
- chartTitle <- paste( chartTitle, "w/ FlowObj" )
-}
-chartTitle <- paste( chartTitle, "\nBatch Size =" )
-chartTitle <- paste( chartTitle, fileData1[ 1,'batch_size' ] )
+title <- ggtitle( chartTitle )
+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' ), legend.position="bottom", legend.text=element_text( size=22 ), legend.title = element_blank(), legend.key.size = unit( 1.5, 'lines' ) )
+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",
+ "#18BA48" ) )
# Store plot configurations as 1 variable
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ title +
+ colors
-# Create the 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.
+# ---------------------------
+# Generating Bar Graph Format
+# ---------------------------
+
print( "Generating bar graph with error bars." )
-colors <- scale_fill_manual( values=c( "#F77670", "#619DFA", "#18BA48" ) )
-barGraphFormat <- geom_bar( stat = "identity", width = width, position = "dodge" )
-errorBarFormat <- geom_errorbar( width = width, position = position_dodge( width ), color=rgb( 140, 140, 140, maxColorValue=255 ) )
-title <- ggtitle( chartTitle )
-values <- geom_text( aes( x=dataFrame$scale, y=dataFrame$ms + 0.035 * max( dataFrame$ms ), label = format( dataFrame$ms, digits=3, big.mark = ",", scientific = FALSE ) ), position=position_dodge( width=width ), size = 5.5, fontface = "bold" )
-wrapLegend <- guides( fill=guide_legend( nrow=1, byrow=TRUE ) )
-result <- fundamentalGraphData + barGraphFormat + colors + errorBarFormat + title + values + wrapLegend
+barGraphFormat <- geom_bar( stat = "identity",
+ width = barWidth,
+ position = "dodge" )
-# Save graph to file
+errorBarFormat <- geom_errorbar( width = barWidth,
+ position = position_dodge( barWidth ),
+ color = errorBarColor )
+
+values <- geom_text( aes( x = dataFrame$scale,
+ y = dataFrame$ms + 0.035 * max( dataFrame$ms ),
+ label = format( dataFrame$ms,
+ digits = 3,
+ big.mark = ",",
+ scientific = FALSE ) ),
+ position = position_dodge( width = barWidth ),
+ size = 5.5,
+ fontface = "bold" )
+
+wrapLegend <- guides( fill = guide_legend( nrow = 1, byrow = TRUE ) )
+
+result <- fundamentalGraphData +
+ barGraphFormat +
+ errorBarFormat +
+ values +
+ wrapLegend
+
+# -----------------------
+# 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 ) )
diff --git a/TestON/JenkinsFile/scripts/SCPFLineGraph.R b/TestON/JenkinsFile/scripts/SCPFLineGraph.R
index 15451a4..f080a4d 100644
--- a/TestON/JenkinsFile/scripts/SCPFLineGraph.R
+++ b/TestON/JenkinsFile/scripts/SCPFLineGraph.R
@@ -22,58 +22,102 @@
# This is the R script that generates the SCPF front page graphs.
+
# **********************************************************
# STEP 1: Data management.
# **********************************************************
+print( "**********************************************************" )
print( "STEP 1: Data management." )
+print( "**********************************************************" )
-# 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/
+# ----------------
+# Import Libraries
+# ----------------
+
print( "Importing libraries." )
library( ggplot2 )
library( reshape2 )
library( RPostgreSQL )
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
# 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>" )
+
+ print( paste( "Usage: Rscript testresultgraph.R",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<graph-title>", # part of the output filename as well
+ "<branch-name>", # part of the output filename
+ "<#-dates>", # part of the output filename
+ "<SQL-command>",
+ "<y-axis-title>", # y-axis may be different among other SCPF graphs (ie: batch size, latency, etc. )
+ "<directory-to-save-graph>",
+ sep = " " ) )
+
q() # basically exit(), but in R
}
-# Filenames for the output graph include the testname, branch, and the graph type.
+# -------------------------------
+# Create Title and Graph Filename
+# -------------------------------
-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 ] )
+print( "Creating title of graph" )
# Title of graph based on command line args.
title <- args[ 5 ]
+print( "Creating graph filename." )
+
+# Filenames for the output graph include the testname, branch, and the graph type.
+outputFile <- paste( args[ 10 ],
+ "SCPF_Front_Page_",
+ gsub( " ", "_", args[ 5 ] ),
+ "_",
+ args[ 6 ],
+ "_",
+ args[ 7 ],
+ "-dates_graph.jpg",
+ sep="" )
+
+# ------------------
+# SQL Initialization
+# ------------------
+
+print( "Initializing SQL" )
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 1 ],
+ port = strtoi( args[ 2 ] ),
+ user = args[ 3 ],
+ password = args[ 4 ] )
+
+print( "Sending SQL command:" )
+print( args[ 8 ] )
+fileData <- dbGetQuery( con, args[ 8 ] )
+
+
# **********************************************************
# 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 into new data frame." )
+print( "Combine data retrieved from databases into a list." )
if ( ncol( fileData ) > 1 ){
for ( i in 2:ncol( fileData ) ){
@@ -81,13 +125,17 @@
}
}
-# Parse lists into data frames.
-# This is where reshape2 comes in. Avgs list is converted to data frame.
-dataFrame <- melt( fileData )
+# --------------------
+# Construct Data Frame
+# --------------------
+print( "Constructing data frame from combined data." )
+
+dataFrame <- melt( fileData )
dataFrame$date <- fileData$date
-colnames( dataFrame ) <- c( "Legend", "Values" )
+colnames( dataFrame ) <- c( "Legend",
+ "Values" )
# Format data frame so that the data is in the same order as it appeared in the file.
dataFrame$Legend <- as.character( dataFrame$Legend )
@@ -105,7 +153,13 @@
# STEP 3: Generate graphs.
# **********************************************************
-print( "STEP 3: Generate graphs." )
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
+
+# -------------------
+# Main Plot Generated
+# -------------------
print( "Creating main plot." )
# Create the primary plot here.
@@ -115,35 +169,91 @@
# - x: x-axis values (usually iterative, but it will become date # later)
# - y: y-axis values (usually tests)
# - color: the category of the colored lines (usually legend of test)
-theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
-mainPlot <- ggplot( data = dataFrame, aes( x = iterative, y = Values, color = Legend ) )
+
+mainPlot <- ggplot( data = dataFrame, aes( x = iterative,
+ y = Values,
+ color = Legend ) )
+
+# -------------------
+# Main Plot Formatted
+# -------------------
print( "Formatting main plot." )
-# Store plot configurations as 1 variable
-fundamentalGraphData <- mainPlot + expand_limits( y = 0 )
+limitExpansion <- expand_limits( y = 0 )
-yScaleConfig <- scale_y_continuous( breaks = seq( 0, max( dataFrame$Values ) * 1.05, by = ceiling( max( dataFrame$Values ) / 10 ) ) )
+maxYDisplay <- max( dataFrame$Values ) * 1.05
+yBreaks <- ceiling( max( dataFrame$Values ) / 10 )
+yScaleConfig <- scale_y_continuous( breaks = seq( 0, maxYDisplay, by = yBreaks ) )
-xLabel <- xlab( "Time" )
+# ------------------------------
+# Fundamental Variables Assigned
+# ------------------------------
+
+print( "Generating fundamental graph data." )
+
+theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
+xLabel <- xlab( "Build" )
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 = 32, face='bold' ), legend.position="bottom", legend.text=element_text( size=22 ), legend.title = element_blank(), legend.key.size = unit( 1.5, 'lines' ), legend.direction = 'horizontal' )
-colors <- scale_color_manual( values=c( "#111111", "#008CFF", "#FF3700", "#00E043", "#EEB600", "#E500FF") )
-wrapLegend <- guides( color=guide_legend( nrow=2, byrow=TRUE ) )
-fundamentalGraphData <- fundamentalGraphData + yScaleConfig + xLabel + yLabel + fillLabel + legendLabels + centerTitle + theme + colors
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
+
+# Set other graph configurations here.
+theme <- theme( axis.text.x = element_blank(),
+ axis.ticks.x = element_blank(),
+ plot.title = element_text( size = 32, face='bold', hjust = 0.5 ),
+ legend.position = "bottom",
+ legend.text = element_text( size=22 ),
+ legend.title = element_blank(),
+ legend.key.size = unit( 1.5, 'lines' ),
+ legend.direction = 'horizontal' )
+
+# Colors used for the lines.
+# Note: graphs that have X lines will use the first X colors in this list.
+colors <- scale_color_manual( values=c( "#111111", # black
+ "#008CFF", # blue
+ "#FF3700", # red
+ "#00E043", # green
+ "#EEB600", # yellow
+ "#E500FF") ) # purple (not used)
+
+wrapLegend <- guides( color = guide_legend( nrow = 2, byrow = TRUE ) )
+title <- ggtitle( title )
+
+fundamentalGraphData <- mainPlot +
+ limitExpansion +
+ yScaleConfig +
+ xLabel +
+ yLabel +
+ theme +
+ colors +
+ wrapLegend +
+ title
+
+# ----------------------------
+# Generating Line Graph Format
+# ----------------------------
+
print( "Generating line graph." )
lineGraphFormat <- geom_line( size = 0.75 )
pointFormat <- geom_point( size = 1.75 )
-title <- ggtitle( title )
-result <- fundamentalGraphData + lineGraphFormat + pointFormat + title + wrapLegend
+result <- fundamentalGraphData +
+ lineGraphFormat +
+ pointFormat
-# Save graph to file
+# -----------------------
+# Exporting Graph to File
+# -----------------------
+
print( paste( "Saving result graph to", outputFile ) )
-ggsave( outputFile, width = 15, height = 10, dpi = 200 )
-print( paste( "Successfully wrote result graph out to", outputFile ) )
+
+ggsave( outputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
+
+print( paste( "[SUCCESS] Successfully wrote result graph out to", outputFile ) )
diff --git a/TestON/JenkinsFile/scripts/SCPFbatchFlowResp.R b/TestON/JenkinsFile/scripts/SCPFbatchFlowResp.R
index 8d0b6b4..d63bce3 100644
--- a/TestON/JenkinsFile/scripts/SCPFbatchFlowResp.R
+++ b/TestON/JenkinsFile/scripts/SCPFbatchFlowResp.R
@@ -21,164 +21,337 @@
# 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
-# Check if sufficient args are provided.
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
if ( is.na( args[ 7 ] ) ){
- print( "Usage: Rscript SCPFbatchFlowResp <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript SCPFbatchFlowResp",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
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, "_PostGraph.jpg", sep="" )
+# -----------------
+# Create File Names
+# -----------------
-print( "Reading from databases." )
+print( "Creating filenames and title of graph." )
-con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 1 ], port=strtoi( args[ 2 ] ), user=args[ 3 ],password=args[ 4 ] )
+postOutputFile <- paste( args[ 7 ],
+ args[ 5 ],
+ "_",
+ args[ 6 ],
+ "_PostGraph.jpg",
+ sep="" )
-command <- paste( "SELECT * FROM batch_flow_tests WHERE branch='", args[ 6 ], sep="" )
-command <- paste( command, "' ORDER BY date DESC LIMIT 3", sep="" )
+delOutputFile <- paste( args[ 7 ],
+ args[ 5 ],
+ "_",
+ args[ 6 ],
+ "_DelGraph.jpg",
+ sep="" )
-print( paste( "Sending SQL command:", command ) )
+postChartTitle <- paste( "Single Bench Flow Latency - Post", "Last 3 Builds", sep = "\n" )
+delChartTitle <- paste( "Single Bench Flow Latency - Del", "Last 3 Builds", sep = "\n" )
+
+# ------------------
+# SQL Initialization
+# ------------------
+
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 1 ],
+ port = strtoi( args[ 2 ] ),
+ user = args[ 3 ],
+ password = args[ 4 ] )
+
+# ---------------------------
+# Batch Flow Resp SQL Command
+# ---------------------------
+
+print( "Generating Batch Flow Resp SQL Command" )
+
+command <- paste( "SELECT * FROM batch_flow_tests WHERE branch='",
+ args[ 6 ],
+ "' ORDER BY date DESC LIMIT 3",
+ sep="" )
+
+print( "Sending SQL command:" )
+print( command )
fileData <- dbGetQuery( con, command )
-chartTitle <- paste( "Single Bench Flow Latency - Post", "Last 3 Builds", sep = "\n" )
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
-avgs <- c()
+print( "**********************************************************" )
+print( "STEP 2: Organize Data." )
+print( "**********************************************************" )
-print( "Sorting data." )
-avgs <- c( fileData[ 'posttoconfrm' ], fileData[ 'elapsepost' ] )
+# -----------------
+# Post Data Sorting
+# -----------------
-dataFrame <- melt( avgs )
-dataFrame$scale <- fileData$scale
-dataFrame$date <- fileData$date
-dataFrame$iterative <- dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
+print( "Sorting data for Post." )
-colnames( dataFrame ) <- c( "ms", "type", "scale", "date", "iterative" )
+postAvgs <- c( fileData[ 'posttoconfrm' ],
+ fileData[ 'elapsepost' ] )
+
+# -------------------------
+# Post Construct Data Frame
+# -------------------------
+
+postDataFrame <- melt( postAvgs )
+postDataFrame$scale <- fileData$scale
+postDataFrame$date <- fileData$date
+postDataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
+
+colnames( postDataFrame ) <- c( "ms",
+ "type",
+ "scale",
+ "date",
+ "iterative" )
# Format data frame so that the data is in the same order as it appeared in the file.
-dataFrame$type <- as.character( dataFrame$type )
-dataFrame$type <- factor( dataFrame$type, levels=unique( dataFrame$type ) )
+postDataFrame$type <- as.character( postDataFrame$type )
+postDataFrame$type <- factor( postDataFrame$type,
+ levels = unique( postDataFrame$type ) )
-dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
+postDataFrame <- na.omit( postDataFrame ) # Omit any data that doesn't exist
-print( "Data Frame Results:" )
-print( dataFrame )
+print( "Post Data Frame Results:" )
+print( postDataFrame )
+
+# ----------------
+# Del Data Sorting
+# ----------------
+
+print( "Sorting data for Del." )
+avgs <- c( fileData[ 'deltoconfrm' ],
+ fileData[ 'elapsedel' ] )
+
+# ------------------------
+# Del Construct Data Frame
+# ------------------------
+
+delDataFrame <- melt( avgs )
+delDataFrame$scale <- fileData$scale
+delDataFrame$date <- fileData$date
+delDataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
+
+colnames( delDataFrame ) <- c( "ms",
+ "type",
+ "scale",
+ "date",
+ "iterative" )
+
+# Format data frame so that the data is in the same order as it appeared in the file.
+delDataFrame$type <- as.character( delDataFrame$type )
+delDataFrame$type <- factor( delDataFrame$type,
+ levels = unique( delDataFrame$type ) )
+
+delDataFrame <- na.omit( delDataFrame ) # Omit any data that doesn't exist
+
+print( "Del Data Frame Results:" )
+print( delDataFrame )
# **********************************************************
# STEP 3: Generate graphs.
# **********************************************************
-print( "Generating fundamental graph data." )
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
+
+# ------------------------------------------
+# Initializing variables used in both graphs
+# ------------------------------------------
+
+print( "Initializing variables used in both graphs." )
theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
-
-mainPlot <- ggplot( data = dataFrame, aes( x = iterative, y = ms, fill = type ) )
-xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative, label = dataFrame$date )
xLabel <- xlab( "Build Date" )
yLabel <- ylab( "Latency (ms)" )
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
+barWidth <- 0.3
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
+
+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' ) )
+
+barGraphFormat <- geom_bar( stat = "identity",
+ width = barWidth )
+
+# -----------------------
+# Post Generate Main Plot
+# -----------------------
+
+print( "Creating main plot for Post graph." )
+
+mainPlot <- ggplot( data = postDataFrame, aes( x = iterative,
+ y = ms,
+ fill = type ) )
+
+# -----------------------------------
+# Post Fundamental Variables Assigned
+# -----------------------------------
+
+print( "Generating fundamental graph data for Post graph." )
+
+xScaleConfig <- scale_x_continuous( breaks = postDataFrame$iterative,
+ label = postDataFrame$date )
+title <- ggtitle( postChartTitle )
-print( "Generating bar graph." )
-width <- 0.3
-barGraphFormat <- geom_bar( stat="identity", width = width )
-sum <- fileData[ 'posttoconfrm' ] + fileData[ 'elapsepost' ]
-values <- geom_text( aes( x=dataFrame$iterative, y=sum + 0.03 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold" )
-title <- ggtitle( chartTitle )
-result <- fundamentalGraphData + barGraphFormat + colors + title + values
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ wrapLegend +
+ colors +
+ title
+# --------------------------------
+# Post Generating Bar Graph Format
+# --------------------------------
-print( paste( "Saving bar chart to", errBarOutputFile ) )
-ggsave( errBarOutputFile, width = 15, height = 10, dpi = 200 )
+print( "Generating bar graph for Post graph." )
-print( paste( "Successfully wrote stacked bar chart out to", errBarOutputFile ) )
+sum <- fileData[ 'posttoconfrm' ] +
+ fileData[ 'elapsepost' ]
+values <- geom_text( aes( x = postDataFrame$iterative,
+ y = sum + 0.03 * max( sum ),
+ label = format( sum,
+ digits = 3,
+ big.mark = ",",
+ scientific = FALSE ) ),
+ size = 7.0,
+ fontface = "bold" )
-# **********************************************************
-# STEP 2: Organize data.
-# **********************************************************
+result <- fundamentalGraphData +
+ barGraphFormat +
+ values
-avgs <- c()
+# ----------------------------
+# Post Exporting Graph to File
+# ----------------------------
-print( "Sorting data." )
-avgs <- c( fileData[ 'deltoconfrm' ], fileData[ 'elapsedel' ] )
+print( paste( "Saving Post bar chart to", postOutputFile ) )
-dataFrame <- melt( avgs )
-dataFrame$scale <- fileData$scale
-dataFrame$date <- fileData$date
-dataFrame$iterative <- dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
+ggsave( postOutputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
-colnames( dataFrame ) <- c( "ms", "type", "scale", "date", "iterative" )
+print( paste( "[SUCCESS] Successfully wrote stacked bar chart out to", postOutputFile ) )
-# Format data frame so that the data is in the same order as it appeared in the file.
-dataFrame$type <- as.character( dataFrame$type )
-dataFrame$type <- factor( dataFrame$type, levels=unique( dataFrame$type ) )
+# ----------------------
+# Del Generate Main Plot
+# ----------------------
-dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
+print( "Creating main plot for Del graph." )
-print( "Data Frame Results:" )
-print( dataFrame )
+mainPlot <- ggplot( data = delDataFrame, aes( x = iterative,
+ y = ms,
+ fill = type ) )
-# **********************************************************
-# STEP 3: Generate graphs.
-# **********************************************************
+# ----------------------------------
+# Del Fundamental Variables Assigned
+# ----------------------------------
-print( "Generating fundamental graph data." )
+print( "Generating fundamental graph data for Del graph." )
-theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
+xScaleConfig <- scale_x_continuous( breaks = delDataFrame$iterative,
+ label = delDataFrame$date )
+title <- ggtitle( delChartTitle )
-mainPlot <- ggplot( data = dataFrame, aes( x = iterative, y = ms, fill = type ) )
-xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative, label = dataFrame$date )
-xLabel <- xlab( "Build Date" )
-yLabel <- ylab( "Latency (ms)" )
-fillLabel <- labs( fill="Type" )
-theme <- theme( plot.title=element_text( hjust = 0.5, size = 32, face='bold' ), legend.position="bottom", legend.text=element_text( size=22 ), legend.title = element_blank(), legend.key.size = unit( 1.5, 'lines' ) )
-colors <- scale_fill_manual( values=c( "#F77670", "#619DFA" ) )
-wrapLegend <- guides( fill=guide_legend( nrow=1, byrow=TRUE ) )
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme + wrapLegend
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ wrapLegend +
+ colors +
+ title
+# -------------------------------
+# Del Generating Bar Graph Format
+# -------------------------------
-print( "Generating bar graph." )
-width <- 0.3
-barGraphFormat <- geom_bar( stat="identity", width = width )
-sum <- fileData[ 'deltoconfrm' ] + fileData[ 'elapsedel' ]
-values <- geom_text( aes( x=dataFrame$iterative, y=sum + 0.03 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold" )
-chartTitle <- paste( "Single Bench Flow Latency - Del", "Last 3 Builds", sep = "\n" )
-title <- ggtitle( chartTitle )
-result <- fundamentalGraphData + barGraphFormat + colors + title + values
+print( "Generating bar graph for Del graph." )
-errBarOutputFile <- paste( args[ 7 ], args[ 5 ], sep="" )
-errBarOutputFile <- paste( errBarOutputFile, args[ 6 ], sep="_" )
-errBarOutputFile <- paste( errBarOutputFile, "_DelGraph.jpg", sep="" )
+sum <- fileData[ 'deltoconfrm' ] +
+ fileData[ 'elapsedel' ]
-print( paste( "Saving bar chart to", errBarOutputFile ) )
-ggsave( errBarOutputFile, width = 15, height = 10, dpi = 200 )
+values <- geom_text( aes( x = delDataFrame$iterative,
+ y = sum + 0.03 * max( sum ),
+ label = format( sum,
+ digits = 3,
+ big.mark = ",",
+ scientific = FALSE ) ),
+ size = 7.0,
+ fontface = "bold" )
-print( paste( "Successfully wrote stacked bar chart out to", errBarOutputFile ) )
\ No newline at end of file
+result <- fundamentalGraphData +
+ barGraphFormat +
+ title +
+ values
+
+# ---------------------------
+# Del Exporting Graph to File
+# ---------------------------
+
+print( paste( "Saving Del bar chart to", delOutputFile ) )
+
+ggsave( delOutputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
+
+print( paste( "[SUCCESS] Successfully wrote stacked bar chart out to", delOutputFile ) )
\ No newline at end of file
diff --git a/TestON/JenkinsFile/scripts/SCPFcbench.R b/TestON/JenkinsFile/scripts/SCPFcbench.R
index 55e3978..fa59c55 100644
--- a/TestON/JenkinsFile/scripts/SCPFcbench.R
+++ b/TestON/JenkinsFile/scripts/SCPFcbench.R
@@ -21,66 +21,123 @@
# 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[ 7 ] ) ){
- print( "Usage: Rscript SCPFcbench <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript SCPFcbench",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
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="" )
+# -----------------
+# Create File Names
+# -----------------
-print( "Reading from databases." )
+print( "Creating filenames and title of graph." )
-con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 1 ], port=strtoi( args[ 2 ] ), user=args[ 3 ],password=args[ 4 ] )
-
-command <- paste( "SELECT * FROM cbench_bm_tests WHERE branch='", args[ 6 ], sep="" )
-command <- paste( command, "' ORDER BY date DESC LIMIT 3", sep="" )
-
-print( paste( "Sending SQL command:", command ) )
-
-fileData <- dbGetQuery( con, command )
+errBarOutputFile <- paste( args[ 7 ],
+ args[ 5 ],
+ "_",
+ args[ 6 ],
+ "_errGraph.jpg",
+ sep="" )
chartTitle <- paste( "Single-Node CBench Throughput", "Last 3 Builds", sep = "\n" )
+# ------------------
+# SQL Initialization
+# ------------------
+
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 1 ],
+ port = strtoi( args[ 2 ] ),
+ user = args[ 3 ],
+ password = args[ 4 ] )
+
+# ------------------
+# Cbench SQL Command
+# ------------------
+
+print( "Generating Scale Topology SQL Command" )
+
+command <- paste( "SELECT * FROM cbench_bm_tests WHERE branch='",
+ args[ 6 ],
+ "' ORDER BY date DESC LIMIT 3",
+ sep="" )
+
+print( "Sending SQL command:" )
+print( command )
+
+fileData <- dbGetQuery( con, command )
+
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
-fileDataNames <- names( fileData )
+print( "**********************************************************" )
+print( "STEP 2: Organize Data." )
+print( "**********************************************************" )
-avgs <- c()
-stds <- c()
+# ------------
+# Data Sorting
+# ------------
print( "Sorting data." )
+
avgs <- c( fileData[ 'avg' ] )
+# --------------------
+# Construct Data Frame
+# --------------------
+
+print( "Constructing Data Frame" )
+
dataFrame <- melt( avgs )
dataFrame$std <- c( fileData$std )
dataFrame$date <- c( fileData$date )
dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
-colnames( dataFrame ) <- c( "ms", "type", "std", "date", "iterative" )
+colnames( dataFrame ) <- c( "ms",
+ "type",
+ "std",
+ "date",
+ "iterative" )
dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
@@ -91,29 +148,91 @@
# STEP 3: Generate graphs.
# **********************************************************
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
+
+# ------------------
+# Generate Main Plot
+# ------------------
+
+print( "Creating main plot." )
+
+mainPlot <- ggplot( data = dataFrame, aes( x = iterative,
+ y = ms,
+ ymin = ms,
+ ymax = ms + std ) )
+
+# ------------------------------
+# Fundamental Variables Assigned
+# ------------------------------
+
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 = iterative, y = ms, ymin = ms, ymax = ms + std ) )
-xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative, label = dataFrame$date )
+barWidth <- 0.3
+xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative,
+ label = dataFrame$date )
xLabel <- xlab( "Build Date" )
yLabel <- ylab( "Responses / sec" )
-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=18, face="bold" ), legend.title = element_blank() )
+fillLabel <- labs( fill = "Type" )
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
+errorBarColor <- rgb( 140,140,140, maxColorValue=255 )
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
+theme <- theme( plot.title = element_text( hjust = 0.5, size = 32, face = 'bold' ),
+ legend.position = "bottom",
+ legend.text = element_text( size = 18, face = "bold" ),
+ legend.title = element_blank() )
+title <- ggtitle( chartTitle )
+
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ title
+
+# ---------------------------
+# Generating Bar Graph Format
+# ---------------------------
print( "Generating bar graph with error bars." )
-width <- 0.3
-barGraphFormat <- geom_bar( stat="identity", position = position_dodge(), width = width, fill="#00AA13" )
-errorBarFormat <- geom_errorbar( width = width, color=rgb( 140,140,140, maxColorValue=255 ) )
-values <- geom_text( aes( x=dataFrame$iterative, y=fileData[ 'avg' ] + 0.025 * max( fileData[ 'avg' ] ), label = format( fileData[ 'avg' ], digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold" )
-title <- ggtitle( chartTitle )
-result <- fundamentalGraphData + barGraphFormat + errorBarFormat + title + values
+barGraphFormat <- geom_bar( stat = "identity",
+ position = position_dodge(),
+ width = barWidth,
+ fill = "#00AA13" )
+
+errorBarFormat <- geom_errorbar( width = barWidth,
+ color = errorBarColor )
+
+values <- geom_text( aes( x=dataFrame$iterative,
+ y=fileData[ 'avg' ] + 0.025 * max( fileData[ 'avg' ] ),
+ label = format( fileData[ 'avg' ],
+ 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 ) )
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 ) )
diff --git a/TestON/JenkinsFile/scripts/SCPFhostLat.R b/TestON/JenkinsFile/scripts/SCPFhostLat.R
index f60fc59..0ae64cf 100644
--- a/TestON/JenkinsFile/scripts/SCPFhostLat.R
+++ b/TestON/JenkinsFile/scripts/SCPFhostLat.R
@@ -21,67 +21,123 @@
# 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
+# -------------------
+# Check CLI Arguments
+# -------------------
-# Check if sufficient args are provided.
+print( "Verifying CLI args." )
+
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>" )
+
+ print( paste( "Usage: Rscript SCPFhostLat",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
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="" )
+# -----------------
+# Create File Names
+# -----------------
-print( "Reading from databases." )
+print( "Creating filenames and title of graph." )
-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 )
+errBarOutputFile <- paste( args[ 7 ],
+ args[ 5 ],
+ "_",
+ args[ 6 ],
+ "_errGraph.jpg",
+ sep="" )
chartTitle <- "Host Latency"
+# ------------------
+# SQL Initialization
+# ------------------
+
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 1 ],
+ port = strtoi( args[ 2 ] ),
+ user = args[ 3 ],
+ password = args[ 4 ] )
+
+# ------------------------
+# Host Latency SQL Command
+# ------------------------
+
+print( "Generating Host Latency SQL Command" )
+
+command <- paste( "SELECT * FROM host_latency_tests WHERE branch = '",
+ args[ 6 ],
+ "' AND date IN ( SELECT MAX( date ) FROM host_latency_tests WHERE branch = '",
+ args[ 6 ],
+ "' ) ",
+ sep = "" )
+
+print( "Sending SQL command:" )
+print( command )
+
+fileData <- dbGetQuery( con, command )
+
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
-print( "STEP 2: Organize data." )
+print( "**********************************************************" )
+print( "STEP 2: Organize Data." )
+print( "**********************************************************" )
-avgs <- c()
+# ------------
+# Data Sorting
+# ------------
print( "Sorting data." )
avgs <- c( fileData[ 'avg' ] )
+# --------------------
+# Construct Data Frame
+# --------------------
+
+print( "Constructing Data Frame" )
+
dataFrame <- melt( avgs )
dataFrame$scale <- fileData$scale
dataFrame$std <- fileData$std
-colnames( dataFrame ) <- c( "ms", "type", "scale", "std" )
+colnames( dataFrame ) <- c( "ms",
+ "type",
+ "scale",
+ "std" )
dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
@@ -92,29 +148,86 @@
# STEP 3: Generate graphs.
# **********************************************************
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
+
+# ------------------
+# Generate Main Plot
+# ------------------
+
+print( "Creating main plot." )
+
+mainPlot <- ggplot( data = dataFrame, aes( x = scale,
+ y = ms,
+ ymin = ms,
+ ymax = ms + std ) )
+
+# ------------------------------
+# Fundamental Variables Assigned
+# ------------------------------
+
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, ymin = ms, ymax = ms + std ) )
-xScaleConfig <- scale_x_continuous( breaks=c( 1, 3, 5, 7, 9) )
+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 = 32, face='bold' ) )
+theme <- theme( plot.title = element_text( hjust = 0.5, size = 32, face ='bold' ) )
+title <- ggtitle( chartTitle )
+errorBarColor <- rgb( 140, 140, 140, maxColorValue = 255 )
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ title
+# ---------------------------
+# Generating Bar Graph Format
+# ---------------------------
print( "Generating bar graph with error bars." )
-width <- 0.9
-barGraphFormat <- geom_bar( stat="identity", position=position_dodge( ), width = width, fill="#A700EF" )
-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 + 0.06 * max( dataFrame$ms ), label = format( dataFrame$ms, digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold" )
-title <- ggtitle( paste( chartTitle, "" ) )
-result <- fundamentalGraphData + barGraphFormat + errorBarFormat + title + values
+barWidth <- 0.9
+barGraphFormat <- geom_bar( stat = "identity",
+ position = position_dodge(),
+ width = barWidth,
+ fill = "#A700EF" )
+
+errorBarFormat <- geom_errorbar( position = position_dodge(),
+ width = barWidth,
+ color = errorBarColor )
+
+values <- geom_text( aes( x=dataFrame$scale,
+ y=dataFrame$ms + 0.06 * max( dataFrame$ms ),
+ label = format( dataFrame$ms,
+ 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 out to", errBarOutputFile ) )
\ No newline at end of file
+ggsave( errBarOutputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
+
+print( paste( "[SUCCESS] Successfully wrote bar chart out to", errBarOutputFile ) )
\ No newline at end of file
diff --git a/TestON/JenkinsFile/scripts/SCPFintentEventTp.R b/TestON/JenkinsFile/scripts/SCPFintentEventTp.R
index 471fc7a..53fe2d4 100644
--- a/TestON/JenkinsFile/scripts/SCPFintentEventTp.R
+++ b/TestON/JenkinsFile/scripts/SCPFintentEventTp.R
@@ -21,88 +21,151 @@
# 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. Args usually include the database filename and the output
-# directory for the graphs to save to.
+# 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 SCPFIntentEventTp.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 SCPFIntentEventTp.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 <- "Intent Event Throughput"
+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, "\nevents/second with Neighbors =", sep="" )
+
if ( args[ 8 ] == 'y' ){
+ fileNeighborsModifier <- "all"
commandNeighborModifier <- "scale=1 OR NOT "
+ chartTitle <- paste( chartTitle, "all" )
+} else {
+ chartTitle <- paste( chartTitle, "0" )
}
-command <- paste( "SELECT scale, SUM( avg ) as avg FROM intent_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 intent_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="" )
-print( paste( "Sending SQL command:", command ) )
+# ------------------
+# SQL Initialization
+# ------------------
+
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 2 ],
+ port = strtoi( args[ 3 ] ),
+ user = args[ 4 ],
+ password = args[ 5 ] )
+
+# -----------------------------------
+# Intent Event Throughput SQL Command
+# -----------------------------------
+
+print( "Generating Intent Event Throughput SQL command." )
+
+command <- paste( "SELECT scale, SUM( avg ) as avg FROM intent_tp",
+ sqlFlowObjModifier,
+ "_tests WHERE (",
+ commandNeighborModifier,
+ "neighbors = 0 ) AND branch = '",
+ args[ 7 ],
+ "' AND date IN ( SELECT max( date ) FROM intent_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.
+# ------------
+# Data Sorting
+# ------------
+
print( "Sorting data." )
avgs <- c( fileData[ 'avg' ] )
-# Parse lists into data frames.
+# --------------------
+# Construct Data Frame
+# --------------------
+
+print( "Constructing 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.
-colnames( dataFrame ) <- c( "throughput", "type", "scale" )
+colnames( dataFrame ) <- c( "throughput",
+ "type",
+ "scale" )
dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
@@ -114,18 +177,15 @@
# 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.
-#
-# 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
@@ -133,41 +193,74 @@
# - 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)
-theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
-mainPlot <- ggplot( data = dataFrame, aes( x = scale, y = throughput, fill = type ) )
+mainPlot <- ggplot( data = dataFrame, aes( x = scale,
+ y = throughput,
+ 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 (events/second)" )
fillLabel <- labs( fill="Type" )
-chartTitle <- "Intent Event Throughput"
-if ( args[ 1 ] == 'y' ){
- chartTitle <- paste( chartTitle, " With Flow Objectives", sep="" )
-}
-chartTitle <- paste( chartTitle, "\nevents/second with Neighbors =", sep="" )
-if ( args[ 8 ] == 'y' ){
- chartTitle <- paste( chartTitle, "all" )
-} else {
- chartTitle <- paste( chartTitle, "0" )
-}
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
-theme <- theme( plot.title=element_text( hjust = 0.5, size = 32, face='bold' ), legend.position="bottom", legend.text=element_text( size=18, face="bold" ), legend.title = element_blank() )
-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, fontface = "bold" )
+theme <- theme( plot.title = element_text( hjust = 0.5, size = 32, face = 'bold' ),
+ legend.position = "bottom",
+ legend.text = element_text( size = 18, face = "bold" ),
+ legend.title = element_blank() )
+
+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,
+ fontface = "bold" )
# Store plot configurations as 1 variable
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme + values
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ values
+# ---------------------------
+# Generating Bar Graph Format
+# ---------------------------
print( "Generating bar graph." )
-barGraphFormat <- geom_bar( stat = "identity", width = width, fill="#169EFF" )
-title <- ggtitle( paste( chartTitle, "" ) )
-result <- fundamentalGraphData + barGraphFormat + title
+barGraphFormat <- geom_bar( stat = "identity",
+ width = width,
+ fill = "#169EFF" )
-# Save graph to file
+title <- ggtitle( chartTitle )
+
+result <- fundamentalGraphData +
+ barGraphFormat +
+ title
+
+# -----------------------
+# Exporting Graph to File
+# -----------------------
+
print( paste( "Saving bar chart to", errBarOutputFile ) )
-ggsave( errBarOutputFile, width = 15, height = 10, dpi = 200 )
-print( paste( "Successfully wrote bar chart out to", errBarOutputFile ) )
+ggsave( errBarOutputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
+
+print( paste( "[SUCCESS] Successfully wrote bar chart out to", errBarOutputFile ) )
diff --git a/TestON/JenkinsFile/scripts/SCPFmastershipFailoverLat.R b/TestON/JenkinsFile/scripts/SCPFmastershipFailoverLat.R
index 90bcb8d..82638dc 100644
--- a/TestON/JenkinsFile/scripts/SCPFmastershipFailoverLat.R
+++ b/TestON/JenkinsFile/scripts/SCPFmastershipFailoverLat.R
@@ -21,136 +21,300 @@
# 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
-# Check if sufficient args are provided.
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
if ( is.na( args[ 7 ] ) ){
- print( "Usage: Rscript SCPFmastershipFailoverLat <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript SCPFmastershipFailoverLat",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
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="" )
+# -----------------
+# Create File Names
+# -----------------
-stackedBarOutputFile <- paste( args[ 7 ], args[ 5 ], sep="" )
-stackedBarOutputFile <- paste( stackedBarOutputFile, args[ 6 ], sep="_" )
-stackedBarOutputFile <- paste( stackedBarOutputFile, "_stackedGraph.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 mastership_failover_tests WHERE branch = '", args[ 6 ], sep = "" )
-command <- paste( command, "' AND date IN ( SELECT MAX( date ) FROM mastership_failover_tests WHERE branch = '", sep = "" )
-command <- paste( command, args[ 6 ], sep = "" )
-command <- paste( command, "' ) ", sep="" )
-
-print( paste( "Sending SQL command:", command ) )
-
-fileData <- dbGetQuery( con, command )
+print( "Creating filenames and title of graph." )
chartTitle <- "Mastership Failover Latency"
+errBarOutputFile <- paste( args[ 7 ],
+ args[ 5 ],
+ "_",
+ args[ 6 ],
+ "_errGraph.jpg",
+ sep="" )
+
+stackedBarOutputFile <- paste( args[ 7 ],
+ args[ 5 ],
+ "_",
+ args[ 6 ],
+ "_stackedGraph.jpg",
+ sep="" )
+
+# ------------------
+# SQL Initialization
+# ------------------
+
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 1 ],
+ port = strtoi( args[ 2 ] ),
+ user = args[ 3 ],
+ password = args[ 4 ] )
+
+# ---------------------------------------
+# Mastership Failover Latency SQL Command
+# ---------------------------------------
+
+print( "Generating Mastership Failover Latency SQL command" )
+
+command <- paste( "SELECT * FROM mastership_failover_tests WHERE branch = '",
+ args[ 6 ],
+ "' AND date IN ( SELECT MAX( date ) FROM mastership_failover_tests WHERE branch = '",
+ args[ 6 ],
+ "' ) ",
+ sep = "" )
+
+print( "Sending SQL command:" )
+print( command )
+
+fileData <- dbGetQuery( con, command )
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
-fileDataNames <- names( fileData )
+print( "**********************************************************" )
+print( "STEP 2: Organize Data." )
+print( "**********************************************************" )
-avgs <- c()
-stds <- c()
+# ------------
+# Data Sorting
+# ------------
+print( "Combining averages into a list." )
-print( "Sorting data." )
-for ( name in fileDataNames ){
- nameLen <- nchar( name )
- if ( nameLen > 2 ){
- if ( substring( name, nameLen - 2, nameLen ) == "avg" ){
- avgs <- c( avgs, fileData[ name ] )
- }
- if ( substring( name, nameLen - 2, nameLen ) == "std" ){
- stds <- c( stds, fileData[ name ] )
- }
- }
-}
+avgs <- c( fileData[ 'kill_deact_avg' ],
+ fileData[ 'deact_role_avg' ] )
-avgData <- melt( avgs )
-avgData$scale <- fileData$scale
-colnames( avgData ) <- c( "ms", "type", "scale" )
+# --------------------
+# Construct Data Frame
+# --------------------
-stdData <- melt( stds )
-colnames( stdData ) <- c( "ms", "type" )
+print( "Constructing Data Frame from list." )
-dataFrame <- na.omit( avgData ) # Omit any data that doesn't exist
+dataFrame <- melt( avgs )
+dataFrame$scale <- fileData$scale
+dataFrame$stds <- c( fileData$kill_deact_std,
+ fileData$deact_role_std )
+
+colnames( dataFrame ) <- c( "ms",
+ "type",
+ "scale",
+ "stds" )
+
+dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
+
+sum <- fileData[ 'deact_role_avg' ] +
+ fileData[ 'kill_deact_avg' ]
print( "Data Frame Results:" )
-print( avgData )
+print( dataFrame )
# **********************************************************
# STEP 3: Generate graphs.
# **********************************************************
-print( "Generating fundamental graph data." )
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
+
+# ------------------------------------
+# Initialize Variables for Both Graphs
+# ------------------------------------
+
+print( "Initializing variables used in both graphs." )
theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
-
-mainPlot <- ggplot( data = avgData, aes( x = scale, y = ms, ymin = ms, ymax = ms + stdData$ms,fill = type ) )
-xScaleConfig <- scale_x_continuous( breaks=c( 1, 3, 5, 7, 9) )
+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 = 32, face='bold' ), legend.position="bottom", legend.text=element_text( size=22 ), legend.title = element_blank(), legend.key.size = unit( 1.5, 'lines' ) )
+fillLabel <- labs( fill = "Type" )
+barWidth <- 0.9
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
+
+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' ) )
+
+barColors <- scale_fill_manual( values=c( "#F77670",
+ "#619DFA" ) )
+
wrapLegend <- guides( fill=guide_legend( nrow=1, byrow=TRUE ) )
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme + wrapLegend
+# ----------------------------------
+# Error Bar Graph Generate Main Plot
+# ----------------------------------
+print( "Creating main plot." )
+
+mainPlot <- ggplot( data = dataFrame, aes( x = scale,
+ y = ms,
+ ymin = ms,
+ ymax = ms + stds,
+ fill = type ) )
+
+# ----------------------------------------------
+# Error Bar Graph Fundamental Variables Assigned
+# ----------------------------------------------
+
+print( "Generating fundamental graph data for the error bar graph." )
+
+errorBarColor <- rgb( 140, 140, 140, maxColorValue=255 )
+
+title <- ggtitle( chartTitle )
+
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ title +
+ wrapLegend
+
+# -------------------------------------------
+# Error Bar Graph Generating Bar Graph Format
+# -------------------------------------------
print( "Generating bar graph with error bars." )
-width <- 0.9
-barGraphFormat <- geom_bar( stat="identity", position=position_dodge(), width = width )
-colors <- scale_fill_manual( values=c( "#F77670", "#619DFA" ) )
-errorBarFormat <- geom_errorbar( width = width, position=position_dodge(), color=rgb( 140, 140, 140, maxColorValue=255 ) )
-values <- geom_text( aes( x=avgData$scale, y=avgData$ms + 0.02 * max( avgData$ms ), label = format( avgData$ms, digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold", position=position_dodge( 0.9 ) )
-title <- ggtitle( paste( chartTitle, "" ) )
-result <- fundamentalGraphData + barGraphFormat + colors + errorBarFormat + title + values
+barGraphFormat <- geom_bar( stat = "identity",
+ position = position_dodge(),
+ width = barWidth )
+
+errorBarFormat <- geom_errorbar( width = barWidth,
+ position = position_dodge(),
+ color = errorBarColor )
+
+values <- geom_text( aes( x = dataFrame$scale,
+ y = dataFrame$ms + 0.02 * max( dataFrame$ms ),
+ label = format( dataFrame$ms,
+ digits = 3,
+ big.mark = ",",
+ scientific = FALSE ) ),
+ size = 7.0,
+ fontface = "bold",
+ position = position_dodge( 0.9 ) )
+
+result <- fundamentalGraphData +
+ barGraphFormat +
+ barColors +
+ errorBarFormat +
+ values
+
+# ---------------------------------------
+# Error Bar Graph Exporting Graph to File
+# ---------------------------------------
print( paste( "Saving bar chart with error bars to", errBarOutputFile ) )
-ggsave( errBarOutputFile, width = 15, height = 10, dpi = 200 )
+ggsave( errBarOutputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
-print( paste( "Successfully wrote bar chart with error bars out to", errBarOutputFile ) )
+print( paste( "[SUCCESS] Successfully wrote bar chart with error bars out to", errBarOutputFile ) )
+# ------------------------------------------------
+# Stacked Bar Graph Fundamental Variables Assigned
+# ------------------------------------------------
+
+print( "Generating fundamental graph data for the stacked bar graph." )
+
+title <- ggtitle( chartTitle )
+
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ title +
+ wrapLegend
+
+# ---------------------------------------------
+# Stacked Bar Graph Generating Bar Graph Format
+# ---------------------------------------------
print( "Generating stacked bar chart." )
-stackedBarFormat <- geom_bar( stat="identity", width=width )
-title <- ggtitle( paste( chartTitle, "" ) )
-sum <- fileData[ 'deact_role_avg' ] + fileData[ 'kill_deact_avg' ]
-values <- geom_text( aes( x=avgData$scale, y=sum + 0.02 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold" )
-result <- fundamentalGraphData + stackedBarFormat + colors + title + values
+stackedBarFormat <- geom_bar( stat = "identity",
+ width = barWidth )
+values <- geom_text( aes( x = dataFrame$scale,
+ y = sum + 0.02 * max( sum ),
+ label = format( sum,
+ digits = 3,
+ big.mark = ",",
+ scientific = FALSE ) ),
+ size = 7.0,
+ fontface = "bold" )
+
+result <- fundamentalGraphData +
+ stackedBarFormat +
+ barColors +
+ title +
+ values
+
+# -----------------------------------------
+# Stacked Bar Graph Exporting Graph to File
+# -----------------------------------------
print( paste( "Saving stacked bar chart to", stackedBarOutputFile ) )
-ggsave( stackedBarOutputFile, width = 15, height = 10, dpi = 200 )
+ggsave( stackedBarOutputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
-print( paste( "Successfully wrote stacked bar chart out to", stackedBarOutputFile ) )
\ No newline at end of file
+print( paste( "[SUCCESS] Successfully wrote stacked bar chart out to", stackedBarOutputFile ) )
diff --git a/TestON/JenkinsFile/scripts/SCPFportLat.R b/TestON/JenkinsFile/scripts/SCPFportLat.R
index 0f9176a..bb43248 100644
--- a/TestON/JenkinsFile/scripts/SCPFportLat.R
+++ b/TestON/JenkinsFile/scripts/SCPFportLat.R
@@ -21,144 +21,346 @@
# 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
-# Check if sufficient args are provided.
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
if ( is.na( args[ 7 ] ) ){
- print( "Usage: Rscript SCPFportLat <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript SCPFportLat",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
q() # basically exit(), but in R
}
-# paste() is used to concatenate strings.
-errBarOutputFileUp <- paste( args[ 7 ], "SCPFportLat_", sep = "" )
-errBarOutputFileUp <- paste( errBarOutputFileUp, args[ 6 ], sep = "" )
-errBarOutputFileUp <- paste( errBarOutputFileUp, "_UpErrBarWithStack.jpg", sep = "" )
+# -----------------
+# Create File Names
+# -----------------
-errBarOutputFileDown <- paste( args[ 7 ], "SCPFportLat_", sep = "" )
-errBarOutputFileDown <- paste( errBarOutputFileDown, args[ 6 ], sep = "" )
-errBarOutputFileDown <- paste( errBarOutputFileDown, "_DownErrBarWithStack.jpg", sep = "" )
+print( "Creating filenames and title of graph." )
-print( "Reading from databases." )
+errBarOutputFileUp <- paste( args[ 7 ],
+ "SCPFportLat_",
+ args[ 6 ],
+ "_UpErrBarWithStack.jpg",
+ sep = "" )
-con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 1 ], port=strtoi( args[ 2 ] ), user=args[ 3 ],password=args[ 4 ] )
+errBarOutputFileDown <- paste( args[ 7 ],
+ "SCPFportLat_",
+ args[ 6 ],
+ "_DownErrBarWithStack.jpg",
+ sep = "" )
-command <- paste( "SELECT * FROM port_latency_details WHERE branch = '", args[ 6 ], sep = "" )
-command <- paste( command, "' AND date IN ( SELECT MAX( date ) FROM port_latency_details WHERE branch = '", sep = "" )
-command <- paste( command, args[ 6 ], sep = "" )
-command <- paste( command, "' ) ", sep="" )
+# ------------------
+# SQL Initialization
+# ------------------
-print( paste( "Sending SQL command:", command ) )
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 1 ],
+ port = strtoi( args[ 2 ] ),
+ user = args[ 3 ],
+ password = args[ 4 ] )
+
+# ------------------------
+# Port Latency SQL Command
+# ------------------------
+
+print( "Generating Port Latency SQL Command" )
+
+command <- paste( "SELECT * FROM port_latency_details WHERE branch = '",
+ args[ 6 ],
+ "' AND date IN ( SELECT MAX( date ) FROM port_latency_details WHERE branch = '",
+ args[ 6 ],
+ "' ) ",
+ sep = "" )
+
+print( "Sending SQL command:" )
+print( command )
fileData <- dbGetQuery( con, command )
-chartTitle <- paste( "Port Latency", args[ 6 ], sep = " - " )
-chartTitle <- paste( chartTitle, "\n" )
-
-
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
-print( "Sorting data." )
+print( "**********************************************************" )
+print( "STEP 2: Organize Data." )
+print( "**********************************************************" )
-upAvgs <- c( fileData[ 'up_ofp_to_dev_avg' ], fileData[ 'up_dev_to_link_avg' ], fileData[ 'up_link_to_graph_avg' ] )
-upAvgsData <- melt( upAvgs )
-upAvgsData$scale <- fileData$scale
-upAvgsData$up_std <- fileData$up_std
+# -----------------------------
+# Port Up Averages Data Sorting
+# -----------------------------
+print( "Sorting data for Port Up Averages." )
-colnames( upAvgsData ) <- c( "ms", "type", "scale", "stds" )
-upAvgsData$type <- as.character( upAvgsData$type )
-upAvgsData$type <- factor( upAvgsData$type, levels=unique( upAvgsData$type ) )
+upAvgs <- c( fileData[ 'up_ofp_to_dev_avg' ],
+ fileData[ 'up_dev_to_link_avg' ],
+ fileData[ 'up_link_to_graph_avg' ] )
-downAvgs <- c( fileData[ 'down_ofp_to_dev_avg' ], fileData[ 'down_dev_to_link_avg' ], fileData[ 'down_link_to_graph_avg' ] )
-downAvgsData <- melt( downAvgs )
-downAvgsData$scale <- fileData$scale
-downAvgsData$down_std <- fileData$down_std
+# ----------------------------
+# Port Up Construct Data Frame
+# ----------------------------
-colnames( downAvgsData ) <- c( "ms", "type", "scale", "stds" )
-downAvgsData$type <- as.character( downAvgsData$type )
-downAvgsData$type <- factor( downAvgsData$type, levels=unique( downAvgsData$type ) )
+print( "Constructing Port Up data frame." )
-upAvgsData <- na.omit( upAvgsData ) # Omit any data that doesn't exist
-downAvgsData <- na.omit( downAvgsData ) # Omit any data that doesn't exist
+upAvgsDataFrame <- melt( upAvgs )
+upAvgsDataFrame$scale <- fileData$scale
+upAvgsDataFrame$up_std <- fileData$up_std
+
+colnames( upAvgsDataFrame ) <- c( "ms",
+ "type",
+ "scale",
+ "stds" )
+
+upAvgsDataFrame <- na.omit( upAvgsDataFrame )
+
+upAvgsDataFrame$type <- as.character( upAvgsDataFrame$type )
+upAvgsDataFrame$type <- factor( upAvgsDataFrame$type, levels=unique( upAvgsDataFrame$type ) )
+
+sumOfUpAvgs <- fileData[ 'up_ofp_to_dev_avg' ] +
+ fileData[ 'up_dev_to_link_avg' ] +
+ fileData[ 'up_link_to_graph_avg' ]
print( "Up Averages Results:" )
-print( upAvgsData )
+print( upAvgsDataFrame )
+
+# -------------------------------
+# Port Down Averages Data Sorting
+# -------------------------------
+
+print( "Sorting data for Port Down Averages." )
+
+downAvgs <- c( fileData[ 'down_ofp_to_dev_avg' ],
+ fileData[ 'down_dev_to_link_avg' ],
+ fileData[ 'down_link_to_graph_avg' ] )
+
+# ------------------------------
+# Port Down Construct Data Frame
+# ------------------------------
+
+print( "Constructing Port Down data frame." )
+
+downAvgsDataFrame <- melt( downAvgs )
+downAvgsDataFrame$scale <- fileData$scale
+downAvgsDataFrame$down_std <- fileData$down_std
+
+colnames( downAvgsDataFrame ) <- c( "ms",
+ "type",
+ "scale",
+ "stds" )
+
+downAvgsDataFrame <- na.omit( downAvgsDataFrame )
+
+downAvgsDataFrame$type <- as.character( downAvgsDataFrame$type )
+downAvgsDataFrame$type <- factor( downAvgsDataFrame$type, levels=unique( downAvgsDataFrame$type ) )
+
+sumOfDownAvgs <- fileData[ 'down_ofp_to_dev_avg' ] +
+ fileData[ 'down_dev_to_link_avg' ] +
+ fileData[ 'down_link_to_graph_avg' ]
print( "Down Averages Results:" )
-print( downAvgsData )
+print( downAvgsDataFrame )
# **********************************************************
# STEP 3: Generate graphs.
# **********************************************************
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
-print( "Generating fundamental graph data (Port Up Latency)." )
-width <- 1
+# ------------------------------------
+# Initialize Variables For Both Graphs
+# ------------------------------------
+
+print( "Initializing variables used in both graphs." )
+
theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
-
-mainPlot <- ggplot( data = upAvgsData, aes( x = scale, y = ms, fill = type, ymin = fileData[ 'up_end_to_end_avg' ], ymax = fileData[ 'up_end_to_end_avg' ] + stds ) )
-xScaleConfig <- scale_x_continuous( breaks=c( 1, 3, 5, 7, 9) )
+barWidth <- 1
+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 = 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", "#18BA48" ) )
wrapLegend <- guides( fill=guide_legend( nrow=1, byrow=TRUE ) )
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
+errorBarColor <- rgb( 140, 140, 140, maxColorValue=255 )
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme + wrapLegend
+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",
+ "#18BA48" ) )
+
+# --------------------------
+# Port Up Generate Main Plot
+# --------------------------
+
+print( "Generating main plot (Port Up Latency)." )
+
+mainPlot <- ggplot( data = upAvgsDataFrame, aes( x = scale,
+ y = ms,
+ fill = type,
+ ymin = fileData[ 'up_end_to_end_avg' ],
+ ymax = fileData[ 'up_end_to_end_avg' ] + stds ) )
+
+# --------------------------------------
+# Port Up Fundamental Variables Assigned
+# --------------------------------------
+
+print( "Generating fundamental graph data (Port Up Latency)." )
+
+title <- ggtitle( "Port Up Latency" )
+
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ wrapLegend +
+ title +
+ colors
+
+# -----------------------------------
+# Port Up Generating Bar Graph Format
+# -----------------------------------
print( "Generating bar graph with error bars (Port Up Latency)." )
-barGraphFormat <- geom_bar( stat="identity", width = width )
-errorBarFormat <- geom_errorbar( width = width, color=rgb( 140, 140, 140, maxColorValue=255 ) )
-sum <- fileData[ 'up_ofp_to_dev_avg' ] + fileData[ 'up_dev_to_link_avg' ] + fileData[ 'up_link_to_graph_avg' ]
-values <- geom_text( aes( x=upAvgsData$scale, y=sum + 0.03 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold" )
-title <- ggtitle( "Port Up Latency" )
-result <- fundamentalGraphData + barGraphFormat + colors + errorBarFormat + title + values
+barGraphFormat <- geom_bar( stat = "identity",
+ width = barWidth )
+errorBarFormat <- geom_errorbar( width = barWidth,
+ color = errorBarColor )
+
+values <- geom_text( aes( x = upAvgsDataFrame$scale,
+ y = sumOfUpAvgs + 0.03 * max( sumOfUpAvgs ),
+ label = format( sumOfUpAvgs,
+ digits=3,
+ big.mark = ",",
+ scientific = FALSE ) ),
+ size = 7.0,
+ fontface = "bold" )
+
+result <- fundamentalGraphData +
+ barGraphFormat +
+ errorBarFormat +
+ values
+
+# -------------------------------
+# Port Up Exporting Graph to File
+# -------------------------------
print( paste( "Saving bar chart with error bars (Port Up Latency) to", errBarOutputFileUp ) )
-ggsave( errBarOutputFileUp, width = 15, height = 10, dpi = 200 )
+ggsave( errBarOutputFileUp,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
-print( paste( "Successfully wrote bar chart with error bars (Port Up Latency) out to", errBarOutputFileUp ) )
+print( paste( "[SUCCESS] Successfully wrote bar chart with error bars (Port Up Latency) out to", errBarOutputFileUp ) )
+# ----------------------------
+# Port Down Generate Main Plot
+# ----------------------------
+
+print( "Generating main plot (Port Down Latency)." )
+
+mainPlot <- ggplot( data = downAvgsDataFrame, aes( x = scale,
+ y = ms,
+ fill = type,
+ ymin = fileData[ 'down_end_to_end_avg' ],
+ ymax = fileData[ 'down_end_to_end_avg' ] + stds ) )
+
+# ----------------------------------------
+# Port Down Fundamental Variables Assigned
+# ----------------------------------------
print( "Generating fundamental graph data (Port Down Latency)." )
-mainPlot <- ggplot( data = downAvgsData, aes( x = scale, y = ms, fill = type, ymin = fileData[ 'down_end_to_end_avg' ], ymax = fileData[ 'down_end_to_end_avg' ] + stds ) )
-wrapLegend <- guides( fill=guide_legend( nrow=1, byrow=TRUE ) )
+title <- ggtitle( "Port Down Latency" )
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme + wrapLegend
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ wrapLegend +
+ title +
+ colors
+
+# -------------------------------------
+# Port Down Generating Bar Graph Format
+# -------------------------------------
print( "Generating bar graph with error bars (Port Down Latency)." )
-barGraphFormat <- geom_bar( stat="identity", width = width )
-errorBarFormat <- geom_errorbar( width = width, color=rgb( 140, 140, 140, maxColorValue=255 ) )
-sum <- fileData[ 'down_ofp_to_dev_avg' ] + fileData[ 'down_dev_to_link_avg' ] + fileData[ 'down_link_to_graph_avg' ]
-values <- geom_text( aes( x=downAvgsData$scale, y=sum + 0.03 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold" )
-title <- ggtitle( "Port Down Latency" )
-result <- fundamentalGraphData + barGraphFormat + colors + errorBarFormat + title + values
+barGraphFormat <- geom_bar( stat = "identity",
+ width = barWidth )
+errorBarFormat <- geom_errorbar( width = barWidth,
+ color = errorBarColor )
+values <- geom_text( aes( x = downAvgsDataFrame$scale,
+ y = sumOfDownAvgs + 0.03 * max( sumOfDownAvgs ),
+ label = format( sumOfDownAvgs,
+ digits=3,
+ big.mark = ",",
+ scientific = FALSE ) ),
+ size = 7.0,
+ fontface = "bold" )
+
+result <- fundamentalGraphData +
+ barGraphFormat +
+ errorBarFormat +
+ values
+
+# ---------------------------------
+# Port Down Exporting Graph to File
+# ---------------------------------
print( paste( "Saving bar chart with error bars (Port Down Latency) to", errBarOutputFileDown ) )
-ggsave( errBarOutputFileDown, width = 15, height = 10, dpi = 200 )
+ggsave( errBarOutputFileDown,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
-print( paste( "Successfully wrote bar chart with error bars (Port Down Latency) out to", errBarOutputFileDown ) )
+print( paste( "[SUCCESS] Successfully wrote bar chart with error bars (Port Down Latency) out to", errBarOutputFileDown ) )
diff --git a/TestON/JenkinsFile/scripts/SCPFscaleTopo.R b/TestON/JenkinsFile/scripts/SCPFscaleTopo.R
index 6be3533..8344efb 100644
--- a/TestON/JenkinsFile/scripts/SCPFscaleTopo.R
+++ b/TestON/JenkinsFile/scripts/SCPFscaleTopo.R
@@ -21,64 +21,121 @@
# 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
-# Check if sufficient args are provided.
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
if ( is.na( args[ 7 ] ) ){
- print( "Usage: Rscript SCPFgraphGenerator <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript SCPFgraphGenerator",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<directory-to-save-graphs>",
+ sep=" ") )
+
q() # basically exit(), but in R
}
-# paste() is used to concatenate strings
-outputFile <- paste( args[ 7 ], args[ 5 ], sep="" )
-outputFile <- paste( outputFile, args[ 6 ], sep="_" )
-outputFile <- paste( outputFile, "_graph.jpg", sep="" )
+# -----------------
+# Create File Names
+# -----------------
-print( "Reading from databases." )
+print( "Creating filenames and title of graph." )
-con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 1 ], port=strtoi( args[ 2 ] ), user=args[ 3 ],password=args[ 4 ] )
+outputFile <- paste( args[ 7 ],
+ args[ 5 ],
+ "_",
+ args[ 6 ],
+ "_graph.jpg",
+ sep="" )
-command <- paste( "SELECT * FROM scale_topo_latency_details WHERE branch = '", args[ 6 ], sep = "" )
-command <- paste( command, "' AND date IN ( SELECT MAX( date ) FROM scale_topo_latency_details WHERE branch = '", sep = "" )
-command <- paste( command, args[ 6 ], sep = "" )
-command <- paste( command, "' ) ", sep="" )
+chartTitle <- "Scale Topology Latency Test"
-print( paste( "Sending SQL command:", command ) )
+# ------------------
+# SQL Initialization
+# ------------------
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 1 ],
+ port = strtoi( args[ 2 ] ),
+ user = args[ 3 ],
+ password = args[ 4 ] )
+
+# --------------------------
+# Scale Topology SQL Command
+# --------------------------
+
+print( "Generating Scale Topology SQL Command" )
+
+command <- paste( "SELECT * FROM scale_topo_latency_details WHERE branch = '",
+ args[ 6 ],
+ "' AND date IN ( SELECT MAX( date ) FROM scale_topo_latency_details WHERE branch = '",
+ args[ 6 ],
+ "' ) ",
+ sep = "" )
+
+print( "Sending SQL command:" )
+print( command )
fileData <- dbGetQuery( con, command )
-title <- paste( args[ 5 ], args[ 6 ], 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.
+# ------------
+# Data Sorting
+# ------------
+
print( "Sorting data." )
-avgs <- c( fileData[ 'last_role_request_to_last_topology' ], fileData[ 'last_connection_to_last_role_request' ], fileData[ 'first_connection_to_last_connection' ] )
+avgs <- c( fileData[ 'last_role_request_to_last_topology' ],
+ fileData[ 'last_connection_to_last_role_request' ],
+ fileData[ 'first_connection_to_last_connection' ] )
+
+# --------------------
+# Construct Data Frame
+# --------------------
+
+print( "Constructing Data Frame" )
# Parse lists into data frames.
-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.
-colnames( dataFrame ) <- c( "s", "type", "scale")
-
+dataFrame <- melt( avgs )
+dataFrame$scale <- fileData$scale
+colnames( dataFrame ) <- c( "s",
+ "type",
+ "scale")
# Format data frame so that the data is in the same order as it appeared in the file.
dataFrame$type <- as.character( dataFrame$type )
@@ -87,7 +144,9 @@
dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
-sum <- fileData[ 'last_role_request_to_last_topology' ] + fileData[ 'last_connection_to_last_role_request' ] + fileData[ 'first_connection_to_last_connection' ]
+sum <- fileData[ 'last_role_request_to_last_topology' ] +
+ fileData[ 'last_connection_to_last_role_request' ] +
+ fileData[ 'first_connection_to_last_connection' ]
print( "Data Frame Results:" )
print( dataFrame )
@@ -96,48 +155,86 @@
# 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.
-#
-# 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( "Creating main plot." )
+
+mainPlot <- ggplot( data = dataFrame, aes( x = iterative,
+ y = s,
+ fill = type ) )
+
+# ------------------------------
+# Fundamental Variables Assigned
+# ------------------------------
print( "Generating fundamental graph data." )
theme_set( theme_grey( base_size = 20 ) ) # set the default text size of the graph.
-
-# 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 = iterative, y = s, fill = type ) )
-
-# Formatting the plot
width <- 0.6 # Width of the bars.
-xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative, label = dataFrame$scale )
+xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative,
+ label = dataFrame$scale )
xLabel <- xlab( "Scale" )
yLabel <- ylab( "Latency (s)" )
fillLabel <- labs( fill="Type" )
-chartTitle <- paste( "Scale Topology Latency Test" )
-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' ) )
-values <- geom_text( aes( x=dataFrame$iterative, y=sum + 0.02 * max( sum ), label = format( sum, big.mark = ",", scientific = FALSE ), fontface = "bold" ), size = 7.0 )
-wrapLegend <- guides( fill=guide_legend( nrow=2, byrow=TRUE ) )
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
+
+theme <- theme( plot.title = element_text( hjust = 0.5, size = 32, face = 'bold' ),
+ legend.position = "bottom",
+ legend.text = element_text( size=22 ),
+ legend.title = element_blank(),
+ legend.key.size = unit( 1.5, 'lines' ) )
+
+values <- geom_text( aes( x = dataFrame$iterative,
+ y = sum + 0.02 * max( sum ),
+ label = format( sum,
+ big.mark = ",",
+ scientific = FALSE ),
+ fontface = "bold" ),
+ size = 7.0 )
+
+wrapLegend <- guides( fill = guide_legend( nrow=2, byrow=TRUE ) )
+
+title <- ggtitle( chartTitle, "" )
+
# Store plot configurations as 1 variable
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme + values + wrapLegend
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ values +
+ wrapLegend +
+ title
+
+# ---------------------------
+# Generating Bar Graph Format
+# ---------------------------
print( "Generating bar graph." )
-barGraphFormat <- geom_bar( stat = "identity", width = width )
-title <- ggtitle( paste( chartTitle, "" ) )
-result <- fundamentalGraphData + barGraphFormat + title
-# Save graph to file
+barGraphFormat <- geom_bar( stat = "identity", width = width )
+
+result <- fundamentalGraphData +
+ barGraphFormat
+
+# -----------------------
+# Exporting Graph to File
+# -----------------------
+
print( paste( "Saving bar chart to", outputFile ) )
-ggsave( outputFile, width = 15, height = 10, dpi = 200 )
-print( paste( "Successfully wrote bar chart out to", outputFile ) )
+
+ggsave( outputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
+
+print( paste( "[SUCCESS] Successfully wrote bar chart out to", outputFile ) )
diff --git a/TestON/JenkinsFile/scripts/SCPFscalingMaxIntents.R b/TestON/JenkinsFile/scripts/SCPFscalingMaxIntents.R
index 0f09023..2ca0627 100644
--- a/TestON/JenkinsFile/scripts/SCPFscalingMaxIntents.R
+++ b/TestON/JenkinsFile/scripts/SCPFscalingMaxIntents.R
@@ -21,75 +21,127 @@
# 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( "**********************************************************" )
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[ 8 ] ) ){
- print( "Usage: Rscript SCPFInstalledIntentsFlows <has-flowObj> <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript SCPFInstalledIntentsFlows",
+ "<has-flowObj>",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
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="" )
+# -----------------
+# Create File Names
+# -----------------
-print( "Reading from databases." )
+print( "Creating filenames and title of graph." )
-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 )
+fileFlowObjModifier <- ""
+sqlFlowObjModifier <- ""
+chartTitle <- "Number of Installed Intents & Flows"
if ( args[ 1 ] == "y" ){
+ fileFlowObjModifier <- "_flowObj"
+ sqlFlowObjModifier <- "fobj_"
chartTitle <- "Number of Installed Intents & Flows\n with Flow Objectives"
-} else {
- chartTitle <- "Number of Installed Intents & Flows"
}
+outputFile <- paste( args[ 8 ],
+ args[ 6 ],
+ fileFlowObjModifier,
+ "_",
+ args[ 7 ],
+ "_errGraph.jpg",
+ sep="" )
+
+# ------------------
+# SQL Initialization
+# ------------------
+
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 2 ],
+ port = strtoi( args[ 3 ] ),
+ user = args[ 4 ],
+ password = args[ 5 ] )
+
+# -------------------------------
+# Scaling Max Intents SQL Command
+# -------------------------------
+
+print( "Scaling Max Intents SQL Command" )
+
+command <- paste( "SELECT * FROM max_intents_",
+ sqlFlowObjModifier,
+ "tests WHERE branch = '",
+ args[ 7 ],
+ "' AND date IN ( SELECT MAX( date ) FROM max_intents_",
+ sqlFlowObjModifier,
+ "tests WHERE branch = '",
+ args[ 7 ],
+ "' ) ",
+ sep="" )
+
+print( "Sending SQL command:" )
+print( command )
+fileData <- dbGetQuery( con, command )
+
# **********************************************************
# STEP 2: Organize data.
# **********************************************************
-fileDataNames <- names( fileData )
+print( "**********************************************************" )
+print( "STEP 2: Organize Data." )
+print( "**********************************************************" )
-avgs <- c()
+# ------------
+# Data Sorting
+# ------------
print( "Sorting data." )
-avgs <- c( fileData[ 'max_intents_ovs' ], fileData[ 'max_flows_ovs' ] )
+
+avgs <- c( fileData[ 'max_intents_ovs' ],
+ fileData[ 'max_flows_ovs' ] )
+
+# --------------------
+# Construct Data Frame
+# --------------------
+
+print( "Constructing Data Frame" )
dataFrame <- melt( avgs )
dataFrame$scale <- fileData$scale
@@ -108,30 +160,90 @@
# STEP 3: Generate graphs.
# **********************************************************
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
+
+# ------------------
+# Generate Main Plot
+# ------------------
+
+print( "Creating main plot." )
+mainPlot <- ggplot( data = dataFrame, aes( x = scale,
+ y = ms,
+ fill = type ) )
+
+# ------------------------------
+# Fundamental Variables Assigned
+# ------------------------------
+
print( "Generating fundamental graph data." )
+barWidth <- 1.3
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) )
+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
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
+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' ) )
-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 ) )
+colors <- scale_fill_manual( values = c( "#F77670",
+ "#619DFA" ) )
+
+wrapLegend <- guides( fill = guide_legend( nrow = 1, byrow = TRUE ) )
title <- ggtitle( chartTitle )
-result <- fundamentalGraphData + barGraphFormat + colors + title + values
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ fillLabel +
+ theme +
+ wrapLegend +
+ title +
+ colors
+
+# ---------------------------
+# Generating Bar Graph Format
+# ---------------------------
+
+print( "Generating bar graph." )
+
+barGraphFormat <- geom_bar( stat = "identity",
+ position = position_dodge(),
+ width = barWidth )
+
+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 ) )
+
+result <- fundamentalGraphData +
+ barGraphFormat +
+ values
+
+# -----------------------
+# Exporting Graph to File
+# -----------------------
print( paste( "Saving bar chart to", outputFile ) )
-ggsave( outputFile, width = 15, height = 10, dpi = 200 )
-print( paste( "Successfully wrote bar chart out to", outputFile ) )
+ggsave( outputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
+
+print( paste( "[SUCCESS] Successfully wrote bar chart out to", outputFile ) )
diff --git a/TestON/JenkinsFile/scripts/SCPFswitchLat.R b/TestON/JenkinsFile/scripts/SCPFswitchLat.R
index 7bf0a44..97b8d44 100644
--- a/TestON/JenkinsFile/scripts/SCPFswitchLat.R
+++ b/TestON/JenkinsFile/scripts/SCPFswitchLat.R
@@ -21,48 +21,92 @@
# 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
-# Check if sufficient args are provided.
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
if ( is.na( args[ 7 ] ) ){
- print( "Usage: Rscript SCPFswitchLat <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript SCPFswitchLat",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<directory-to-save-graphs>",
+ sep=" ") )
+
q() # basically exit(), but in R
}
-# paste() is used to concatenate strings.
-errBarOutputFileUp <- paste( args[ 7 ], "SCPFswitchLat_", sep = "" )
-errBarOutputFileUp <- paste( errBarOutputFileUp, args[ 6 ], sep = "" )
-errBarOutputFileUp <- paste( errBarOutputFileUp, "_UpErrBarWithStack.jpg", sep = "" )
+# -----------------
+# Create File Names
+# -----------------
-errBarOutputFileDown <- paste( args[ 7 ], "SCPFswitchLat_", sep = "" )
-errBarOutputFileDown <- paste( errBarOutputFileDown, args[ 6 ], sep = "" )
-errBarOutputFileDown <- paste( errBarOutputFileDown, "_DownErrBarWithStack.jpg", sep = "" )
+print( "Creating filenames and title of graph." )
-print( "Reading from databases." )
+errBarOutputFileUp <- paste( args[ 7 ],
+ "SCPFswitchLat_",
+ args[ 6 ],
+ "_UpErrBarWithStack.jpg",
+ sep="" )
-con <- dbConnect( dbDriver( "PostgreSQL" ), dbname="onostest", host=args[ 1 ], port=strtoi( args[ 2 ] ), user=args[ 3 ],password=args[ 4 ] )
+errBarOutputFileDown <- paste( args[ 7 ],
+ "SCPFswitchLat_",
+ args[ 6 ],
+ "_DownErrBarWithStack.jpg",
+ sep="" )
+# ------------------
+# SQL Initialization
+# ------------------
-command <- paste( "SELECT * FROM switch_latency_details WHERE branch = '", args[ 6 ], sep="" )
-command <- paste( command, "' AND date IN ( SELECT MAX( date ) FROM switch_latency_details WHERE branch='", sep = "")
-command <- paste( command, args[ 6 ], sep="" )
-command <- paste( command, "' )", sep="" )
+print( "Initializing SQL" )
-print( paste( "Sending SQL command:", command ) )
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 1 ],
+ port = strtoi( args[ 2 ] ),
+ user = args[ 3 ],
+ password = args[ 4 ] )
+
+# --------------------------
+# Switch Latency SQL Command
+# --------------------------
+
+print( "Generating Switch Latency SQL Command" )
+
+command <- paste( "SELECT * FROM switch_latency_details WHERE branch = '",
+ args[ 6 ],
+ "' AND date IN ( SELECT MAX( date ) FROM switch_latency_details WHERE branch='",
+ args[ 6 ],
+ "' )",
+ sep="" )
+
+print( "Sending SQL command:" )
+print( command )
fileData <- dbGetQuery( con, command )
@@ -70,31 +114,83 @@
# STEP 2: Organize data.
# **********************************************************
-print( "Sorting data." )
+print( "**********************************************************" )
+print( "STEP 2: Organize Data." )
+print( "**********************************************************" )
-upAvgs <- c( fileData[ 'up_device_to_graph_avg' ], fileData[ 'role_reply_to_device_avg' ], fileData[ 'role_request_to_role_reply_avg' ], fileData[ 'feature_reply_to_role_request_avg' ], fileData[ 'tcp_to_feature_reply_avg' ] )
+# -------------------------------
+# Switch Up Averages Data Sorting
+# -------------------------------
+
+print( "Sorting data for Switch Up Averages." )
+
+upAvgs <- c( fileData[ 'up_device_to_graph_avg' ],
+ fileData[ 'role_reply_to_device_avg' ],
+ fileData[ 'role_request_to_role_reply_avg' ],
+ fileData[ 'feature_reply_to_role_request_avg' ],
+ fileData[ 'tcp_to_feature_reply_avg' ] )
+
+# ------------------------------
+# Switch Up Construct Data Frame
+# ------------------------------
+
+print( "Constructing Switch Up data frame." )
+
upAvgsData <- melt( upAvgs )
upAvgsData$scale <- fileData$scale
upAvgsData$up_std <- fileData$up_std
+upAvgsData <- na.omit( upAvgsData )
-colnames( upAvgsData ) <- c( "ms", "type", "scale", "stds" )
+colnames( upAvgsData ) <- c( "ms",
+ "type",
+ "scale",
+ "stds" )
+
upAvgsData$type <- as.character( upAvgsData$type )
upAvgsData$type <- factor( upAvgsData$type, levels=unique( upAvgsData$type ) )
-downAvgs <- c( fileData[ 'down_device_to_graph_avg' ], fileData[ 'ack_to_device_avg' ], fileData[ 'fin_ack_to_ack_avg' ] )
+sumOfUpAvgs <- fileData[ 'up_device_to_graph_avg' ] +
+ fileData[ 'role_reply_to_device_avg' ] +
+ fileData[ 'role_request_to_role_reply_avg' ] +
+ fileData[ 'feature_reply_to_role_request_avg' ] +
+ fileData[ 'tcp_to_feature_reply_avg' ]
+
+print( "Up Averages Results:" )
+print( upAvgsData )
+
+# ---------------------------------
+# Switch Down Averages Data Sorting
+# ---------------------------------
+
+print( "Sorting data for Switch Down Averages." )
+
+downAvgs <- c( fileData[ 'down_device_to_graph_avg' ],
+ fileData[ 'ack_to_device_avg' ],
+ fileData[ 'fin_ack_to_ack_avg' ] )
+
+# --------------------------------
+# Switch Down Construct Data Frame
+# --------------------------------
+
+print( "Constructing Switch Down data frame." )
+
downAvgsData <- melt( downAvgs )
downAvgsData$scale <- fileData$scale
downAvgsData$down_std <- fileData$down_std
-colnames( downAvgsData ) <- c( "ms", "type", "scale", "stds" )
+colnames( downAvgsData ) <- c( "ms",
+ "type",
+ "scale",
+ "stds" )
+
downAvgsData$type <- as.character( downAvgsData$type )
downAvgsData$type <- factor( downAvgsData$type, levels=unique( downAvgsData$type ) )
-upAvgsData <- na.omit( upAvgsData ) # Omit any data that doesn't exist
downAvgsData <- na.omit( downAvgsData )
-print( "Up Averages Results:" )
-print( upAvgsData )
+sumOfDownAvgs <- fileData[ 'down_device_to_graph_avg' ] +
+ fileData[ 'ack_to_device_avg' ] +
+ fileData[ 'fin_ack_to_ack_avg' ]
print( "Down Averages Results:" )
print( downAvgsData )
@@ -103,58 +199,164 @@
# STEP 3: Generate graphs.
# **********************************************************
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
-print( "Generating fundamental graph data (Switch Up Latency)." )
-width <- 1
+# ------------------------------------
+# Initialize Variables For Both Graphs
+# ------------------------------------
-theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graph.
+print( "Initializing variables used in both graphs." )
-mainPlot <- ggplot( data = upAvgsData, aes( x = scale, y = ms, fill = type, ymin = fileData[ 'up_end_to_end_avg' ], ymax = fileData[ 'up_end_to_end_avg' ] + stds ) )
-xScaleConfig <- scale_x_continuous( breaks=c( 1, 3, 5, 7, 9) )
+theme_set( theme_grey( base_size = 22 ) ) # set the default text size of the graphs
+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 = 32, face='bold' ), legend.position="bottom", legend.text=element_text( size=22 ), legend.title = element_blank(), legend.key.size = unit( 1.5, 'lines' ) )
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
+errorBarColor <- rgb( 140, 140, 140, maxColorValue = 255 )
+barWidth <- 1
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
+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' ) )
+
+# ----------------------------
+# Switch Up Generate Main Plot
+# ----------------------------
+
+print( "Creating main plot (Switch Up Latency)." )
+
+mainPlot <- ggplot( data = upAvgsData, aes( x = scale,
+ y = ms,
+ fill = type,
+ ymin = fileData[ 'up_end_to_end_avg' ],
+ ymax = fileData[ 'up_end_to_end_avg' ] + stds ) )
+
+# ----------------------------------------
+# Switch Up Fundamental Variables Assigned
+# ----------------------------------------
+
+print( "Generating fundamental graph data (Switch Up Latency)." )
+
+title <- ggtitle( "Switch Up Latency" )
+
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ theme +
+ title
+
+# -------------------------------------
+# Switch Up Generating Bar Graph Format
+# -------------------------------------
print( "Generating bar graph with error bars (Switch Up Latency)." )
-barGraphFormat <- geom_bar( stat="identity", width = width )
-errorBarFormat <- geom_errorbar( width = width, color=rgb( 140, 140, 140, maxColorValue=255 ) )
-sum <- fileData[ 'up_device_to_graph_avg' ] + fileData[ 'role_reply_to_device_avg' ] + fileData[ 'role_request_to_role_reply_avg' ] + fileData[ 'feature_reply_to_role_request_avg' ] + fileData[ 'tcp_to_feature_reply_avg' ]
-values <- geom_text( aes( x=upAvgsData$scale, y=sum + 0.04 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold" )
-title <- ggtitle( "Switch Up Latency" )
-wrapLegend <- guides( fill=guide_legend( nrow=2, byrow=TRUE ) )
-result <- fundamentalGraphData + barGraphFormat + errorBarFormat + title + values + wrapLegend
+barGraphFormat <- geom_bar( stat = "identity", width = barWidth )
+errorBarFormat <- geom_errorbar( width = barWidth, color = errorBarColor )
+
+barGraphValues <- geom_text( aes( x = upAvgsData$scale,
+ y = sumOfUpAvgs + 0.04 * max( sumOfUpAvgs ),
+ label = format( sumOfUpAvgs,
+ digits = 3,
+ big.mark = ",",
+ scientific = FALSE ) ),
+ size = 7.0,
+ fontface = "bold" )
+
+wrapLegend <- guides( fill = guide_legend( nrow = 2, byrow = TRUE ) )
+
+result <- fundamentalGraphData +
+ barGraphFormat +
+ errorBarFormat +
+ barGraphValues +
+ wrapLegend
+
+# ---------------------------------
+# Switch Up Exporting Graph to File
+# ---------------------------------
print( paste( "Saving bar chart with error bars (Switch Up Latency) to", errBarOutputFileUp ) )
-ggsave( errBarOutputFileUp, width = 15, height = 10, dpi = 200 )
-print( paste( "Successfully wrote bar chart with error bars (Switch Up Latency) out to", errBarOutputFileUp ) )
+ggsave( errBarOutputFileUp,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
-# Generate switch down latency graph
+print( paste( "[SUCCESS] Successfully wrote bar chart with error bars (Switch Up Latency) out to", errBarOutputFileUp ) )
+
+# ------------------------------
+# Switch Down Generate Main Plot
+# ------------------------------
+
+print( "Creating main plot (Switch Down Latency)." )
+
+mainPlot <- ggplot( data = downAvgsData, aes( x = scale,
+ y = ms,
+ fill = type,
+ ymin = fileData[ 'down_end_to_end_avg' ],
+ ymax = fileData[ 'down_end_to_end_avg' ] + stds ) )
+
+# ------------------------------------------
+# Switch Down Fundamental Variables Assigned
+# ------------------------------------------
print( "Generating fundamental graph data (Switch Down Latency)." )
-mainPlot <- ggplot( data = downAvgsData, aes( x = scale, y = ms, fill = type, ymin = fileData[ 'down_end_to_end_avg' ], ymax = fileData[ 'down_end_to_end_avg' ] + stds ) )
-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", "#18BA48" ) )
-
-fundamentalGraphData <- mainPlot + xScaleConfig + xLabel + yLabel + fillLabel + theme
-
-print( "Generating bar graph with error bars (Switch Down Latency)." )
-barGraphFormat <- geom_bar( stat="identity", width = width )
-errorBarFormat <- geom_errorbar( width = width, color=rgb( 140, 140, 140, maxColorValue=255 ) )
+colors <- scale_fill_manual( values=c( "#F77670", # Red
+ "#619DFA", # Blue
+ "#18BA48" ) ) # Green
title <- ggtitle( "Switch Down Latency" )
-sum <- fileData[ 'down_device_to_graph_avg' ] + fileData[ 'ack_to_device_avg' ] + fileData[ 'fin_ack_to_ack_avg' ]
-values <- geom_text( aes( x=downAvgsData$scale, y=sum + 0.04 * max( sum ), label = format( sum, digits=3, big.mark = ",", scientific = FALSE ) ), size = 7.0, fontface = "bold" )
-wrapLegend <- guides( fill=guide_legend( nrow=1, byrow=TRUE ) )
-result <- fundamentalGraphData + barGraphFormat + colors + errorBarFormat + title + values + wrapLegend
+
+fundamentalGraphData <- mainPlot +
+ xScaleConfig +
+ xLabel +
+ yLabel +
+ theme +
+ title
+
+# ---------------------------------------
+# Switch Down Generating Bar Graph Format
+# ---------------------------------------
+
+print( "Generating bar graph with error bars (Switch Down Latency)." )
+barGraphFormat <- geom_bar( stat = "identity", width = barWidth )
+errorBarFormat <- geom_errorbar( width = barWidth, color = errorBarColor )
+
+barGraphValues <- geom_text( aes( x = downAvgsData$scale,
+ y = sumOfDownAvgs + 0.04 * max( sumOfDownAvgs ),
+ label = format( sumOfDownAvgs,
+ digits = 3,
+ big.mark = ",",
+ scientific = FALSE ) ),
+ size = 7.0,
+ fontface = "bold" )
+
+wrapLegend <- guides( fill = guide_legend( nrow = 1, byrow = TRUE ) )
+
+result <- fundamentalGraphData +
+ barGraphFormat +
+ colors +
+ errorBarFormat +
+ barGraphValues +
+ wrapLegend
+
+# -----------------------------------
+# Switch Down Exporting Graph to File
+# -----------------------------------
print( paste( "Saving bar chart with error bars (Switch Down Latency) to", errBarOutputFileDown ) )
-ggsave( errBarOutputFileDown, width = 15, height = 10, dpi = 200 )
+ggsave( errBarOutputFileDown,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
-print( paste( "Successfully wrote bar chart with error bars (Switch Down Latency) out to", errBarOutputFileDown ) )
+print( paste( "[SUCCESS] Successfully wrote bar chart with error bars (Switch Down Latency) out to", errBarOutputFileDown ) )
diff --git a/TestON/JenkinsFile/scripts/testCaseGraphGenerator.R b/TestON/JenkinsFile/scripts/testCaseGraphGenerator.R
index 2973755..f8ec145 100644
--- a/TestON/JenkinsFile/scripts/testCaseGraphGenerator.R
+++ b/TestON/JenkinsFile/scripts/testCaseGraphGenerator.R
@@ -26,72 +26,137 @@
# STEP 1: Data management.
# **********************************************************
+print( "**********************************************************" )
print( "STEP 1: Data management." )
+print( "**********************************************************" )
# 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 )
-# 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/
+# ----------------
+# Import Libraries
+# ----------------
+
print( "Importing libraries." )
library( ggplot2 )
library( reshape2 )
library( RPostgreSQL )
-# Check if sufficient args are provided.
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
if ( is.na( args[ 8 ] ) ){
- print( "Usage: Rscript testCaseGraphGenerator.R <database-host> <database-port> <database-user-id> <database-password> <test-name> <branch-name> <#-builds-to-show> <directory-to-save-graphs>" )
+
+ print( paste( "Usage: Rscript testCaseGraphGenerator.R",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>", # part of the output filename
+ "<branch-name>", # for sql and output filename
+ "<#-builds-to-show>", # for sql and output filename
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
q() # basically exit(), but in R
}
-# Filenames for the output graph include the testname, branch, and the graph type.
-outputFile <- paste( args[ 8 ], args[ 5 ], sep="" )
-outputFile <- paste( outputFile, args[ 6 ], sep="_" )
-outputFile <- paste( outputFile, args[ 7 ], sep="_" )
-outputFile <- paste( outputFile, "builds", sep="-" )
-outputFile <- paste( outputFile, "_graph.jpg", sep="" )
+# -------------------------------
+# Create Title and Graph Filename
+# -------------------------------
-# 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( "Creating title of graph." )
-print( "Creating SQL command." )
-# Creating SQL command based on command line args.
-command <- paste( "SELECT * FROM executed_test_tests WHERE actual_test_name='", args[ 5 ], sep="" )
-command <- paste( command, "' AND branch='", sep="" )
-command <- paste( command, args[ 6 ], sep="" )
-command <- paste( command, "' ORDER BY date DESC LIMIT ", sep="" )
-command <- paste( command, args[ 7 ], sep="" )
+title <- paste( args[ 5 ],
+ " - ",
+ args[ 6 ],
+ " \n Results of Last ",
+ args[ 7 ],
+ " Builds",
+ sep="" )
+
+print( "Creating graph filename." )
+
+outputFile <- paste( args[ 8 ],
+ args[ 5 ],
+ "_",
+ args[ 6 ],
+ "_",
+ args[ 7 ],
+ "-builds_graph.jpg",
+ sep="" )
+
+# ------------------
+# SQL Initialization
+# ------------------
+
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ 1 ],
+ port = strtoi( args[ 2 ] ),
+ user = args[ 3 ],
+ password = args[ 4 ] )
+
+# ---------------------
+# Test Case SQL Command
+# ---------------------
+print( "Generating Test Case SQL command." )
+
+command <- paste( "SELECT * FROM executed_test_tests WHERE actual_test_name='",
+ args[ 5 ],
+ "' AND branch='",
+ args[ 6 ],
+ "' ORDER BY date DESC LIMIT ",
+ args[ 7 ],
+ sep="" )
+
+print( "Sending SQL command:" )
+print( command )
fileData <- dbGetQuery( con, command )
-# Title of graph based on command line args.
-title <- paste( args[ 5 ], args[ 6 ], sep=" - " )
-title <- paste( title, "Results of Last ", sep=" \n " )
-title <- paste( title, args[ 7 ], sep="" )
-title <- paste( title, " Builds", 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 into new data frame." )
-categories <- c( fileData[ 'num_failed' ], fileData[ 'num_passed' ], fileData[ 'num_planned' ] )
+# -------------------------------------------------------
+# Combining Passed, Failed, and Planned Data
+# -------------------------------------------------------
-# Parse lists into data frames.
-# This is where reshape2 comes in. Avgs list is converted to data frame.
+print( "Combining Passed, Failed, and Planned Data." )
+
+categories <- c( fileData[ 'num_failed' ],
+ fileData[ 'num_passed' ],
+ fileData[ 'num_planned' ] )
+
+# --------------------
+# Construct Data Frame
+# --------------------
+
+print( "Constructing data frame from combined data." )
+
dataFrame <- melt( categories )
+
+# Rename column names in dataFrame
+colnames( dataFrame ) <- c( "Tests",
+ "Status" )
+
+# Add build dates to the dataFrame
dataFrame$build <- fileData$build
-colnames( dataFrame ) <- c( "Tests", "Status", "Build" )
# Format data frame so that the data is in the same order as it appeared in the file.
dataFrame$Status <- as.character( dataFrame$Status )
-dataFrame$Status <- factor( dataFrame$Status, levels=unique( dataFrame$Status ) )
+dataFrame$Status <- factor( dataFrame$Status, levels = unique( dataFrame$Status ) )
# Add planned, passed, and failed results to the dataFrame (for the fill below the lines)
dataFrame$num_planned <- fileData$num_planned
@@ -101,7 +166,8 @@
# Adding a temporary reversed iterative list to the dataFrame so that there are no gaps in-between build numbers.
dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )
-dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
+# Omit any data that doesn't exist
+dataFrame <- na.omit( dataFrame )
print( "Data Frame Results:" )
print( dataFrame )
@@ -110,7 +176,13 @@
# STEP 3: Generate graphs.
# **********************************************************
-print( "STEP 3: Generate graphs." )
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
+
+# -------------------
+# Main Plot Generated
+# -------------------
print( "Creating main plot." )
# Create the primary plot here.
@@ -120,40 +192,111 @@
# - x: x-axis values (usually iterative, but it will become build # later)
# - y: y-axis values (usually tests)
# - color: the category of the colored lines (usually status of test)
-theme_set( theme_grey( base_size = 26 ) ) # set the default text size of the graph.
-mainPlot <- ggplot( data = dataFrame, aes( x = iterative, y = Tests, color = Status ) )
+
+mainPlot <- ggplot( data = dataFrame, aes( x = iterative,
+ y = Tests,
+ color = Status ) )
+
+# -------------------
+# Main Plot Formatted
+# -------------------
print( "Formatting main plot." )
+
# geom_ribbon is used so that there is a colored fill below the lines. These values shouldn't be changed.
-failedColor <- geom_ribbon( aes( ymin = 0, ymax = dataFrame$num_failed ), fill = "red", linetype = 0, alpha = 0.07 )
-passedColor <- geom_ribbon( aes( ymin = 0, ymax = dataFrame$num_passed ), fill = "green", linetype = 0, alpha = 0.05 )
-plannedColor <- geom_ribbon( aes( ymin = 0, ymax = dataFrame$num_planned ), fill = "blue", linetype = 0, alpha = 0.01 )
+failedColor <- geom_ribbon( aes( ymin = 0,
+ ymax = dataFrame$num_failed ),
+ fill = "red",
+ linetype = 0,
+ alpha = 0.07 )
-colors <- scale_color_manual( values=c( "#E80000", "#00B208", "#00A5FF") )
+passedColor <- geom_ribbon( aes( ymin = 0,
+ ymax = dataFrame$num_passed ),
+ fill = "green",
+ linetype = 0,
+ alpha = 0.05 )
-xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative, label = dataFrame$Build )
-yScaleConfig <- scale_y_continuous( breaks = seq( 0, max( dataFrame$Tests ), by = ceiling( max( dataFrame$Tests ) / 10 ) ) )
+plannedColor <- geom_ribbon( aes( ymin = 0,
+ ymax = dataFrame$num_planned ),
+ fill = "blue",
+ linetype = 0,
+ alpha = 0.01 )
+
+# Colors for the lines
+lineColors <- scale_color_manual( values=c( "#E80000", # red
+ "#00B208", # green
+ "#00A5FF") ) # blue
+
+# ------------------------------
+# Fundamental Variables Assigned
+# ------------------------------
+
+print( "Generating fundamental graph data." )
+
+theme_set( theme_grey( base_size = 26 ) ) # set the default text size of the graph.
+
+xScaleConfig <- scale_x_continuous( breaks = dataFrame$iterative,
+ label = dataFrame$Build )
+yScaleConfig <- scale_y_continuous( breaks = seq( 0, max( dataFrame$Tests ),
+ by = ceiling( max( dataFrame$Tests ) / 10 ) ) )
xLabel <- xlab( "Build Number" )
yLabel <- ylab( "Test Cases" )
-fillLabel <- labs( fill="Type" )
-legendLabels <- scale_colour_discrete( labels = c( "Failed Cases", "Passed Cases", "Planned Cases" ) )
-centerTitle <- theme( plot.title=element_text( hjust = 0.5 ) ) # To center the title text
-theme <- theme( plot.title = element_text( size = 32, face='bold' ), axis.text.x = element_text( angle = 0, size = 14 ), legend.position="bottom", legend.text=element_text( size=22 ), legend.title = element_blank(), legend.key.size = unit( 1.5, 'lines' ) )
+imageWidth <- 15
+imageHeight <- 10
+imageDPI <- 200
+
+legendLabels <- scale_colour_discrete( labels = c( "Failed Cases",
+ "Passed Cases",
+ "Planned Cases" ) )
+
+# Set other graph configurations here.
+theme <- theme( plot.title = element_text( hjust = 0.5, size = 32, face ='bold' ),
+ axis.text.x = element_text( angle = 0, size = 14 ),
+ legend.position = "bottom",
+ legend.text = element_text( size = 22 ),
+ legend.title = element_blank(),
+ legend.key.size = unit( 1.5, 'lines' ) )
+
+title <- ggtitle( title )
# Store plot configurations as 1 variable
-fundamentalGraphData <- mainPlot + plannedColor + passedColor + failedColor + xScaleConfig + yScaleConfig + xLabel + yLabel + fillLabel + colors + legendLabels + centerTitle + theme
+fundamentalGraphData <- mainPlot +
+ plannedColor +
+ passedColor +
+ failedColor +
+ xScaleConfig +
+ yScaleConfig +
+ xLabel +
+ yLabel +
+ lineColors +
+ legendLabels +
+ theme +
+ title
+
+# ----------------------------
+# Generating Line Graph Format
+# ----------------------------
print( "Generating line graph." )
lineGraphFormat <- geom_line( size = 1.1 )
pointFormat <- geom_point( size = 3 )
-title <- ggtitle( title )
-result <- fundamentalGraphData + lineGraphFormat + pointFormat + title
+result <- fundamentalGraphData +
+ lineGraphFormat +
+ pointFormat
-# Save graph to file
+# -----------------------
+# Exporting Graph to File
+# -----------------------
+
print( paste( "Saving result graph to", outputFile ) )
-ggsave( outputFile, width = 15, height = 10, dpi = 200 )
-print( paste( "Successfully wrote result graph out to", outputFile ) )
+
+ggsave( outputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI )
+
+print( paste( "[SUCCESS] Successfully wrote result graph out to", outputFile ) )