TestON/JenkinsFile/wikiGraphRScripts/trendSCPF.R - OnosSystemTest - Gitiles

 # Copyright 2017 Open Networking Foundation (ONF)
 #
 # Please refer questions to either the onos test mailing list at <onos-test@onosproject.org>,
 # the System Testing Plans and Results wiki page at <https://wiki.onosproject.org/x/voMg>,
 # or the System Testing Guide page at <https://wiki.onosproject.org/x/WYQg>
 #
 #     TestON is free software: you can redistribute it and/or modify
 #     it under the terms of the GNU General Public License as published by
 #     the Free Software Foundation, either version 2 of the License, or
 #     (at your option) any later version.
 #
 #     TestON is distributed in the hope that it will be useful,
 #     but WITHOUT ANY WARRANTY; without even the implied warranty of
 #     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 #     GNU General Public License for more details.
 #
 #     You should have received a copy of the GNU General Public License
 #     along with TestON.  If not, see <http://www.gnu.org/licenses/>.
 #
 # If you have any questions, or if you don't understand R,
 # please contact Jeremy Ronquillo: j_ronquillo@u.pacific.edu

 # This is the R script that generates the SCPF front page graphs.


 # **********************************************************
 # STEP 1: Data management.
 # **********************************************************

 # Args 1 through 6 reside in fundamentalGraphData.R
 num_dates = 7
 sql_commands = 8
 y_axis = 9
 old_flow = 10
 save_directory = 11

 print( "**********************************************************" )
 print( "STEP 1: Data management." )
 print( "**********************************************************" )

 # ----------------
 # Import Libraries
 # ----------------

 print( "Importing libraries." )
 library( ggplot2 )
 library( reshape2 )
 library( RPostgreSQL )
 source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/saveGraph.R" )
 source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/fundamentalGraphData.R" )
 source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/initSQL.R" )
 source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/cliArgs.R" )

 # -------------------
 # Check CLI Arguments
 # -------------------

 print( "Verifying CLI args." )

 args <- commandArgs( trailingOnly=TRUE )

 # Check if sufficient args are provided.
 if ( length( args ) != save_directory ){
     specialArgs <- c(  "#-dates",
                        "SQL-command",
                        "y-axis-title",
                        "using-old-flow" )
     usage( "trendSCPF.R", specialArgs )
     quit( status = 1 )
 }

 # -------------------------------
 # Create Title and Graph Filename
 # -------------------------------

 print( "Creating title of graph" )

 # Title of graph based on command line args.

 title <- args[ graph_title ]
 title <- paste( title, if( args[ old_flow ] == "y" ) "\nWith Eventually Consistent Flow Rule Store" else "" )

 print( "Creating graph filename." )

 # Filenames for the output graph include the testname, branch, and the graph type.
 outputFile <- paste( args[ save_directory ],
                     "SCPF_Front_Page_",
                     gsub( " ", "_", args[ graph_title ] ),
                     "_",
                     args[ branch_name ],
                     "_",
                     args[ num_dates ],
                     "-dates",
                     if( args[ old_flow ] == "y" ) "_OldFlow" else "",
                     "_graph.jpg",
                     sep="" )

 # ------------------
 # SQL Initialization
 # ------------------

 print( "Initializing SQL" )
 con <- initSQL( args[ database_host ], args[ database_port ], args[ database_u_id ], args[ database_pw ] )

 fileData <- retrieveData( con, args[ sql_commands ] )

 # **********************************************************
 # STEP 2: Organize data.
 # **********************************************************

 print( "**********************************************************" )
 print( "STEP 2: Organize Data." )
 print( "**********************************************************" )

 # Create lists c() and organize data into their corresponding list.
 print( "Combine data retrieved from databases into a list." )

 buildNums <- fileData$build
 fileData$build <- c()
 print( fileData )

 if ( ncol( fileData ) > 1 ){
     for ( i in 2:ncol( fileData ) ){
         fileData[ i ] <- fileData[ i - 1 ] + fileData[ i ]
     }
 }


 # --------------------
 # Construct Data Frame
 # --------------------

 print( "Constructing data frame from combined data." )

 dataFrame <- melt( fileData )
 dataFrame$date <- fileData$date

 colnames( dataFrame ) <- c( "Legend",
                             "Values" )

 # Format data frame so that the data is in the same order as it appeared in the file.
 dataFrame$Legend <- as.character( dataFrame$Legend )
 dataFrame$Legend <- factor( dataFrame$Legend, levels=unique( dataFrame$Legend ) )
 dataFrame$build <- buildNums

 # Adding a temporary iterative list to the dataFrame so that there are no gaps in-between date numbers.
 dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )

 dataFrame <- na.omit( dataFrame )   # Omit any data that doesn't exist

 print( "Data Frame Results:" )
 print( dataFrame )

 # **********************************************************
 # STEP 3: Generate graphs.
 # **********************************************************

 print( "**********************************************************" )
 print( "STEP 3: Generate Graph." )
 print( "**********************************************************" )

 # -------------------
 # Main Plot Generated
 # -------------------

 print( "Creating main plot." )
 # Create the primary plot here.
 # ggplot contains the following arguments:
 #     - data: the data frame that the graph will be based off of
 #    - aes: the asthetics of the graph which require:
 #        - x: x-axis values (usually iterative, but it will become date # later)
 #        - y: y-axis values (usually tests)
 #        - color: the category of the colored lines (usually legend of test)

 mainPlot <- ggplot( data = dataFrame, aes( x = iterative,
                                            y = Values,
                                            color = Legend ) )

 # -------------------
 # Main Plot Formatted
 # -------------------

 print( "Formatting main plot." )

 limitExpansion <- expand_limits( y = 0 )

 tickLength <- 3
 breaks <- seq( max( dataFrame$iterative ) %% tickLength, max( dataFrame$iterative ), by = tickLength )
 breaks <- breaks[ which( breaks != 0 ) ]

 maxYDisplay <- max( dataFrame$Values ) * 1.05
 yBreaks <- ceiling( max( dataFrame$Values ) / 10 )
 yScaleConfig <- scale_y_continuous( breaks = seq( 0, maxYDisplay, by = yBreaks ) )
 xScaleConfig <- scale_x_continuous( breaks = breaks, label = rev( dataFrame$build )[ breaks ] )

 # ------------------------------
 # Fundamental Variables Assigned
 # ------------------------------

 print( "Generating fundamental graph data." )

 defaultTextSize()
 xLabel <- xlab( "Build" )
 yLabel <- ylab( args[ y_axis ] )

 # Set other graph configurations here.
 theme <- graphTheme()

 title <- labs( title = title, subtitle = lastUpdatedLabel() )

 # 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( webColor( "black" ),   # black
                                         webColor( "blue" ),   # blue
                                         webColor( "red" ),   # red
                                         webColor( "green" ),   # green
                                         webColor( "yellow" ),   # yellow
                                         webColor( "purple" ) ) ) # purple (not used)

 wrapLegend <- wrapLegend()

 fundamentalGraphData <- mainPlot +
                         limitExpansion +
                         xScaleConfig +
                         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 )

 result <- fundamentalGraphData +
           lineGraphFormat +
           pointFormat

 # -----------------------
 # Exporting Graph to File
 # -----------------------

 saveGraph( outputFile ) # from saveGraph.R
 quit( status = 0 )
	# Copyright 2017 Open Networking Foundation (ONF)
	#
	# Please refer questions to either the onos test mailing list at <onos-test@onosproject.org>,
	# the System Testing Plans and Results wiki page at <https://wiki.onosproject.org/x/voMg>,
	# or the System Testing Guide page at <https://wiki.onosproject.org/x/WYQg>
	#
	# TestON is free software: you can redistribute it and/or modify
	# it under the terms of the GNU General Public License as published by
	# the Free Software Foundation, either version 2 of the License, or
	# (at your option) any later version.
	#
	# TestON is distributed in the hope that it will be useful,
	# but WITHOUT ANY WARRANTY; without even the implied warranty of
	# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
	# GNU General Public License for more details.
	#
	# You should have received a copy of the GNU General Public License
	# along with TestON. If not, see <http://www.gnu.org/licenses/>.
	#
	# If you have any questions, or if you don't understand R,
	# please contact Jeremy Ronquillo: j_ronquillo@u.pacific.edu

	# This is the R script that generates the SCPF front page graphs.


	# **********************************************************
	# STEP 1: Data management.
	# **********************************************************

	# Args 1 through 6 reside in fundamentalGraphData.R
	num_dates = 7
	sql_commands = 8
	y_axis = 9
	old_flow = 10
	save_directory = 11

	print( "**********************************************************" )
	print( "STEP 1: Data management." )
	print( "**********************************************************" )

	# ----------------
	# Import Libraries
	# ----------------

	print( "Importing libraries." )
	library( ggplot2 )
	library( reshape2 )
	library( RPostgreSQL )
	source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/saveGraph.R" )
	source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/fundamentalGraphData.R" )
	source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/initSQL.R" )
	source( "~/OnosSystemTest/TestON/JenkinsFile/wikiGraphRScripts/dependencies/cliArgs.R" )

	# -------------------
	# Check CLI Arguments
	# -------------------

	print( "Verifying CLI args." )

	args <- commandArgs( trailingOnly=TRUE )

	# Check if sufficient args are provided.
	if ( length( args ) != save_directory ){
	specialArgs <- c( "#-dates",
	"SQL-command",
	"y-axis-title",
	"using-old-flow" )
	usage( "trendSCPF.R", specialArgs )
	quit( status = 1 )
	}

	# -------------------------------
	# Create Title and Graph Filename
	# -------------------------------

	print( "Creating title of graph" )

	# Title of graph based on command line args.

	title <- args[ graph_title ]
	title <- paste( title, if( args[ old_flow ] == "y" ) "\nWith Eventually Consistent Flow Rule Store" else "" )

	print( "Creating graph filename." )

	# Filenames for the output graph include the testname, branch, and the graph type.
	outputFile <- paste( args[ save_directory ],
	"SCPF_Front_Page_",
	gsub( " ", "_", args[ graph_title ] ),
	"_",
	args[ branch_name ],
	"_",
	args[ num_dates ],
	"-dates",
	if( args[ old_flow ] == "y" ) "_OldFlow" else "",
	"_graph.jpg",
	sep="" )

	# ------------------
	# SQL Initialization
	# ------------------

	print( "Initializing SQL" )
	con <- initSQL( args[ database_host ], args[ database_port ], args[ database_u_id ], args[ database_pw ] )

	fileData <- retrieveData( con, args[ sql_commands ] )

	# **********************************************************
	# STEP 2: Organize data.
	# **********************************************************

	print( "**********************************************************" )
	print( "STEP 2: Organize Data." )
	print( "**********************************************************" )

	# Create lists c() and organize data into their corresponding list.
	print( "Combine data retrieved from databases into a list." )

	buildNums <- fileData$build
	fileData$build <- c()
	print( fileData )

	if ( ncol( fileData ) > 1 ){
	for ( i in 2:ncol( fileData ) ){
	fileData[ i ] <- fileData[ i - 1 ] + fileData[ i ]
	}
	}


	# --------------------
	# Construct Data Frame
	# --------------------

	print( "Constructing data frame from combined data." )

	dataFrame <- melt( fileData )
	dataFrame$date <- fileData$date

	colnames( dataFrame ) <- c( "Legend",
	"Values" )

	# Format data frame so that the data is in the same order as it appeared in the file.
	dataFrame$Legend <- as.character( dataFrame$Legend )
	dataFrame$Legend <- factor( dataFrame$Legend, levels=unique( dataFrame$Legend ) )
	dataFrame$build <- buildNums

	# Adding a temporary iterative list to the dataFrame so that there are no gaps in-between date numbers.
	dataFrame$iterative <- rev( seq( 1, nrow( fileData ), by = 1 ) )

	dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist

	print( "Data Frame Results:" )
	print( dataFrame )

	# **********************************************************
	# STEP 3: Generate graphs.
	# **********************************************************

	print( "**********************************************************" )
	print( "STEP 3: Generate Graph." )
	print( "**********************************************************" )

	# -------------------
	# Main Plot Generated
	# -------------------

	print( "Creating main plot." )
	# Create the primary plot here.
	# ggplot contains the following arguments:
	# - data: the data frame that the graph will be based off of
	# - aes: the asthetics of the graph which require:
	# - x: x-axis values (usually iterative, but it will become date # later)
	# - y: y-axis values (usually tests)
	# - color: the category of the colored lines (usually legend of test)

	mainPlot <- ggplot( data = dataFrame, aes( x = iterative,
	y = Values,
	color = Legend ) )

	# -------------------
	# Main Plot Formatted
	# -------------------

	print( "Formatting main plot." )

	limitExpansion <- expand_limits( y = 0 )

	tickLength <- 3
	breaks <- seq( max( dataFrame$iterative ) %% tickLength, max( dataFrame$iterative ), by = tickLength )
	breaks <- breaks[ which( breaks != 0 ) ]

	maxYDisplay <- max( dataFrame$Values ) * 1.05
	yBreaks <- ceiling( max( dataFrame$Values ) / 10 )
	yScaleConfig <- scale_y_continuous( breaks = seq( 0, maxYDisplay, by = yBreaks ) )
	xScaleConfig <- scale_x_continuous( breaks = breaks, label = rev( dataFrame$build )[ breaks ] )

	# ------------------------------
	# Fundamental Variables Assigned
	# ------------------------------

	print( "Generating fundamental graph data." )

	defaultTextSize()
	xLabel <- xlab( "Build" )
	yLabel <- ylab( args[ y_axis ] )

	# Set other graph configurations here.
	theme <- graphTheme()

	title <- labs( title = title, subtitle = lastUpdatedLabel() )

	# 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( webColor( "black" ), # black
	webColor( "blue" ), # blue
	webColor( "red" ), # red
	webColor( "green" ), # green
	webColor( "yellow" ), # yellow
	webColor( "purple" ) ) ) # purple (not used)

	wrapLegend <- wrapLegend()

	fundamentalGraphData <- mainPlot +
	limitExpansion +
	xScaleConfig +
	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 )

	result <- fundamentalGraphData +
	lineGraphFormat +
	pointFormat

	# -----------------------
	# Exporting Graph to File
	# -----------------------

	saveGraph( outputFile ) # from saveGraph.R
	quit( status = 0 )