[ONOS-7495]: Refactor Wiki Test Result Graph R Scripts
Change-Id: Iccbe89838bba21af276463e73091341063dc7b39
diff --git a/TestON/JenkinsFile/wikiGraphRScripts/SCPFspecificGraphRScripts/SCPFintentEventTp.R b/TestON/JenkinsFile/wikiGraphRScripts/SCPFspecificGraphRScripts/SCPFintentEventTp.R
new file mode 100644
index 0000000..e9a9dc4
--- /dev/null
+++ b/TestON/JenkinsFile/wikiGraphRScripts/SCPFspecificGraphRScripts/SCPFintentEventTp.R
@@ -0,0 +1,310 @@
+# Copyright 2017 Open Networking Foundation (ONF)
+#
+# Please refer questions to either the onos test mailing list at <onos-test@onosproject.org>,
+# the System Testing Plans and Results wiki page at <https://wiki.onosproject.org/x/voMg>,
+# or the System Testing Guide page at <https://wiki.onosproject.org/x/WYQg>
+#
+# TestON is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 2 of the License, or
+# (at your option) any later version.
+#
+# TestON is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with TestON. If not, see <http://www.gnu.org/licenses/>.
+#
+# If you have any questions, or if you don't understand R,
+# please contact Jeremy Ronquillo: j_ronquillo@u.pacific.edu
+
+# **********************************************************
+# STEP 1: Data management.
+# **********************************************************
+
+print( "**********************************************************" )
+print( "STEP 1: Data management." )
+print( "**********************************************************" )
+has_flow_obj = 1
+database_host = 2
+database_port = 3
+database_u_id = 4
+database_pw = 5
+test_name = 6
+branch_name = 7
+has_neighbors = 8
+old_flow = 9
+save_directory = 10
+
+# Command line arguments are read.
+print( "Reading commmand-line args." )
+args <- commandArgs( trailingOnly=TRUE )
+
+# ----------------
+# Import Libraries
+# ----------------
+
+print( "Importing libraries." )
+library( ggplot2 )
+library( reshape2 )
+library( RPostgreSQL ) # For databases
+
+# -------------------
+# Check CLI Arguments
+# -------------------
+
+print( "Verifying CLI args." )
+
+if ( is.na( args[ save_directory ] ) ){
+
+ print( paste( "Usage: Rscript SCPFIntentEventTp.R",
+ "<has-flow-obj>",
+ "<database-host>",
+ "<database-port>",
+ "<database-user-id>",
+ "<database-password>",
+ "<test-name>",
+ "<branch-name>",
+ "<has-neighbors>",
+ "<using-old-flow>",
+ "<directory-to-save-graphs>",
+ sep=" " ) )
+
+ quit( status = 1 ) # basically exit(), but in R
+}
+
+# -----------------
+# Create File Names
+# -----------------
+
+print( "Creating filenames and title of graph." )
+
+chartTitle <- "Intent Event Throughput"
+fileNeighborsModifier <- "no"
+commandNeighborModifier <- ""
+fileFlowObjModifier <- ""
+sqlFlowObjModifier <- ""
+
+if ( args[ has_flow_obj ] == 'y' ){
+ fileFlowObjModifier <- "_flowObj"
+ sqlFlowObjModifier <- "_fobj"
+ chartTitle <- paste( chartTitle, " with Flow Objectives", sep="" )
+}
+
+chartTitle <- paste( chartTitle, "\nevents/second with Neighbors =", sep="" )
+
+fileOldFlowModifier <- ""
+if ( args[ has_neighbors ] == 'y' ){
+ fileNeighborsModifier <- "all"
+ commandNeighborModifier <- "scale=1 OR NOT "
+ chartTitle <- paste( chartTitle, "all" )
+} else {
+ chartTitle <- paste( chartTitle, "0" )
+}
+if ( args[ old_flow ] == 'y' ){
+ fileOldFlowModifier <- "_OldFlow"
+ chartTitle <- paste( chartTitle, "With Eventually Consistent Flow Rule Store", sep="\n" )
+}
+
+errBarOutputFile <- paste( args[ save_directory ],
+ args[ test_name ],
+ "_",
+ args[ branch_name ],
+ "_",
+ fileNeighborsModifier,
+ "-neighbors",
+ fileFlowObjModifier,
+ fileOldFlowModifier,
+ "_graph.jpg",
+ sep="" )
+
+# ------------------
+# SQL Initialization
+# ------------------
+
+print( "Initializing SQL" )
+
+con <- dbConnect( dbDriver( "PostgreSQL" ),
+ dbname = "onostest",
+ host = args[ database_host ],
+ port = strtoi( args[ database_port ] ),
+ user = args[ database_u_id ],
+ password = args[ database_pw ] )
+
+# -----------------------------------
+# 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[ branch_name ],
+ "' AND date IN ( SELECT max( date ) FROM intent_tp",
+ sqlFlowObjModifier,
+ "_tests WHERE branch='",
+ args[ branch_name ],
+ "' AND ",
+ ( if( args[ old_flow ] == 'y' ) "" else "NOT " ),
+ "is_old_flow",
+ " ) GROUP BY scale ORDER BY scale",
+ sep="" )
+
+print( "Sending SQL command:" )
+print( command )
+
+fileData <- dbGetQuery( con, command )
+
+# **********************************************************
+# STEP 2: Organize data.
+# **********************************************************
+
+print( "**********************************************************" )
+print( "STEP 2: Organize Data." )
+print( "**********************************************************" )
+
+# ------------
+# Data Sorting
+# ------------
+
+print( "Sorting data." )
+
+requiredColumns <- c( "avg" )
+
+tryCatch( avgs <- c( fileData[ requiredColumns] ),
+ error = function( e ) {
+ print( "[ERROR] One or more expected columns are missing from the data. Please check that the data and SQL command are valid, then try again." )
+ print( "Required columns: " )
+ print( requiredColumns )
+ print( "Actual columns: " )
+ print( names( fileData ) )
+ print( "Error dump:" )
+ print( e )
+ quit( status = 1 )
+ }
+ )
+
+# --------------------
+# 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" )
+
+dataFrame <- na.omit( dataFrame ) # Omit any data that doesn't exist
+
+print( "Data Frame Results:" )
+print( dataFrame )
+
+
+# **********************************************************
+# STEP 3: Generate graphs.
+# **********************************************************
+
+print( "**********************************************************" )
+print( "STEP 3: Generate Graph." )
+print( "**********************************************************" )
+
+# ------------------
+# Generate Main Plot
+# ------------------
+
+print( "Generating main plot." )
+# Create the primary plot here.
+# ggplot contains the following arguments:
+# - data: the data frame that the graph will be based off of
+# - aes: the asthetics of the graph which require:
+# - x: x-axis values (usually node scaling)
+# - y: y-axis values (usually time in milliseconds)
+# - fill: the category of the colored side-by-side bars (usually type)
+
+mainPlot <- ggplot( data = dataFrame, aes( x = scale,
+ y = throughput,
+ 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" )
+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(),
+ plot.subtitle = element_text( size=16, hjust=1.0 ) )
+
+subtitle <- paste( "Last Updated: ", format( Sys.time(), format = "%b %d, %Y at %I:%M %p %Z" ), sep="" )
+
+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
+
+# ---------------------------
+# Generating Bar Graph Format
+# ---------------------------
+
+print( "Generating bar graph." )
+barGraphFormat <- geom_bar( stat = "identity",
+ width = width,
+ fill = "#169EFF" )
+
+title <- labs( title = chartTitle, subtitle = subtitle )
+
+result <- fundamentalGraphData +
+ barGraphFormat +
+ title
+
+# -----------------------
+# Exporting Graph to File
+# -----------------------
+
+print( paste( "Saving bar chart to", errBarOutputFile ) )
+
+tryCatch( ggsave( errBarOutputFile,
+ width = imageWidth,
+ height = imageHeight,
+ dpi = imageDPI ),
+ error = function( e ){
+ print( "[ERROR] There was a problem saving the graph due to a graph formatting exception. Error dump:" )
+ print( e )
+ quit( status = 1 )
+ }
+ )
+
+print( paste( "[SUCCESS] Successfully wrote bar chart out to", errBarOutputFile ) )
+quit( status = 0 )