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Add R Script Computing the Swarm Plot "The Maximum Transmission Switc…
…hing Flow Problem" (#91) * Add the R script that computes the swarm plot in [1], * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci, * Publication: [1] "The Maximum Transmission Switching Flow Problem", 2018, ACM e-Energy, doi:10.1145/3208903.3208910. Changes to be committed: new file: evaluations/2018_ACM_The-Maximum-Transmission-Switching-Flow-Problem/statistics/plot-maxst-vs-mtsf-violin-swarm.R
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...-Maximum-Transmission-Switching-Flow-Problem/statistics/plot-maxst-vs-mtsf-violin-swarm.R
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| #! /opt/local/bin/Rscript | ||
| # | ||
| # plot-maxst-vs-mtsf-violin-swarm.R | ||
| # | ||
| # Created on: - | ||
| # Author: Franziska Wegner | ||
| # | ||
| # This script computes the swarm plot in "The Maximum Transmission Switching | ||
| # Flow Problem", 2018, ACM e-Energy, doi:10.1145/3208903.3208910. | ||
| # | ||
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| source("../Helper/plotting.R", chdir=T) | ||
| source("../Helper/colors.R", chdir=T) | ||
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| # Arguments | ||
| args <- commandArgs(trailingOnly = TRUE) | ||
| argument.path <- args[1] | ||
| argument.output <- args[2] | ||
| argument.standAlone <- args[3] | ||
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| argument.latex_path <- args[4] | ||
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| if(is.na(argument.path)){ | ||
| argument.path <- "/Users/fwegner/Documents/work/paper/MTSF-ACM-e-Energy/02-ACM/data/results/" | ||
| } | ||
| if(is.na(argument.output)){ | ||
| argument.output <- "/Users/fwegner/Documents/work/paper/MTSF-ACM-e-Energy/02-ACM/plots/plot-maxst-vs-mtsf-violin-swarm.tex" | ||
| } | ||
| if(is.na(argument.standAlone)){ | ||
| argument.standAlone <- FALSE | ||
| } | ||
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| if(!is.na(argument.latex_path)){ | ||
| options(latexcmd <- argument.latex_path) | ||
| }else{ | ||
| argument.latex_path <- "/opt/local/bin/pdflatex" | ||
| options(latexcmd <- "/opt/local/bin/pdflatex") | ||
| } | ||
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| # Extract data from file | ||
| data_dc_mtsf_gurobi <- read.csv( paste( argument.path, "dc_mtsf_gurobi.csv", sep = ""), header=TRUE, sep=",") | ||
| data_dc_mtsf_gurobi$path <- NULL; | ||
| data_dc_maxst_mf_gurobi <- read.csv( paste( argument.path, "dc_maxst_mf_gurobi.csv", sep = ""), header=TRUE, sep=",") | ||
| data_dc_maxst_mf_gurobi$path <- NULL; | ||
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| # Format data | ||
| data_dc_mtsf_gurobi$opt <- as.numeric( format( round( data_dc_mtsf_gurobi$opt, digits = 2), nsmall = 2) ) | ||
| names(data_dc_mtsf_gurobi) <- c("Name", "NumberOfVertices", "NumberOfEdges", "MtsfOptimumValue", "GenerationUpperBound", "MtsfNumberOfSwitchings") | ||
| data_dc_maxst_mf_gurobi$opt <- as.numeric( format( round( data_dc_maxst_mf_gurobi$opt, digits = 2), nsmall = 2) ) | ||
| names(data_dc_maxst_mf_gurobi) <- c("Name", "NumberOfVertices", "NumberOfEdges", "MaxstOptimumValue", "GenerationUpperBound", "MaxstNumberOfSwitchings") | ||
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| # Merge data | ||
| data <- NULL | ||
| data <- merge ( data_dc_mtsf_gurobi, data_dc_maxst_mf_gurobi, | ||
| by = c( "Name","NumberOfVertices", "NumberOfEdges","GenerationUpperBound" ), | ||
| type = "inner" ) | ||
| data <- subset ( data, data$MtsfOptimumValue > 0 ) | ||
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| # Normalize using MTSF optimum value | ||
| data$MaxstOptimumValue <- data$MaxstOptimumValue / data$MtsfOptimumValue | ||
| data$Season <- rep(0, nrow(data) ) | ||
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| # Plot as TIKZ | ||
| if ( argument.standAlone == TRUE ) { | ||
| tex_output_file <- paste(argument.output, "-StandAlone", "",sep = "") | ||
| tikzDevice::tikz( tex_output_file, | ||
| width = 6.1, | ||
| height = 3.75, | ||
| pointsize = 8, | ||
| standAlone = TRUE ) | ||
| } else { | ||
| tex_output_file <- paste(argument.output, "",sep = "") | ||
| tikzDevice::tikz( tex_output_file, | ||
| width = 6.1, | ||
| height = 3.75, | ||
| pointsize = 8, | ||
| standAlone = FALSE ) | ||
| } | ||
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| # create extra margin room on the right for an axis | ||
| # mar=c(unten, links, oben, rechts) | ||
| par(mar=c(4.8,5,3.5,5.3)+.1, mgp = c(4, 0.8, 0), xpd=TRUE) | ||
| par(las=1, cex=1.2) # make label text perpendicular to axis | ||
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| # Generate violin plot with jitter and other features | ||
| rectWorseHalfOpt <- data.frame(ymin=-Inf, ymax=0.5, xmin=-Inf, xmax=Inf) | ||
| rectBetterHalfOpt <- data.frame(ymin=0.5, ymax=Inf, xmin=-Inf, xmax=Inf) | ||
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| g <- ggplot( data, | ||
| aes( x = Season, | ||
| y = MaxstOptimumValue | ||
| ) | ||
| ) + geom_rect( data = rectWorseHalfOpt, | ||
| aes( xmin = xmin, | ||
| xmax = xmax, | ||
| ymin = ymin, | ||
| ymax = ymax | ||
| ), | ||
| color = KITyellow15, | ||
| fill = KITyellow15, | ||
| alpha = 0.3, | ||
| inherit.aes = FALSE | ||
| ) + geom_rect( data = rectBetterHalfOpt, | ||
| aes( xmin = xmin, | ||
| xmax = xmax, | ||
| ymin = ymin, | ||
| ymax = ymax | ||
| ), | ||
| color = KITyellow15, | ||
| fill = KITgreen15, | ||
| alpha = 0.2, | ||
| inherit.aes = FALSE | ||
| ) + geom_violin( alpha = 0.5, | ||
| color = KITseablue50, | ||
| fill = KITseablue15, | ||
| trim = FALSE | ||
| # ) + geom_jitter(alpha=0.5, | ||
| # aes(color=Season), | ||
| # color = KITred, | ||
| # position = position_jitter(width = 0.1) | ||
| ) + geom_dotplot( #aes(color=Season), | ||
| binaxis = 'y', | ||
| binwidth = 0.045, | ||
| stackdir = 'center', | ||
| dotsize = 0.5, | ||
| color = KITred30, | ||
| fill = KITred50, | ||
| alpha = 0.8 | ||
| ) + coord_flip( | ||
| ) + annotate("text", x = 0.5, | ||
| y = 0.225,#0.4 | ||
| label = "\\bf Worse than~$\\frac{ \\mathsf{OPT}_{\\mathsf{MTSF}} }{ 2 }$", parse = FALSE, color = KITorange | ||
| ) + annotate("text", x = 0.5, | ||
| y = 0.775, | ||
| label = "\\bf Better than~$\\frac{ \\mathsf{ OPT }_{ \\mathsf{MTSF} } }{ 2 }$", parse = FALSE, color = KITgreen | ||
| ) | ||
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| ticksHelper <- c(0,0.25,0.5,0.75,1) | ||
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| g + labs(y = "Normalized flow value~$F(\\mathcal{N}, f)$~by~$\\mathsf{ OPT }_{ \\mathsf{MTSF} }$ in MW", | ||
| x = "$\\mathsf{MaxST}$" | ||
| ) + stat_summary(fun.data = mean_sdl, | ||
| fun.args = list(mult = 0.4), | ||
| geom = "pointrange", | ||
| color = KITgreen30, | ||
| size = 0.5 | ||
| ) + stat_summary(fun.y = median, | ||
| geom = "point", | ||
| size = 2.9, | ||
| color = KITgreen30, | ||
| shape = 18 | ||
| ) + theme_gray(base_size = 14 | ||
| ) + theme(#axis.title.x = element_blank(), | ||
| axis.text.y = element_blank(), | ||
| axis.text.x = element_text(size=13), | ||
| axis.ticks.y = element_blank(), | ||
| axis.title.x = element_text(margin = margin(t = 13.5, r = 0, b = 0, l = 0)) | ||
| # text = element_text(size=8)#, | ||
| # axis.text.x = element_text(colour="grey20",size=20,angle=90,hjust=.5,vjust=.5,face="plain"), | ||
| # axis.text.y = element_text(colour="grey20",size=12,angle=0,hjust=1,vjust=0,face="plain"), | ||
| # axis.title.x = element_text(colour="grey20",size=12,angle=0,hjust=.5,vjust=0,face="plain"), | ||
| # axis.title.y = element_text(colour="grey20",size=12,angle=90,hjust=.5,vjust=.5,face="plain") | ||
| # axis.text.x = element_text(angle=90, hjust=1) | ||
| # axis.ticks.x = element_blank() | ||
| ) + scale_y_continuous(breaks=ticksHelper | ||
| ) | ||
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| #+ ylim(-0.06,1.06) | ||
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| print( paste("File written to: ", tex_output_file, sep = "") ) | ||
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| #par(font=1) | ||
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| dev.off() |