From 06fdba8e3ac40cc2ecee5e574e0d4925eb801138 Mon Sep 17 00:00:00 2001 From: jasondsc Date: Wed, 11 Aug 2021 13:56:47 -0400 Subject: [PATCH] Add files via upload --- 6_Plotting_results_with_ggplot.R | 236 +++++++++++++++++++++++++++++++ 1 file changed, 236 insertions(+) diff --git a/6_Plotting_results_with_ggplot.R b/6_Plotting_results_with_ggplot.R index 2658655..60d0bde 100644 --- a/6_Plotting_results_with_ggplot.R +++ b/6_Plotting_results_with_ggplot.R @@ -89,3 +89,239 @@ ggplot(data=df_1, aes(x=feat, y=value, fill=feat)) + geom_bar(stat = "identity", # Second Component ggplot(data=df_2, aes(x=feat, y=value, fill=feat)) + geom_bar(stat = "identity", width = 1) +theme_minimal() + theme(text = element_text(size=40), legend.title=element_blank(), legend.position = c(-1.7, -1.2)) + labs(y="Design Salience", x="",title="") + coord_flip() + geom_errorbar(aes(ymin=lower, ymax=upper), width=.2) + scale_fill_manual(values=cbbPalette) + +############################### scatter plot of all fingerprinting ####################################### +rm(df, df2, data_plot) +df=read.csv("Desktop/OMEGA_Fingerprinting_data_two_session_for_plot.csv", header = TRUE) +df$ACC=as.numeric(df$ACC)*100 +df$band= factor(df$band,levels = c("Fullband", "Delta", "Theta", "Alpha", "Beta", "Gamma", "High Gamma")) +df$band=plyr::mapvalues(df$band, unique(df$band), c("Delta", "Theta", "Alpha", "Beta", "Gamma", "High\nGamma", "Broadband")) +df$dataset=plyr::mapvalues(df$dataset, unique(df$dataset), c(" Dataset 1 -> 2", " Dataset 2 -> 1")) + +data_plot=df[,1:4] +df=read.csv("Desktop/OMEGA_Fingerprint_data_for_plot.csv", header = TRUE) +df$ACC=as.numeric(df$ACC)*100 +df$band= factor(df$band,levels = c("Fullband", "Delta", "Theta", "Alpha", "Beta", "Gamma", "High Gamma")) +df$band=plyr::mapvalues(df$band, unique(df$band), c("Delta", "Theta", "Alpha", "Beta", "Gamma", "High\nGamma", "Broadband")) +df$dataset=plyr::mapvalues(df$dataset, unique(df$dataset), c(" Dataset 1 -> 2", " Dataset 2 -> 1")) + +data_plot=rbind(data_plot,df[,1:4]) + +df=read.csv("Desktop/OMEGA_Fingerprinting_data_short_for_plot.csv", header = TRUE, stringsAsFactors = FALSE) +df$ACC=as.numeric(df$ACC)*100 +df$band= factor(df$band,levels = c("Fullband", "Delta", "Theta", "Alpha", "Beta", "Gamma", "High Gamma")) +df$band=plyr::mapvalues(df$band, unique(df$band), c("Delta", "Theta", "Alpha", "Beta", "Gamma", "High\nGamma", "Broadband")) +df$dataset[df$dataset=="d" & df$Dataset_parent=="D1D2"] = " Dataset 1 -> 2" +df$dataset[df$dataset=="t" & df$Dataset_parent=="D1D2"] = " Dataset 2 -> 1" +df$dataset[df$dataset=="d" & df$Dataset_parent=="D1D3"] = " Dataset 1 -> 3" +df$dataset[df$dataset=="t" & df$Dataset_parent=="D1D3"] = " Dataset 3 -> 1" +df$dataset[df$dataset=="d" & df$Dataset_parent=="D2D3"] = " Dataset 2 -> 3" +df$dataset[df$dataset=="t" & df$Dataset_parent=="D2D3"] = " Dataset 3 -> 2" + +data_plot=rbind(data_plot,df[,2:5]) + +df=read.csv("Desktop/OMEGA_short_review_complete_full.csv", header = TRUE, stringsAsFactors = FALSE) +df2=read.csv("Desktop/OMEGA_fingerprinting_reviewer_short_2session.csv", header = TRUE, stringsAsFactors = FALSE) +df=rbind(df,df2[,1:5]) +df$ACC=as.numeric(df$ACC)*100 +df$band= factor(df$band,levels = c("Fullband", "Delta", "Theta", "Alpha", "Beta", "Gamma", "High Gamma")) +df$band=plyr::mapvalues(df$band, unique(df$band), c("Delta", "Theta", "Alpha", "Beta", "Gamma", "High\nGamma", "Broadband")) +df$dataset[df$dataset=="d" & df$Dataset_parent=="D1D2"] = " identify dataset 2 from 1" +df$dataset[df$dataset=="t" & df$Dataset_parent=="D1D2"] = " identify dataset 1 from 2" +df$dataset[df$dataset=="d" & df$Dataset_parent=="D1D3"] = " identify dataset 2 from 1" +df$dataset[df$dataset=="t" & df$Dataset_parent=="D1D3"] = " identify dataset 1 from 2" +df$dataset[df$dataset=="d" & df$Dataset_parent=="D2D3"] = " identify dataset 2 from 1" +df$dataset[df$dataset=="t" & df$Dataset_parent=="D2D3"] = " identify dataset 1 from 2" + +data_plot=rbind(data_plot,df[,2:5]) +data_plot$dataset[data_plot$band=='High Gamma']="High Gamma" + + +cbbPalette <- c( "#6683f8","#f483a1", "#F0E442", "#0072B2", "#D55E00", "#CC79A7", "#f3b2bf") +pd <- position_dodge(-0.6) +jitter <- position_jitter(width = 0.01, height = 0) +ggplot(data=data_plot, aes(x=band, y=ACC, colour=Method, width=.5)) + geom_jitter( position= position_jitterdodge(jitter.width=0.1,dodge.width=-0.6), size=4 )+ stat_summary(fun.data = mean_se, geom = "errorbar", size=2.5, width=0.5, position = pd) + + stat_summary(fun.data = "mean_cl_boot", geom = "point", size= 10, position = pd) +theme_minimal() + scale_fill_grey() + labs(y="Accuracy (%)", x="",title="") + theme(text = element_text(size=40), legend.title=element_blank()) + scale_color_manual(values=cbbPalette) + +dodge <- position_dodge(width = 0.6) +ggplot(data=data_plot, aes(x=band, y=ACC, colour=Method, width=.5)) + geom_jitter(position= position_jitterdodge(jitter.width=0.3, dodge.width=0.7), size=4, alpha=0.5 ) + stat_summary(fun.data = mean_se, geom = "errorbar", size=2.5, width=0, position = dodge) + + stat_summary(fun.data = "mean_cl_boot", geom = "point", size= 10, position = dodge) +theme_minimal() + labs(y="Accuracy (%)", x="",title="") + theme(text = element_text(size=40), legend.title=element_blank()) + scale_color_manual(values=cbbPalette) + + +data_plot %>% group_by(band) %>% summarize(ACC1=mean(ACC)) +data_plot %>% group_by(band, Method) %>% summarize(ACC1=mean(ACC)) + + + +######################################################## +# plotting brains with ggseg +######################################################## +library(ggseg) +library(dplyr) +library(ggplot2) +library(RColorBrewer) +someData <- tibble( + region = rep(c("transverse temporal", "insula", + "precentral","superior parietal"), 2), + p = sample(seq(0.5,1,.01), 8), + groups = c(rep("g1", 4), rep("g2", 4)) +) + + +df=read.csv('~/Desktop/McGill/python_codes/PSD_ICC_orig_atlas.csv', header = FALSE, stringsAsFactors = FALSE) +colnames(df)[1]='region' +df$hemi[] ='' +df$hemi[seq(2,68,2)] ='right' +df$hemi[seq(1,67,2)] ='left' +#df$region[seq(1,68,2)]=paste('lh_', df$region[seq(1,68,2)], sep='') +#df$region[seq(2,68,2)]=paste('rh_', df$region[seq(2,68,2)], sep='') + +# delta +someData= tibble(df$region, rowMeans(df[,2:9]), df$hemi) +colnames(someData)[2]='p' +colnames(someData)[1]='region' +colnames(someData)[3]='hemi' +someData$p[someData$p<0.4]=0.4 +someData$p[someData$p>0.8]=0.8 +ggplot(someData) + + geom_brain(atlas = dk, + position = position_brain(hemi ~ side), + aes(fill = p)) + + scale_fill_distiller(palette = "RdBu" + , limits = c(0.4, 0.8))+ + #viridis::scale_fill_viridis(option = 'magma',limits=c(0.4, 0.8 ))+ + #scale_fill_gradient2(low="white", mid="#EC352F", high="#6C1917", + # midpoint=0.6, + # limits=c(0.4, 0.8 ))+ + theme_void() + + labs(title = "delta") +#> merging atlas and data by 'region' +ggsave('~/Desktop/figure_DRAFTS/new_topo/ICC_Delta_m', device = "pdf") + + + +# theta +someData= tibble(df$region, rowMeans(df[,10:17]), df$hemi) +colnames(someData)[2]='p' +colnames(someData)[1]='region' +colnames(someData)[3]='hemi' +someData$p[someData$p<0.4]=0.4 +someData$p[someData$p>0.8]=0.8 +ggplot(someData) + + geom_brain(atlas = dk, + position = position_brain(hemi ~ side), + aes(fill = p)) + + #viridis::scale_fill_viridis(option = 'magma',limits=c(0.4, 0.8 ))+ + scale_fill_distiller(palette = "RdBu" + , limits = c(0.4, 0.8))+ + # scale_fill_gradient2(low="white", mid="#EC352F", high="#6C1917", + # midpoint=0.6, + # limits=c(0.4, 0.8 ))+ + theme_void() + + labs(title = "theta") +#> merging atlas and data by 'region' +ggsave('~/Desktop/figure_DRAFTS/new_topo/ICC_Theta_m', device = "pdf") + + + +# alpha +someData= tibble(df$region, rowMeans(df[,18:27]),df$hemi) +colnames(someData)[2]='p' +colnames(someData)[1]='region' +colnames(someData)[3]='hemi' +someData$p[someData$p<0.4]=0.4 +someData$p[someData$p>0.8]=0.8 +ggplot(someData) + + geom_brain(atlas = dk, + position = position_brain(hemi ~ side), + aes(fill = p)) + + #viridis::scale_fill_viridis(option = 'magma',limits=c(0.4, 0.8 ))+ + scale_fill_distiller(palette = "RdBu" + , limits = c(0.4, 0.8))+ + #scale_fill_gradient(brewer.pal(n = 2, name = "Reds")) + + # scale_fill_gradient2(low="white", mid="#EC352F", high="#6C1917", + # midpoint=0.6, + # limits=c(0.4, 0.8 ))+ + theme_void() + + labs(title = "Alpha") +#> merging atlas and data by 'region' +ggsave('~/Desktop/figure_DRAFTS/new_topo/ICC_Alpha_m', device = "pdf") + + +# beta +someData= tibble(df$region, rowMeans(df[,28:61]),df$hemi) +colnames(someData)[2]='p' +colnames(someData)[1]='region' +colnames(someData)[3]='hemi' +someData$p[someData$p<0.4]=0.4 +someData$p[someData$p>0.8]=0.8 +ggplot(someData) + + geom_brain(atlas = dk, + position = position_brain(hemi ~ side), + aes(fill = p)) + + #viridis::scale_fill_viridis(option = 'magma',limits=c(0.4, 0.8 ))+ + scale_fill_distiller(palette = "RdBu" + , limits = c(0.4, 0.8))+ + #scale_fill_gradient(brewer.pal(n = 2, name = "Reds")) + + # scale_fill_gradient2(low="white", mid="#EC352F", high="#6C1917", + # midpoint=0.6, + # limits=c(0.4, 0.8 ))+ + theme_void() + + labs(title = "Beta") +#> merging atlas and data by 'region' +ggsave('~/Desktop/figure_DRAFTS/new_topo/ICC_Beta_rb', device = "pdf") + + + +# gamma +someData= tibble(df$region, rowMeans(df[,62:101]),df$hemi) +colnames(someData)[2]='p' +colnames(someData)[1]='region' +colnames(someData)[3]='hemi' +someData$p[someData$p<0.4]=0.4 +someData$p[someData$p>0.8]=0.8 +ggplot(someData) + + geom_brain(atlas = dk, + position = position_brain(hemi ~ side), + aes(fill = p)) + + scale_fill_distiller(palette = "RdBu" + , limits = c(0.4, 0.8))+ + #viridis::scale_fill_viridis(option = 'magma',limits=c(0.4, 0.8 ))+ + #scale_fill_gradient(brewer.pal(n = 2, name = "Reds")) + + # scale_fill_gradient2(low="white", mid="#EC352F", high="#6C1917", + # midpoint=0.6, + # limits=c(0.4, 0.8 ))+ + theme_void() + + labs(title = "Gamma") +#> merging atlas and data by 'region' +ggsave('~/Desktop/figure_DRAFTS/new_topo/ICC_Gamma_m', device = "pdf") + + + +# Hgamma +someData= tibble(df$region, rowMeans(df[,102:302]),df$hemi) +colnames(someData)[2]='p' +colnames(someData)[1]='region' +colnames(someData)[3]='hemi' +someData$p[someData$p<0.4]=0.4 +someData$p[someData$p>0.8]=0.8 +ggplot(someData) + + geom_brain(atlas = dk, + position = position_brain(hemi ~ side), + aes(fill = p)) + + scale_fill_distiller(palette = "RdBu" + , limits = c(0.4, 0.8))+ + #viridis::scale_fill_viridis(option = 'magma',limits=c(0.4, 0.8 ))+ + #scale_fill_gradient(brewer.pal(n = 2, name = "Reds")) + + # scale_fill_gradient2(low="white", mid="#EC352F", high="#6C1917", + # midpoint=0.6, + # limits=c(0.4, 0.8 ))+ + theme_void() + + labs(title = "High Gamma") +#> merging atlas and data by 'region' +ggsave('~/Desktop/figure_DRAFTS/new_topo/ICC_HighGamma_rb', device = "pdf") + + + + +