##@knitr trialplot
library(dplyr)
if(!exists("from_cache")){
from_cache = TRUE
}
plot_trial <- function(df_){
plot(
y,
xlim = c(0, max_end),
ylim = c(-0.5, 0.5),
lwd = 0.2,
lty = 3,
col = "gray40",
type = 'l',
xlab = '',
ylab = '',
yaxt = 'n',
xaxt = 'n'
)
for(k in (1:dim(df_)[1])){
rcol <- keycols[df_$col_key[k]]
if(df_$col_key[k]!=4){
count <<- count + 1
rect((
df_$stim_start[k]-240),
-0.5,
df_$stim_start[k],
0.5,
col = rcol,
border = "transparent")
text(df_$stim_start[k]-120, 0, paste0(count),
cex = 1.3,
col = "gray90"
)
}
abline(v = (df_$stim_start[k]+1), col = "chartreuse3", lwd = 3)
}
}
count = 0
metadf <- readRDS(cache_file("windows2", "meta"))
# Fix errror:
metadf$col_key[13] <- 4
trial_keys <- unique(metadf$key)
max_end <- max(metadf$stim_end)
x <- (0:max_end)
y <- rep(0, length(x))
keycols <- eegpalette()
# pdf(file.path(getwd(), paste0("figures/", prefix, "-param-plots-notrandom.pdf")),
# width = 9, height = 4)
par(mfrow = c(8,2), mar = c(1, 0.5, 1, 0.5), cex.axis = 1.4, cex.lab = 1.4)
for(k in 1:length(trial_keys)){
df_ <- metadf %>% dplyr::filter(key == trial_keys[k])
plot_trial(df_)
}
plot(1, type = 'n', axes = "FALSE")
legend(x = "center", inset = 0,
c("No response", "1st response ", "2nd response"),
col = keycols, pch = 15, cex = 1.3, horiz = TRUE)
plot(1, type = 'n', axes = "FALSE")
# dev.off()
## @knitr save-trial-plot
if(!from_cache){
pdf(file.path(getwd(), paste0("figures/", prefix, "-param-plots-notrandom.pdf")),
width = 9, height = 4)
par(mfrow = c(8,2), mar = c(1, 0.5, 1, 0.5), cex.axis = 1.4, cex.lab = 1.4)
for(k in 1:length(trial_keys)){
df_ <- metadf %>% dplyr::filter(key == trial_keys[k])
plot_trial(df_)
}
plot(1, type = 'n', axes = "FALSE")
legend(x = "center", inset = 0,
c("No response", "1st response ", "2nd response"),
col = keycols, pch = 15, cex = 1.3, horiz = TRUE)
plot(1, type = 'n', axes = "FALSE")
dev.off()
}
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