exdt1 <- gen_data(1, c(0, 0, 0), rho_d = 0)
p1 <- ggplot(exdt1, aes(y = y, x = c,
group = idtx,
color = t,
linetype = as.factor(x))) +
scale_y_continuous('gLMS') +
scale_x_continuous('Concentration', breaks = c(100, 200, 400)) +
scale_color_discrete('Taste', guide = FALSE) +
scale_linetype_discrete('Time', labels = c('Before', 'After')) +
geom_point() +
geom_line() +
facet_grid(~ t) +
ggtitle('Randomly generated psychophysical curves for a single subject\n when no fasting effect exists for any taste') +
theme(plot.title = element_text(size = 10))
exdt2 <- gen_data(1, c(1, 1, 0), rho_d = 0)
p2 <- ggplot(exdt2, aes(y = y, x = c,
group = idtx,
color = t,
linetype = as.factor(x))) +
scale_y_continuous('gLMS') +
scale_x_continuous('Concentration', breaks = c(100, 200, 400)) +
scale_color_discrete('Taste', guide = FALSE) +
scale_linetype_discrete('', labels = c('Baseline', 'After 5 days fasting')) +
geom_point() +
geom_line() +
facet_grid(~ t) +
ggtitle('Randomly generated psychophysical curves for a single subject\n when fasting effect increases average gLMS for all tastes a and b') +
theme(plot.title = element_text(size = 10),
legend.position = c(.2, .8),
legend.background = element_blank())
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