CODEWITHSUNDEEP
rggplot2
Shannon Cahalan
Shannon Cahalan

Reputation: 53

Rearranging trendline colors in ggplot

I created a plot that turned out mostly how I'd like it in ggplot but I need the lines to appear in a slightly different color arrangement.

enter image description here

Basically, I need all "mean" lines to appear in blue and all "odd" lines to appear in red. Pref 1 will appear in either the lighter or darker shade and vice versa. As you can see ggplot has not quite done that.

p2 <- ggplot(asd_pref_plot_groups, aes(x, pref_plot_groups$predicted, col = combined)) +
  geom_line(size=1.5) +
  scale_color_manual(values = c("blue","deepskyblue","red","pink")) +
  geom_ribbon(aes(ymin=conf.low,ymax=conf.high, fill=combined),alpha=.2,colour=NA) +
  scale_fill_manual(values = c("blue","deepskyblue","red","pink")) +
  geom_point(data=summStats,aes(trial,mean,col = combined),size=2) +
  scale_color_manual(values = c("blue","deepskyblue","red","pink")) +
  theme_bw() +
  xlab('Trial') +
  ylab('Prediction Error') +
  ggtitle('ASD learning about TD vs. ASD \n learning about ASD') +
  theme(text=element_text(size=20),
        plot.title = element_text(hjust = 0.5),
        panel.border = element_blank())

Above is my code. I thought I could shift around scale_color_manual as needed but it doesn't seem to work? Is there an easy fix or does this extend to my data frames. Thank you

Upvotes: 0

Views: 93

Answers (1)

Allan Cameron
Allan Cameron

Reputation: 174586

Your question didn't include any example data, so I have had to try to recreate your data set (see footnote)

To ensure we are on the right track, I will use exactly your plotting code to get a very similar plot:

ggplot(asd_pref_plot_groups, aes(x, pref_plot_groups$predicted, col = combined)) +
  geom_line(size=1.5) +
  scale_color_manual(values = c("blue","deepskyblue","red","pink")) +
  geom_ribbon(aes(ymin = conf.low, ymax = conf.high, fill = combined), 
              alpha = 0.2, colour = NA) +
  scale_fill_manual(values = c("blue","deepskyblue","red","pink")) +
  geom_point(data = summStats, aes(trial, mean,col = combined), size = 2) +
  scale_color_manual(values = c("blue","deepskyblue","red","pink")) +
  theme_bw() +
  xlab('Trial') +
  ylab('Prediction Error') +
  ggtitle('ASD learning about TD vs. ASD \n learning about ASD') +
  theme(text=element_text(size=20),
        plot.title = element_text(hjust = 0.5),
        panel.border = element_blank())

enter image description here

All we need to do here is to remove one of your redundant scale_color_manual calls (you currently have 2), and change the ordering of the colors in both the fill and color scales:

ggplot(asd_pref_plot_groups, aes(x, pref_plot_groups$predicted, 
                                 col = combined, fill = combined)) +
  geom_line(size = 1.5) +
  geom_ribbon(aes(ymin = conf.low, ymax = conf.high), 
              alpha = 0.2, colour = NA) +
  scale_fill_manual(values = c("blue","red", "deepskyblue", "pink")) +
  scale_color_manual(values = c("blue","red","deepskyblue", "pink")) +
  geom_point(data = summStats, aes(trial, mean,col = combined), size = 2) +
  theme_bw() +
  xlab('Trial') +
  ylab('Prediction Error') +
  ggtitle('ASD learning about TD vs. ASD \n learning about ASD') +
  theme(text=element_text(size=20),
        plot.title = element_text(hjust = 0.5),
        panel.border = element_blank())

enter image description here

Footnote: Reproducible data to approximate data in question

set.seed(1)

asd_pref_plot_groups <- data.frame(x = rep(c(1, 60), 4),
                                   combined = rep(c('pref1_mean', 'pref1_odd',
                                                    'pref2_mean', 'pref2_odd'),
                                                  each = 2),
                                   predicted = c(1.3, 1.3, 1.45, 1.3,
                                                 2, 1.75, 2.05, 1.77),
                                   conf.high = c(1.35, 1.35, 1.5, 1.35,
                                                 2.05, 1.8, 2.1, 1.82),
                                   conf.low = c(1.25, 1.25, 1.4, 1.25,
                                                1.95, 1.7, 2, 1.72))

pref_plot_groups <- asd_pref_plot_groups

summStats <- data.frame(trial = rep(1:60, 4),
                        combined = rep(c('pref1_mean', 'pref1_odd',
                                         'pref2_mean', 'pref2_odd'),
                                       each = 60),
                        mean = c(rnorm(60, seq(1.3, 1.3, length = 60), 0.05),
                                 rnorm(60, seq(1.45, 1.3, length = 60), 0.05),
                                 rnorm(60, seq(2, 1.75, length = 60), 0.05),
                                 rnorm(60, seq(2.05, 1.77, length = 60), 0.05)))

Upvotes: 1

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