问题：Plot alpha 值随 Y 轴缩放/ggplot 方面的观察数量

Question

I haven't found anyone else with this issue. Here is my plot: facet plot

Why are there different alpha values for each facet?

As you can see, the alpha value of the geom_rect() elements seems to scale with the y-axis or number of observations, maybe because I have set these to "free_y" in the facet_wrap() argument. How can I prevent this from happening?

Here is my code:

plot_data %>%
ggplot(aes(Date, n)) +
geom_rect(data= plot_data, inherit.aes = FALSE,
            aes(xmin=current_date - lubridate::weeks(1), xmax=current_date, ymin=-Inf, ymax=+Inf), 
            fill='pink', alpha=0.2) +
geom_col() + 
facet_wrap(~Type, scales = "free_y") +
xlab("Date") +
ylab("Count") +
theme_bw() +
scale_y_continuous(breaks = integer_breaks()) +
scale_alpha_manual(values = 0.2) +
theme(axis.text.x=element_text(angle=90, hjust=1))

Cheers!

Answer 1

TL;DR - It seems this is probably due to overplotting. You have 5 rect geoms drawn in the facet, but probably more than 5 observations in your dataset. The fix is to summarize your data and associate geom_rect() to plot with the summarized dataset.

Since OP did not provide an example dataset, we can only guess at the reason, but likely what's happening here is due to overplotting. geom_rect() behaves like all other geoms, which is to say that ggplot2 will draw or add to any geom layer with every observation (row) in the original dataset. If the geoms are drawn across facets and overlap in position , then you'll get overplotting. You can notice that this is happening based on:

• Different alpha appearing on each facet, even though it should be constant based on the code, and
• The fact that in order to get the rectangles to look like "light red", OP had to use pink color and an alpha value of 0.2... which shouldn't look like that if there was only one rect drawn.

Representative Example of the Issue

Here's an example that showcases the problem and how you can fix it using mtcars :

library(ggplot2)
df <- mtcars
p <- ggplot(df, aes(disp, mpg)) + geom_point() +
  facet_wrap(~cyl) +
  theme_bw()
p + geom_rect(
  aes(xmin=200, xmax=300, ymin=-Inf, ymax=Inf),
  alpha=0.01, fill='red')

Like OP's case, we expect all rectangles to be the same alpha value, but they are not. Also, note the alpha value is ridiculously low ( 0.01 ) for the color you see there. What's going on should be more obvious if we check number of observations in mtcars that falls within each facet:

> library(dplyr)
> mtcars %>% group_by(cyl) %>% tally()
# A tibble: 3 x 2
    cyl     n
  <dbl> <int>
1     4    11
2     6     7
3     8    14

There's a lower number of observations where cyl==6 and cyl==4 has lower observations than cyl==8 . This corresponds precisely to the alpha values we see for the geoms in the plot, so this is what's going on. For each observation, a rectangle is drawn over the same position and so there are 7 rectangles drawn in the middle facet, 14 on the right facet, and 11 on the left facet.

Fixing the Issue: Summarize the Data

To fix the issue, you should summarize your data and use the summarized dataset for plotting the rectangles.

summary_df <- df %>%
  group_by(cyl) %>%
  summarize(mean_d = mean(disp))

p + geom_rect(
  data = summary_df,
  aes(x=1, y=1, xmin=mean_d-50, xmax=mean_d+50, ymin=-Inf, ymax=Inf),
  alpha=0.2, fill='red')

Since summary_df has only 3 observations (one for each group of cyl ), the rectangles are drawn correctly and now alpha=0.2 with fill="red" gives the expected result. One thing to note here is that we still have to define x and y in the aes() . I set them both to 1 because although geom_rect() doesn't use them, ggplot2 still expects to find them in the dataset summary_df because we stated that they are assigned to that plot globally up in ggplot(df, aes(x=..., y=...)) . The fix is to either move the aes() declaration into geom_point() or just assign both to be constant values in geom_rect() .