geom_smooth(): One line, different colors - r

Question

I am currently trying to customize my plot with the goal to have a plot like this:
If I try to specify the color or linetype in either aes() or mapping = aes(), I get two different smooths. One for each class. This makes sense, because the smoothing will be applied once for each type.
If I use group = 1 in the aestetics, I will get one line, also one color/linetype.
But I can not find a solution to have one smooth line with different colors/linetypes for each class.
My code:
ggplot(df2, aes(x = dateTime, y = capacity)) +
#geom_line(size = 0) +
stat_smooth(geom = "area", method = "loess", show.legend = F,
mapping = aes(x = dateTime, y = capacity, fill = type, color = type, linetype = type)) +
scale_color_manual(values = c(col_fill, col_fill)) +
scale_fill_manual(values = c(col_fill, col_fill2))
The result for my data:
Reproduceable code:
File: enter link description here (I can not make this file shorter and copy it hear, else I get errors with smoothing for too few data points)
df2 <- read.csv("tmp.csv")
df2$dateTime <- as.POSIXct(df2$dateTime, format = "%Y-%m-%d %H:%M:%OS")
col_lines <- "#8DA8C5"
col_fill <- "#033F77"
col_fill2 <- "#E5E9F2"
ggplot(df2, aes(x = dateTime, y = capacity)) +
stat_smooth(geom = "area", method = "loess", show.legend = F,
mapping = aes(x = dateTime, y = capacity, fill = type, color = type, linetype = type)) +
scale_color_manual(values = c(col_fill, col_fill)) +
scale_fill_manual(values = c(col_fill, col_fill2))

Answer 1

I would suggest to model the data outside the plotting function and then plot it with ggplot. I used the pipes (%>%) and mutate from the tidyversefor convenient reasons, but you don't have to. Also, I prefer to have a line and a fill separated to avoid the dashed line on the right side of your plot.
df2$index <- as.numeric(df2$dateTime) #create an index for the loess model
model <- loess(capacity ~ index, data = df2) #model the capacity
plot <- df2 %>% mutate(capacity_predicted = predict(model)) %>% # use the predicted data for the capacity
ggplot(aes(x = dateTime, y = capacity_predicted)) +
geom_ribbon(aes(ymax = capacity_predicted, ymin = 0, fill = type, group = type)) +
geom_line(aes( color = type, linetype = type)) +
scale_color_manual(values = c(col_fill, col_fill)) +
scale_fill_manual(values = c(col_fill, col_fill2)) +
theme_minimal() +
theme(legend.position = "none")
plot
Please tell me if it works (I don't have the original data to test it), and if you would like a version without tidyverse functions.
EDIT:
Not very clean, but a smoother curve can be obtained with this code:
df3 <- data.frame(index = seq(min(df2$index), max(df2$index), length.out = 300),
type = "historic", stringsAsFactors = F)
modelling_date_index <- 1512562500
df3$type[df3$index <= modelling_date_index] = "predict"
plot <- df3 %>% mutate(capacity_predicted = predict(model, newdata = index),
dateTime = as.POSIXct(index, origin = '1970-01-01')) %>%
# arrange(dateTime) %>%
ggplot(aes(x = dateTime, y = capacity_predicted)) +
geom_ribbon(aes(ymax = capacity_predicted, ymin = 0, fill = type, group =
type)) +
geom_line(aes( color = type, linetype = type)) +
scale_color_manual(values = c(col_fill, col_fill)) +
scale_fill_manual(values = c(col_fill, col_fill2)) +
theme_minimal()+
theme(legend.position = "none")
plot