R: Object not found with ggplot

Question

I am trying to add legend names to a ggplot but I always get an "object not found error".

  mycol = pft$colour
  myname = pft$name
  #mycol "#E5E503" "#9FFF8C" "#44CC29" "#137300" "#B2B224" "#0066CC" "#99CCFF" "#00407F" "#FF999B" "#E5171A" "#990003" "#A38FCC" "#7F40FF" "#A1E5CF" "#6B998A" "#F2F291" "#BF60A7" "#404040"
  #myname "C4 grass" "Early tropical" "Mid tropical" "Late tropical" "Temperate C3 Grass" "North Pine" "South Pine" "Late conifer" "Early hardwood" "Mid hardwood" "Late hardwood" "C3 crop" "C3 pasture" "C4 crop" "C4 pasture" "C3 grass" "Lianas" "Total"             
  test_data_long = melt(szpft[[vnam]][,ndbh+1,],
                        varnames = c("year","mpft"), na.rm = T)
  ggplot(data=test_data_long,aes(x=year,y=value, colour = mycol[mpft])) +
    geom_line(aes(group = mpft)) +
    scale_colour_identity(guide = "legend") +
    scale_fill_continuous(name="PFT", labels = myname[mpft])

test_data_long is a data.frame that looks like this.

    year mpft     value
20  2004    2  2.294562
21  2005    2  2.415901
22  2006    2  2.532214
23  2007    2  2.649968
24  2008    2  2.760934
25  2009    2  2.849097
26  2010    2  2.967846
27  2011    2  3.102287
28  2012    2  3.244338
29  2013    2  3.386014
30  2014    2  3.528662
31  2015    2  3.675095
32  2016    2  3.828054
33  2017    2  3.976928
34  2018    2  4.133859
35  2019    2  4.305039
36  2020    2  4.488999
37  2021    2  4.673952
38  2022    2  4.861845
39  2004    3  4.518262
40  2005    3  4.668800
41  2006    3  4.821924
42  2007    3  4.973597

I would like to use the mpft column as an index to define grouping, color, title ecc.

mycol and myname are vectors that contain colours (hex) and names corresponding to the different mpft lines to plot. The exact error I get is

Error in check_breaks_labels(breaks, labels) : object 'mpft' not found

Removing the last line of the script produce the next figure, so the problem lies in the last line. Why is mpft recognized before and not after?

EDIT

To be clearer,

  mycol = pft$colour
  myname = pft$name
  test_data_long = melt(szpft[[vnam]][,ndbh+1,],
                        varnames = c("year","mpft"), na.rm = T)
  ggplot(data=test_data_long,aes(x=year,y=value, colour = mycol[mpft])) +
    geom_line(aes(group = mpft)) +
    scale_colour_identity(guide = "legend") 

produces the graph in figure and gives no error.

EDIT

I'll provide a simplified, reproducible example of what I want to achieve here.

mycol = c("#A38FCC","#7F40FF")
mynam = c("random_line1", "random_line2")
set.seed(123)
df=data.frame(month = month.abb, 
          mpft  = c(rep(1,6),rep(2,6)), 
          ran = runif(12,0.,10.))

That produces a dataframe with month, mpft, and ran value. I want the ggplot to have month on the x-axis and ran on the y-axis. Furthermore I want the points to be plotted with mycol[1] colour ("#A38FCC" color) and the legend to display mynam[1] as title (random_line1 as title) if mpft = 1.

Answer 1

This is similar to the other answer but without needless dplyr mumbo-jumbo and pointing out some important details. The point is that if you want manual colors, you should use a manual color scale.

mycol = c("#A38FCC","#7F40FF")
mynam = c("random_line1", "random_line2")
set.seed(123)
df=data.frame(
              #month needs to be an ordered factor to get correct order in the plot
              #an unordered factor would be ordered alphabetically by ggplot2
              month = ordered(month.abb, levels = month.abb), 
              mpft  = c(rep(1,6),rep(2,6)), 
              ran = runif(12,0.,10.))

library(ggplot2)

ggplot(df, aes(x=month,y=ran, 
               colour = factor(mpft) #you want a discrete color scale
               )) +
  geom_line(aes(group = mpft), size = 1) +
  scale_colour_manual(name = "mynam",
                      #always pass named character vectors here to ensure correct mapping
                      values = setNames(mycol, unique(df$mpft)), 
                      labels = setNames(mynam, unique(df$mpft))) 

Answer 2

EDIT: Using the reproducible example given in an edit to the question, the following code is provided.

library(dplyr)
df %>%  ggplot(.,aes(x=month,y=ran, colour= as.factor(mpft))) +
    geom_line(aes(group = mpft)) +
  scale_color_manual(guide = guide_legend(title = "Legend"),
                     values = mycol,
                     labels = mynam)

This code will only give the right colours if all the lines are in the figure, if they aren't then the colours will change to prevent this use the following code.

  #This example uses three types, of which we only want 2
mycol = c("#A38FCC","#8f9e00","#7F40FF")
myname = c("random_line1","random_line2","random_line3")
set.seed(123)
df=data.frame(month = rep(month.abb,3), 
              mpft  = c(rep(1,12),rep(2,12),rep(3,12)), 
              ran = runif(36,0.,10.))

#this creates a dataframe that maps mpft to it's name and hex code
details <- data.frame(mpft = 1:length(mycol), 
                      mycol=(mycol), 
                      myname= myname, 
                      stringsAsFactors = FALSE)

#merge the two data frames
df2 <- df %>% left_join(., details, by="mpft") 

#We experiment to see if the colour scheme is maintained by removing one of the types
df3 <- df2 %>% filter(mpft !=2)

#Arrange the newly formed dataframe in order of mpft, although it makes no difference in this example it is crucial if the observatiions of mpft are not in numerical order.
df3 <- df3  %>% arrange(mpft)

 #Colours wrong!
 df2%>%  ggplot(.,aes(x=month,y=ran, colour= myname)) +
    geom_line(aes(group = mpft)) + 
  scale_color_manual(guide = guide_legend(title = "Legend"),
                     values = unique(df2$mycol) )
#Colours Correct!
df3%>%  ggplot(.,aes(x=month,y=ran, colour= myname)) +
    geom_line(aes(group = mpft)) + 
  scale_color_manual(guide = guide_legend(title = "Legend"),
                     values = unique(df3$mycol) )

The above code chunk will maintain your colour scheme even if for some reason not all types are in the plot