If Else Condition in Ggplot to Add an Extra Layer

if else condition in ggplot to add an extra layer

What you are seeing is a syntax error. The most robust way I can think of is:

tmp.data<-c(1,2,3) 
if(tmp.data[1]!="no value") {
   p = p + geom_point()
}
p + geom_line()

So you compose the object p in a sequence, only adding geom_point() when the if statements yields TRUE.

Add layers conditionally to a gglplot depending on the value of a function variable

Try appending layers to the ggplot object rather than having one big expression. This way you can add some logic about what layers to add. Note that I couldn't really test this without tsne.meta.

tsnePlotSubcluster <- function(feature = "subcluster", # can be area, age, subcluster
                               subclust = "cluster_1",
                               size.grey = 0.25, 
                               size.color = 0.3) {

  # params <- plot.params[[celltype]]
  # cluster.colors <- color.values[[celltype]]$i

  p <- ggplot(tsne.meta) + 

    # Plot cells in all other subclusters in grey.
    geom_point(data = filter(tsne.meta, ! subcluster.merge == subclust),
               aes(tSNE_1, tSNE_2, alpha = nGene), 
               colour = "grey90", size = size.grey)

  # a) Highlight subcluster:
  # Plot cells from selected subcluster in color.
  if(feature == "subclust") {
    p <- p + geom_point(data = filter(tsne.meta, subcluster.merge == subclust), 
                        aes(tSNE_1, tSNE_2, color = nGene, alpha = nGene),
                        size = size.color) + 
      theme(legend.position = 'none') +
      scale_color_viridis_c(option = "plasma", begin = 0.1, end = 0.6)
  }
  #  b) Color subcluster cells by age:
  else if(feature == "age") {
    p <- p + geom_point(data = filter(tsne.meta, subcluster.merge == subclust), 
                        aes(tSNE_1, tSNE_2, color = Age, alpha = nGene),
                        size = size.color) + 
      scale_color_viridis_d(option = "plasma") +
      theme(legend.position = 'top')
  }

  #  c) Color subcluster cells by area:
  else if(feature == "area") {
    p <- p + geom_point(data = filter(tsne.meta, subcluster.merge == subclust), 
                        aes(tSNE_1, tSNE_2, color = area, alpha = nGene),
                        size = size.color) + 
      scale_color_viridis_d(option = "viridis") +
      theme(legend.position = 'top')
  }

  p <- p + labs(title = paste(celltype, "|", subclust)) +

    theme(plot.subtitle = element_text(color="grey18", size=11, family="Helvetica", face = "plain", hjust = 0.5),
          plot.title = element_text(color="grey18", size=12, family="Helvetica", face = "plain"),
          axis.title = element_blank(),
          axis.text = element_blank(),
          axis.ticks = element_blank(),
          axis.line = element_blank(),
          panel.background = element_blank(),
          panel.grid = element_blank()
    )

  return(p)
  # png(paste0("tSNE_", celltype, "_", subclust,".png"), height = 5, width = 6, units = 'in', res = 300)
  # print(p)
  # dev.off()
}

You also may want to look at programmatic aes

condition inside geom (ggplot)

We can use ifelse

library(dplyr)
library(ggplot2)
df %>%
   ggplot() + 
      geom_point(aes(x = ID, y = ifelse(heat.s == 0, value, heat), color = 'red3'))

---

Or we can do the change before

df %>%
   mutate(value = case_when(heat.s == 0~ value, TRUE ~ heat)) %>% 
   ggplot() + 
       geom_point(aes(x = ID, y = value, color = 'red3'))

if else condition in ggplot to add an extra layer

What you are seeing is a syntax error. The most robust way I can think of is:

tmp.data<-c(1,2,3) 
if(tmp.data[1]!="no value") {
   p = p + geom_point()
}
p + geom_line()

So you compose the object p in a sequence, only adding geom_point() when the if statements yields TRUE.

ifelse() condition not working correctly for ggplot

Perhaps you could try something like this:

library(tidyverse)
C %>% 
  mutate(color = if_else(abs(C1) > abs(C2), "Condition 1", "Condition 2")) %>% 
  ggplot(aes(x = C1, y = C2, label = State, color = color)) +
  geom_point() +
  scale_color_manual(
    values = c("Condition 1" = "green", "Condition 2" = "red"),
    name = "New title"
  ) +
  ggrepel::geom_text_repel(color = "black")

The if_else operation is a vectorized command that creates a new variable based on the conditions you outlined above. Running it before the plotting operation makes it a little easier to visualize what's going on.

ggplot line or point plotting conditionally

Maybe this is what you're looking for? I like @arvi1000's answer---nice and clear---but you can put the if statement inside a single ggplot addition expression:

type = "line"
## also try with
# type = "point"

ggplot(mtcars, aes(x = wt, y = mpg)) + {
      if(type == "point") geom_point() else geom_line()
    } +
    theme_bw()

---

For multiple layers, you could do something like this:

gg = ggplot(mtcars, aes(x = wt, y = mpg))

{
  if(type == "point") {
    gg + geom_point() 
  } else {
    gg + geom_line() + stat_smooth()
  }
} + theme_bw()

(Of course, adding the theme_bw() to the original gg definition would be cleaner, but this demonstrates that it can be added later.)

Conditionally modify ggplot theme based on presence of facets?

I think Oliver was thinking in the correct direction.

I don't think the theme_custom function is the correct place to check the plot for conditional theming, because theme functions are mostly agnostic about the precise plot that they are added to.

Instead, I think the appropriate place to check the plot is when the theme is added to the plot. You could write a theme function like the following, which sets a different class to the output.

theme_custom <- function() {
  out <- theme_minimal()
  class(out) <- c("conditional_theme", class(out))
  out
}

Now everytime a theme is added to a plot, this is done through the ggplot_add.theme function, which we can rewrite for the conditional_theme class. In my opinion, the correct way to check if a plot is facetted, is to check the class of the plot$facet slot, which can be FacetGrid, FacetWrap etc when a proper facet is added and defaults to FacetNull when no facet is set.

ggplot_add.conditional_theme <- function(object, plot, object_name) {
  if (!inherits(plot$facet, "FacetNull")) {
    object <- object + theme(panel.border = element_rect(colour = "grey50", fill = NA))
  }
  plot$theme <- ggplot2:::add_theme(plot$theme, object, object_name)
  plot
}

And now the use cases should work as intended:

ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  facet_wrap(vars(cyl)) +
  theme_custom()

ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  theme_custom() 

The only downside is that you would literally have to add the theme to the plot every time and you can't use the theme_set(theme_custom()) to have this apply to any plot in the session.

ggplot2 facet grid with conditional facets and tidy evaluation

Maybe we should remove NULL elements from vars specs to make this easier. I have opened an issue: https://github.com/tidyverse/ggplot2/issues/2986

You can use rlang::quo_is_null() to check for quo(NULL). I would do it in a separate step for clarity.

plot_iris <- function(df_in, facet_var = NULL){
  facet_quo <- enquo(facet_var)

  if (rlang::quo_is_null(facet_quo)) {
    rows <- vars()
  } else {
    rows <- vars(!!facet_quo)
  }

  ggplot(df_in) +
    geom_point(aes(Sepal.Length, Sepal.Width)) +
    facet_grid(rows, vars(idx))
}

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