Plot order scatterplot ggplot2

Question

I’m doing a scatterplot and mapping the points by color (two categories) and size (a discrete variable).

The points must overlap, as they are measured from the same place, in different times

The problem is: the largest point is plotted 'in front' of the smallest, then superimposed. Even using alpha to make 'transparent' is getting very ugly.

Is there any way I can reverse the order that ggplot plots the variables?

Here is a chart print. Ideally, black dots should be plotted behind red dots.

Edit:

LIGHT <-
 structure(list(Sensor = c("Sensor 01", "Sensor 02", 
 "Sensor 03", "Sensor 04", "Sensor 05", "Sensor 06", 
 "Sensor 07", "Sensor 08", "Sensor 09", "Sensor 10", 
 "Sensor 11", "Sensor 12", "Sensor 13", "Sensor 14", 
 "Sensor 15", "Sensor 01", "Sensor 02", "Sensor 03", 
 "Sensor 04", "Sensor 05"), Light = c(29.2326025, 
 19.1888217741935, 20.2879273387097, 22.6006463709677, 
 29.4652291129032, 31.4922126612903, 18.0189039516129, 
 44.2132503225806, 19.6836093548387, 29.6778536290323, 
 23.7034666935484, 37.4008766935484, 32.4513981451613, 
 57.5753566129032, 41.8583696774194, 64.6308373214286, 
 44.2330882142857, 45.8567069642857, 61.8264760714286, 
 57.66113125), Dif_PAR.sensor = c(136.820568709677, 
 146.864349435484, 145.765243870968, 143.45252483871, 
 136.587942096774, 134.560958548387, 148.034267258065, 
 121.839920887097, 146.369561854839, 136.375317580645, 
 142.349704516129, 128.652294516129, 133.601773064516, 
 108.477814596774, 124.194801532258, 81.3658292857143, 
 101.763578392857, 100.139959642857, 84.1701905357143, 
 88.3355353571429), Percent_of_PAR = c(19.0689480982097, 
 14.2716407995484, 15.1293532713629, 15.8380714606935, 
 17.456968456871, 18.0777406968065, 13.7234488349113, 
 72.7551326408065, 11.6857118804435, 21.3044665453226, 
 16.434219278871, 25.781927983129, 23.9310200270565, 
 42.2960034949194, 32.4126078909758, 39.0122370998214, 
 26.402147205, 30.3298732019643, 36.2347200010714, 
 31.7127142146429), Height = c(11.3, 11.65, 12.8, 13.1, 
 13.1, 13.45, 13.5, 15.05, 16.15, 16.5, 17.7, 18.45, 18.5, 
 19, 20.1, 11.3, 11.65, 12.8, 13.1, 13.1), North = c(0, 0, 
 0, 1.5, 3, 0, 0, 0, 1.9, 2.3, 0.4, 0, 4.2, 0, 1, 0, 0, 0, 
 1.5, 3), South = c(0, 0, 0, 0, 0, 0.1, 1.5, 0.7, 0, 0, 0, 
 0, 0, 0.2, 0, 0, 0, 0, 0, 0), East = c(0.3, 0, 1.9, 0, 0.7, 
 0, 0, 0.3, 0, 0.6, 1, 0, 0, 0, 0.2, 0.3, 0, 1.9, 0, 0.7), 
 West = c(0, 0, 0, 0, 0, 2.5, 0.1, 0, 1.9, 0, 0, 2, 0, 0, 
 0, 0, 0, 0, 0, 0 ), Northeast = c(0, 0, 2.45, 1.95, 3.55, 
 0, 0, 0, 0, 2.9, 1.6, 0, 0, 0, 1.5, 0, 0, 2.45, 1.95, 3.55), 
 Northwest = c(0, 0, 0, 0, 0, 0, 0, 0, 3.25, 0, 0, 0, 4.6, 
 0, 0, 0, 0, 0, 0, 0), Southeast = c(0.85, 0, 0, 0, 0, 0, 0, 
 1.3, 0, 0, 0, 0, 0, 0, 0, 0.85, 0, 0, 0, 0), Southwest = c(0, 
 0, 0, 0, 0, 2.95, 1.95, 0, 0, 0, 0, 2.5, 0, 0.8, 0, 0, 0, 0, 
 0, 0), Dist_to_tree_center = c(0.85, 0, 2.45, 1.95, 3.55, 
 2.95, 1.95, 1.3, 3.25, 2.9, 1.6, 2.5, 4.6, 0.8, 1.5, 0.85, 
 0, 2.45, 1.95, 3.55), N_S = c(-0.5, 0, 0.5, 1.9, 3.4, -0.5, 
 -1.9, -1.1, 2.3, 2.7, 0.8, -0.5, 4.6, -0.6, 1.4, -0.5, 0, 0.5, 
 1.9, 3.4), E_W = c(0.7, 0, 2.4, 0.5, 1.1, -2.9, -0.5, 0.7, 
 -2.3, 1, 1.4, -2.4, -0.5, -0.5, 0.6, 0.7, 0, 2.4, 0.5, 1.1), 
 Aspect = c("Southeast", "On the bole", "Northeast", 
 "Northeast", "Northeast", "Southwest", "Southwest", 
 "Southeast", "Northwest", "Northeast", "Northeast", 
 "Southwest", "Northwest", "Southwest", "Northeast", 
 "Southeast", "On the bole", "Northeast", "Northeast", 
 "Northeast"), Leaf_set = c("With", "With", "With", 
 "With", "With", "With", "With", "With", "With", "With", 
 "With", "With", "With", "With", "With", "Without", 
 "Without", "Without", "Without", "Without")), 
 row.names = c(NA, 20L), class = "data.frame")

The code I used was this:

ggplight <- ggplot(LIGHT, aes(x=Dist_to_tree_center, y=Height, size = Percent_of_PAR, color=Leaf_set))+
  scale_color_manual(values=colors, labels=c("With leaves", "Without leaves"))+
  geom_point(alpha=.4) + 
  scale_size(range = c(3, 15), name="Light")+
  
  labs(x = 'Distance to tree centre (m)', y = 'Height (m)', color='', title = '(b)', subtitle = '')+
  
  theme_classic(base_size = 30)+
  theme(panel.background = element_blank())+
  theme(panel.grid.major = element_blank())+
  theme(panel.grid.minor = element_blank())+
  theme(plot.background = element_blank())+
  guides(color = FALSE)+
  theme(legend.position=c(1,0.1), legend.justification=c(1,-0.1))+
  theme(legend.background = element_rect(fill="transparent"))

Answer 1

One way to plot the smallest points over the largest ones is to notice that the smallest points correspond to the Leaf_set == "With" and use two geom_point, filtering the Leaf_set corresponding to each of the values. First the "Without" and then the "With".

library(ggplot2)

ggplight <- ggplot(LIGHT, aes(Dist_to_tree_center, Height, size = Percent_of_PAR, color = Leaf_set))+
  geom_point(
    data = subset(LIGHT, Leaf_set == "Without"),
    alpha = 0.6
  ) +
  geom_point(
    data = subset(LIGHT, Leaf_set == "With"),
    alpha = 0.6
  ) +
  scale_color_manual(breaks = c("With", "Without"), values = colors) +
  scale_size(range = c(3, 15), name="Light")+
  labs(x = 'Distance to tree centre (m)', y = 'Height (m)', color='', title = '(b)', subtitle = '') +
  guides(color = "none") +
  theme_Mariana()

ggplight

---

theme of the graph

theme_Mariana <- function(){ 
    theme_classic() + 
    theme(
        title = element_text(face = "bold"),
        axis.title = element_text(face = "bold"),
        panel.background = element_blank(),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        plot.background = element_blank(),
        legend.title = element_text(face = "bold"),
        legend.text = element_text(face = "bold"),
        legend.position = c(1, 0.05), 
        legend.justification = c("right", "bottom"),
        legend.background = element_rect(fill = "transparent")
    )
}