Overview
This script shows how to generate run time and memory figure for simPIC.
Run time and memory
Load table from data/Figure4
Plots
Build six panels:
(a) Run time vs nCells (colored by nPeaks; mean ± SD).
(b) Memory vs nCells (colored by nPeaks; mean ± SD).
(c) Run time vs nPeaks comparing simPIC vs simCAS (fixed nCells as in the inputs).
(d) Memory vs nPeaks comparing simPIC vs simCAS (same setup).
(e) Run time vs nCells comparing simPIC vs simCAS (fixed nPeaks as in the inputs; subset to ≤4k cells for clarity).
(f) Memory vs nCells comparing simPIC vs simCAS (fixed nPeaks; full range).
Show code
pa1 <- ggplot(averages, aes(x = as.factor(nCells), y = AvgExecutionTime,
label = as.character(nPeaks),
group = as.factor(nPeaks))) +
geom_point(aes(color = as.factor(nPeaks)), size = 3) +
geom_errorbar(aes(ymin = AvgExecutionTime - SDExecutionTime,
ymax = AvgExecutionTime + SDExecutionTime), width = 0.05) +
geom_line(aes(color = as.factor(nPeaks)), linewidth = 1, alpha = 0.5) +
ggtitle("Run Time (s)") +
labs(x = "nCells", y = "Run Time (s)") +
scale_color_brewer(palette = "Set1", name = "nPeaks") +
theme_minimal() +
theme(legend.position = "none") +
theme(legend.position = c(0.05, 0.95),
legend.justification = c("left", "top"),
legend.background = element_rect(fill = "white",
color = "black", linewidth = 0.5)) +
theme(plot.title = element_text(hjust = 0.5))
pa2 <- ggplot(averages, aes(x = as.factor(nCells), y = AvgMemoryUsage,
label = as.character(nPeaks),
group = as.factor(nPeaks))) +
geom_point(aes(color = as.factor(nPeaks)), size = 3) +
geom_errorbar(aes(ymin = AvgMemoryUsage - SDMemoryUsage,
ymax = AvgMemoryUsage + SDMemoryUsage),
width = 0.05) +
geom_line(aes(color = as.factor(nPeaks)), linewidth = 1, alpha = 0.5) +
ggtitle("Memory usage (GB)") +
labs(x = "nCells", y = "Memory usage (GB)") +
scale_color_brewer(palette = "Set1", name = "nPeaks") +
theme_minimal() +
theme(legend.position = "none") +
theme(legend.position = c(0.05, 0.95),
legend.justification = c("left", "top"),
legend.background = element_rect(fill = "white",
color = "black", size = 0.5)) +
theme(plot.title = element_text(hjust = 0.5))
simcas_npeaksconst_df <- readxl::read_xlsx("../data/Figure4/simcas_memdf_100kpeaks.xlsx")
simcas_ncellsconst_df <- readxl::read_xlsx("../data/Figure4/simcas_timeandmem_2kcells.xlsx")
simcas_avgs_npeaksconst <- simcas_npeaksconst_df %>%
group_by(nCells, nPeaks) %>%
summarise(AvgExecutionTime = mean(ExecutionTime),
AvgMemoryUsage = mean(MemoryUsage),
SDExecutionTime = sd(ExecutionTime),
SDMemoryUsage = sd(MemoryUsage))
simcas_avgs_npeaksconst$simulator <- rep("simCAS",6)
simcas_avgs_ncellsconst <- simcas_ncellsconst_df %>%
group_by(nCells, nPeaks) %>%
summarise(AvgExecutionTime = mean(ExecutionTime),
AvgMemoryUsage = mean(MemoryUsage),
SDExecutionTime = sd(ExecutionTime),
SDMemoryUsage = sd(MemoryUsage))
simcas_avgs_ncellsconst$simulator <- rep("simCAS",4)
simPIC_df <- as.data.frame(averages[c(11,12,13,14),])
simPIC_df$simulator <- rep("simPIC",4)
df <- rbind(simcas_avgs_ncellsconst,simPIC_df)
df$AvgExecutionTime <- as.numeric(as.character(df$AvgExecutionTime))
df$AvgMemoryUsage <- as.numeric(as.character(df$AvgMemoryUsage))
df$nPeaks <- factor(df$nPeaks, levels = c(10000, 20000, 50000, 100000))
pa3 <- ggplot(df, aes(x = nPeaks, y = AvgExecutionTime, color = simulator,
linetype = simulator, group = simulator)) +
geom_line(linetype ="solid") +
geom_point() +
geom_errorbar(aes(ymin = AvgExecutionTime - SDExecutionTime,
ymax = AvgExecutionTime + SDExecutionTime),
width = 0.05, color = "black") +
labs(x = "nPeaks", y = "Run Time (s)", title = "Run Time (s) simPIC vs simCAS") +
scale_y_continuous(breaks = seq(0, max(df$AvgExecutionTime), by = 20),
limits = c(0, max(df$AvgExecutionTime) + 2)) +
theme_minimal() +
theme(legend.position = "none") +
theme(legend.position = c(0.05, 0.95),
legend.justification = c("left", "top"),
legend.background = element_rect(fill = "white",
color = "black", size = 1)) +
theme(plot.title = element_text(hjust = 0.5),
axis.text.x = element_text(size=14),
axis.text.y = element_text(size=14),
axis.title = element_text(size = 15, face = "bold"))+
scale_color_manual(values = c("simCAS" = "#984EA3", "simPIC" = "#4DAF4A"))
pa4 <- ggplot(df, aes(x = nPeaks, y = AvgMemoryUsage, color = simulator,
linetype = simulator, group = simulator)) +
geom_line(linetype ="solid") +
geom_point() +
geom_errorbar(aes(ymin = AvgMemoryUsage - SDMemoryUsage,
ymax = AvgMemoryUsage + SDMemoryUsage),
width = 0.05, color = "black") +
labs(x = "nPeaks", y = "Memory usage (GB)",
title = "Memory usage (GB) simPIC vs simCAS") +
scale_y_continuous(breaks = seq(0, 8, by = 2),
limits = c(0, max(df$AvgMemoryUsage) + 1)) +
theme_minimal() +
theme(legend.position = "none") +
theme(legend.position = c(0.05, 0.95),
legend.justification = c("left", "top"),
legend.background = element_rect(fill = "white",
color = "black", size = 1)) +
theme(plot.title = element_text(hjust = 0.5),
axis.text.x = element_text(size=14),
axis.text.y = element_text(size=14),
axis.title = element_text(size = 15, face = "bold"))+
scale_color_manual(values = c("simCAS" = "#984EA3", "simPIC" = "#4DAF4A"))
simPIC_mem_df <- as.data.frame(averages[c(4,9,14,19,24,29),])
simPIC_mem_df$simulator <- rep("simPIC",6)
memdf <- rbind(simcas_avgs_npeaksconst,simPIC_mem_df)
memdf$nCells <- factor(memdf$nCells, levels = c(500,1000,2000,4000,8000,10000))
memdf$AvgExecutionTime <- as.numeric(as.character(memdf$AvgExecutionTime))
memdf$AvgMemoryUsage <- as.numeric(as.character(memdf$AvgMemoryUsage))
# We are plotting only upto nCells=4000
memdf_sub <- memdf[-c(5:6,11:12),]
pa5 <- ggplot(memdf_sub, aes(x = nCells, y = AvgExecutionTime,
color = simulator,
linetype = simulator,
group = simulator)) +
geom_line(linetype ="solid") +
geom_point() +
geom_errorbar(aes(ymin = AvgExecutionTime - SDExecutionTime,
ymax = AvgExecutionTime + SDExecutionTime),
width = 0.05, color = "black") +
labs(x = "nCells", y = "Run Time (s)",
title = "Run Time (s) simPIC vs simCAS") +
scale_y_continuous(breaks = seq(0, 100,
by = 10),
limits = c(0, max(memdf_sub$AvgExecutionTime) + 8)) +
theme_minimal() +
theme(legend.position = "none") +
theme(legend.position = c(0.05, 0.95),
legend.justification = c("left", "top"),
legend.background = element_rect(fill = "white",
color = "black", size = 1)) +
theme(plot.title = element_text(hjust = 0.5),
axis.text.x = element_text(size=14),
axis.text.y = element_text(size=14),
axis.title = element_text(size = 15, face = "bold"))+
scale_color_manual(values = c("simCAS" = "#984EA3", "simPIC" = "#4DAF4A"))
pa6 <- ggplot(memdf, aes(x = nCells, y = AvgMemoryUsage,
color = simulator,
linetype = simulator, group = simulator)) +
geom_line(linetype ="solid") +
geom_point() +
geom_errorbar(aes(ymin = AvgMemoryUsage - SDMemoryUsage,
ymax = AvgMemoryUsage + SDMemoryUsage),
width = 0.05, color = "black") +
labs(x = "nCells", y = "Memory usage (GB)",
title = "Memory usage (GB) simPIC vs simCAS") +
scale_y_continuous(breaks = seq(0, max(memdf$AvgMemoryUsage), by = 2),
limits = c(0, max(memdf$AvgMemoryUsage) + 1)) +
theme_minimal() +
theme(legend.position = "none") +
theme(legend.position = c(0.05, 0.95),
legend.justification = c("left", "top"),
legend.background = element_rect(fill = "white",
color = "black", size = 1)) +
theme(plot.title = element_text(hjust = 0.5),
axis.text.x = element_text(size=14),
axis.text.y = element_text(size=14),
axis.title = element_text(size = 15, face = "bold"))+
scale_color_manual(values = c("simCAS" = "#984EA3", "simPIC" = "#4DAF4A"))Show code
wrap_plots(list(pa1,pa2,pa3,pa4,pa5,pa6), nrow = 3, ncol=2)+
plot_annotation(tag_levels = "a") &
theme(plot.tag = element_text(face = "bold"))