benchmarks/performance-benchmarks/benchmark_analysis.R
In SciOmicsLab/PhenoComb: Phenotype Combinatorial Analysis
library("rstudioapi")
setwd(dirname(getActiveDocumentContext()$path))
library(plotly)
library(dplyr)
get_run_time <- function(file_path, type = "full"){
txt <- readLines(file_path)
if(type == "full"){
start <- txt[1]
end <- txt[length(txt)]
}
if(type == "pre_process"){
start <- txt[1]
for(i in 1:length(txt)){
if(grepl( "Getting unique phenotypes", txt[i], fixed = TRUE)){
end <- txt[i]
break
}
}
}
if(type == "combinatorics_run"){
for(i in 1:length(txt)){
if(grepl( "Getting unique phenotypes", txt[i], fixed = TRUE)){
start <- txt[i]
}
}
end <- txt[length(txt)]
}
start <- regmatches(start, gregexpr("(?<=\\[).*?(?=\\])",start, perl=T))[[1]]
start <- as.POSIXct(start,format="%Y/%m/%d %H:%M:%OS")
end <- regmatches(end, gregexpr("(?<=\\[).*?(?=\\])",end, perl=T))[[1]]
end <- as.POSIXct(end,format="%Y/%m/%d %H:%M:%OS")
return(as.numeric(difftime(end, start, units = "sec")))
}
get_phenotypes_generated <- function(file_path){
txt <- readLines(file_path)
phenotypes_generated <- 0
for(i in 1:length(txt)){
if(grepl( "Writing", txt[i], fixed = TRUE)){
if(grepl( "done", txt[i], fixed = TRUE)) next #Fixing one other log line that thas "writing" word. Can be done more elegantly.
phenotypes_generated <- phenotypes_generated + as.integer(sub(".*?Writing .*?(\\d+).*", "\\1", txt[i]))
}
}
rm(txt)
return(phenotypes_generated)
}
get_chunk_runtime <- function(file_path){
txt <- readLines(file_path)
chunk_runtime <- NULL
for(i in 1:length(txt)){
if(grepl( "Computing marker combinations", txt[i], fixed = TRUE)){
start <- txt[i]
}
if(grepl( "Marker combinations computed", txt[i], fixed = TRUE)){
end <- txt[i]
start <- regmatches(start, gregexpr("(?<=\\[).*?(?=\\])",start, perl=T))[[1]]
start <- as.POSIXct(start,format="%Y/%m/%d %H:%M:%OS")
end <- regmatches(end, gregexpr("(?<=\\[).*?(?=\\])",end, perl=T))[[1]]
end <- as.POSIXct(end,format="%Y/%m/%d %H:%M:%OS")
chunk_runtime <- c(chunk_runtime, as.numeric(difftime(end, start, units = "sec")))
}
}
return(chunk_runtime)
}
get_chunk_phenotypes_generated <- function(file_path){
txt <- readLines(file_path)
phenotypes_generated <- NULL
for(i in 1:length(txt)){
if(grepl( "Writing", txt[i], fixed = TRUE)){
phenotypes_generated <- c(phenotypes_generated, as.integer(sub(".*?Writing .*?(\\d+).*", "\\1", txt[i])))
}
}
return(phenotypes_generated)
}
get_chunk_info <- function(results_folder,experiment_id,replicates){
file_name <- file.path(results_folder, paste("experiment_",experiment_id,"_replicate_1.log",sep = ""))
chunk_results <- get_chunk_phenotypes_generated(file_name)
chunk_results <- data.frame(chunk = 1:length(chunk_results), phenotypes_generated = chunk_results)
chunk_results <- merge(chunk_results,data.frame(Replicate = 1:replicates))
chunk_runtimes <- NULL
for(i in 1:replicates){
file_name <- file.path(results_folder, paste("experiment_",experiment_id,"_replicate_",i,".log",sep = ""))
chunk_runtimes <- c(chunk_runtimes,get_chunk_runtime(file_name))
}
chunk_results$runtime <- chunk_runtimes
return(chunk_results)
}
read_results <- function(experiments,results_folder,replicates){
results <- merge(experiments,data.frame(Replicate = 1:replicates))
for(i in 1:nrow(results)){
file_name <- paste("experiment_",results[i,"experiment_ID"],"_replicate_",results[i,"Replicate"],".log",sep = "")
file_path <- file.path(results_folder,file_name)
if(file.exists(file_path)){
results[i,"preprocess_runtime"] <- get_run_time(file_path,type = "pre_process")
results[i,"combinatorics_runtime"] <- get_run_time(file_path,type = "combinatorics_run")
results[i,"runtime"] <- get_run_time(file_path)
results[i,"phenotypes_generated"] <- get_phenotypes_generated(file_path)
}
}
return(results)
}
plot_nphenotypes <- function(){
phen_data <- expand.grid(4:28,2:3)
colnames(phen_data) <- c("markers","states")
phen_data$phenotypes <- (phen_data$states + 1)^(phen_data$markers)
fig <- plot_ly(phen_data, x = ~markers, y = ~phenotypes, color = ~factor(states), type = 'scatter', mode = 'markers+lines',
colors = c('#29a329','#006450'),
marker = list(),
showlegend = TRUE)
fig <- fig %>% layout(yaxis = list(title = "Number of Phenotypes", type = "log"),
xaxis = list(
title = "Number of Markers",
tickmode = "array",
nticks = 7,
tickvals = c(4,10,15,20,25,30,35),
range = c(3, 35)
),
legend = list(x = 0.08, y = 0.98,title=list(text='States'))
)
return(fig)
}
plot_nmarker_experiment_runtime <- function(results){
runtime_data <- summarise(group_by(filter(results,experiment == "n_markers"), markers),
mean(combinatorics_runtime)/3600,
max(combinatorics_runtime)/3600,
min(combinatorics_runtime)/3600
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(yaxis = list(title = "Runtime (hours)", type = "log"),
xaxis = list(
title = "Number of Markers",
tickmode = "array",
nticks = 7,
tickvals = c(4,10,15,20,25,30,35),
range = c(3, 35)
)
)
return(fig)
}
plot_max_phen_len_experiment_runtime <- function(results){
results[results$experiment == "n_markers" & results$markers == 15, "experiment"] <- "max_phen_len"
runtime_data <- summarise(group_by(filter(results,experiment == "max_phen_len"), max_phen_len),
mean(combinatorics_runtime),
max(combinatorics_runtime),
min(combinatorics_runtime)
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(yaxis = list(title = "Runtime (seconds)", type = "log",
range=c(1,2.4)),
xaxis = list(
title = "Maximum Phenotype Length"
)
)
return(fig)
}
plot_n_cells_experiment_runtime <- function(results){
runtime_data <- summarise(group_by(filter(results,experiment == "n_cells"), cells),
mean(combinatorics_runtime),
max(combinatorics_runtime),
min(combinatorics_runtime)
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
runtime_data <- runtime_data[runtime_data$x >= 10000,]
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(yaxis = list(title = "Runtime (seconds)",range = c(0,200)),
xaxis = list(
title = "Number of Cells",
tickmode = "array",
nticks = nrow(runtime_data),
tickvals = runtime_data$x
)
)
return(fig)
}
plot_n_samples_experiment_runtime <- function(results){
runtime_data <- summarise(group_by(filter(results,experiment == "n_samples"), samples),
mean(combinatorics_runtime),
max(combinatorics_runtime),
min(combinatorics_runtime)
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(yaxis = list(title = ""),
xaxis = list(
title = "Number of Samples",
tickmode = "array",
nticks = 5,
tickvals = c(20,50,80,100,200)
)
)
return(fig)
}
plot_n_threads_experiment_runtime <- function(results){
runtime_data <- summarise(group_by(filter(results,experiment == "n_threads"), threads),
mean(combinatorics_runtime),
max(combinatorics_runtime),
min(combinatorics_runtime)
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(
xaxis = list(
title = "Number of Threads",
tickmode = "array",
nticks = 6,
tickvals = c(1,4,8,16,32,50)
)
)
return(fig)
}
add_point_to_figure <- function(fig,x,y,ann, color='purple'){
dt <- data.frame(x = x,y = y, ann = ann)
t <- list(
family = "PT Sans Narrow",
size = 7,
color = toRGB("grey50"))
fig <- fig %>% add_markers(data = dt, x = ~x, y = ~y, type = 'scatter', mode = 'markers',
marker = list(color = color),
showlegend = FALSE,
inherit = FALSE)
fig <- fig %>% add_text(data = dt, x = ~x, y = ~y, text = ~ann, textfont = t, textposition = "top right",showlegend = FALSE,
inherit = FALSE)
return(fig)
}
read_flowtype_results <- function(results_folder,replicates){
results <- read.csv("./flowType_experiment_results.csv")
# cut it off at (about) 100 hours
results <- results %>%
mutate (flowType_runtime = (results$combinatorics_runtime / 3600 ))
results <- results %>%
filter(results$flowType_runtime <= 110)
return(results)
}
experiments <- read.csv("experiments.csv")
replicates <- 3
results_folder <- "outputs"
results <- read_results(experiments,results_folder,replicates)
real_datasets_result_folder <- "real_datasets_results"
real_datasets <- c("combinatorial_phenotypes_parent_CD45+CD14+.log",
"combinatorial_phenotypes_parent_CD45+CD3-CD19-CD56-CD14-.log",
"combinatorial_phenotypes_parent_CD45+CD19+.log",
"combinatorial_phenotypes_parent_CD45+CD56+.log",
"combinatorial_phenotypes_parent_CD45+CD3+.log",
"HIV_combinatorial_phenotypes.log")
dataset_names <- c("CD45+CD14+",
"CD45+CD3-CD19-CD56-CD14-",
"CD45+CD19+",
"cCD45+CD56+",
"CD45+CD3+",
"HIV")
real_datasets_n_markers <- c(16,18,22,16,26,12)
real_datasets_runtimes <- unlist(lapply(real_datasets, function(i) get_run_time(file.path(real_datasets_result_folder,i),type = "combinatorics_run")/3600))
real_datasets_phenotypes <- unlist(lapply(real_datasets, function(i) get_phenotypes_generated(file.path(real_datasets_result_folder,i))))
n_phenotypes <- plot_nphenotypes()
n_phenotypes <- add_point_to_figure(n_phenotypes,real_datasets_n_markers,real_datasets_phenotypes,dataset_names)
n_marker <- plot_nmarker_experiment_runtime(results)
n_marker <- add_point_to_figure(n_marker,real_datasets_n_markers,real_datasets_runtimes,dataset_names)
# adding flowType in orange for comparison
flowtype_results <- read_flowtype_results()
n_marker <- add_point_to_figure(n_marker, flowtype_results$markers, flowtype_results$flowType_runtime, "", color='orange')
row1 <- subplot(
n_phenotypes,
n_marker,
plot_max_phen_len_experiment_runtime(results),
nrows = 1,
widths = c(0.3,0.3,0.3),
margin = 0.05,
titleX = TRUE, titleY = TRUE
)
row2 <- subplot(
plot_n_cells_experiment_runtime(results),
plot_n_samples_experiment_runtime(results),
plot_n_threads_experiment_runtime(results),
nrows = 1,
widths = c(0.3,0.3,0.3),
margin = 0.05,
titleX = TRUE, titleY = TRUE)
subplot(row1,row2,nrows = 2,margin = 0.08, titleX = TRUE, titleY = TRUE)
save_image(subplot(row1,row2,nrows = 2,margin = 0.08, titleX = TRUE, titleY = TRUE), "benchmark.pdf",width = 800, height = 500)
SciOmicsLab/PhenoComb documentation built on Aug. 26, 2023, 1:28 p.m.
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library("rstudioapi")
setwd(dirname(getActiveDocumentContext()$path))
library(plotly)
library(dplyr)
get_run_time <- function(file_path, type = "full"){
txt <- readLines(file_path)
if(type == "full"){
start <- txt[1]
end <- txt[length(txt)]
}
if(type == "pre_process"){
start <- txt[1]
for(i in 1:length(txt)){
if(grepl( "Getting unique phenotypes", txt[i], fixed = TRUE)){
end <- txt[i]
break
}
}
}
if(type == "combinatorics_run"){
for(i in 1:length(txt)){
if(grepl( "Getting unique phenotypes", txt[i], fixed = TRUE)){
start <- txt[i]
}
}
end <- txt[length(txt)]
}
start <- regmatches(start, gregexpr("(?<=\\[).*?(?=\\])",start, perl=T))[[1]]
start <- as.POSIXct(start,format="%Y/%m/%d %H:%M:%OS")
end <- regmatches(end, gregexpr("(?<=\\[).*?(?=\\])",end, perl=T))[[1]]
end <- as.POSIXct(end,format="%Y/%m/%d %H:%M:%OS")
return(as.numeric(difftime(end, start, units = "sec")))
}
get_phenotypes_generated <- function(file_path){
txt <- readLines(file_path)
phenotypes_generated <- 0
for(i in 1:length(txt)){
if(grepl( "Writing", txt[i], fixed = TRUE)){
if(grepl( "done", txt[i], fixed = TRUE)) next #Fixing one other log line that thas "writing" word. Can be done more elegantly.
phenotypes_generated <- phenotypes_generated + as.integer(sub(".*?Writing .*?(\\d+).*", "\\1", txt[i]))
}
}
rm(txt)
return(phenotypes_generated)
}
get_chunk_runtime <- function(file_path){
txt <- readLines(file_path)
chunk_runtime <- NULL
for(i in 1:length(txt)){
if(grepl( "Computing marker combinations", txt[i], fixed = TRUE)){
start <- txt[i]
}
if(grepl( "Marker combinations computed", txt[i], fixed = TRUE)){
end <- txt[i]
start <- regmatches(start, gregexpr("(?<=\\[).*?(?=\\])",start, perl=T))[[1]]
start <- as.POSIXct(start,format="%Y/%m/%d %H:%M:%OS")
end <- regmatches(end, gregexpr("(?<=\\[).*?(?=\\])",end, perl=T))[[1]]
end <- as.POSIXct(end,format="%Y/%m/%d %H:%M:%OS")
chunk_runtime <- c(chunk_runtime, as.numeric(difftime(end, start, units = "sec")))
}
}
return(chunk_runtime)
}
get_chunk_phenotypes_generated <- function(file_path){
txt <- readLines(file_path)
phenotypes_generated <- NULL
for(i in 1:length(txt)){
if(grepl( "Writing", txt[i], fixed = TRUE)){
phenotypes_generated <- c(phenotypes_generated, as.integer(sub(".*?Writing .*?(\\d+).*", "\\1", txt[i])))
}
}
return(phenotypes_generated)
}
get_chunk_info <- function(results_folder,experiment_id,replicates){
file_name <- file.path(results_folder, paste("experiment_",experiment_id,"_replicate_1.log",sep = ""))
chunk_results <- get_chunk_phenotypes_generated(file_name)
chunk_results <- data.frame(chunk = 1:length(chunk_results), phenotypes_generated = chunk_results)
chunk_results <- merge(chunk_results,data.frame(Replicate = 1:replicates))
chunk_runtimes <- NULL
for(i in 1:replicates){
file_name <- file.path(results_folder, paste("experiment_",experiment_id,"_replicate_",i,".log",sep = ""))
chunk_runtimes <- c(chunk_runtimes,get_chunk_runtime(file_name))
}
chunk_results$runtime <- chunk_runtimes
return(chunk_results)
}
read_results <- function(experiments,results_folder,replicates){
results <- merge(experiments,data.frame(Replicate = 1:replicates))
for(i in 1:nrow(results)){
file_name <- paste("experiment_",results[i,"experiment_ID"],"_replicate_",results[i,"Replicate"],".log",sep = "")
file_path <- file.path(results_folder,file_name)
if(file.exists(file_path)){
results[i,"preprocess_runtime"] <- get_run_time(file_path,type = "pre_process")
results[i,"combinatorics_runtime"] <- get_run_time(file_path,type = "combinatorics_run")
results[i,"runtime"] <- get_run_time(file_path)
results[i,"phenotypes_generated"] <- get_phenotypes_generated(file_path)
}
}
return(results)
}
plot_nphenotypes <- function(){
phen_data <- expand.grid(4:28,2:3)
colnames(phen_data) <- c("markers","states")
phen_data$phenotypes <- (phen_data$states + 1)^(phen_data$markers)
fig <- plot_ly(phen_data, x = ~markers, y = ~phenotypes, color = ~factor(states), type = 'scatter', mode = 'markers+lines',
colors = c('#29a329','#006450'),
marker = list(),
showlegend = TRUE)
fig <- fig %>% layout(yaxis = list(title = "Number of Phenotypes", type = "log"),
xaxis = list(
title = "Number of Markers",
tickmode = "array",
nticks = 7,
tickvals = c(4,10,15,20,25,30,35),
range = c(3, 35)
),
legend = list(x = 0.08, y = 0.98,title=list(text='States'))
)
return(fig)
}
plot_nmarker_experiment_runtime <- function(results){
runtime_data <- summarise(group_by(filter(results,experiment == "n_markers"), markers),
mean(combinatorics_runtime)/3600,
max(combinatorics_runtime)/3600,
min(combinatorics_runtime)/3600
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(yaxis = list(title = "Runtime (hours)", type = "log"),
xaxis = list(
title = "Number of Markers",
tickmode = "array",
nticks = 7,
tickvals = c(4,10,15,20,25,30,35),
range = c(3, 35)
)
)
return(fig)
}
plot_max_phen_len_experiment_runtime <- function(results){
results[results$experiment == "n_markers" & results$markers == 15, "experiment"] <- "max_phen_len"
runtime_data <- summarise(group_by(filter(results,experiment == "max_phen_len"), max_phen_len),
mean(combinatorics_runtime),
max(combinatorics_runtime),
min(combinatorics_runtime)
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(yaxis = list(title = "Runtime (seconds)", type = "log",
range=c(1,2.4)),
xaxis = list(
title = "Maximum Phenotype Length"
)
)
return(fig)
}
plot_n_cells_experiment_runtime <- function(results){
runtime_data <- summarise(group_by(filter(results,experiment == "n_cells"), cells),
mean(combinatorics_runtime),
max(combinatorics_runtime),
min(combinatorics_runtime)
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
runtime_data <- runtime_data[runtime_data$x >= 10000,]
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(yaxis = list(title = "Runtime (seconds)",range = c(0,200)),
xaxis = list(
title = "Number of Cells",
tickmode = "array",
nticks = nrow(runtime_data),
tickvals = runtime_data$x
)
)
return(fig)
}
plot_n_samples_experiment_runtime <- function(results){
runtime_data <- summarise(group_by(filter(results,experiment == "n_samples"), samples),
mean(combinatorics_runtime),
max(combinatorics_runtime),
min(combinatorics_runtime)
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(yaxis = list(title = ""),
xaxis = list(
title = "Number of Samples",
tickmode = "array",
nticks = 5,
tickvals = c(20,50,80,100,200)
)
)
return(fig)
}
plot_n_threads_experiment_runtime <- function(results){
runtime_data <- summarise(group_by(filter(results,experiment == "n_threads"), threads),
mean(combinatorics_runtime),
max(combinatorics_runtime),
min(combinatorics_runtime)
)
colnames(runtime_data) <- c("x",
"mean",
"max",
"min"
)
fig <- plot_ly(runtime_data, x = ~x, y = ~max, type = 'scatter', mode = 'lines',
line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~min, type = 'scatter', mode = 'lines',
fill = 'tonexty', fillcolor='rgba(0,100,80,0.2)', line = list(color = 'rgba(1,1,1,0)'),
showlegend = FALSE)
fig <- fig %>% add_trace(y = ~mean, type = 'scatter', mode = 'lines + markers',
line = list(color = 'rgba(0,100,80,1)'),
marker = list(color = 'rgba(41, 163, 41,1)'),
showlegend = FALSE)
fig <- fig %>% layout(
xaxis = list(
title = "Number of Threads",
tickmode = "array",
nticks = 6,
tickvals = c(1,4,8,16,32,50)
)
)
return(fig)
}
add_point_to_figure <- function(fig,x,y,ann, color='purple'){
dt <- data.frame(x = x,y = y, ann = ann)
t <- list(
family = "PT Sans Narrow",
size = 7,
color = toRGB("grey50"))
fig <- fig %>% add_markers(data = dt, x = ~x, y = ~y, type = 'scatter', mode = 'markers',
marker = list(color = color),
showlegend = FALSE,
inherit = FALSE)
fig <- fig %>% add_text(data = dt, x = ~x, y = ~y, text = ~ann, textfont = t, textposition = "top right",showlegend = FALSE,
inherit = FALSE)
return(fig)
}
read_flowtype_results <- function(results_folder,replicates){
results <- read.csv("./flowType_experiment_results.csv")
# cut it off at (about) 100 hours
results <- results %>%
mutate (flowType_runtime = (results$combinatorics_runtime / 3600 ))
results <- results %>%
filter(results$flowType_runtime <= 110)
return(results)
}
experiments <- read.csv("experiments.csv")
replicates <- 3
results_folder <- "outputs"
results <- read_results(experiments,results_folder,replicates)
real_datasets_result_folder <- "real_datasets_results"
real_datasets <- c("combinatorial_phenotypes_parent_CD45+CD14+.log",
"combinatorial_phenotypes_parent_CD45+CD3-CD19-CD56-CD14-.log",
"combinatorial_phenotypes_parent_CD45+CD19+.log",
"combinatorial_phenotypes_parent_CD45+CD56+.log",
"combinatorial_phenotypes_parent_CD45+CD3+.log",
"HIV_combinatorial_phenotypes.log")
dataset_names <- c("CD45+CD14+",
"CD45+CD3-CD19-CD56-CD14-",
"CD45+CD19+",
"cCD45+CD56+",
"CD45+CD3+",
"HIV")
real_datasets_n_markers <- c(16,18,22,16,26,12)
real_datasets_runtimes <- unlist(lapply(real_datasets, function(i) get_run_time(file.path(real_datasets_result_folder,i),type = "combinatorics_run")/3600))
real_datasets_phenotypes <- unlist(lapply(real_datasets, function(i) get_phenotypes_generated(file.path(real_datasets_result_folder,i))))
n_phenotypes <- plot_nphenotypes()
n_phenotypes <- add_point_to_figure(n_phenotypes,real_datasets_n_markers,real_datasets_phenotypes,dataset_names)
n_marker <- plot_nmarker_experiment_runtime(results)
n_marker <- add_point_to_figure(n_marker,real_datasets_n_markers,real_datasets_runtimes,dataset_names)
# adding flowType in orange for comparison
flowtype_results <- read_flowtype_results()
n_marker <- add_point_to_figure(n_marker, flowtype_results$markers, flowtype_results$flowType_runtime, "", color='orange')
row1 <- subplot(
n_phenotypes,
n_marker,
plot_max_phen_len_experiment_runtime(results),
nrows = 1,
widths = c(0.3,0.3,0.3),
margin = 0.05,
titleX = TRUE, titleY = TRUE
)
row2 <- subplot(
plot_n_cells_experiment_runtime(results),
plot_n_samples_experiment_runtime(results),
plot_n_threads_experiment_runtime(results),
nrows = 1,
widths = c(0.3,0.3,0.3),
margin = 0.05,
titleX = TRUE, titleY = TRUE)
subplot(row1,row2,nrows = 2,margin = 0.08, titleX = TRUE, titleY = TRUE)
save_image(subplot(row1,row2,nrows = 2,margin = 0.08, titleX = TRUE, titleY = TRUE), "benchmark.pdf",width = 800, height = 500)
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