Nothing
inst/miscell/benchmark_1_0.05.R
In OncoSimulR: Forward Genetic Simulation of Cancer Progression with Epistasis
### Benchmark runs. This produces "benchmark_1.RData"
rm(list = ls())
set.seed(NULL)
library(OncoSimulR)
######################################################################
######################################################################
######################################################################
######################################################################
system_summary <- function() {
return(list(versioninfo = version,
memimfo = system("free", intern = TRUE),
cpuinfo = system("cat /proc/cpuinfo | grep 'model name'", intern = TRUE),
packageinfo = paste("OncoSimulR, ", packageVersion("OncoSimulR")),
## nodeinfo = Sys.info()$nodename,
## nodelinuxinfo = paste(Sys.info()$sysname, Sys.info()$release),
dateinfo = date()))
}
stats_simuls <- function(sim) {
## sim is an oncoSimulPop output
trf <- function(x) {
tt <- try(c(NumClones = x$NumClones,
NumIter = x$NumIter,
FinalTime = x$FinalTime,
TotalPopSize = x$TotalPopSize,
Attempts = x$other$attemptsUsed))
if(!inherits(tt, "try-error")) {
return(tt)
} else {
return(c(NumClones = NA,
NumIter = NA,
FinalTime = NA,
TotalPopSize = NA,
Attempts = NA))
}
}
tmp <- try(do.call("rbind", lapply(sim, trf)))
unlist(lapply(as.data.frame(tmp), summary))
}
all_sim_stats <- function(...) {
## Returns a single data frame with all benchmark info
## in ... pass the names of the objects
names <- as.character(as.list(match.call())[-c(1)])
m1 <- do.call("rbind", lapply(list(...), stats_simuls))
rownames(m1) <- names
Numindiv <- unlist(lapply(list(...), length))
time <- unlist(lapply(paste0("t_", names), get))
size <- unlist(lapply(list(...), object.size))
df <- data.frame(m1, size, time, Numindiv)
df$time_per_simul <- df$time/df$Numindiv
df$size_mb_per_simul <- df$size/(df$Numindiv * 1024^2)
attributes(df)$system_summary <- system_summary()
return(df)
}
######################################################################
######################################################################
######################################################################
######################################################################
pancr <- allFitnessEffects(
data.frame(parent = c("Root", rep("KRAS", 4),
"SMAD4", "CDNK2A",
"TP53", "TP53", "MLL3"),
child = c("KRAS","SMAD4", "CDNK2A",
"TP53", "MLL3",
rep("PXDN", 3), rep("TGFBR2", 2)),
s = 0.05,
sh = -0.9,
typeDep = "MN"),
drvNames = c("KRAS", "SMAD4", "CDNK2A", "TP53",
"MLL3", "TGFBR2", "PXDN"))
Nindiv <- 100
## keepEvery = 1
t_exp1 <- system.time(
exp1 <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_mc1 <- system.time(
mc1 <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = 1,
model = "McFL",
mc.cores = 1))["elapsed"]
## keepEvery = NA
t_exp2 <- system.time(
exp2 <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
t_mc2 <- system.time(
mc2 <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = NA,
model = "McFL",
mc.cores = 1))["elapsed"]
### exp3 to exp6
t_exp3 <- system.time(
exp3 <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e4,
p2 = 0.1, n2 = 5e5,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp4 <- system.time(
exp4 <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e4,
p2 = 0.1, n2 = 5e5,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp5 <- system.time(
exp5 <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e5,
p2 = 0.1, n2 = 5e7,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp6 <- system.time(
exp6 <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e5,
p2 = 0.1, n2 = 5e7,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
####################################################
###### onlyCancer = FALSE
## keepEvery = 1
t_exp1_noc <- system.time(
exp1_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_mc1_noc <- system.time(
mc1_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = 1,
model = "McFL",
mc.cores = 1))["elapsed"]
## keepEvery = NA
t_exp2_noc <- system.time(
exp2_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
t_mc2_noc <- system.time(
mc2_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = NA,
model = "McFL",
mc.cores = 1))["elapsed"]
### exp3_noc to exp6_noc
t_exp3_noc <- system.time(
exp3_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e4,
p2 = 0.1, n2 = 5e5,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp4_noc <- system.time(
exp4_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e4,
p2 = 0.1, n2 = 5e5,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp5_noc <- system.time(
exp5_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e5,
p2 = 0.1, n2 = 5e7,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp6_noc <- system.time(
exp6_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e5,
p2 = 0.1, n2 = 5e7,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
benchmark_1_0.05 <- all_sim_stats(exp1, mc1, exp2, mc2, exp3, exp4, exp5, exp6,
exp1_noc, mc1_noc, exp2_noc, mc2_noc, exp3_noc, exp4_noc, exp5_noc, exp6_noc
)
## Add the info about key settings
benchmark_1_0.05$keepEvery <- c(1, 1, NA, NA, 1, NA, 1, NA,
1, 1, NA, NA, 1, NA, 1, NA)
benchmark_1_0.05$PDBaseline <- c(rep(1.2 * 500, 4), 5e4, 5e4, 5e5, 5e5,
rep(1.2 * 500, 4), 5e4, 5e4, 5e5, 5e5)
benchmark_1_0.05$n2 <- c(rep(2 * 500, 4), 5e5, 5e5, 5e7, 5e7,
rep(2 * 500, 4), 5e5, 5e5, 5e7, 5e7)
benchmark_1_0.05$onlyCancer <- c(rep(TRUE, 8), rep(FALSE, 8))
save(file = "../../data/benchmark_1_0.05.RData", benchmark_1_0.05)
gc()
## ######################################################################
## ######################################################################
## ############### ##############
## ############### If you do it by hand ... ##############
## ############### ##############
## ######################################################################
## ######################################################################
## cat("\n\n\n t_exp1 = ", t_exp1, "\n")
## object.size(exp1)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp1, "[[", "NumClones")))
## summary(unlist(lapply(exp1, "[[", "NumIter")))
## summary(unlist(lapply(exp1, "[[", "FinalTime")))
## summary(unlist(lapply(exp1, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_mc1 = ", t_mc1, "\n")
## object.size(mc1)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(mc1, "[[", "NumClones")))
## summary(unlist(lapply(mc1, "[[", "NumIter")))
## summary(unlist(lapply(mc1, "[[", "FinalTime")))
## summary(unlist(lapply(mc1, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp2 = ", t_exp2, "\n")
## object.size(exp2)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp2, "[[", "NumClones")))
## summary(unlist(lapply(exp2, "[[", "NumIter")))
## summary(unlist(lapply(exp2, "[[", "FinalTime")))
## summary(unlist(lapply(exp2, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_mc2 = ", t_mc2, "\n")
## object.size(mc2)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(mc2, "[[", "NumClones")))
## summary(unlist(lapply(mc2, "[[", "NumIter")))
## summary(unlist(lapply(mc2, "[[", "FinalTime")))
## summary(unlist(lapply(mc2, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp3 = ", t_exp3, "\n")
## object.size(exp3)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp3, "[[", "NumClones")))
## summary(unlist(lapply(exp3, "[[", "NumIter")))
## summary(unlist(lapply(exp3, "[[", "FinalTime")))
## summary(unlist(lapply(exp3, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp4 = ", t_exp4, "\n")
## object.size(exp4)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp4, "[[", "NumClones")))
## summary(unlist(lapply(exp4, "[[", "NumIter")))
## summary(unlist(lapply(exp4, "[[", "FinalTime")))
## summary(unlist(lapply(exp4, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp5 = ", t_exp5, "\n")
## object.size(exp5)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp5, "[[", "NumClones")))
## summary(unlist(lapply(exp5, "[[", "NumIter")))
## summary(unlist(lapply(exp5, "[[", "FinalTime")))
## summary(unlist(lapply(exp5, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp6 = ", t_exp6, "\n")
## object.size(exp6)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp6, "[[", "NumClones")))
## summary(unlist(lapply(exp6, "[[", "NumIter")))
## summary(unlist(lapply(exp6, "[[", "FinalTime")))
## summary(unlist(lapply(exp6, "[[", "TotalPopSize")))
## ## Median runs until cancer
## lapply(list(exp1, mc1, exp2, mc2, exp3, exp4, exp5, exp6),
## function(y) median(unlist(lapply(y, function(x) x$other$attemptsUsed))))
## cat("\n\n\n t_exp1_noc = ", t_exp1_noc, "\n")
## object.size(exp1_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp1_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp1_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp1_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp1_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_mc1_noc = ", t_mc1_noc, "\n")
## object.size(mc1_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(mc1_noc, "[[", "NumClones")))
## summary(unlist(lapply(mc1_noc, "[[", "NumIter")))
## summary(unlist(lapply(mc1_noc, "[[", "FinalTime")))
## summary(unlist(lapply(mc1_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp2_noc = ", t_exp2_noc, "\n")
## object.size(exp2_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp2_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp2_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp2_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp2_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_mc2_noc = ", t_mc2_noc, "\n")
## object.size(mc2_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(mc2_noc, "[[", "NumClones")))
## summary(unlist(lapply(mc2_noc, "[[", "NumIter")))
## summary(unlist(lapply(mc2_noc, "[[", "FinalTime")))
## summary(unlist(lapply(mc2_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp3_noc = ", t_exp3_noc, "\n")
## object.size(exp3_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp3_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp3_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp3_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp3_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp4_noc = ", t_exp4_noc, "\n")
## object.size(exp4_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp4_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp4_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp4_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp4_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp5_noc = ", t_exp5_noc, "\n")
## object.size(exp5_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp5_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp5_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp5_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp5_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp6_noc = ", t_exp6_noc, "\n")
## object.size(exp6_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp6_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp6_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp6_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp6_noc, "[[", "TotalPopSize")))
## ## Median runs until cancer
## lapply(list(exp1_noc, mc1_noc, exp2_noc, mc2_noc, exp3_noc, exp4_noc, exp5_noc, exp6_noc),
## function(y) median(unlist(lapply(y, function(x) x$other$attemptsUsed))))
## ## bench1 <- data.frame(
## ## time = c(t_exp1, t_mc1, t_exp2, t_mc2, t_exp3, t_exp4, t_exp5, t_exp6),
## ## size = unlist(lapply(list(exp1, mc1, exp2, mc2, exp3, exp4, exp5, exp6),
## ## object.size))/(Nindiv * 1024^2),
## ## lapply(list(exp1, mc1, exp2, mc2, exp3, exp4, exp5, exp6),
## ## function(y) median(unlist(lapply(y, function(x) x$other$attemptsUsed))))
## ## )
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### Benchmark runs. This produces "benchmark_1.RData"
rm(list = ls())
set.seed(NULL)
library(OncoSimulR)
######################################################################
######################################################################
######################################################################
######################################################################
system_summary <- function() {
return(list(versioninfo = version,
memimfo = system("free", intern = TRUE),
cpuinfo = system("cat /proc/cpuinfo | grep 'model name'", intern = TRUE),
packageinfo = paste("OncoSimulR, ", packageVersion("OncoSimulR")),
## nodeinfo = Sys.info()$nodename,
## nodelinuxinfo = paste(Sys.info()$sysname, Sys.info()$release),
dateinfo = date()))
}
stats_simuls <- function(sim) {
## sim is an oncoSimulPop output
trf <- function(x) {
tt <- try(c(NumClones = x$NumClones,
NumIter = x$NumIter,
FinalTime = x$FinalTime,
TotalPopSize = x$TotalPopSize,
Attempts = x$other$attemptsUsed))
if(!inherits(tt, "try-error")) {
return(tt)
} else {
return(c(NumClones = NA,
NumIter = NA,
FinalTime = NA,
TotalPopSize = NA,
Attempts = NA))
}
}
tmp <- try(do.call("rbind", lapply(sim, trf)))
unlist(lapply(as.data.frame(tmp), summary))
}
all_sim_stats <- function(...) {
## Returns a single data frame with all benchmark info
## in ... pass the names of the objects
names <- as.character(as.list(match.call())[-c(1)])
m1 <- do.call("rbind", lapply(list(...), stats_simuls))
rownames(m1) <- names
Numindiv <- unlist(lapply(list(...), length))
time <- unlist(lapply(paste0("t_", names), get))
size <- unlist(lapply(list(...), object.size))
df <- data.frame(m1, size, time, Numindiv)
df$time_per_simul <- df$time/df$Numindiv
df$size_mb_per_simul <- df$size/(df$Numindiv * 1024^2)
attributes(df)$system_summary <- system_summary()
return(df)
}
######################################################################
######################################################################
######################################################################
######################################################################
pancr <- allFitnessEffects(
data.frame(parent = c("Root", rep("KRAS", 4),
"SMAD4", "CDNK2A",
"TP53", "TP53", "MLL3"),
child = c("KRAS","SMAD4", "CDNK2A",
"TP53", "MLL3",
rep("PXDN", 3), rep("TGFBR2", 2)),
s = 0.05,
sh = -0.9,
typeDep = "MN"),
drvNames = c("KRAS", "SMAD4", "CDNK2A", "TP53",
"MLL3", "TGFBR2", "PXDN"))
Nindiv <- 100
## keepEvery = 1
t_exp1 <- system.time(
exp1 <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_mc1 <- system.time(
mc1 <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = 1,
model = "McFL",
mc.cores = 1))["elapsed"]
## keepEvery = NA
t_exp2 <- system.time(
exp2 <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
t_mc2 <- system.time(
mc2 <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = NA,
model = "McFL",
mc.cores = 1))["elapsed"]
### exp3 to exp6
t_exp3 <- system.time(
exp3 <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e4,
p2 = 0.1, n2 = 5e5,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp4 <- system.time(
exp4 <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e4,
p2 = 0.1, n2 = 5e5,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp5 <- system.time(
exp5 <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e5,
p2 = 0.1, n2 = 5e7,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp6 <- system.time(
exp6 <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e5,
p2 = 0.1, n2 = 5e7,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
####################################################
###### onlyCancer = FALSE
## keepEvery = 1
t_exp1_noc <- system.time(
exp1_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_mc1_noc <- system.time(
mc1_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = 1,
model = "McFL",
mc.cores = 1))["elapsed"]
## keepEvery = NA
t_exp2_noc <- system.time(
exp2_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
t_mc2_noc <- system.time(
mc2_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = "default",
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = NA,
model = "McFL",
mc.cores = 1))["elapsed"]
### exp3_noc to exp6_noc
t_exp3_noc <- system.time(
exp3_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e4,
p2 = 0.1, n2 = 5e5,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp4_noc <- system.time(
exp4_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e4,
p2 = 0.1, n2 = 5e5,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp5_noc <- system.time(
exp5_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e5,
p2 = 0.1, n2 = 5e7,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = 1,
model = "Exp",
mc.cores = 1))["elapsed"]
t_exp6_noc <- system.time(
exp6_noc <- oncoSimulPop(Nindiv, pancr,
detectionProb = c(PDBaseline = 5e5,
p2 = 0.1, n2 = 5e7,
checkSizePEvery = 20),
detectionSize = NA,
detectionDrivers = NA,
finalTime = NA, onlyCancer = FALSE,
keepPhylog = TRUE, keepEvery = NA,
model = "Exp",
mc.cores = 1))["elapsed"]
benchmark_1_0.05 <- all_sim_stats(exp1, mc1, exp2, mc2, exp3, exp4, exp5, exp6,
exp1_noc, mc1_noc, exp2_noc, mc2_noc, exp3_noc, exp4_noc, exp5_noc, exp6_noc
)
## Add the info about key settings
benchmark_1_0.05$keepEvery <- c(1, 1, NA, NA, 1, NA, 1, NA,
1, 1, NA, NA, 1, NA, 1, NA)
benchmark_1_0.05$PDBaseline <- c(rep(1.2 * 500, 4), 5e4, 5e4, 5e5, 5e5,
rep(1.2 * 500, 4), 5e4, 5e4, 5e5, 5e5)
benchmark_1_0.05$n2 <- c(rep(2 * 500, 4), 5e5, 5e5, 5e7, 5e7,
rep(2 * 500, 4), 5e5, 5e5, 5e7, 5e7)
benchmark_1_0.05$onlyCancer <- c(rep(TRUE, 8), rep(FALSE, 8))
save(file = "../../data/benchmark_1_0.05.RData", benchmark_1_0.05)
gc()
## ######################################################################
## ######################################################################
## ############### ##############
## ############### If you do it by hand ... ##############
## ############### ##############
## ######################################################################
## ######################################################################
## cat("\n\n\n t_exp1 = ", t_exp1, "\n")
## object.size(exp1)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp1, "[[", "NumClones")))
## summary(unlist(lapply(exp1, "[[", "NumIter")))
## summary(unlist(lapply(exp1, "[[", "FinalTime")))
## summary(unlist(lapply(exp1, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_mc1 = ", t_mc1, "\n")
## object.size(mc1)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(mc1, "[[", "NumClones")))
## summary(unlist(lapply(mc1, "[[", "NumIter")))
## summary(unlist(lapply(mc1, "[[", "FinalTime")))
## summary(unlist(lapply(mc1, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp2 = ", t_exp2, "\n")
## object.size(exp2)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp2, "[[", "NumClones")))
## summary(unlist(lapply(exp2, "[[", "NumIter")))
## summary(unlist(lapply(exp2, "[[", "FinalTime")))
## summary(unlist(lapply(exp2, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_mc2 = ", t_mc2, "\n")
## object.size(mc2)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(mc2, "[[", "NumClones")))
## summary(unlist(lapply(mc2, "[[", "NumIter")))
## summary(unlist(lapply(mc2, "[[", "FinalTime")))
## summary(unlist(lapply(mc2, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp3 = ", t_exp3, "\n")
## object.size(exp3)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp3, "[[", "NumClones")))
## summary(unlist(lapply(exp3, "[[", "NumIter")))
## summary(unlist(lapply(exp3, "[[", "FinalTime")))
## summary(unlist(lapply(exp3, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp4 = ", t_exp4, "\n")
## object.size(exp4)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp4, "[[", "NumClones")))
## summary(unlist(lapply(exp4, "[[", "NumIter")))
## summary(unlist(lapply(exp4, "[[", "FinalTime")))
## summary(unlist(lapply(exp4, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp5 = ", t_exp5, "\n")
## object.size(exp5)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp5, "[[", "NumClones")))
## summary(unlist(lapply(exp5, "[[", "NumIter")))
## summary(unlist(lapply(exp5, "[[", "FinalTime")))
## summary(unlist(lapply(exp5, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp6 = ", t_exp6, "\n")
## object.size(exp6)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp6, "[[", "NumClones")))
## summary(unlist(lapply(exp6, "[[", "NumIter")))
## summary(unlist(lapply(exp6, "[[", "FinalTime")))
## summary(unlist(lapply(exp6, "[[", "TotalPopSize")))
## ## Median runs until cancer
## lapply(list(exp1, mc1, exp2, mc2, exp3, exp4, exp5, exp6),
## function(y) median(unlist(lapply(y, function(x) x$other$attemptsUsed))))
## cat("\n\n\n t_exp1_noc = ", t_exp1_noc, "\n")
## object.size(exp1_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp1_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp1_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp1_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp1_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_mc1_noc = ", t_mc1_noc, "\n")
## object.size(mc1_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(mc1_noc, "[[", "NumClones")))
## summary(unlist(lapply(mc1_noc, "[[", "NumIter")))
## summary(unlist(lapply(mc1_noc, "[[", "FinalTime")))
## summary(unlist(lapply(mc1_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp2_noc = ", t_exp2_noc, "\n")
## object.size(exp2_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp2_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp2_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp2_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp2_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_mc2_noc = ", t_mc2_noc, "\n")
## object.size(mc2_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(mc2_noc, "[[", "NumClones")))
## summary(unlist(lapply(mc2_noc, "[[", "NumIter")))
## summary(unlist(lapply(mc2_noc, "[[", "FinalTime")))
## summary(unlist(lapply(mc2_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp3_noc = ", t_exp3_noc, "\n")
## object.size(exp3_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp3_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp3_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp3_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp3_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp4_noc = ", t_exp4_noc, "\n")
## object.size(exp4_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp4_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp4_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp4_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp4_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp5_noc = ", t_exp5_noc, "\n")
## object.size(exp5_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp5_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp5_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp5_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp5_noc, "[[", "TotalPopSize")))
## cat("\n\n")
## cat("\n\n\n t_exp6_noc = ", t_exp6_noc, "\n")
## object.size(exp6_noc)/(Nindiv * 1024^2)
## cat("\n\n")
## summary(unlist(lapply(exp6_noc, "[[", "NumClones")))
## summary(unlist(lapply(exp6_noc, "[[", "NumIter")))
## summary(unlist(lapply(exp6_noc, "[[", "FinalTime")))
## summary(unlist(lapply(exp6_noc, "[[", "TotalPopSize")))
## ## Median runs until cancer
## lapply(list(exp1_noc, mc1_noc, exp2_noc, mc2_noc, exp3_noc, exp4_noc, exp5_noc, exp6_noc),
## function(y) median(unlist(lapply(y, function(x) x$other$attemptsUsed))))
## ## bench1 <- data.frame(
## ## time = c(t_exp1, t_mc1, t_exp2, t_mc2, t_exp3, t_exp4, t_exp5, t_exp6),
## ## size = unlist(lapply(list(exp1, mc1, exp2, mc2, exp3, exp4, exp5, exp6),
## ## object.size))/(Nindiv * 1024^2),
## ## lapply(list(exp1, mc1, exp2, mc2, exp3, exp4, exp5, exp6),
## ## function(y) median(unlist(lapply(y, function(x) x$other$attemptsUsed))))
## ## )
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