laboratory_scripts/user_file.R
In Thibaudpmx/QSPVP: Parameter Space Mapping algorithms to accelerate the creation of plausible Virtual Patients
library(QSPVP)
library(profvis)
library(microbenchmark)
# Step 1 create or load project ---------------------------------------------------
create_VT_Project("D:/these/Second_project/QSP/modeling_work/VT_simeoni")
# Step 2: fulfil the file
shell.exec("D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config.r")
shell.exec("D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/2_verif.r")
# test
ind_param = tibble(k1 = 3, k2 = 0.4, ke = 27.5/52.8, lambda0 = 0.06, lambda1 = 6, Vd = 52.8)
celltheque
dose = 100
add_events <- tibble(cmt = c("Central")) %>% # Administration sampling, with "concX" being replaced by concentration
mutate(time = 0, amt = dose)
#
res <- simulations(ind_param = ind_param, add_events = add_events,returnSim = T)
simulations(ind_param = ind_param, add_events = add_events,returnSim = T) %>%
filter(time >23)
simulations(ind_param = ind_param, add_events = add_events,returnSim = F)
#
# res %>%
# gather("key", "value", Conc, tumVol) %>%
# ggplot()+
# geom_line(aes(time, value))+
# facet_wrap(~key, scales = "free")+
# scale_y_log10()
read.table("D:/Peccary_Annexe/Exemple_demo/Simeoni/closeIV/IndividualParameters/estimatedIndividualParameters.txt", header = T, sep = ",") %>%
as_tibble %>%
filter(id == 218)
# Step3: create celltheque
#%>%
# slice(1:(3*6000))# what you want to add in your celltheque as individuals
# targets <- tribble(~protocols, ~time, ~cmt, ~ min, ~max,
# "dose0",10,"tumVol", 50, 120,
# "dose0",25,"tumVol", 70,220,
# "dose0",0,"Conc",0,1,
# "dose50",10,"tumVol", 40,125,
# "dose50",25,"tumVol", 30,70,
# "dose50",10,"Conc", 1e-6,1,
# "dose100",25,"tumVol", 3,167)
# Two compart ---------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
self$param_increase
self$make_filters()
# self$set_targets(filter = cmt == "tumVol", ntime = 6)
self$set_targets(filter = Dose ==50 & cmt == "tumVol",timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0,8,0.2),
ke = 1 ,#* seq(0.6,1.4,0.2),
lambda0 =seq(0,0.16,0.025),
lambda1 = c(12),
Vd = 40) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = T)
self$plot_VP()
self$plot_2D(x = k2, y = lambda0,plotoreturn = 1, add_point = T)
self$plot_2D(x = k2, y = lambda0,toaddneg = VP_df, plotMain = T)
self$n_filter_reduc()
# self$fill_simul()
self$filters_neg_above
self$filters_neg_below
self$filters_pos_below
self$filters_pos_above
# 2cm big -----------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = cmt == "tumVol" ,timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0,8,0.0025),
ke = 1 ,#* seq(0.6,1.4,0.2),
lambda0 =seq(0,0.16,0.0025),
lambda1 = c(12),
w0 = 50,
Vd = 40) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
# self$add_VP(VP_df, fillatend = F, reducefilteratend = T, npersalve = 2000, time_compteur = F, methodFilter = 1)
self$add_VP(VP_df, fillatend = F, reducefilteratend = T, npersalve = 2000, time_compteur = F, methodFilter = 2, use_green_filter = F)
self$n_filter_reduc()
self$plot_VP(nmax = 2000)
self$targets
self$poolVP %>%
unnest(simul) %>%
filter(time == 12 & tumVol < 21) %>%
pull(cellid) -> idtarget
self$plot_2D(x = k2, y = lambda0, plotMain = F, plotoreturn = 1, add_point = T)
self$n_filter_reduc()
ti <- Sys.time()
self$fill_simul()
difftime( Sys.time(), ti, units = "sec")
self$filters_neg_above
self$filters_neg_below
self$filters_pos_above
self$filters_pos_below
# three compart ---------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = Dose == 50 & cmt == "tumVol",timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0,8,0.5),
ke = 1 ,#* seq(0.6,1.4,0.2),
w0 = 50,
lambda0 =seq(0.04,0.16,0.025),
lambda1 = c(12),
Vd = c(20:40)) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
# VP_df <- crossing(k1 = c(0.5),
# k2 = seq(0,8,0.1),
# ke = 1 ,#* seq(0.6,1.4,0.2),
# lambda0 =seq(0,0.16,0.01),
# lambda1 = c(12),
# Vd = c(0:40)) %>% #c(0.8,1,1.2)) %>%
# map_df(function(x){
#
# if(is.character(x)) return(x)
# round(x,3)
#
# } )
self$add_VP(VP_df, fillatend =F, reducefilteratend = F)
self$plot_VP()
self$n_filter_reduc()
# self$plot_2D(k2, lambda0, plotMain = T)
self$plot_3D(k2, lambda0, Vd)
self$filters_neg_above
self$filters_neg_below
self$filters_pos_above
self$filters_pos_below
# 4 dimensions and more
# Infinite dimension ------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
#
# saveRDS(self, "D:/these/Second_project/QSP/modeling_work/VT_simeoni/longrun.RDS")
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = Dose == 50 & cmt == "tumVol",timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
w0 = 50,
k2 = seq(0,8,0.1),
ke = seq(0.6,1.4,0.4),
lambda0 =seq(0,0.16,0.03),
lambda1 = c(10,12,14,33),
Vd = c(0:40)) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
t0 <- Sys.time()
self$add_VP(VP_df, fillatend = F, reducefilteratend = F,use_green_filter = T, npersalve = 2000, time_compteur = T, pctActivGreen = 0.75)
Sys.time() - t0
self$timeTrack
self$plot_VP(nmax = 2000)
self$n_filter_reduc()
self$compute_zone_maybe()
self$compute_zone_sure()
self$zone_maybe
self$zone_sure
# verif
self <- VP_proj_creator$new()
#
# saveRDS(self, "D:/these/Second_project/QSP/modeling_work/VT_simeoni/longrun.RDS")
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = Dose == 50 & cmt == "tumVol",timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0.1,0.2,0.05),
ke = seq(0.6,1,0.1),
lambda0 =seq(0.03,0.06,0.01),
lambda1 = seq(10,12,0.5),
Vd = seq(13,14,0.1)) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F,use_green_filter = F, npersalve = 2000, time_compteur = F, pctActivGreen = 0.75)
self$plot_VP()
# w0 wrong ----------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(manual = tibble(protocol = "dose50", cmt = "tumVol", time = 40, min = 80, max = 85))
VP_df <- crossing(k1 = c(0),
k2 = 0:8,
ke = 1 ,#* seq(0.6,1.4,0.2),
lambda0 = 50,
lambda1 = c(20,100,1),
w0 = seq(20,400,1),
Vd = 40) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
# self$add_VP(VP_df, fillatend = F, reducefilteratend = T, npersalve = 2000, time_compteur = F, methodFilter = 1)
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, npersalve = 2000, time_compteur = F, methodFilter = 2, use_green_filter = F)
# PK AND PD ---------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
# self$set_targets(filter = cmt == "tumVol", ntime = 6)
self$set_targets(filter = Dose ==50 ,timeforce = c(3,19, 30,45))
tar <- self$targets ; tar$min[[5]] <- 0.005; tar$max[[2]] <-100; tar$max[[3]] <- 200; tar$max[[5]] <- 300
self$targets <- tar
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0,8,0.1),
ke = seq(0,3,0.2) ,#* seq(0.6,1.4,0.2),
lambda0 = c(0.025),
lambda1 = c(12),
Vd = 40) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend =F, use_green_filter = F)
self$plot_VP()
self$poolVP
# Lindner ! --------------------------------------------------------------
# Defining targets
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner.r")
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",740,"Pore", 20, 23
))
VP_df <- crossing(Bcl20 = seq(100,1000,100),
Bclxl0 = seq(100,1000,100),
Mcl10 = 50 ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,100),
PUMA0 =seq(100,1000,100),
NOXA0 = seq(100,1000,100),
BAXc0 = 1000,
BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
lindner$add_VP(VP_df, fillatend = F, reducefilteratend = F)
self$plot_VP()
# Massive screening -------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner.r")
self$targets <- tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",740,"Pore", 20, 20.0001
)
domain <- tribble(~param, ~from, ~to, ~step,
"Bcl20", 0, 1000, 1 ,
"Bclxl0", 0, 1000, 1,
"Mcl10", 0,1000,1,
"BIM0", 0, 1000, 1 ,
"PUMA0", 0, 1000, 1,
"NOXA0", 0,1000,1,
"BAXc0", 1000,1000,0,
"BAK0" , 1000,1000,0
)
demo <- self$big_screening(domain)
demo2 <- self$big_screening(domain = demo[[1]])
demo3 <- self$big_screening(domain = demo2[[1]])
demo3 %>%
unnest() %>%
filter(time == 740) %>%
pull(Pore)
# Test IF -----------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new(sourcefile = "file:///D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_deux_elim.r")
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"dose50",20,"Conc", 0.1, 23
))
self$param_reduce
self$make_filters(cmt = "Conc")
VP_df <- crossing( k21 = seq(0,1,0.1),
k12 = seq(0,1,0.1),
ke = seq(0,1,0.1),
ke2 = seq(0,1,0.1),
V1 = seq(1,10,1)
) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F)
self$plot_VP(nmax = 1000)
# Non usable param Handle -------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
#
# saveRDS(self, "D:/these/Second_project/QSP/modeling_work/VT_simeoni/longrun.RDS")
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = cmt == "tumVol",timeforce = c(12,19, 30,45))
self$targets$min <- map2_dbl(self$targets$min, self$targets$max, ~ mean(c(.x, .y))) %>% round
VP_df <- crossing(k2 = seq(0,8,0.1),
ke = 1 ,#* seq(0.6,1.4,0.2),
lambda0 =seq(0,0.16,0.01),
lambda1 = c(10,12,14,33),
Vd = c(0:40)) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
fix_df <- tibble(k1 = seq(0,2,0.5))
t0 <- Sys.time()
self$add_VP(VP_df,fix_df = fix_df, fillatend = F, reducefilteratend = F,use_green_filter = F, npersalve = 2000, time_compteur = F, pctActivGreen = 0.75)
Sys.time() - t0
self$plot_VP(nmax = 2000)
# Test Lindner normal -----------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",90,"TimeAbove", 1E-1, Inf
))
below <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
below$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",90,"TimeAbove", -Inf, 1E-1
))
VP_df <- crossing(Bcl20 = seq(100,1000,200),
Bclxl0 = seq(100,1000,200),
Mcl10 = c(0,50,100,150) ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,200),
PUMA0 =seq(100,1000,200),
NOXA0 = seq(100,1000,200),
BAXc0 = 1000,
BAK0 = 0) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
# VP_df <- crossing(Bcl20 = 500,
# Bclxl0 =500,
# Mcl10 = 50 ,#* seq(0.6,1.4,0.2),
# BIM0 = 500,
# PUMA0 = 500,
# NOXA0 = seq(100,1000,100),
# BAXc0 = 1000,
# BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
# map_df(function(x){
#
# if(is.character(x)) return(x)
# round(x,3)
#
# } )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
saveRDS(self, "D:/these/Second_project/QSP/modeling_work/VT_simeoni/death.RDS")
self$poolVP
below$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
self$p
self$poolVP %>%
filter(TimeAbove_BU !=0) %>%
slice(1:500) %>%
unnest() %>%
ggplot()+
geom_line(aes(time, Pore, group = factor(id)))+
geom_hline(yintercept = 10, col = "red")
# Test Lindner normal vs 1 drug -----------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
protocols <- list( unique = tibble(cmt = "Bcl2", time = 0, amt = 0),
apog = tibble(cmt = "ApoG2", time = 50, amt = 50))
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
self$protocols <- protocols
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",300,"TimeAbove", -Inf, 1E-1,
"apog",300,"TimeAbove", 1E-1, Inf
))
VP_df <- crossing(Bcl20 = seq(100,1000,200),
Bclxl0 = seq(100,1000,200),
Mcl10 = c(0,50,100,150) ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,200),
PUMA0 =seq(100,1000,200),
NOXA0 = seq(100,1000,200),
BAXc0 = 1000,
BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
self$poolVP %>%
arrange(id) %>%
unnest(simul) %>%
ggplot()+
geom_line(aes(time, Pore, group = id))+
facet_wrap(~protocol)+
geom_hline(yintercept = 10, col = "red")+
coord_cartesian(xlim = c(62,72))
self$poolVP %>%
unnest(simul)
# Test Lindner normal vs 1 drug -----------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
protocols <- list( unique = tibble(cmt = "Bcl2", time = 0, amt = 0),
apog = tibble(cmt = "ApoG2", time = 50, amt = 50),
ABT737 = tibble(cmt = "ABT737", time = 50, amt = 25))
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
self$protocols <- protocols
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",300,"TimeAbove", -Inf, 1E-1,
"apog",300,"TimeAbove", 1E-1, Inf,
"ABT737",300,"TimeAbove", -Inf, 1E-1
))
VP_df <- crossing(Bcl20 = seq(100,1000,200),
Bclxl0 = seq(100,1000,200),
Mcl10 = c(0,50,100,150) ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,200),
PUMA0 =seq(100,1000,200),
NOXA0 = seq(100,1000,200),
BAXc0 = 1000,
BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
self$poolVP %>%
arrange(id) %>%
unnest(simul) %>%
mutate(protocol = if_else(protocol == "unique", "No Drug" , protocol)) %>%
ggplot()+
geom_line(aes(time, Pore, group = id))+
facet_wrap(~protocol)+
geom_hline(yintercept = 10, col = "red")+
coord_cartesian(xlim = c(62,72))
# Test Lindner normal vs 1 drug -----------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
protocols <- list( unique = tibble(cmt = "Bcl2", time = 0, amt = 0),
apog = tibble(cmt = "ApoG2", time = 50, amt = 50),
ABT737 = tibble(cmt = "ABT737", time = 50, amt = 25))
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
self$protocols <- protocols
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",300,"TimeAbove", -Inf, 1E-1,
"apog",300,"TimeAbove", -Inf, 1E-1,
"ABT737",300,"TimeAbove", 1E-1, Inf
))
VP_df <- crossing(Bcl20 = seq(100,1000,200),
Bclxl0 = seq(100,1000,200),
Mcl10 = c(0,50,100,150) ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,200),
PUMA0 =seq(100,1000,200),
NOXA0 = seq(100,1000,200),
BAXc0 = 1000,
BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
self$compute_zone_maybe()
self$poolVP %>%
arrange(id) %>%
unnest(simul) %>%
ggplot()+
geom_line(aes(time, Pore, group = id))+
facet_wrap(~protocol)+
geom_hline(yintercept = 10, col = "red")+
coord_cartesian(xlim = c(62,72))
Thibaudpmx/QSPVP documentation built on Nov. 14, 2022, 7:07 p.m.
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library(QSPVP)
library(profvis)
library(microbenchmark)
# Step 1 create or load project ---------------------------------------------------
create_VT_Project("D:/these/Second_project/QSP/modeling_work/VT_simeoni")
# Step 2: fulfil the file
shell.exec("D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config.r")
shell.exec("D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/2_verif.r")
# test
ind_param = tibble(k1 = 3, k2 = 0.4, ke = 27.5/52.8, lambda0 = 0.06, lambda1 = 6, Vd = 52.8)
celltheque
dose = 100
add_events <- tibble(cmt = c("Central")) %>% # Administration sampling, with "concX" being replaced by concentration
mutate(time = 0, amt = dose)
#
res <- simulations(ind_param = ind_param, add_events = add_events,returnSim = T)
simulations(ind_param = ind_param, add_events = add_events,returnSim = T) %>%
filter(time >23)
simulations(ind_param = ind_param, add_events = add_events,returnSim = F)
#
# res %>%
# gather("key", "value", Conc, tumVol) %>%
# ggplot()+
# geom_line(aes(time, value))+
# facet_wrap(~key, scales = "free")+
# scale_y_log10()
read.table("D:/Peccary_Annexe/Exemple_demo/Simeoni/closeIV/IndividualParameters/estimatedIndividualParameters.txt", header = T, sep = ",") %>%
as_tibble %>%
filter(id == 218)
# Step3: create celltheque
#%>%
# slice(1:(3*6000))# what you want to add in your celltheque as individuals
# targets <- tribble(~protocols, ~time, ~cmt, ~ min, ~max,
# "dose0",10,"tumVol", 50, 120,
# "dose0",25,"tumVol", 70,220,
# "dose0",0,"Conc",0,1,
# "dose50",10,"tumVol", 40,125,
# "dose50",25,"tumVol", 30,70,
# "dose50",10,"Conc", 1e-6,1,
# "dose100",25,"tumVol", 3,167)
# Two compart ---------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
self$param_increase
self$make_filters()
# self$set_targets(filter = cmt == "tumVol", ntime = 6)
self$set_targets(filter = Dose ==50 & cmt == "tumVol",timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0,8,0.2),
ke = 1 ,#* seq(0.6,1.4,0.2),
lambda0 =seq(0,0.16,0.025),
lambda1 = c(12),
Vd = 40) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = T)
self$plot_VP()
self$plot_2D(x = k2, y = lambda0,plotoreturn = 1, add_point = T)
self$plot_2D(x = k2, y = lambda0,toaddneg = VP_df, plotMain = T)
self$n_filter_reduc()
# self$fill_simul()
self$filters_neg_above
self$filters_neg_below
self$filters_pos_below
self$filters_pos_above
# 2cm big -----------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = cmt == "tumVol" ,timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0,8,0.0025),
ke = 1 ,#* seq(0.6,1.4,0.2),
lambda0 =seq(0,0.16,0.0025),
lambda1 = c(12),
w0 = 50,
Vd = 40) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
# self$add_VP(VP_df, fillatend = F, reducefilteratend = T, npersalve = 2000, time_compteur = F, methodFilter = 1)
self$add_VP(VP_df, fillatend = F, reducefilteratend = T, npersalve = 2000, time_compteur = F, methodFilter = 2, use_green_filter = F)
self$n_filter_reduc()
self$plot_VP(nmax = 2000)
self$targets
self$poolVP %>%
unnest(simul) %>%
filter(time == 12 & tumVol < 21) %>%
pull(cellid) -> idtarget
self$plot_2D(x = k2, y = lambda0, plotMain = F, plotoreturn = 1, add_point = T)
self$n_filter_reduc()
ti <- Sys.time()
self$fill_simul()
difftime( Sys.time(), ti, units = "sec")
self$filters_neg_above
self$filters_neg_below
self$filters_pos_above
self$filters_pos_below
# three compart ---------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = Dose == 50 & cmt == "tumVol",timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0,8,0.5),
ke = 1 ,#* seq(0.6,1.4,0.2),
w0 = 50,
lambda0 =seq(0.04,0.16,0.025),
lambda1 = c(12),
Vd = c(20:40)) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
# VP_df <- crossing(k1 = c(0.5),
# k2 = seq(0,8,0.1),
# ke = 1 ,#* seq(0.6,1.4,0.2),
# lambda0 =seq(0,0.16,0.01),
# lambda1 = c(12),
# Vd = c(0:40)) %>% #c(0.8,1,1.2)) %>%
# map_df(function(x){
#
# if(is.character(x)) return(x)
# round(x,3)
#
# } )
self$add_VP(VP_df, fillatend =F, reducefilteratend = F)
self$plot_VP()
self$n_filter_reduc()
# self$plot_2D(k2, lambda0, plotMain = T)
self$plot_3D(k2, lambda0, Vd)
self$filters_neg_above
self$filters_neg_below
self$filters_pos_above
self$filters_pos_below
# 4 dimensions and more
# Infinite dimension ------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
#
# saveRDS(self, "D:/these/Second_project/QSP/modeling_work/VT_simeoni/longrun.RDS")
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = Dose == 50 & cmt == "tumVol",timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
w0 = 50,
k2 = seq(0,8,0.1),
ke = seq(0.6,1.4,0.4),
lambda0 =seq(0,0.16,0.03),
lambda1 = c(10,12,14,33),
Vd = c(0:40)) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
t0 <- Sys.time()
self$add_VP(VP_df, fillatend = F, reducefilteratend = F,use_green_filter = T, npersalve = 2000, time_compteur = T, pctActivGreen = 0.75)
Sys.time() - t0
self$timeTrack
self$plot_VP(nmax = 2000)
self$n_filter_reduc()
self$compute_zone_maybe()
self$compute_zone_sure()
self$zone_maybe
self$zone_sure
# verif
self <- VP_proj_creator$new()
#
# saveRDS(self, "D:/these/Second_project/QSP/modeling_work/VT_simeoni/longrun.RDS")
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = Dose == 50 & cmt == "tumVol",timeforce = c(12,19, 30,45))
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0.1,0.2,0.05),
ke = seq(0.6,1,0.1),
lambda0 =seq(0.03,0.06,0.01),
lambda1 = seq(10,12,0.5),
Vd = seq(13,14,0.1)) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F,use_green_filter = F, npersalve = 2000, time_compteur = F, pctActivGreen = 0.75)
self$plot_VP()
# w0 wrong ----------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(manual = tibble(protocol = "dose50", cmt = "tumVol", time = 40, min = 80, max = 85))
VP_df <- crossing(k1 = c(0),
k2 = 0:8,
ke = 1 ,#* seq(0.6,1.4,0.2),
lambda0 = 50,
lambda1 = c(20,100,1),
w0 = seq(20,400,1),
Vd = 40) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
# self$add_VP(VP_df, fillatend = F, reducefilteratend = T, npersalve = 2000, time_compteur = F, methodFilter = 1)
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, npersalve = 2000, time_compteur = F, methodFilter = 2, use_green_filter = F)
# PK AND PD ---------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
# self$set_targets(filter = cmt == "tumVol", ntime = 6)
self$set_targets(filter = Dose ==50 ,timeforce = c(3,19, 30,45))
tar <- self$targets ; tar$min[[5]] <- 0.005; tar$max[[2]] <-100; tar$max[[3]] <- 200; tar$max[[5]] <- 300
self$targets <- tar
VP_df <- crossing(k1 = c(0.5),
k2 = seq(0,8,0.1),
ke = seq(0,3,0.2) ,#* seq(0.6,1.4,0.2),
lambda0 = c(0.025),
lambda1 = c(12),
Vd = 40) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend =F, use_green_filter = F)
self$plot_VP()
self$poolVP
# Lindner ! --------------------------------------------------------------
# Defining targets
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner.r")
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",740,"Pore", 20, 23
))
VP_df <- crossing(Bcl20 = seq(100,1000,100),
Bclxl0 = seq(100,1000,100),
Mcl10 = 50 ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,100),
PUMA0 =seq(100,1000,100),
NOXA0 = seq(100,1000,100),
BAXc0 = 1000,
BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
lindner$add_VP(VP_df, fillatend = F, reducefilteratend = F)
self$plot_VP()
# Massive screening -------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner.r")
self$targets <- tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",740,"Pore", 20, 20.0001
)
domain <- tribble(~param, ~from, ~to, ~step,
"Bcl20", 0, 1000, 1 ,
"Bclxl0", 0, 1000, 1,
"Mcl10", 0,1000,1,
"BIM0", 0, 1000, 1 ,
"PUMA0", 0, 1000, 1,
"NOXA0", 0,1000,1,
"BAXc0", 1000,1000,0,
"BAK0" , 1000,1000,0
)
demo <- self$big_screening(domain)
demo2 <- self$big_screening(domain = demo[[1]])
demo3 <- self$big_screening(domain = demo2[[1]])
demo3 %>%
unnest() %>%
filter(time == 740) %>%
pull(Pore)
# Test IF -----------------------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new(sourcefile = "file:///D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_deux_elim.r")
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"dose50",20,"Conc", 0.1, 23
))
self$param_reduce
self$make_filters(cmt = "Conc")
VP_df <- crossing( k21 = seq(0,1,0.1),
k12 = seq(0,1,0.1),
ke = seq(0,1,0.1),
ke2 = seq(0,1,0.1),
V1 = seq(1,10,1)
) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F)
self$plot_VP(nmax = 1000)
# Non usable param Handle -------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new()
#
# saveRDS(self, "D:/these/Second_project/QSP/modeling_work/VT_simeoni/longrun.RDS")
# self$set_targets(filter = Dose == 50 & cmt == "tumVol", ntime = 8)
self$set_targets(filter = cmt == "tumVol",timeforce = c(12,19, 30,45))
self$targets$min <- map2_dbl(self$targets$min, self$targets$max, ~ mean(c(.x, .y))) %>% round
VP_df <- crossing(k2 = seq(0,8,0.1),
ke = 1 ,#* seq(0.6,1.4,0.2),
lambda0 =seq(0,0.16,0.01),
lambda1 = c(10,12,14,33),
Vd = c(0:40)) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
fix_df <- tibble(k1 = seq(0,2,0.5))
t0 <- Sys.time()
self$add_VP(VP_df,fix_df = fix_df, fillatend = F, reducefilteratend = F,use_green_filter = F, npersalve = 2000, time_compteur = F, pctActivGreen = 0.75)
Sys.time() - t0
self$plot_VP(nmax = 2000)
# Test Lindner normal -----------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",90,"TimeAbove", 1E-1, Inf
))
below <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
below$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",90,"TimeAbove", -Inf, 1E-1
))
VP_df <- crossing(Bcl20 = seq(100,1000,200),
Bclxl0 = seq(100,1000,200),
Mcl10 = c(0,50,100,150) ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,200),
PUMA0 =seq(100,1000,200),
NOXA0 = seq(100,1000,200),
BAXc0 = 1000,
BAK0 = 0) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
# VP_df <- crossing(Bcl20 = 500,
# Bclxl0 =500,
# Mcl10 = 50 ,#* seq(0.6,1.4,0.2),
# BIM0 = 500,
# PUMA0 = 500,
# NOXA0 = seq(100,1000,100),
# BAXc0 = 1000,
# BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
# map_df(function(x){
#
# if(is.character(x)) return(x)
# round(x,3)
#
# } )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
saveRDS(self, "D:/these/Second_project/QSP/modeling_work/VT_simeoni/death.RDS")
self$poolVP
below$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
self$p
self$poolVP %>%
filter(TimeAbove_BU !=0) %>%
slice(1:500) %>%
unnest() %>%
ggplot()+
geom_line(aes(time, Pore, group = factor(id)))+
geom_hline(yintercept = 10, col = "red")
# Test Lindner normal vs 1 drug -----------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
protocols <- list( unique = tibble(cmt = "Bcl2", time = 0, amt = 0),
apog = tibble(cmt = "ApoG2", time = 50, amt = 50))
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
self$protocols <- protocols
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",300,"TimeAbove", -Inf, 1E-1,
"apog",300,"TimeAbove", 1E-1, Inf
))
VP_df <- crossing(Bcl20 = seq(100,1000,200),
Bclxl0 = seq(100,1000,200),
Mcl10 = c(0,50,100,150) ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,200),
PUMA0 =seq(100,1000,200),
NOXA0 = seq(100,1000,200),
BAXc0 = 1000,
BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
self$poolVP %>%
arrange(id) %>%
unnest(simul) %>%
ggplot()+
geom_line(aes(time, Pore, group = id))+
facet_wrap(~protocol)+
geom_hline(yintercept = 10, col = "red")+
coord_cartesian(xlim = c(62,72))
self$poolVP %>%
unnest(simul)
# Test Lindner normal vs 1 drug -----------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
protocols <- list( unique = tibble(cmt = "Bcl2", time = 0, amt = 0),
apog = tibble(cmt = "ApoG2", time = 50, amt = 50),
ABT737 = tibble(cmt = "ABT737", time = 50, amt = 25))
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
self$protocols <- protocols
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",300,"TimeAbove", -Inf, 1E-1,
"apog",300,"TimeAbove", 1E-1, Inf,
"ABT737",300,"TimeAbove", -Inf, 1E-1
))
VP_df <- crossing(Bcl20 = seq(100,1000,200),
Bclxl0 = seq(100,1000,200),
Mcl10 = c(0,50,100,150) ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,200),
PUMA0 =seq(100,1000,200),
NOXA0 = seq(100,1000,200),
BAXc0 = 1000,
BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
self$poolVP %>%
arrange(id) %>%
unnest(simul) %>%
mutate(protocol = if_else(protocol == "unique", "No Drug" , protocol)) %>%
ggplot()+
geom_line(aes(time, Pore, group = id))+
facet_wrap(~protocol)+
geom_hline(yintercept = 10, col = "red")+
coord_cartesian(xlim = c(62,72))
# Test Lindner normal vs 1 drug -----------------------------------------------------
source("D:/these/Second_project/QSP/QSPVP/R/R6object.R")
protocols <- list( unique = tibble(cmt = "Bcl2", time = 0, amt = 0),
apog = tibble(cmt = "ApoG2", time = 50, amt = 50),
ABT737 = tibble(cmt = "ABT737", time = 50, amt = 25))
self <- VP_proj_creator$new(sourcefile = "D:/these/Second_project/QSP/modeling_work/VT_simeoni/1_user_inputs/1_config_Lindner_origin.r")
self$protocols <- protocols
self$set_targets(manual = tribble(~protocol, ~time, ~cmt, ~ min, ~max,
"unique",300,"TimeAbove", -Inf, 1E-1,
"apog",300,"TimeAbove", -Inf, 1E-1,
"ABT737",300,"TimeAbove", 1E-1, Inf
))
VP_df <- crossing(Bcl20 = seq(100,1000,200),
Bclxl0 = seq(100,1000,200),
Mcl10 = c(0,50,100,150) ,#* seq(0.6,1.4,0.2),
BIM0 = seq(100,1000,200),
PUMA0 =seq(100,1000,200),
NOXA0 = seq(100,1000,200),
BAXc0 = 1000,
BAK0 = 1000) %>% #c(0.8,1,1.2)) %>%
map_df(function(x){
if(is.character(x)) return(x)
round(x,3)
} )
self$add_VP(VP_df, fillatend = F, reducefilteratend = F, use_green_filter = T, keep = "Pore")
self$compute_zone_maybe()
self$poolVP %>%
arrange(id) %>%
unnest(simul) %>%
ggplot()+
geom_line(aes(time, Pore, group = id))+
facet_wrap(~protocol)+
geom_hline(yintercept = 10, col = "red")+
coord_cartesian(xlim = c(62,72))
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