featuring : nouvelle version du mechanisticModel

refactor : correction erreur pour fixer des variables
output : suppression des outputs inutiles

settings.json

 {
   "analysis_name": "Identifi",
-  "r_script": "identif_mu.R",
+  "r_script": "identifiabilite.R",
   "py_env": "base",
   "reticulate_env": "",
   "logfile": "install.log",
@@ -18,7 +18,7 @@
     "lib": ""
   },
   "dependencies": {
-    "R-local": ["mechanisticModel.tar.gz"],
+    "R-local": ["mechanisticModel_1.5.6.tar.gz"],
     "R": ["glue","doParallel"],
     "reticulate": [],
     "python": []

src/identif_alpha.R

@@ -5,22 +5,18 @@ library(doParallel)
 
 
 
-control <- saemix::saemixControl(map = FALSE,fix.seed = T, fim = FALSE, ll.is = FALSE, nbiter.saemix = c(300, 50), nb.chains = 1, nbiter.burn = 5, nbiter.mcmc = c(2, 2, 2, 0), displayProgress = FALSE, print= FALSE, save = FALSE,  nbdisplay = 50)
+control <- saemix::saemixControl(map = FALSE,fix.seed = T, fim = FALSE, ll.is = FALSE, nbiter.saemix = c(300, 50), nb.chains = 1, nbiter.burn = 5, nbiter.mcmc = c(2, 2, 2, 0), displayProgress = FALSE, print= FALSE, save = FALSE,  nbdisplay = 50, save.graphs = F)
 
 alpha_pop = exp(-6.34)
 mu_pop = exp(-26.8)
 sigma = 1
-omega_alpha = 1
-omega_mu = 0
+omega_alpha = 3.37
+omega_mu = 3.78
 
-true_v = c(alpha_pop,mu_pop,sigma,omega_alpha,omega_mu)
 
+true_v = c(alpha_pop,mu_pop,sigma,omega_alpha,omega_mu)
 
 
-alpha <- c()
-mu <- c()
-omega_alpha <- c()
-omega_mu <- c()
 
 Ncpus <- parallel::detectCores() - 1
 cl <- parallel::makeCluster(Ncpus)
@@ -40,17 +36,23 @@ res <- foreach::foreach(i=1:100 , .packages = c("tidyverse","mechanisticModel"))
     Surv(tps, event) ~ TTR(vdiag),
     log(alpha) ~ 1, log(mu) ~ 1,
     data = JD1,
-    alpha_0 = 0.001, mu_0 = 2e-12, sigma_0 = 1, omega_0 = c(1, 0),
+    alpha_0 = 0.001, mu_0 = 2e-12, sigma_0 = sigma, omega_0 = c(3.37, 1),
     beta_0 = list(alpha = numeric(), mu = numeric()),
     options = control
   ) 
-  m = fit(m, silent = T, N_sim_surv = 0)
+    m = fit(m, silent = T, N_sim_surv = 0, omega.estim = c(1, 0), fixed.estim = c(1, 0, 0))
 }
 
 
 parallel::stopCluster(cl)
 
 
+alpha <- c()
+mu <- c()
+omega_alpha <- c()
+omega_mu <- c()
+
+
 for(i in 1:100){
   alpha <- append(alpha,unlist(res[[i]]$coefs[1])[1])
   mu <- append(mu,unlist(res[[i]]$coefs[1])[2])

src/identif_mu.R

@@ -5,34 +5,27 @@ library(doParallel)
 
 
 
-control <- saemix::saemixControl(map = FALSE,fix.seed = T, fim = FALSE, ll.is = FALSE, nbiter.saemix = c(300, 50), nb.chains = 1, nbiter.burn = 5, nbiter.mcmc = c(2, 2, 2, 0), displayProgress = FALSE, print= FALSE, save = FALSE,  nbdisplay = 50)
+control <- saemix::saemixControl(map = FALSE,fix.seed = T, fim = FALSE, ll.is = FALSE, nbiter.saemix = c(300, 50), nb.chains = 1, nbiter.burn = 5, nbiter.mcmc = c(2, 2, 2, 0), displayProgress = FALSE, print= FALSE, save = FALSE,  nbdisplay = 50, save.graphs = F)
 
 alpha_pop = exp(-6.34)
 mu_pop = exp(-26.8)
 sigma = 1
-omega_alpha = 0
-omega_mu = 1
+omega_alpha = 3.37
+omega_mu = 3.78
 
 true_v = c(alpha_pop,mu_pop,sigma,omega_alpha,omega_mu)
 
-
-
-alpha <- c()
-mu <- c()
-omega_alpha <- c()
-omega_mu <- c()
-
 Ncpus <- parallel::detectCores() - 1
 cl <- parallel::makeCluster(Ncpus)
 doParallel::registerDoParallel(cl)
 
-res <- foreach::foreach(i=1:100 , .packages = c("tidyverse","mechanisticModel"))%dopar%{
+res <- foreach::foreach(i=1:100, .packages = c("tidyverse","mechanisticModel"))%dopar%{
   
   set.seed(i)
   
   control$seed <- i
   
-  JD1 <- GDC(1000,22.38,1.33,exp(-6.34),exp(-26.8),1,0,1,20*365)
+  JD1 <- GDC(1000,22.38,1.33,exp(-6.34),exp(-26.8),1,3.37,3.78,20*365)
   JD1 <- JD1 %>% filter(tps > 0)
   
   
@@ -40,16 +33,20 @@ res <- foreach::foreach(i=1:100 , .packages = c("tidyverse","mechanisticModel"))
     Surv(tps, event) ~ TTR(vdiag),
     log(alpha) ~ 1, log(mu) ~ 1,
     data = JD1,
-    alpha_0 = 0.001, mu_0 = 2e-12, sigma_0 = 1, omega_0 = c(0, 1),
+    alpha_0 = 0.001, mu_0 = 2e-12, sigma_0 = sigma, omega_0 = c(1, 3.78),
     beta_0 = list(alpha = numeric(), mu = numeric()),
     options = control
   ) 
-  m = fit(m, silent = T, N_sim_surv = 0)
+  m = fit(m, silent = T, N_sim_surv = 0, omega.estim = c(0, 1), fixed.estim = c(0, 1, 0))
 }
 
 
 parallel::stopCluster(cl)
 
+alpha <- c()
+mu <- c()
+omega_alpha <- c()
+omega_mu <- c()
 
 for(i in 1:100){
   alpha <- append(alpha,unlist(res[[i]]$coefs[1])[1])

src/identifiabilite.R

@@ -5,7 +5,7 @@ library(doParallel)
 
 
 
-control <- saemix::saemixControl(map = FALSE,fix.seed = T, fim = FALSE, ll.is = FALSE, nbiter.saemix = c(300, 50), nb.chains = 1, nbiter.burn = 5, nbiter.mcmc = c(2, 2, 2, 0), displayProgress = FALSE, print= FALSE, save = FALSE,  nbdisplay = 50)
+control <- saemix::saemixControl(map = FALSE,fix.seed = T, fim = FALSE, ll.is = FALSE, nbiter.saemix = c(300, 50), nb.chains = 1, nbiter.burn = 5, nbiter.mcmc = c(2, 2, 2, 0), displayProgress = FALSE, print= FALSE, save = FALSE,  nbdisplay = 50, save.graphs = F)
 
 alpha_pop = exp(-6.34)
 mu_pop = exp(-26.8)
@@ -15,13 +15,6 @@ omega_mu = 3.78
 
 true_v = c(alpha_pop,mu_pop,sigma,omega_alpha,omega_mu)
 
-
-
-alpha <- c()
-mu <- c()
-omega_alpha <- c()
-omega_mu <- c()
-
 Ncpus <- parallel::detectCores() - 1
 cl <- parallel::makeCluster(Ncpus)
 doParallel::registerDoParallel(cl)
@@ -40,17 +33,22 @@ res <- foreach::foreach(i=1:100 , .packages = c("tidyverse","mechanisticModel"))
     Surv(tps, event) ~ TTR(vdiag),
     log(alpha) ~ 1, log(mu) ~ 1,
     data = JD1,
-    alpha_0 = 0.001, mu_0 = 2e-12, sigma_0 = 1, omega_0 = c(3, 3),
+    alpha_0 = 0.001, mu_0 = 2e-12, sigma_0 = sigma, omega_0 = c(3, 3),
     beta_0 = list(alpha = numeric(), mu = numeric()),
     options = control
   ) 
-  m = fit(m, silent = T, N_sim_surv = 0)
+  m = fit(m, silent = T, N_sim_surv = 0, omega.estim = c(1, 1), fixed.estim = c(1, 1, 0))
 }
 
 
 parallel::stopCluster(cl)
 
 
+alpha <- c()
+mu <- c()
+omega_alpha <- c()
+omega_mu <- c()
+
 for(i in 1:100){
   alpha <- append(alpha,unlist(res[[i]]$coefs[1])[1])
   mu <- append(mu,unlist(res[[i]]$coefs[1])[2])