RXR-2598: consolidate model compilation & tests

tests/testthat/setup.R

@@ -1,6 +1,13 @@
+# =============================================================================
+# Shared models compiled once at test session startup
+# =============================================================================
+
+# --- Library models (standard PK models) ---
 mod_1cmt_iv <- new_ode_model("pk_1cmt_iv")
 mod_2cmt_iv <- new_ode_model("pk_2cmt_iv")
 mod_1cmt_oral <- new_ode_model("pk_1cmt_oral")
+
+# --- Custom 1cmt oral with lagtime ---
 mod_1cmt_oral_lagtime <- new_ode_model(
   code = "
     dAdt[0] = -KA * A[0]
@@ -11,7 +18,9 @@ mod_1cmt_oral_lagtime <- new_ode_model(
   dose = list(cmt = 1, bioav = 1),
   parameters = list(CL = 5, V = 50, KA = 0.5, TLAG = 0.83)
 )
-oral_1cmt_allometric <- new_ode_model( # also timevarying and dose-dependence factor
+
+# --- 1cmt oral with allometric scaling, time-varying CL, dose-dependent V ---
+oral_1cmt_allometric <- new_ode_model(
   code = "
       if(t<168.0) {
         CLi = CL * pow(WT/70, 0.75)
@@ -32,3 +41,167 @@ oral_1cmt_allometric <- new_ode_model( # also timevarying and dose-dependence fa
   declare_variables = c("CLi", "Vi"),
   parameters = list(KA = 0.5, CL = 5, V = 50)
 )
+
+# --- From test_iov.R: IOV models ---
+pars_iov <- list(
+  "kappa_CL_1" = 0,
+  "kappa_CL_2" = 0,
+  "kappa_CL_3" = 0,
+  "eta_CL" = 0,
+  "CL" = 5,
+  "V" = 50,
+  "KA" = 1
+)
+pars_iov_no_iov <- list(
+  "CL" = 5,
+  "V" = 50,
+  "KA" = 1
+)
+pk_iov_none <- new_ode_model(
+  code = "
+      dAdt[1] = -KA * A[1]
+      dAdt[2] = +KA * A[1] -(CL/V) * A[2]
+    ",
+  obs = list(cmt = 2, scale = "V"),
+  dose = list(cmt = 1, bioav = 1),
+  parameters = names(pars_iov_no_iov),
+  cpp_show_code = FALSE
+)
+pk_iov <- new_ode_model(
+  code = "
+      CL_iov = CL * exp(kappa_CL + eta_CL);
+      dAdt[1] = -KA * A[1]
+      dAdt[2] = +KA * A[1] -(CL_iov/V) * A[2]
+    ",
+  iov = list(
+    cv = list(CL = 0.2),
+    n_bins = 3
+  ),
+  obs = list(cmt = 2, scale = "V"),
+  dose = list(cmt = 1, bioav = 1),
+  declare_variables = c("kappa_CL", "CL_iov"),
+  parameters = names(pars_iov),
+  cpp_show_code = FALSE
+)
+
+# --- From test_compare_results.R ---
+dose_in_cmt_2 <- new_ode_model(
+  code = "
+      dAdt[1] = -KA * A[1];
+      dAdt[2] = KA*A[1] -(CL/V) * A[2]
+      dAdt[3] = S2*(A[2]-A[3])
+    ",
+  obs = list(cmt = 2, scale = "V"),
+  dose = list(cmt = 2),
+  cpp_show_code = FALSE
+)
+
+# --- From test_multi_obs.R: Multi-observation model ---
+vars_multi_obs <- c("CONC", "METAB", "METAB2", "ACT")
+pk_multi_obs <- new_ode_model(
+  code = "dAdt[1] = -(CL/V)*A[1]; CONC = 1000*A[1]/V; METAB = CONC/2; METAB2 = CONC * t; ACT = 15",
+  obs = list(variable = vars_multi_obs),
+  declare_variables = vars_multi_obs,
+  cpp_show_code = FALSE
+)
+
+# --- From test_mixture_model.R ---
+covs_mixture <- list(WT = new_covariate(70))
+mod_mixture <- new_ode_model(
+  code = "
+      dAdt[0] = -(CL*(WT/70.0)/V)*A[0];
+    ",
+  pk_code = " ",
+  obs = list(cmt = 1, scale = "V"),
+  mixture = list(CL = list(values = c(5, 15), probability = 0.3)),
+  covariates = covs_mixture
+)
+
+# --- Conditional models (skip on CRAN due to compilation time) ---
+if (identical(Sys.getenv("NOT_CRAN"), "true")) {
+
+  # Library models
+  pk_3cmt_iv <- new_ode_model("pk_3cmt_iv")
+  pk_2cmt_oral <- new_ode_model("pk_2cmt_oral")
+  pk_3cmt_oral <- new_ode_model("pk_3cmt_oral")
+  mod_1cmt_iv_mm <- new_ode_model("pk_1cmt_iv_mm")
+
+  # --- From test_advan_with_auc.R: Models with AUC compartments ---
+  parameters_advan_auc <- list(
+    CL = 10, V = 50, KA = 0.5, Q = 5, V2 = 100, Q2 = 3, V3 = 150, F1 = 1
+  )
+  mod_1cmt_auc <- new_ode_model(
+    code = "dAdt[1] = -(CL/V)*A[1]; dAdt[2] = A[1]/V;",
+    parameters = parameters_advan_auc
+  )
+  mod_2cmt_auc <- new_ode_model(
+    code = "
+    dAdt[1] = -(CL/V)*A[1] - (Q/V)*A[1] + (Q/V2)*A[2];
+    dAdt[2] = +(Q/V)*A[1] - (Q/V2)*A[2];
+    dAdt[3] = A[1]/V;
+  ",
+    parameters = parameters_advan_auc
+  )
+  mod_3cmt_auc <- new_ode_model(
+    code = "
+    dAdt[1] = -(CL/V)*A[1] - (Q/V)*A[1] + (Q/V2)*A[2] - (Q2/V)*A[1] + (Q2/V3)*A[3];
+    dAdt[2] =                (Q/V)*A[1]  -(Q/V2)*A[2]                             ;
+    dAdt[3] =                                           (Q2/V)*A[1] - (Q2/V3)*A[3];
+    dAdt[4] = A[1]/V;
+  ",
+    parameters = parameters_advan_auc
+  )
+
+  # --- From test_timevar_cov.R: 2cmt with time-varying covariates ---
+  mod_2cmt_timevar <- new_ode_model(
+    code = "
+      dAdt[1] = -(Q/V)*A[1] + (Q/V2)*A[2] -(CLi/V)*A[1];
+      dAdt[2] = -(Q/V2)*A[2] + (Q/V)*A[1];
+    ",
+    pk_code = "CLi = CL + CRCL",
+    obs = list(cmt = 2, scale = "V"),
+    covariates = list(CRCL = new_covariate(5)),
+    declare_variables = "CLi",
+    cpp = FALSE
+  )
+
+  # --- From test_t_init.R: Model with state initialization ---
+  mod_t_init <- new_ode_model(
+    code = "CLi = CL; Vi = V; dAdt[1] = -(CLi/Vi)*A[1]; CONC = A[1]/Vi",
+    state_init = "A[1] = TDM_INIT * Vi",
+    parameters = list(CL = 7.67, V = 97.7, TDM_INIT = 500),
+    obs = list(cmt = 1, scale = "Vi"),
+    declare_variables = c("CONC", "CLi", "Vi"),
+    cpp_show_code = FALSE
+  )
+
+  # --- From test_reparametrization.R: Carreno 2cmt model ---
+  covs_carreno <- list(
+    CRCL = new_covariate(5),
+    CL_HEMO = new_covariate(0)
+  )
+  model_carreno <- new_ode_model(
+    code = "
+    CLi = SCLInter + SCLSlope * (CRCL*16.667) + CL_HEMO \
+    Vi = V \
+    Qi = K12 * Vi \
+    V2i = Qi / K21 \
+    dAdt[0] = -(CLi/V)*A[0] - K12*A[0] + K21*A[1] \
+    dAdt[1] = K12*A[0] - K21*A[1] \
+    dAdt[2] = A[0]/V
+  ",
+    parameters = list(
+      V = 25.76, SCLSlope = 0.036, K12 = 2.29, K21 = 1.44,
+      SCLInter = 0.18, TDM_INIT = 0
+    ),
+    declare_variables = c("CLi", "Qi", "Vi", "V2i"),
+    covariates = covs_carreno,
+    obs = list(cmt = 1, scale = "V"),
+    reparametrization = list(
+      "CL" = "SCLInter + SCLSlope * (CRCL*16.667) + CL_HEMO",
+      "V" = "V",
+      "Q" = "K12 * V",
+      "V2" = "(K12 * V) / K21"
+    )
+  )
+}