Use odeintr instead of ccSolve for compiling modelsodeintr

1 files changed, 18 insertions, 9 deletions

diff --git a/tests/testthat/test_mkinpredict_SFO_SFO.R b/tests/testthat/test_mkinpredict_SFO_SFO.R
index b7004f64..b6e5f9e2 100644
--- a/tests/testthat/test_mkinpredict_SFO_SFO.R
+++ b/tests/testthat/test_mkinpredict_SFO_SFO.R
@@ -28,19 +28,22 @@ test_that("Variants of model predictions for SFO_SFO model give equivalent resul
   # and relative tolerance is thus not met

   tol = 0.01

   SFO_SFO.1 <- mkinmod(parent = list(type = "SFO", to = "m1"),

-         m1 = list(type = "SFO"), use_of_ff = "min", quiet = TRUE)

+         m1 = list(type = "SFO"), use_of_ff = "min", quiet = TRUE, odeintr_compile = "yes")

   SFO_SFO.2 <- mkinmod(parent = list(type = "SFO", to = "m1"),

          m1 = list(type = "SFO"), use_of_ff = "max", quiet = TRUE)

 

   ot = seq(0, 100, by = 1)

-  r.1.e <- subset(mkinpredict(SFO_SFO.1, 

-             c(k_parent_m1 = 0.1, k_parent_sink = 0.1, k_m1_sink = 0.1), 

-             c(parent = 100, m1 = 0), ot, solution_type = "eigen"), 

-                 time %in% c(1, 10, 50, 100))

-  r.1.d <- subset(mkinpredict(SFO_SFO.1, 

-             c(k_parent_m1 = 0.1, k_parent_sink = 0.1, k_m1_sink = 0.1), 

-             c(parent = 100, m1 = 0), ot, solution_type = "deSolve"), 

-                 time %in% c(1, 10, 50, 100))

+  test_parms = c(k_parent_m1 = 0.1, k_parent_sink = 0.1, k_m1_sink = 0.1) 

+  test_ini = c(parent = 100, m1 = 0)

+  r.1.e <- subset(mkinpredict(SFO_SFO.1, test_parms, test_ini, ot,

+                              solution_type = "eigen"), 

+                  time %in% c(1, 10, 50, 100))

+  r.1.d <- subset(mkinpredict(SFO_SFO.1, test_parms, test_ini, ot,

+                              solution_type = "deSolve"), 

+                  time %in% c(1, 10, 50, 100))

+  r.1.o <- subset(mkinpredict(SFO_SFO.1, test_parms, test_ini, ot,

+                              solution_type = "odeintr"), 

+                  time %in% c(1, 10, 50, 100))

 

   r.2.e <- subset(mkinpredict(SFO_SFO.2, c(k_parent = 0.2, f_parent_to_m1 = 0.5, k_m1 = 0.1), 

 	    c(parent = 100, m1 = 0), ot, solution_type = "eigen"),

@@ -55,6 +58,12 @@ test_that("Variants of model predictions for SFO_SFO model give equivalent resul
   dev.1.e_d.percent = ifelse(is.na(dev.1.e_d.percent), 0, dev.1.e_d.percent)

   expect_equivalent(dev.1.e_d.percent < tol, rep(TRUE, length(dev.1.e_d.percent)))

 

+  # Compare eigen and odeintr for minimum use of formation fractions

+  dev.1.e_o.percent = 100 * (r.1.e[-1] - r.1.o[-1])/r.1.e[-1]

+  dev.1.e_o.percent = as.numeric(unlist((dev.1.e_o.percent)))

+  dev.1.e_o.percent = ifelse(is.na(dev.1.e_o.percent), 0, dev.1.e_o.percent)

+  expect_equivalent(dev.1.e_o.percent < tol, rep(TRUE, length(dev.1.e_o.percent)))

+

   # Compare eigen and deSolve for maximum use of formation fractions

   dev.2.e_d.percent = 100 * (r.1.e[-1] - r.1.d[-1])/r.1.e[-1]

   dev.2.e_d.percent = as.numeric(unlist((dev.2.e_d.percent)))