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-rw-r--r--tests/testthat/test_mkinpredict_SFO_SFO.R26
1 files changed, 14 insertions, 12 deletions
diff --git a/tests/testthat/test_mkinpredict_SFO_SFO.R b/tests/testthat/test_mkinpredict_SFO_SFO.R
index 347aa50b..d0dc7cdb 100644
--- a/tests/testthat/test_mkinpredict_SFO_SFO.R
+++ b/tests/testthat/test_mkinpredict_SFO_SFO.R
@@ -5,26 +5,28 @@ test_that("Variants of model predictions for SFO_SFO model give equivalent resul
# Do not use time 0, as eigenvalue based solution does not give 0 at time 0 for metabolites
# 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)
- SFO_SFO.2 <- mkinmod(parent = list(type = "SFO", to = "m1"),
- m1 = list(type = "SFO"), use_of_ff = "max", quiet = TRUE)
+ SFO_SFO.1 <- mkinmod(parent = mkinsub("SFO", to = "m1"),
+ m1 = mkinsub("SFO"), use_of_ff = "min", quiet = TRUE)
+ SFO_SFO.2 <- mkinmod(parent = mkinsub("SFO", to = "m1"),
+ m1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE)
ot = seq(0, 100, by = 1)
- r.1.e <- subset(mkinpredict(SFO_SFO.1,
+ r.1.e <- subset(as.data.frame(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"),
+ c(parent = 100, m1 = 0), ot, solution_type = "eigen")),
time %in% c(1, 10, 50, 100))
- r.1.d <- subset(mkinpredict(SFO_SFO.1,
+ r.1.d <- subset(as.data.frame(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"),
+ c(parent = 100, m1 = 0), ot, solution_type = "deSolve")),
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"),
+ r.2.e <- subset(as.data.frame(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")),
time %in% c(1, 10, 50, 100))
- r.2.d <- 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 = "deSolve"),
+ r.2.d <- subset(as.data.frame(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 = "deSolve")),
time %in% c(1, 10, 50, 100))
# Compare eigen and deSolve for minimum use of formation fractions

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