From fbf43bbfd6e7ed265fea1cfd0e6b0004dbb6cde2 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 15 May 2015 11:02:19 +0200 Subject: Also migrate test for mkinpredict --- tests/testthat/test_mkinpredict_SFO_SFO.R | 70 +++++++++++++++++++++++++++++++ 1 file changed, 70 insertions(+) create mode 100644 tests/testthat/test_mkinpredict_SFO_SFO.R (limited to 'tests/testthat/test_mkinpredict_SFO_SFO.R') diff --git a/tests/testthat/test_mkinpredict_SFO_SFO.R b/tests/testthat/test_mkinpredict_SFO_SFO.R new file mode 100644 index 00000000..1238bb28 --- /dev/null +++ b/tests/testthat/test_mkinpredict_SFO_SFO.R @@ -0,0 +1,70 @@ +# $Id: jranke $ + +# Copyright (C) 2012-2015 Johannes Ranke +# Contact: jranke@uni-bremen.de + +# This file is part of the R package mkin + +# mkin is free software: you can redistribute it and/or modify it under the +# terms of the GNU General Public License as published by the Free Software +# Foundation, either version 3 of the License, or (at your option) any later +# version. + +# This program is distributed in the hope that it will be useful, but WITHOUT +# ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS +# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more +# details. + +# You should have received a copy of the GNU General Public License along with +# this program. If not, see + +# This was migrated from an RUnit test in inst/unitTests/runit.mkinpredict.R + +context("Model predictions with mkinpredict") +test_that("Variants of model predictions for SFO_SFO model give equivalent results", { + # Check model specification and solution types for SFO_SFO + # Relative Tolerance is 0.01% + # 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") + SFO_SFO.2 <- mkinmod(parent = list(type = "SFO", to = "m1"), + m1 = list(type = "SFO"), use_of_ff = "max") + + 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)) + + 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"), + 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"), + time %in% c(1, 10, 50, 100)) + + # Compare eigen and deSolve for minimum use of formation fractions + dev.1.e_d.percent = 100 * (r.1.e[-1] - r.1.d[-1])/r.1.e[-1] + dev.1.e_d.percent = as.numeric(unlist((dev.1.e_d.percent))) + 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 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))) + dev.2.e_d.percent = ifelse(is.na(dev.2.e_d.percent), 0, dev.2.e_d.percent) + expect_equivalent(dev.2.e_d.percent < tol, rep(TRUE, length(dev.2.e_d.percent))) + + # Compare minimum and maximum use of formation fractions + dev.1_2.e.percent = 100 * (r.1.e[-1] - r.2.e[-1])/r.1.e[-1] + dev.1_2.e.percent = as.numeric(unlist((dev.1_2.e.percent))) + dev.1_2.e.percent = ifelse(is.na(dev.1_2.e.percent), 0, dev.1_2.e.percent) + expect_equivalent(dev.1_2.e.percent < tol, rep(TRUE, length(dev.1_2.e.percent))) + +}) -- cgit v1.2.1