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-# $Id: jranke $
-
-# Copyright (C) 2012 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 <http://www.gnu.org/licenses/>
-
-# Check solution types for SFO {{{
-test.SFO_solution_types <- function()
-{
- ot = seq(0, 100, by = 1)
- SFO <- mkinmod(parent = list(type = "SFO"))
- SFO.analytical <- round(subset(mkinpredict(SFO, c(k_parent_sink = 0.1),
- c(parent = 100), ot, solution_type = "analytical"), time == 100), digits=5)
- SFO.deSolve <- round(subset(mkinpredict(SFO, c(k_parent_sink = 0.1),
- c(parent = 100), ot, solution_type = "deSolve"), time == 100), digits=5)
- SFO.eigen <- round(subset(mkinpredict(SFO, c(k_parent_sink = 0.1),
- c(parent = 100), ot, solution_type = "eigen"), time == 100), digits=5)
-
- checkEquals(SFO.analytical, SFO.deSolve)
- checkEquals(SFO.analytical, SFO.eigen)
-} # }}}
-
-# 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
-test.SFO_solution_types <- function()
-{
- 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)
- checkIdentical(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)
- checkIdentical(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)
- checkIdentical(dev.1_2.e.percent < tol, rep(TRUE, length(dev.1_2.e.percent)))
-
-} # }}}
-
-# vim: set foldmethod=marker ts=2 sw=2 expandtab:

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