From 01c69fcff8c5a82b4c80faaeb44ff00827e792ca Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 14 May 2015 00:21:12 +0200 Subject: Start of migration from RUnit to testthat --- tests/testthat/runit.mkinerrmin.R | 62 ++++++++++ tests/testthat/runit.mkinfit.R | 227 +++++++++++++++++++++++++++++++++++++ tests/testthat/runit.mkinpredict.R | 86 ++++++++++++++ tests/testthat/test_parent_only.R | 48 ++++++++ 4 files changed, 423 insertions(+) create mode 100644 tests/testthat/runit.mkinerrmin.R create mode 100644 tests/testthat/runit.mkinfit.R create mode 100644 tests/testthat/runit.mkinpredict.R create mode 100644 tests/testthat/test_parent_only.R (limited to 'tests/testthat') diff --git a/tests/testthat/runit.mkinerrmin.R b/tests/testthat/runit.mkinerrmin.R new file mode 100644 index 00000000..56a33ff9 --- /dev/null +++ b/tests/testthat/runit.mkinerrmin.R @@ -0,0 +1,62 @@ +# Test SFO_SFO model with FOCUS_2006_D against Schaefer 2007 paper, tolerance = 1% # {{{ +# and check chi2 error values against values obtained with mkin 0.33 +test.FOCUS_2006_D_SFO_SFO <- function() +{ + 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") + + fit.1.e <- mkinfit(SFO_SFO.1, FOCUS_2006_D) + fit.1.d <- mkinfit(SFO_SFO.1, solution_type = "deSolve", FOCUS_2006_D) + fit.2.e <- mkinfit(SFO_SFO.2, FOCUS_2006_D) + fit.2.d <- mkinfit(SFO_SFO.2, solution_type = "deSolve", FOCUS_2006_D) + + FOCUS_2006_D_results_schaefer07_means <- c( + parent_0 = 99.65, DT50_parent = 7.04, DT50_m1 = 131.34) + + r.1.e <- c(fit.1.e$bparms.optim[[1]], endpoints(fit.1.e)$distimes[[1]]) + r.1.d <- c(fit.1.d$bparms.optim[[1]], endpoints(fit.1.d)$distimes[[1]]) + r.2.e <- c(fit.2.e$bparms.optim[[1]], endpoints(fit.2.e)$distimes[[1]]) + r.2.d <- c(fit.2.d$bparms.optim[[1]], endpoints(fit.2.d)$distimes[[1]]) + + dev.1.e <- 100 * (r.1.e - FOCUS_2006_D_results_schaefer07_means)/r.1.e + checkIdentical(as.numeric(abs(dev.1.e)) < 1, rep(TRUE, 3)) + dev.1.d <- 100 * (r.1.d - FOCUS_2006_D_results_schaefer07_means)/r.1.d + checkIdentical(as.numeric(abs(dev.1.d)) < 1, rep(TRUE, 3)) + dev.2.e <- 100 * (r.2.e - FOCUS_2006_D_results_schaefer07_means)/r.2.e + checkIdentical(as.numeric(abs(dev.2.e)) < 1, rep(TRUE, 3)) + dev.2.d <- 100 * (r.2.d - FOCUS_2006_D_results_schaefer07_means)/r.2.d + checkIdentical(as.numeric(abs(dev.2.d)) < 1, rep(TRUE, 3)) + + round(mkinerrmin(fit.2.e), 4) + round(mkinerrmin(fit.2.d), 4) + + errmin.FOCUS_2006_D_rounded = data.frame( + err.min = c(0.0640, 0.0646, 0.0469), + n.optim = c(4, 2, 2), + df = c(15, 7, 8), + row.names = c("All data", "parent", "m1")) + checkEqualsNumeric(round(mkinerrmin(fit.2.e), 4), + errmin.FOCUS_2006_D_rounded) +} # }}} + +# Test SFO_SFO model with FOCUS_2006_E against values obtained with mkin 0.33 {{{ +test.FOCUS_2006_E_SFO_SFO <- function() +{ + SFO_SFO.2 <- mkinmod(parent = list(type = "SFO", to = "m1"), + m1 = list(type = "SFO"), use_of_ff = "max") + + fit.2.e <- mkinfit(SFO_SFO.2, FOCUS_2006_E) + + round(mkinerrmin(fit.2.e), 4) + errmin.FOCUS_2006_E_rounded = data.frame( + err.min = c(0.1544, 0.1659, 0.1095), + n.optim = c(4, 2, 2), + df = c(13, 7, 6), + row.names = c("All data", "parent", "m1")) + checkEqualsNumeric(round(mkinerrmin(fit.2.e), 4), + errmin.FOCUS_2006_E_rounded) +} # }}} + + diff --git a/tests/testthat/runit.mkinfit.R b/tests/testthat/runit.mkinfit.R new file mode 100644 index 00000000..8eefb995 --- /dev/null +++ b/tests/testthat/runit.mkinfit.R @@ -0,0 +1,227 @@ +# Copyright (C) 2010-2014 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 + +# Test SFO model to a relative tolerance of 1% # {{{ +test.FOCUS_2006_SFO <- function() +{ + SFO.1 <- mkinmod(parent = list(type = "SFO")) + SFO.2 <- mkinmod(parent = list(type = "SFO"), use_of_ff = "max") + + fit.A.SFO.1 <- mkinfit(SFO.1, FOCUS_2006_A, quiet=TRUE) + fit.A.SFO.2 <- mkinfit(SFO.2, FOCUS_2006_A, quiet=TRUE) + + median.A.SFO <- as.numeric(lapply(subset(FOCUS_2006_SFO_ref_A_to_F, dataset == "A", + c(M0, k, DT50, DT90)), "median")) + + fit.A.SFO.1.r <- as.numeric(c(fit.A.SFO.1$bparms.optim, endpoints(fit.A.SFO.1)$distimes)) + dev.A.SFO.1 <- abs(round(100 * ((median.A.SFO - fit.A.SFO.1.r)/median.A.SFO), digits=1)) + checkIdentical(dev.A.SFO.1 < 1, rep(TRUE, length(dev.A.SFO.1))) + + fit.A.SFO.2.r <- as.numeric(c(fit.A.SFO.2$bparms.optim, endpoints(fit.A.SFO.2)$distimes)) + dev.A.SFO.2 <- abs(round(100 * ((median.A.SFO - fit.A.SFO.2.r)/median.A.SFO), digits=1)) + checkIdentical(dev.A.SFO.2 < 1, rep(TRUE, length(dev.A.SFO.2))) + + fit.C.SFO.1 <- mkinfit(SFO.1, FOCUS_2006_C, quiet=TRUE) + fit.C.SFO.2 <- mkinfit(SFO.2, FOCUS_2006_C, quiet=TRUE) + + median.C.SFO <- as.numeric(lapply(subset(FOCUS_2006_SFO_ref_A_to_F, dataset == "C", + c(M0, k, DT50, DT90)), "median")) + + fit.C.SFO.1.r <- as.numeric(c(fit.C.SFO.1$bparms.optim, endpoints(fit.C.SFO.1)$distimes)) + dev.C.SFO.1 <- abs(round(100 * ((median.C.SFO - fit.C.SFO.1.r)/median.C.SFO), digits=1)) + checkIdentical(dev.C.SFO.1 < 1, rep(TRUE, length(dev.C.SFO.1))) + + fit.C.SFO.2.r <- as.numeric(c(fit.C.SFO.2$bparms.optim, endpoints(fit.C.SFO.2)$distimes)) + dev.C.SFO.2 <- abs(round(100 * ((median.C.SFO - fit.C.SFO.2.r)/median.C.SFO), digits=1)) + checkIdentical(dev.C.SFO.2 < 1, rep(TRUE, length(dev.C.SFO.2))) +} # }}} + +# Test FOMC model to a relative tolerance of 1% {{{ +# See kinfit vignette for a discussion of FOMC fits to FOCUS_2006_A +# In this case, only M0, DT50 and DT90 are checked +test.FOCUS_2006_FOMC <- function() +{ + FOMC <- mkinmod(parent = list(type = "FOMC")) + + # FOCUS_2006_A (compare kinfit vignette for discussion) + fit.A.FOMC <- mkinfit(FOMC, FOCUS_2006_A, quiet=TRUE) + + median.A.FOMC <- as.numeric(lapply(subset(FOCUS_2006_FOMC_ref_A_to_F, dataset == "A", + c(M0, alpha, beta, DT50, DT90)), "median")) + + fit.A.FOMC.r <- as.numeric(c(fit.A.FOMC$bparms.optim, endpoints(fit.A.FOMC)$distimes[c("DT50", "DT90")])) + dev.A.FOMC <- abs(round(100 * ((median.A.FOMC - fit.A.FOMC.r)/median.A.FOMC), digits=1)) + dev.A.FOMC <- dev.A.FOMC[c(1, 4, 5)] + checkIdentical(dev.A.FOMC < 1, rep(TRUE, length(dev.A.FOMC))) + + # FOCUS_2006_B + fit.B.FOMC <- mkinfit(FOMC, FOCUS_2006_B, quiet=TRUE) + + median.B.FOMC <- as.numeric(lapply(subset(FOCUS_2006_FOMC_ref_A_to_F, dataset == "B", + c(M0, alpha, beta, DT50, DT90)), "median")) + + fit.B.FOMC.r <- as.numeric(c(fit.B.FOMC$bparms.optim, endpoints(fit.B.FOMC)$distimes[c("DT50", "DT90")])) + dev.B.FOMC <- abs(round(100 * ((median.B.FOMC - fit.B.FOMC.r)/median.B.FOMC), digits=1)) + dev.B.FOMC <- dev.B.FOMC[c(1, 4, 5)] + checkIdentical(dev.B.FOMC < 1, rep(TRUE, length(dev.B.FOMC))) + + # FOCUS_2006_C + fit.C.FOMC <- mkinfit(FOMC, FOCUS_2006_C, quiet=TRUE) + + median.C.FOMC <- as.numeric(lapply(subset(FOCUS_2006_FOMC_ref_A_to_F, dataset == "C", + c(M0, alpha, beta, DT50, DT90)), "median")) + + fit.C.FOMC.r <- as.numeric(c(fit.C.FOMC$bparms.optim, endpoints(fit.C.FOMC)$distimes[c("DT50", "DT90")])) + dev.C.FOMC <- abs(round(100 * ((median.C.FOMC - fit.C.FOMC.r)/median.C.FOMC), digits=1)) + dev.C.FOMC <- dev.C.FOMC[c(1, 4, 5)] + checkIdentical(dev.C.FOMC < 1, rep(TRUE, length(dev.C.FOMC))) +} # }}} + +# Test DFOP model, tolerance of 1% with the exception of f parameter for A {{{ +test.FOCUS_2006_DFOP <- function() +{ + DFOP <- mkinmod(parent = list(type = "DFOP")) + + # FOCUS_2006_A + # Results were too much dependent on algorithm, as this dataset + # is pretty much SFO. "Port" gave a lower deviance, but deviated from the + # median of FOCUS_2006 solutions + + # FOCUS_2006_B + fit.B.DFOP <- mkinfit(DFOP, FOCUS_2006_B, quiet=TRUE) + + median.B.DFOP <- as.numeric(lapply(subset(FOCUS_2006_DFOP_ref_A_to_B, dataset == "B", + c(M0, k1, k2, f, DT50, DT90)), "median")) + + fit.B.DFOP.r <- as.numeric(c(fit.B.DFOP$bparms.optim, endpoints(fit.B.DFOP)$distimes[c("DT50", "DT90")])) + dev.B.DFOP <- abs(round(100 * ((median.B.DFOP - fit.B.DFOP.r)/median.B.DFOP), digits=1)) + # about 0.6% deviation for parameter f, the others are <= 0.1% + checkIdentical(dev.B.DFOP < 1, rep(TRUE, length(dev.B.DFOP))) +} # }}} + +# Test HS model to a relative tolerance of 1% excluding Mathematica values {{{ +# as they are unreliable +test.FOCUS_2006_HS <- function() +{ + HS <- mkinmod(parent = list(type = "HS")) + + # FOCUS_2006_A + fit.A.HS <- mkinfit(HS, FOCUS_2006_A, quiet=TRUE) + + median.A.HS <- as.numeric(lapply(subset(FOCUS_2006_HS_ref_A_to_F, dataset == "A", + c(M0, k1, k2, tb, DT50, DT90)), "median")) + + fit.A.HS.r <- as.numeric(c(fit.A.HS$bparms.optim, endpoints(fit.A.HS)$distimes[c("DT50", "DT90")])) + dev.A.HS <- abs(round(100 * ((median.A.HS - fit.A.HS.r)/median.A.HS), digits=1)) + # about 6.7% deviation for parameter f, the others are < 0.1% + checkIdentical(dev.A.HS < 1, rep(TRUE, length(dev.A.HS))) + + # FOCUS_2006_B + fit.B.HS <- mkinfit(HS, FOCUS_2006_B, quiet=TRUE) + + median.B.HS <- as.numeric(lapply(subset(FOCUS_2006_HS_ref_A_to_F, dataset == "B", + c(M0, k1, k2, tb, DT50, DT90)), "median")) + + fit.B.HS.r <- as.numeric(c(fit.B.HS$bparms.optim, endpoints(fit.B.HS)$distimes[c("DT50", "DT90")])) + dev.B.HS <- abs(round(100 * ((median.B.HS - fit.B.HS.r)/median.B.HS), digits=1)) + # < 10% deviation for M0, k1, DT50 and DT90, others are problematic + dev.B.HS <- dev.B.HS[c(1, 2, 5, 6)] + checkIdentical(dev.B.HS < 10, rep(TRUE, length(dev.B.HS))) + + # FOCUS_2006_C + fit.C.HS <- mkinfit(HS, FOCUS_2006_C, quiet=TRUE) + + median.C.HS <- as.numeric(lapply(subset(FOCUS_2006_HS_ref_A_to_F, dataset == "C", + c(M0, k1, k2, tb, DT50, DT90)), "median")) + + fit.C.HS.r <- as.numeric(c(fit.C.HS$bparms.optim, endpoints(fit.C.HS)$distimes[c("DT50", "DT90")])) + dev.C.HS <- abs(round(100 * ((median.C.HS - fit.C.HS.r)/median.C.HS), digits=1)) + # deviation <= 0.1% + checkIdentical(dev.C.HS < 1, rep(TRUE, length(dev.C.HS))) +} # }}} + +# Test SFORB model against DFOP solutions to a relative tolerance of 1% # {{{ +test.FOCUS_2006_SFORB <- function() +{ + SFORB <- mkinmod(parent = list(type = "SFORB")) + + # FOCUS_2006_A + # Again it does not make a lot of sense to use a SFO dataset for this + + # FOCUS_2006_B + fit.B.SFORB.1 <- mkinfit(SFORB, FOCUS_2006_B, quiet=TRUE) + fit.B.SFORB.2 <- mkinfit(SFORB, FOCUS_2006_B, solution_type = "deSolve", quiet=TRUE) + + median.B.SFORB <- as.numeric(lapply(subset(FOCUS_2006_DFOP_ref_A_to_B, dataset == "B", + c(M0, k1, k2, DT50, DT90)), "median")) + + fit.B.SFORB.1.r <- as.numeric(c( + parent_0 = fit.B.SFORB.1$bparms.optim[[1]], + k1 = endpoints(fit.B.SFORB.1)$SFORB[[1]], + k2 = endpoints(fit.B.SFORB.1)$SFORB[[2]], + endpoints(fit.B.SFORB.1)$distimes[c("DT50", "DT90")])) + dev.B.SFORB.1 <- abs(round(100 * ((median.B.SFORB - fit.B.SFORB.1.r)/median.B.SFORB), digits=1)) + checkIdentical(dev.B.SFORB.1 < 1, rep(TRUE, length(dev.B.SFORB.1))) + + fit.B.SFORB.2.r <- as.numeric(c( + parent_0 = fit.B.SFORB.2$bparms.optim[[1]], + k1 = endpoints(fit.B.SFORB.2)$SFORB[[1]], + k2 = endpoints(fit.B.SFORB.2)$SFORB[[2]], + endpoints(fit.B.SFORB.2)$distimes[c("DT50", "DT90")])) + dev.B.SFORB.2 <- abs(round(100 * ((median.B.SFORB - fit.B.SFORB.2.r)/median.B.SFORB), digits=1)) + checkIdentical(dev.B.SFORB.2 < 1, rep(TRUE, length(dev.B.SFORB.2))) +} # }}} + +# Test eigenvalue based fit to Schaefer 2007 data against solution from conference paper {{{ +test.mkinfit.schaefer07_complex_example <- function() +{ + schaefer07_complex_model <- mkinmod( + parent = list(type = "SFO", to = c("A1", "B1", "C1"), sink = FALSE), + A1 = list(type = "SFO", to = "A2"), + B1 = list(type = "SFO"), + C1 = list(type = "SFO"), + A2 = list(type = "SFO"), use_of_ff = "max") + + # If we use the default algorithm 'Marq' we need to give a good starting + # estimate for k_A2 in order to find the solution published by Schaefer et al. + fit <- mkinfit(schaefer07_complex_model, method.modFit = "Port", + mkin_wide_to_long(schaefer07_complex_case, time = "time")) + s <- summary(fit) + r <- schaefer07_complex_results + attach(as.list(fit$bparms.optim)) + r$mkin <- c( + k_parent, + s$distimes["parent", "DT50"], + s$ff["parent_A1"], + k_A1, + s$distimes["A1", "DT50"], + s$ff["parent_B1"], + k_B1, + s$distimes["B1", "DT50"], + s$ff["parent_C1"], + k_C1, + s$distimes["C1", "DT50"], + s$ff["A1_A2"], + k_A2, + s$distimes["A2", "DT50"]) + r$means <- (r$KinGUI + r$ModelMaker)/2 + r$mkin.deviation <- abs(round(100 * ((r$mkin - r$means)/r$means), digits=1)) + checkIdentical(r$mkin.deviation < 10, rep(TRUE, 14)) +} # }}} + +# vim: set foldmethod=marker ts=2 sw=2 expandtab: diff --git a/tests/testthat/runit.mkinpredict.R b/tests/testthat/runit.mkinpredict.R new file mode 100644 index 00000000..997857ce --- /dev/null +++ b/tests/testthat/runit.mkinpredict.R @@ -0,0 +1,86 @@ +# $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 + +# 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: diff --git a/tests/testthat/test_parent_only.R b/tests/testthat/test_parent_only.R new file mode 100644 index 00000000..16fc5131 --- /dev/null +++ b/tests/testthat/test_parent_only.R @@ -0,0 +1,48 @@ +context("Fitting of parent only models") + +calc_dev.percent <- function(fitlist, reference) { + for (i in 1:length(fitlist)) { + fit <- fitlist[[i]] + results <- c(fit$bparms.optim, + endpoints(fit)$distimes$DT50, + endpoints(fit)$distimes$DT90) + dev.percent[[i]] <- abs(100 * ((reference - results)/reference)) + } + return(dev.percent) +} + +SFO <- mkinmod(parent = list(type = "SFO")) +FOMC <- mkinmod(parent = list(type = "FOMC")) + +test_that("SFO fit for FOCUS A deviates less than 0.1% from median of values from FOCUS report", { + fits.A.SFO <- list() + fits.A.SFO[[1]] <- mkinfit("SFO", FOCUS_2006_A, quiet=TRUE) + fits.A.SFO[[2]] <- mkinfit(SFO, FOCUS_2006_A, quiet=TRUE) + fits.A.SFO[[3]] <- mkinfit(SFO, FOCUS_2006_A, quiet=TRUE, solution_type = "eigen") + fits.A.SFO[[4]] <- mkinfit(SFO, FOCUS_2006_A, quiet=TRUE, solution_type = "deSolve") + + median.A.SFO <- as.numeric(lapply(subset(FOCUS_2006_SFO_ref_A_to_F, + dataset == "A", + c(M0, k, DT50, DT90)), "median")) + + dev.percent <- calc_dev.percent(fits.A.SFO, median.A.SFO) + expect_equivalent(dev.percent[[1]] < 0.1, rep(TRUE, 4)) + expect_equivalent(dev.percent[[2]] < 0.1, rep(TRUE, 4)) + expect_equivalent(dev.percent[[3]] < 0.1, rep(TRUE, 4)) + expect_equivalent(dev.percent[[4]] < 0.1, rep(TRUE, 4)) +}) + +test_that("SFO fit for FOCUS C deviates less than 0.1% from median of values from FOCUS report", { + fits.C.SFO <- list() + fits.C.SFO[[1]] <- mkinfit("SFO", FOCUS_2006_C, quiet=TRUE) + fits.C.SFO[[2]] <- mkinfit(SFO, FOCUS_2006_C, quiet=TRUE) + fits.C.SFO[[3]] <- mkinfit(SFO, FOCUS_2006_C, quiet=TRUE, solution_type = "deSolve") + + median.C.SFO <- as.numeric(lapply(subset(FOCUS_2006_SFO_ref_A_to_F, + dataset == "C", + c(M0, k, DT50, DT90)), "median")) + dev.percent <- calc_dev.percent(fits.C.SFO, median.C.SFO) + expect_equivalent(dev.percent[[1]] < 0.1, rep(TRUE, 4)) + expect_equivalent(dev.percent[[2]] < 0.1, rep(TRUE, 4)) + expect_equivalent(dev.percent[[3]] < 0.1, rep(TRUE, 4)) +}) -- cgit v1.2.1