R version 4.4.0 RC (2024-04-16 r86468 ucrt) -- "Puppy Cup"
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> ## This file is part of SimInf, a framework for stochastic
> ## disease spread simulations.
> ##
> ## Copyright (C) 2015 -- 2024 Stefan Widgren
> ##
> ## SimInf 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.
> ##
> ## SimInf 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 <https://www.gnu.org/licenses/>.
> 
> library(SimInf)
> library(tools)
> source("util/check.R")
> 
> model <- SIR(u0     = data.frame(S = 1:3, I = 4:6, R = 7:9),
+              tspan  = 1:10,
+              events = NULL,
+              beta   = 0,
+              gamma  = 0)
> 
> res <- assertError(
+     v0(model) <- data.frame(phi = 10:13))
> check_error(res, "The number of rows in 'v0' must match nodes in 'model'.")
> 
> v0(model) <- data.frame(phi = 1:3)
> stopifnot(identical(model@v0, matrix(numeric(0), nrow = 0, ncol = 0)))
> 
> ## Check that a matrix is coerced to a data.frame.
> res <- SimInf:::check_v0(matrix(1:9,
+                                 ncol = 3,
+                                 dimnames = list(NULL, c("A", "B", "C"))),
+                          c("A", "B", "C"))
> stopifnot(identical(res,
+                     data.frame(A = 1:3,
+                                B = 4:6,
+                                C = 7:9)))
> 
> ## Check that a named vector is coerced to a data.frame.
> res <- SimInf:::check_v0(c(A = 1, B = 4, C = 7), c("A", "B", "C"))
> stopifnot(identical(res,
+                     data.frame(A = 1,
+                                B = 4,
+                                C = 7)))
> 
> ## Create an 'SISe' model with 6 nodes.
> model <- SISe(u0 = data.frame(S = 100:105, I = 1:6), tspan = 1:10,
+               phi = rep(0, 6), upsilon = 0.02, gamma = 0.1, alpha = 1,
+               epsilon = 1.1e-5, beta_t1 = 0.15, beta_t2 = 0.15,
+               beta_t3 = 0.15, beta_t4 = 0.15, end_t1 = 91, end_t2 = 182,
+               end_t3 = 273, end_t4 = 365)
> 
> res <- assertError(
+     v0(model) <- data.frame(A = 1:6))
> check_error(res, "Missing columns in 'v0'.")
> 
> v0(model) <- data.frame(phi = 1:6)
> stopifnot(identical(model@v0,
+                     matrix(c(1, 2, 3, 4, 5, 6),
+                            nrow = 1,
+                            ncol = 6,
+                            dimnames = list("phi", NULL))))
> 
> proc.time()
   user  system elapsed 
   0.82    0.18    1.01