# spatial models ---------------------------------------------------------- test_that("read_model() restores a single-map model object", { map <- readRDS("map.rds") pop <- population("pop", N = 10, time = 100, center = c(10, 40), radius = 100000, map = map) model_dir <- file.path(tempdir(), "tmp-single-map-model-serialization") model1 <- compile_model(pop, path = model_dir, resolution = 10000, generation_time = 1, overwrite = TRUE, force = TRUE, competition = 100e3, mating = 100e3, dispersal = 10e3, direction = "backward") model2 <- read_model(model1$path) # make sure that all components of the model list object before and after # serialization are equal components <- c("checksums", "splits", "resizes", "geneflow", "maps", "direction", "length", "generation_time", "resolution", "world") expect_true(all(sapply(components, function(i) all.equal(model1[[i]], model2[[i]])))) expect_true(all(sapply(seq_along(model1$populations), function(i) all(model1$populations[[i]] == model2$populations[[i]])))) expect_equal(names(model1$populations), names(model1$populations)) }) test_that("read_model() restores a complex model object", { map <- readRDS("map.rds") p1 <- population(name = "pop1", N = 700, time = 40000, radius = 600000, center = c(10, 25), map = map) p2 <- population(name = "pop2", parent = p1, time = 30000, N = 500, center = c(10, 25), radius = 300000) %>% move(trajectory = list(c(25, 25), c(40, 30), c(40, 40), c(50, 50)), start = 29000, end = 25000, snapshots = 30) p3 <- population(name = "pop3", parent = p2, time = 20000, N = 2000, polygon = list(c(-10, 50), c(10, 50), c(20, 53), c(40, 60), c(40, 70), c(-10, 65))) p4 <- population(name = "pop4", parent = p2, time = 15000, N = 2000, polygon = list(c(-10, 35), c(20, 37), c(25, 40), c(30, 45), c(10, 50), c(-10, 45))) p5 <- population(name = "pop5", parent = p1, time = 10000, N = 300, center = c(10, 25), radius = 300000) %>% move(trajectory = list(c(-5, 33), c(-5, 40)), start = 9000, end = 8000, snapshots = 20) %>% expand_range(by = 2000000, start = 7000, end = 2000, snapshots = 10) geneflow <- list( gene_flow(from = p5, to = p4, rate = 0.2, start = 2000, end = 0), gene_flow(from = p5, to = p3, rate = 0.3, start = 2000, end = 0) ) model_dir <- file.path(tempdir(), "tmp-complex-map-model-serialization") model1 <- compile_model( path = model_dir, populations = list(p1, p2, p3, p4, p5), gene_flow = geneflow, generation_time = 30, resolution = 10000, overwrite = TRUE, force = TRUE, competition = 100e3, mating = 100e3, dispersal = 10e3 ) model2 <- read_model(model1$path) components <- c("checksums", "splits", "resizes", "geneflow", "maps", "length", "orig_length", "direction", "generation_time", "resolution", "world") expect_true(all(sapply(components, function(i) all.equal(model1[[i]], model2[[i]])))) expect_true(all(sapply(seq_along(model1$populations), function(i) all(model1$populations[[i]] == model2$populations[[i]])))) expect_equal(names(model1$populations), names(model1$populations)) }) test_that("non-unique population names lead to error", { map <- readRDS("map.rds") p1 <- population(name = "pop1", N = 700, time = 1, radius = 600000, center = c(10, 25), map = map) p2 <- population(name = "pop2", N = 700, time = 1, radius = 600000, center = c(10, 25), map = map) p3 <- population(name = "pop2", N = 700, time = 1, radius = 600000, center = c(10, 25), map = map) model_dir <- file.path(tempdir(), "tmp-name-uniqueness") expect_error( compile_model(path = model_dir, populations = list(p1, p2, p3), generation_time = 30, resolution = 10000, overwrite = TRUE, force = TRUE, simulation_length = 10, competition = 100e3, mating = 100e3, dispersal = 10e3), "All populations must have unique names" ) p1 <- population(name = "pop1", N = 700, time = 1, radius = 600000, center = c(10, 25), map = map) p2 <- population(name = "pop2", N = 700, time = 1, radius = 600000, center = c(10, 25), map = map) p3 <- population(name = "pop3", N = 700, time = 1, radius = 600000, center = c(10, 25), map = map) model_dir <- file.path(tempdir(), "tmp-name-uniqueness") expect_silent(compile_model(path = model_dir, populations = list(p1, p2, p3), generation_time = 30, resolution = 10000, overwrite = TRUE, force = TRUE, simulation_length = 10, competition = 100e3, mating = 100e3, dispersal = 10e3)) }) # non-spatial models ------------------------------------------------------ test_that("read_model() restores a single-map model object (nonspatial)", { pop <- population("pop", N = 10, time = 100) model_dir <- file.path(tempdir(), "tmp-single-map-model-serialization") model1 <- compile_model(pop, path = model_dir, generation_time = 1, overwrite = TRUE, force = TRUE, direction = "backward") model2 <- read_model(model1$path) # make sure that all components of the model list object before and after # serialization are equal components <- c("checksums", "splits", "resizes", "geneflow", "maps", "direction", "length", "generation_time", "resolution", "world") expect_true(all(sapply(components, function(i) all.equal(model1[[i]], model2[[i]])))) expect_true(all(sapply(seq_along(model1$populations), function(i) all(unlist(model1$populations[[i]]) == unlist(model2$populations[[i]]))))) }) test_that("read_model() restores a complex model object (nonspatial)", { p1 <- population(name = "pop1", N = 700, time = 40000) p2 <- population(name = "pop2", parent = p1, time = 30000, N = 500) p3 <- population(name = "pop3", parent = p2, time = 20000, N = 2000) p4 <- population(name = "pop4", parent = p2, time = 15000, N = 2000) p5 <- population(name = "pop5", parent = p1, time = 10000, N = 300) geneflow <- list( gene_flow(from = p5, to = p4, rate = 0.2, start = 2000, end = 0), gene_flow(from = p5, to = p3, rate = 0.3, start = 2000, end = 0) ) model_dir <- file.path(tempdir(), "tmp-complex-map-model-serialization-nonspatial") model1 <- compile_model( path = model_dir, populations = list(p1, p2, p3, p4, p5), gene_flow = geneflow, generation_time = 30, overwrite = TRUE, force = TRUE ) model2 <- read_model(model1$path) components <- c("checksums", "splits", "resizes", "geneflow", "maps", "length", "orig_length", "direction", "generation_time", "resolution", "world") expect_true(all(sapply(components, function(i) all.equal(model1[[i]], model2[[i]])))) expect_true(all(sapply(seq_along(model1$populations), function(i) all(unlist(model1$populations[[i]]) == unlist(model2$populations[[i]]))))) expect_equal(names(model1$populations), names(model1$populations)) }) test_that("non-unique population names lead to error (nonspatial)", { p1 <- population(name = "pop1", N = 700, time = 1) p2 <- population(name = "pop2", N = 700, time = 1) p3 <- population(name = "pop2", N = 700, time = 1) model_dir <- file.path(tempdir(), "tmp-name-uniqueness-nonspatial") expect_error( compile_model(path = model_dir, populations = list(p1, p2, p3), generation_time = 30, resolution = 10000, overwrite = TRUE, force = TRUE, simulation_length = 10), "All populations must have unique names" ) p1 <- population(name = "pop1", N = 700, time = 1) p2 <- population(name = "pop2", N = 700, time = 1) p3 <- population(name = "pop3", N = 700, time = 1) model_dir <- file.path(tempdir(), "tmp-name-uniqueness-nonspatial") expect_silent(compile_model(path = model_dir, populations = list(p1, p2, p3), generation_time = 30, resolution = 10000, overwrite = TRUE, force = TRUE, simulation_length = 10)) }) test_that("checksums are enforced", { pop <- population("pop", N = 10, time = 100) model_dir <- file.path(tempdir(), "tmp-checksums") model1 <- compile_model(pop, path = model_dir, generation_time = 1, overwrite = TRUE, force = TRUE, direction = "backward") model2 <- read_model(model_dir) expect_warning(verify_checksums(file.path(model_dir, model1$checksums$file[1]), paste0(model1$checksums$hash[1], "asdf")), "Checksum of .* does not match") expect_equal(model1$checksums$hash, model2$checksums$hash) })