library(testthat) library(ENMTools) set.seed(2282023) #data(iberolacerta.clade) #data(euro.worldclim) expect_species <- function(species){ expect_true(inherits(species, c("list", "enmtools.species"))) expect_equal(names(species), c("range", "presence.points", "background.points", "models", "species.name")) expect_true(inherits(species$range, "SpatRaster")) expect_true(inherits(species$presence.points, "SpatVector")) expect_true(inherits(species$species.name, "character")) } expect_enmtools_model <- function(model){ expect_true(inherits(model, "enmtools.model"), info = "Not an enmtools.model object") expect_true(all(names(model) %in% c("species.name", "analysis.df", "test.data", "test.prop", "model", "training.evaluation", "test.evaluation", "env.training.evaluation", "env.test.evaluation", "rts.test", "suitability", "clamping.strength", "call", "notes", "response.plots", "formula")), info = "Unexpected items in enmtools.model object!") expect_true(inherits(model$species.name, "character"), info = "species.name is not a character") expect_true(inherits(model$analysis.df, "data.frame"), info = "analysis.df is not a data frame") expect_true(inherits(model$test.prop, "numeric"), info = "test.prop is not numeric") expect_true(all(class(model$model) %in% c("MaxEnt", "Domain", "Bioclim", "randomForest.formula", "randomForest", "list", "glm", "lm", "gam", "ranger")), info = "Class of model is not recognized") # Evaluation on training data happens unless it's bypassed (GLM only I think) expect_true(inherits(model$training.evaluation, "ModelEvaluation")) expect_true(inherits(model$env.training.evaluation, "ModelEvaluation")) # Evaluation on test data is for test.prop > 0 only if(model$test.prop > 0){ expect_true(inherits(model$test.evaluation, "ModelEvaluation"), info = "Test proportion greater than 0 but test.evaluation is not a ModelEvaluation object") expect_true(inherits(model$env.test.evaluation, "ModelEvaluation"), info = "Test proportion greater than 0 but env.test.evaluation is not a ModelEvaluation object") expect_true(inherits(model$test.data, "SpatVector"), info = "Test proportion is greater than 0 but test.data is not a SpatVector") } else { expect_true(inherits(model$test.evaluation, "logical")) expect_true(inherits(model$test.data, "logical")) } expect_true(inherits(model$suitability, "SpatRaster")) expect_true(inherits(model$response.plots, "list")) expect_true(all(sapply(model$response.plots, class) %in% c("gg", "ggplot"))) } monticola <- iberolacerta.clade$species$monticola martinezricai <- iberolacerta.clade$species$martinezricai cyreni <- iberolacerta.clade$species$cyreni horvathi <- iberolacerta.clade$species$horvathi aurelioi <- iberolacerta.clade$species$aurelioi aranica <- iberolacerta.clade$species$aranica bonnali <- iberolacerta.clade$species$bonnali ib.tree <- iberolacerta.clade$tree test_that("enmtools.species object work", { expect_species(monticola) expect_species(martinezricai) expect_species(cyreni) expect_species(horvathi) expect_species(aurelioi) expect_species(aranica) expect_species(bonnali) }) #' Make an enmtools.clade object #' #' iberolacerta.clade <- enmtools.clade(species = list(monticola = monticola, martinezricai = martinezricai, cyreni = cyreni, horvathi = horvathi, aurelioi = aurelioi, aranica = aranica, bonnali = bonnali), tree = ib.tree) check.clade(iberolacerta.clade) #' Build ENMs using various methods and test outputs #' #' test_that("enmtools.model objects work for core methods", { cyreni.dm <- enmtools.dm(cyreni, euro.worldclim, test.prop = 0.2) cyreni.bc <- enmtools.bc(cyreni, euro.worldclim, test.prop = 0) expect_enmtools_model(cyreni.dm) expect_enmtools_model(cyreni.bc) cyreni.bc <- enmtools.bc(cyreni, euro.worldclim, test.prop = 0.2) expect_enmtools_model(cyreni.bc) cyreni.glm <- enmtools.glm(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2) expect_enmtools_model(cyreni.glm) expect_enmtools_model(cyreni.glm) p.dm <- plot(cyreni.dm) expect_s3_class(p.dm, "ggplot") expect_output(print(cyreni.dm, plot = FALSE)) p.bc <- plot(cyreni.bc) expect_s3_class(p.bc, "ggplot") expect_output(print(cyreni.bc, plot = FALSE)) p.glm <- plot(cyreni.glm) expect_s3_class(p.glm, "ggplot") expect_output(print(cyreni.glm, plot = FALSE)) # skip_on_ci() ## Generally slow tests skip_on_cran() cyreni.dm.rts1 <- enmtools.dm(cyreni, euro.worldclim, test.prop = 0.2, rts = 2) cyreni.bc.rts1 <- enmtools.bc(cyreni, euro.worldclim, test.prop = 0.2, rts = 10) cyreni.dm.rts2 <- enmtools.dm(cyreni, euro.worldclim, test.prop = 0, rts = 2) cyreni.bc.rts2 <- enmtools.bc(cyreni, euro.worldclim, test.prop = 0, rts = 10) cyreni.glm.rts1 <- enmtools.glm(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2, rts = 10) cyreni.glm.rts2 <- enmtools.glm(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0, rts = 10) expect_enmtools_model(cyreni.dm.rts1) expect_enmtools_model(cyreni.bc.rts1) expect_enmtools_model(cyreni.dm.rts2) expect_enmtools_model(cyreni.bc.rts2) expect_enmtools_model(cyreni.glm.rts1) expect_enmtools_model(cyreni.glm.rts2) # cyreni.mx <- enmtools.maxent(cyreni, euro.worldclim, test.prop = 0.2) # expect_enmtools_model(cyreni.mx) }) test_that("rf model objects work", { skip_if_not_installed("randomForest") expect_warning(cyreni.rf <- enmtools.rf(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2)) expect_enmtools_model(cyreni.rf) p <- plot(cyreni.rf) expect_s3_class(p, "ggplot") expect_output(print(cyreni.rf, plot = FALSE)) ## slow skip_on_cran() suppressWarnings(cyreni.rf.rts1 <- enmtools.rf(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2, rts.reps = 10)) suppressWarnings(cyreni.rf.rts2 <- enmtools.rf(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0, rts.reps = 10)) expect_enmtools_model(cyreni.rf.rts1) expect_enmtools_model(cyreni.rf.rts2) }) # test_that("ranger model objects work", { # skip_if_not_installed("ranger") # cyreni.rf.ranger <- enmtools.rf.ranger(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2) # expect_enmtools_model(cyreni.rf.ranger) # p <- plot(cyreni.rf.ranger) # expect_s3_class(p, "ggplot") # expect_output(print(cyreni.rf.ranger, plot = FALSE)) # # ## slow # skip_on_cran() # suppressWarnings(cyreni.rf.ranger.rts1 <- enmtools.rf.ranger(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2, # rts.reps = 10)) # suppressWarnings(cyreni.rf.ranger.rts2 <- enmtools.rf.ranger(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0, # rts.reps = 10)) # expect_enmtools_model(cyreni.rf.ranger.rts1) # expect_enmtools_model(cyreni.rf.ranger.rts2) # }) # test_that("ppm model objects work", { # skip_if_not_installed("ppmlasso") # cyreni.ppm <- enmtools.ppmlasso(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2) # expect_enmtools_model(cyreni.ppm) # }) test_that("gam model objects work", { skip_if_not_installed("mgcv") cyreni.gam <- enmtools.gam(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2) expect_enmtools_model(cyreni.gam) p <- plot(cyreni.gam) expect_s3_class(p, "ggplot") expect_output(print(cyreni.gam, plot = FALSE)) ## slow skip_on_cran() cyreni.gam.rts1 <- enmtools.gam(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2, rts.reps = 10) cyreni.gam.rts2 <- enmtools.gam(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0, rts.reps = 10) expect_enmtools_model(cyreni.gam.rts1) expect_enmtools_model(cyreni.gam.rts2) }) #' Simple interactive.plot tests test_that("interactive.plot produces correct object", { skip_if_not_installed("leaflet") skip_on_ci() cyreni.dm <- enmtools.dm(cyreni, euro.worldclim, test.prop = 0.2) m_dm <- interactive.plot(cyreni.dm) m_dm_cluster <- interactive.plot(cyreni.dm, cluster.points = TRUE) expect_s3_class(m_dm, "leaflet") expect_s3_class(m_dm_cluster, "leaflet") expect_match(sapply(m_dm_cluster$x$calls, function(x) x$method), "addRasterImage", all = FALSE) expect_match(sapply(m_dm$x$calls, function(x) x$method), "addRasterImage", all = FALSE) }) test_that("backwards compatability works", { cyreni <- iberolacerta.clade$species$cyreni loaded <- load("sysdata.rda") on.exit(rm(list = loaded), add = TRUE, after = FALSE) expect_warning(cyreni.glm.raster <- enmtools.glm(cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2), "env is not the expected SpatRaster class", fixed = TRUE) expect_enmtools_model(cyreni.glm.raster) suppressWarnings(cyreni.glm.raster2 <- enmtools.glm(iberolacerta.clade$species$cyreni, euro.worldclim, f = pres ~ bio1 + bio9, test.prop = 0.2)) expect_enmtools_model(cyreni.glm.raster2) }) #' Geographic space metrics and visualization #' #' #' Env space metrics and visualization #' #' #' Monte Carlo tests, ENMTools-style #' #' #' Ecospat tests #' #'