tests/testthat/test_SAM_poisson.R

In skiptoniam/ecomix: Fitting Finite Mixture Models to Ecological Data

context('species_mix generic functions five: poisson functions')
library(ecomix)

testthat::test_that('species mix poisson', {

  set.seed(42)
  sam_form <- as.formula(paste0('cbind(',paste(paste0('spp',1:20),collapse = ','),")~x1+x2"))
  alpha <- rnorm(20,0, 0.5)
  beta <- matrix(c(-0.6,0.5,
                   -0.5,-0.5,
                   0.9,-0.9),
                 3,2,byrow=TRUE)
  dat <- data.frame(y=1, x1=runif(100,0,2.5),x2=rnorm(100,0,2.5))
  simulated_data <- species_mix.simulate(archetype_formula = sam_form,
                                         species_formula = ~1,
                                         dat = dat,
                                         nArchetypes = 3,
                                         alpha=alpha,
                                         beta=beta, family = "poisson")
  y <- as.matrix(simulated_data[,grep("spp",colnames(simulated_data))])
  X <- simulated_data[,-grep("spp",colnames(simulated_data))]
  W <- as.matrix(X[,1,drop=FALSE])
  U <- NULL
  X <- as.matrix(X[,-1])
  offset <- rep(0,nrow(y))
  weights <- rep(1,nrow(y))
  spp_weights <- rep(1,ncol(y))
  site_spp_weights <- matrix(1,nrow(y),ncol(y))
  y_is_na <- matrix(FALSE,nrow(y),ncol(y))
  G <- 3
  S <- ncol(y)
  control <- ecomix:::set_control_sam(list())
  disty <- 2
  size <- rep(1,nrow(y))
  powers <- rep(1.5,nrow(y))

  i <- 1
  testthat::expect_length(ecomix:::apply_species_fits(i, y, X, W, U, site_spp_weights, offset, y_is_na, disty, size, powers),5)
  fm_poissonint <- ecomix:::plapply(1:S, ecomix:::apply_species_fits,
                                      y, X, W, U, site_spp_weights, offset, y_is_na, disty, size, powers, .parallel = control$cores, .verbose = !control$quiet)
  testthat::expect_length(do.call(cbind,fm_poissonint)[1,],S)

  #get the taus
  sv <- ecomix:::get_initial_values_sam(y, X, W, U, site_spp_weights, offset, y_is_na, G, S, disty, size, powers, control)

  # get the loglikelihood based on these values
  logls <- ecomix:::get_logls_sam(y, X, W, U, G, S, spp_weights,
                                  site_spp_weights, offset, y_is_na, disty,
                                  size, powers, control, sv, get_fitted = FALSE)
  pis <- rep(1/G, G)
  taus <- ecomix:::get_taus(pis, logls$logl_sp, G, S)
  taus <- ecomix:::shrink_taus(taus, G)

  ## get to this in a bit
  # gg <- 1
  # testthat::expect_length(ecomix:::apply_glm_mix_coefs_sams(gg, y, X, W, site_spp_weights, offset, y_is_na, disty, taus, fits, logls$fitted, size),2)

  # ## now let's try and fit the optimisation
  start_vals <- ecomix:::starting_values_wrapper(y, X, W, U, spp_weights, site_spp_weights, offset, y_is_na, G, S, disty, size, powers, control)
  tmp <- ecomix:::sam_optimise(y, X, W, U, offset, spp_weights, site_spp_weights, y_is_na, S, G, disty, size, powers, start_vals = start_vals, control)
  testthat::expect_length(tmp,21)

  set.seed(123)
  tmp <- ecomix:::species_mix.fit(y=y, X=X, W=W, U=U, G=G, S=S,
                                  spp_weights=spp_weights,
                                  site_spp_weights=site_spp_weights,
                                  offset=offset, disty=disty, y_is_na=y_is_na, size=size, powers=powers,
                                  control=ecomix:::set_control_sam(list(print_cpp_start_vals = TRUE)))

  sp_form <- ~1
  fm1 <- species_mix(archetype_formula = sam_form, species_formula = sp_form,
                     data = simulated_data, family = 'poisson',
                     nArchetypes = 3)
  testthat::expect_s3_class(fm1,'species_mix')

  fm2 <- species_mix(sam_form, sp_form, data = simulated_data, family = 'poisson',
                     nArchetypes = 3,control=list(em_prefit = FALSE))
  testthat::expect_s3_class(fm2,'species_mix')

})