More autojags tests

4 files changed, 109 insertions, 1 deletions

diff --git a/R/autojags.R b/R/autojags.R
index 74da81d..035f9c9 100644
--- a/R/autojags.R
+++ b/R/autojags.R
@@ -7,7 +7,7 @@ autojags <- function(data,inits=NULL,parameters.to.save,model.file,n.chains,n.ad
     stop("The seed argument is no longer supported, use set.seed() instead", call.=FALSE)
   }
   if(n.chains<2) stop('Number of chains must be >1 to calculate Rhat.')
-  if((max.iter < n.burnin) & verbose){
+  if(max.iter < n.burnin){
     old_warn <- options()$warn
     options(warn=1)
     warning('Maximum iterations includes burn-in and should be larger than burn-in.')
diff --git a/inst/tinytest/autojags_ref_alliter.Rds b/inst/tinytest/autojags_ref_alliter.Rds
new file mode 100644
index 0000000..b85d544
--- /dev/null
+++ b/inst/tinytest/autojags_ref_alliter.Rds
diff --git a/inst/tinytest/test_autojags.R b/inst/tinytest/test_autojags.R
index d8b6b84..5753cc8 100644
--- a/inst/tinytest/test_autojags.R
+++ b/inst/tinytest/test_autojags.R
@@ -53,3 +53,93 @@ expect_inherits(out, "jagsUIbasic")
 expect_equal(coda::varnames(out$samples), 
              c("alpha","beta", "sigma", paste0("mu[",1:16,"]"),"deviance"))
 expect_equal(names(out), c("samples", "model"))
+
+# Save all iterations----------------------------------------------------------
+set.seed(123)
+params <- c('alpha','beta','sigma', 'mu')     
+
+nul <- capture.output(
+            out <- autojags(data = data, inits = inits, parameters.to.save = params,
+            model.file = modfile, n.chains = 3, n.adapt = 100, n.burnin=50, 
+            iter.increment=10, n.thin = 1, verbose=TRUE, save.all.iter=TRUE))
+
+# Runs three updates of 10 iterations each
+expect_true(grepl("Note: ALL iterations", nul[6]))
+expect_true(grepl("Update 3", nul[10]))
+expect_true(nul[11] == "")
+# All are combined to yield 30 total iterations in each chain
+expect_equal(coda::niter(out$samples), 30)
+ref <- readRDS("autojags_ref_alliter.Rds")
+out$mcmc.info$elapsed.mins <- ref$mcmc.inf$elapsed.mins
+expect_identical(out[-c(17,18,21)], ref[-c(17,18,21)])
+
+# Parallel----------------------------------------------------------
+at_home <- identical( Sys.getenv("AT_HOME"), "TRUE" )
+if(at_home){
+  set.seed(123)
+  nul <- capture.output(
+            out <- autojags(data = data, inits = inits, parameters.to.save = params,
+            model.file = modfile, n.chains = 3, n.adapt = 100, n.burnin=50, 
+            iter.increment=10, n.thin = 2, verbose=TRUE, parallel=TRUE, save.all.iter=FALSE))
+  # Runs two updates of 40 iterations each
+  expect_true(grepl("Update 13", nul[18]))
+  expect_equal(nul[19], "")
+
+  ref <- readRDS("autojags_ref.Rds")
+
+  out$mcmc.info$elapsed.mins <- ref$mcmc.inf$elapsed.mins
+  expect_identical(out[-c(17,18,20:22)], ref[-c(17,18,20:22)])
+
+  # Save all iter
+  set.seed(123)
+  params <- c('alpha','beta','sigma', 'mu')     
+
+  nul <- capture.output(
+            out <- autojags(data = data, inits = inits, parameters.to.save = params,
+            model.file = modfile, n.chains = 3, n.adapt = 100, n.burnin=50, 
+            iter.increment=10, n.thin = 1, verbose=TRUE, parallel=TRUE, save.all.iter=TRUE))
+  expect_true(grepl("Update 3", nul[10]))
+  expect_equal(nul[11], "")
+
+  expect_equal(coda::niter(out$samples), 30)
+  ref <- readRDS("autojags_ref_alliter.Rds")
+  expect_identical(out[-c(17,18,20:22)], ref[-c(17,18,20:22)])
+}
+
+# test.Rhat--------------------------------------------------------------------
+samples <- readRDS('coda_samples.Rds')
+
+rhats <- sapply(1:coda::nvar(samples), function(i) coda::gelman.diag(samples[,i],
+                                                      autoburnin=FALSE)$psrf[1])
+
+# None above 1.1
+expect_false(any(rhats > 1.1))
+expect_false(jagsUI:::test.Rhat(samples, 1.1, params.omit=NULL, verbose=FALSE))
+
+# Sigma is above 1.05
+expect_true(any(rhats > 1.05))
+expect_true(jagsUI:::test.Rhat(samples, 1.05, params.omit=NULL, verbose=FALSE))
+
+nul <- capture.output(jagsUI:::test.Rhat(samples, 1.05, params.omit=NULL, verbose=TRUE))
+expect_true(grepl("sigma", nul[1]))
+
+# Exclude sigma
+expect_false(jagsUI:::test.Rhat(samples, 1.05, params.omit="sigma", verbose=FALSE))
+
+# Test input errors------------------------------------------------------------
+expect_error(out <- autojags(data = data, inits = inits, parameters.to.save = params,
+            model.file = modfile, n.chains = 3, n.adapt = 100, n.burnin=50, 
+            iter.increment=10, n.thin = 2, verbose=FALSE, seed=123))
+
+expect_error(out <- autojags(data = data, inits = inits, parameters.to.save = params,
+            model.file = modfile, n.chains = 1, n.adapt = 100, n.burnin=50, 
+            iter.increment=10, n.thin = 2, verbose=FALSE))
+
+expect_warning(out <- autojags(data = data, inits = inits, parameters.to.save = params,
+            model.file = modfile, n.chains = 3, n.adapt = 100, n.burnin=50, 
+            iter.increment=10, n.thin = 2, verbose=FALSE, max.iter=40))
+
+nul <- capture.output(out <- autojags(data = data, inits = inits, parameters.to.save = params,
+            model.file = modfile, n.chains = 3, n.adapt = 100, n.burnin=0, 
+            iter.increment=10, n.thin = 2, verbose=TRUE, max.iter=5))
+expect_equal(nul[8], "Maximum iterations reached.")
diff --git a/inst/tinytest/test_mcmc_tools.R b/inst/tinytest/test_mcmc_tools.R
index 8e5f9cb..73871f9 100644
--- a/inst/tinytest/test_mcmc_tools.R
+++ b/inst/tinytest/test_mcmc_tools.R
@@ -89,3 +89,21 @@ expect_equal(get_inds('kappa',params_raw),
 params_raw <- 'alpha'
 expect_warning(test <- get_inds('alpha',params_raw)[1,1])
 expect_true(is.na(test))
+
+# test that bind.mcmc works correctly------------------------------------------
+cs1 <- readRDS('coda_samples.Rds')
+cs2 <- readRDS('coda_samples.Rds')
+
+iter_increment <- coda::niter(cs1) * coda::thin(cs1)
+test <- jagsUI:::bind.mcmc(cs1, cs2, stats::start(cs1), iter_increment)
+expect_equal(coda::niter(test), 60)
+expect_equal(coda::varnames(test), coda::varnames(cs1))
+expect_equal(stats::start(cs1), stats::start(test))
+expect_equal(stats::end(test), stats::end(cs1) + iter_increment)
+
+comb <- rbind(
+  rbind(as.matrix(cs1[[1]]), as.matrix(cs2[[1]])),
+  rbind(as.matrix(cs1[[2]]), as.matrix(cs2[[2]])),
+  rbind(as.matrix(cs1[[3]]), as.matrix(cs2[[3]]))
+)
+expect_identical(comb, as.matrix(test))