Batch processing for hierarchical fits

- 'R/mhmkin.R': New method for performing multiple hierarchical mkin fits in one function call, optionally in parallel.

- 'R/saem.R': 'logLik' and 'update' methods for 'saem.mmkin' objects.

- 'R/illparms.R': Add methods for 'saem.mmkin' and 'mhmkin' objects.

tests: Use 2 cores on travis, should work according to docs

5 files changed, 33 insertions, 2 deletions

diff --git a/tests/testthat/convergence_fits_synth_const.txt b/tests/testthat/convergence_fits_synth_const.txt
new file mode 100644
index 00000000..e69de29b
--- /dev/null
+++ b/tests/testthat/convergence_fits_synth_const.txt
diff --git a/tests/testthat/convergence_hfits_synth.txt b/tests/testthat/convergence_hfits_synth.txt
new file mode 100644
index 00000000..e69de29b
--- /dev/null
+++ b/tests/testthat/convergence_hfits_synth.txt
diff --git a/tests/testthat/illparms_hfits_synth.txt b/tests/testthat/illparms_hfits_synth.txt
new file mode 100644
index 00000000..e69de29b
--- /dev/null
+++ b/tests/testthat/illparms_hfits_synth.txt
diff --git a/tests/testthat/setup_script.R b/tests/testthat/setup_script.R
index 62cdf78e..af059668 100644
--- a/tests/testthat/setup_script.R
+++ b/tests/testthat/setup_script.R
@@ -8,8 +8,8 @@ if (identical(Sys.getenv("NOT_CRAN"), "true")) {
   n_cores <- 1
 }
 
-# We are only allowed one core on travis, but they also set NOT_CRAN=true
-if (Sys.getenv("TRAVIS") != "") n_cores = 1
+# Use the two available cores on travis
+if (Sys.getenv("TRAVIS") != "") n_cores = 2
 
 # On Windows we would need to make a cluster first
 if (Sys.info()["sysname"] == "Windows") n_cores = 1
diff --git a/tests/testthat/test_mhmkin.R b/tests/testthat/test_mhmkin.R
new file mode 100644
index 00000000..5243f971
--- /dev/null
+++ b/tests/testthat/test_mhmkin.R
@@ -0,0 +1,31 @@
+context("Batch fitting and diagnosing hierarchical kinetic models")
+
+test_that("Multiple hierarchical kinetic models can be fitted and diagnosed", {
+
+  skip_on_cran()
+  fits_synth_const <- suppressWarnings(
+    mmkin(c("SFO", "FOMC"), ds_sfo[1:6], cores = n_cores, quiet = TRUE))
+
+  fits_synth_tc <- suppressWarnings(
+    update(fits_synth_const, error_model = "tc"))
+
+  expect_known_output(
+    convergence(fits_synth_const),
+    "convergence_fits_synth_const.txt")
+
+  hfits <- mhmkin(list(fits_synth_const, fits_synth_tc))
+
+  expect_known_output(
+    convergence(hfits),
+    "convergence_hfits_synth.txt")
+
+  expect_known_output(
+    illparms(hfits),
+    "illparms_hfits_synth.txt")
+
+  expect_equal(which.min(AIC(hfits)), 3)
+
+  hfit_sfo_tc <- update(hfits[["SFO", "tc"]],
+    covariance.model = diag(c(0, 1)))
+  expect_equal(illparms(hfit_sfo_tc), character(0))
+})