Improve output and update tests

Remove skipped tests as I do not intend to reactivate them

5 files changed, 49 insertions, 78 deletions

diff --git a/tests/testthat/DFOP_FOCUS_C_messages.txt b/tests/testthat/DFOP_FOCUS_C_messages.txt
index 5327b3f6..9abde683 100644
--- a/tests/testthat/DFOP_FOCUS_C_messages.txt
+++ b/tests/testthat/DFOP_FOCUS_C_messages.txt
@@ -1,148 +1,148 @@
 parent_0 log_k1 log_k2 g_ilr sigma 
 85.1 -2.302585 -4.60517 0 
-Negative log-likelihood at call 1: 7391.39
+Sum of squared residuals at call 1: 7391.39
 85.1 -2.302585 -4.60517 0 
 85.1 -2.302585 -4.60517 0 
-Negative log-likelihood at call 3: 7391.389
+Sum of squared residuals at call 3: 7391.389
 85.1 -2.302585 -4.60517 0 
-Negative log-likelihood at call 4: 7391.389
+Sum of squared residuals at call 4: 7391.389
 85.1 -2.302585 -4.60517 1.490116e-08 
 85.06371 -1.77328 -4.250366 0.7698268 
-Negative log-likelihood at call 6: 2000.127
+Sum of squared residuals at call 6: 2000.127
 85.06375 -1.77328 -4.250366 0.7698268 
 85.06371 -1.773322 -4.250366 0.7698268 
 85.06371 -1.77328 -4.250408 0.7698268 
 85.06371 -1.77328 -4.250366 0.7697847 
 85.03542 -0.9608523 -4.11546 1.336361 
-Negative log-likelihood at call 11: 32.97798
+Sum of squared residuals at call 11: 32.97798
 85.03542 -0.9608523 -4.11546 1.336361 
 85.03542 -0.9608526 -4.11546 1.336361 
 85.03542 -0.9608523 -4.11546 1.336361 
 85.03542 -0.9608523 -4.11546 1.336361 
 85.03704 -0.256064 -4.273512 0.6447755 
 85.03285 -0.7822828 -4.127513 1.312494 
-Negative log-likelihood at call 17: 5.348133
+Sum of squared residuals at call 17: 5.348133
 85.03286 -0.7822828 -4.127513 1.312494 
-Negative log-likelihood at call 18: 5.348132
+Sum of squared residuals at call 18: 5.348132
 85.03285 -0.7822828 -4.127513 1.312494 
-Negative log-likelihood at call 19: 5.348131
+Sum of squared residuals at call 19: 5.348131
 85.03285 -0.7822828 -4.127513 1.312494 
 85.03285 -0.7822828 -4.127513 1.312494 
-Negative log-likelihood at call 21: 5.348131
+Sum of squared residuals at call 21: 5.348131
 85.02325 -0.74968 -4.059 1.14891 
 85.03127 -0.7909068 -4.114802 1.268157 
-Negative log-likelihood at call 23: 4.704445
+Sum of squared residuals at call 23: 4.704445
 85.03127 -0.7909068 -4.114802 1.268157 
-Negative log-likelihood at call 24: 4.704444
+Sum of squared residuals at call 24: 4.704444
 85.03127 -0.7909068 -4.114802 1.268157 
 85.03127 -0.7909068 -4.1148 1.268157 
-Negative log-likelihood at call 26: 4.704433
+Sum of squared residuals at call 26: 4.704433
 85.03127 -0.7909068 -4.114802 1.268158 
 85.03001 -0.7801506 -4.069435 1.262797 
-Negative log-likelihood at call 28: 4.421625
+Sum of squared residuals at call 28: 4.421625
 85.03001 -0.7801506 -4.069435 1.262797 
 85.03001 -0.7801507 -4.069435 1.262797 
-Negative log-likelihood at call 30: 4.421624
+Sum of squared residuals at call 30: 4.421624
 85.03001 -0.7801506 -4.069435 1.262797 
 85.03001 -0.7801506 -4.069435 1.262797 
 85.02878 -0.7900844 -4.023945 1.256918 
 85.02964 -0.7857352 -4.054587 1.260236 
-Negative log-likelihood at call 34: 4.414346
+Sum of squared residuals at call 34: 4.414346
 85.02964 -0.7857352 -4.054587 1.260236 
 85.02964 -0.7857351 -4.054587 1.260236 
-Negative log-likelihood at call 36: 4.414346
+Sum of squared residuals at call 36: 4.414346
 85.02964 -0.7857352 -4.054588 1.260236 
 85.02964 -0.7857352 -4.054587 1.260236 
 85.02812 -0.7778128 -4.042219 1.25389 
-Negative log-likelihood at call 39: 4.372463
+Sum of squared residuals at call 39: 4.372463
 85.02812 -0.7778128 -4.042219 1.25389 
 85.02812 -0.7778129 -4.042219 1.25389 
-Negative log-likelihood at call 41: 4.372462
+Sum of squared residuals at call 41: 4.372462
 85.02812 -0.7778128 -4.042219 1.25389 
 85.02812 -0.7778128 -4.042219 1.25389 
 85.02419 -0.7765144 -4.02942 1.245094 
 85.0263 -0.7778419 -4.036021 1.249634 
-Negative log-likelihood at call 45: 4.369313
+Sum of squared residuals at call 45: 4.369313
 85.0263 -0.7778419 -4.036021 1.249634 
 85.0263 -0.7778418 -4.036021 1.249634 
-Negative log-likelihood at call 47: 4.369313
+Sum of squared residuals at call 47: 4.369313
 85.0263 -0.7778419 -4.036022 1.249634 
 85.0263 -0.7778419 -4.036021 1.249634 
-Negative log-likelihood at call 49: 4.369313
+Sum of squared residuals at call 49: 4.369313
 85.02267 -0.7786811 -4.02967 1.252015 
-Negative log-likelihood at call 50: 4.365062
+Sum of squared residuals at call 50: 4.365062
 85.02268 -0.7786811 -4.02967 1.252015 
 85.02267 -0.7786812 -4.02967 1.252015 
 85.02267 -0.7786811 -4.02967 1.252015 
-Negative log-likelihood at call 53: 4.365062
+Sum of squared residuals at call 53: 4.365062
 85.02267 -0.7786811 -4.02967 1.252015 
 85.01633 -0.7763163 -4.027611 1.248897 
-Negative log-likelihood at call 55: 4.364078
+Sum of squared residuals at call 55: 4.364078
 85.01633 -0.7763163 -4.027611 1.248897 
-Negative log-likelihood at call 56: 4.364078
+Sum of squared residuals at call 56: 4.364078
 85.01633 -0.7763164 -4.027611 1.248897 
-Negative log-likelihood at call 57: 4.364077
+Sum of squared residuals at call 57: 4.364077
 85.01633 -0.7763163 -4.027611 1.248897 
 85.01633 -0.7763163 -4.027611 1.248897 
 85.00894 -0.7777917 -4.026307 1.24772 
-Negative log-likelihood at call 60: 4.364052
+Sum of squared residuals at call 60: 4.364052
 85.00894 -0.7777917 -4.026307 1.24772 
-Negative log-likelihood at call 61: 4.364052
+Sum of squared residuals at call 61: 4.364052
 85.00894 -0.7777917 -4.026307 1.24772 
-Negative log-likelihood at call 62: 4.364052
+Sum of squared residuals at call 62: 4.364052
 85.00894 -0.7777917 -4.026307 1.24772 
 85.00894 -0.7777917 -4.026307 1.24772 
-Negative log-likelihood at call 64: 4.364052
+Sum of squared residuals at call 64: 4.364052
 85.00518 -0.7773082 -4.026004 1.248453 
-Negative log-likelihood at call 65: 4.362751
+Sum of squared residuals at call 65: 4.362751
 85.00519 -0.7773082 -4.026004 1.248453 
 85.00518 -0.7773083 -4.026004 1.248453 
-Negative log-likelihood at call 67: 4.362751
+Sum of squared residuals at call 67: 4.362751
 85.00518 -0.7773082 -4.026005 1.248453 
 85.00518 -0.7773082 -4.026004 1.248453 
 85.00134 -0.7776046 -4.025878 1.248775 
-Negative log-likelihood at call 70: 4.362721
+Sum of squared residuals at call 70: 4.362721
 85.00135 -0.7776046 -4.025878 1.248775 
-Negative log-likelihood at call 71: 4.362721
+Sum of squared residuals at call 71: 4.362721
 85.00134 -0.7776046 -4.025878 1.248775 
-Negative log-likelihood at call 72: 4.362721
+Sum of squared residuals at call 72: 4.362721
 85.00134 -0.7776046 -4.025878 1.248775 
 85.00134 -0.7776046 -4.025878 1.248775 
 85.0032 -0.7774734 -4.0257 1.248643 
-Negative log-likelihood at call 75: 4.362715
+Sum of squared residuals at call 75: 4.362715
 85.0032 -0.7774734 -4.0257 1.248643 
 85.0032 -0.7774734 -4.0257 1.248643 
-Negative log-likelihood at call 77: 4.362715
+Sum of squared residuals at call 77: 4.362715
 85.0032 -0.7774735 -4.0257 1.248643 
 85.0032 -0.7774734 -4.0257 1.248643 
 85.0032 -0.7774734 -4.0257 1.248643 
 85.0032 -0.7774734 -4.0257 1.248643 
 85.00249 -0.7774909 -4.025911 1.248679 
-Negative log-likelihood at call 82: 4.362715
+Sum of squared residuals at call 82: 4.362715
 85.0025 -0.7774909 -4.025911 1.248679 
-Negative log-likelihood at call 83: 4.362715
+Sum of squared residuals at call 83: 4.362715
 85.00249 -0.7774909 -4.025911 1.248679 
 85.00249 -0.7774905 -4.025911 1.248679 
 85.00249 -0.7774914 -4.025911 1.248679 
-Negative log-likelihood at call 86: 4.362715
+Sum of squared residuals at call 86: 4.362715
 85.00249 -0.7774909 -4.025911 1.248679 
 85.00249 -0.7774909 -4.025911 1.248679 
 85.00249 -0.7774909 -4.025911 1.248679 
 85.00249 -0.7774909 -4.025911 1.248679 
 85.00274 -0.7774922 -4.025821 1.248672 
-Negative log-likelihood at call 91: 4.362714
+Sum of squared residuals at call 91: 4.362714
 85.00274 -0.7774922 -4.025821 1.248672 
 85.00274 -0.7774922 -4.025821 1.248672 
-Negative log-likelihood at call 93: 4.362714
+Sum of squared residuals at call 93: 4.362714
 85.00274 -0.7774921 -4.025821 1.248672 
-Negative log-likelihood at call 94: 4.362714
+Sum of squared residuals at call 94: 4.362714
 85.00274 -0.7774922 -4.025821 1.248672 
 85.00274 -0.7774922 -4.025821 1.248672 
 85.00274 -0.7774922 -4.025821 1.248672 
 85.00274 -0.7774922 -4.025821 1.248672 
 85.00274 -0.7774922 -4.025821 1.248672 
 85.00273 -0.7774912 -4.025817 1.24867 
-Negative log-likelihood at call 100: 4.362714
+Sum of squared residuals at call 100: 4.362714
 85.00275 -0.7774912 -4.025817 1.24867 
 85.00271 -0.7774912 -4.025817 1.24867 
 85.00273 -0.7774905 -4.025817 1.24867 
@@ -152,7 +152,7 @@ Negative log-likelihood at call 100: 4.362714
 85.00273 -0.7774912 -4.025817 1.248671 
 85.00273 -0.7774912 -4.025817 1.248669 
 85.00274 -0.7774913 -4.025819 1.248671 
-Negative log-likelihood at call 109: 4.362714
+Sum of squared residuals at call 109: 4.362714
 85.00276 -0.7774913 -4.025819 1.248671 
 85.00272 -0.7774913 -4.025819 1.248671 
 85.00274 -0.7774904 -4.025819 1.248671 
diff --git a/tests/testthat/FOCUS_2006_D.csf b/tests/testthat/FOCUS_2006_D.csf
index 84500b54..9e912a28 100644
--- a/tests/testthat/FOCUS_2006_D.csf
+++ b/tests/testthat/FOCUS_2006_D.csf
@@ -5,7 +5,7 @@ Description:
 MeasurementUnits: % AR
 TimeUnits: days
 Comments: Created using mkin::CAKE_export
-Date: 2019-04-10
+Date: 2019-04-24
 Optimiser: IRLS
 
 [Data]
diff --git a/tests/testthat/summary_DFOP_FOCUS_C.txt b/tests/testthat/summary_DFOP_FOCUS_C.txt
index 1d669d43..b0a6bb6d 100644
--- a/tests/testthat/summary_DFOP_FOCUS_C.txt
+++ b/tests/testthat/summary_DFOP_FOCUS_C.txt
@@ -10,10 +10,10 @@ d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
 
 Model predictions using solution type analytical 
 
-Fitted with method using test 0 model solutions performed in test time 0 s
+Fitted using test 0 model solutions performed in test time 0 s
 
 Error model:
-NULL
+Constant variance 
 
 Starting values for parameters to be optimised:
              value   type
@@ -61,7 +61,7 @@ k2        0.01785   7.636 7.901e-04  0.01241  0.02568
 g         0.85390  83.310 6.221e-08  0.82310  0.88020
 sigma     0.69620   4.243 6.618e-03  0.24060  1.15200
 
-Chi2 error levels in percent:
+FOCUS Chi2 error levels in percent:
          err.min n.optim df
 All data   2.661       4  5
 parent     2.661       4  5
diff --git a/tests/testthat/test_FOCUS_D_UBA_expertise.R b/tests/testthat/test_FOCUS_D_UBA_expertise.R
index 3a49078c..a282f5e7 100644
--- a/tests/testthat/test_FOCUS_D_UBA_expertise.R
+++ b/tests/testthat/test_FOCUS_D_UBA_expertise.R
@@ -74,22 +74,3 @@ test_that("Fits without internal transformations are correct for FOCUS D", {
 # References:
 # Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative
 # zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452
-
-test_that("The t-value for fits using internal transformations corresponds with results from FME, synthetic data", {
-  skip_on_cran()
-  m_synth_DFOP_par.minff <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
-                             M1 = mkinsub("SFO"),
-                             M2 = mkinsub("SFO"),
-                             use_of_ff = "min", quiet = TRUE)
-
-  fit_DFOP_par_c_2 <- mkinfit(m_synth_DFOP_par.minff,
-                            synthetic_data_for_UBA_2014[[12]]$data,
-                            quiet = TRUE)
-
-  skip("Hessian matrices and df calculations differ from those in FME")
-  # Note that the k1 and k2 are exchanged in the untransformed fit evaluated with FME for this test
-  expect_equal(signif(summary(fit_DFOP_par_c_2)$bpar[1:7, "t value"], 5),
-               c(parent_0 = 80.054, k_M1_sink = 12.291, k_M2_sink = 10.588,
-                 f_parent_to_M1 = 21.4960, f_parent_to_M2 = 24.0890,
-                 k1 = 16.1450, k2 = 8.1747))
-})
diff --git a/tests/testthat/test_logistic.R b/tests/testthat/test_logistic.R
index 9f50f32e..5a89fbf5 100644
--- a/tests/testthat/test_logistic.R
+++ b/tests/testthat/test_logistic.R
@@ -34,13 +34,3 @@ test_that("The logistic model fit is reproducible", {
   dtx <- endpoints(m)$distimes["parent", ]
   expect_equivalent(dtx, c(36.865, 62.415, 4297.854, 10.833), tolerance = 0.001)
 })
-
-test_that("The logistic fit can be done via differential equation", {
-  # This is slow as we did not implement conversion to C
-  # because it is unlikely we will use the logistic model with metabolites
-  skip("Skip slow fit of logistic model using deSolve without compilation")
-  m_2 <- mkinfit("logistic", d_2_1[[1]], solution_type = "deSolve", 
-                 quiet = TRUE)
-  dtx_2 <- endpoints(m_2)$distimes["parent", ]
-  expect_equivalent(dtx_2, c(36.865, 62.415, 4297.854, 10.833), tolerance = 0.001)
-})