Basic test for two-component reweighting

2 files changed, 13 insertions, 9 deletions

diff --git a/test.log b/test.log
index ff374f43..4da96066 100644
--- a/test.log
+++ b/test.log
@@ -2,10 +2,10 @@ Loading mkin
 Testing mkin
 ✔ | OK F W S | Context
 
⠏ |  0       | Calculation of FOCUS chi2 error levels
⠋ |  1       | Calculation of FOCUS chi2 error levels
⠙ |  2       | Calculation of FOCUS chi2 error levels
✔ |  2       | Calculation of FOCUS chi2 error levels [2.5 s]
-
⠏ |  0       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠋ |  1       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠙ |  2       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠹ |  3       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠸ |  4       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠼ |  5       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠴ |  6       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠦ |  7       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠧ |  8       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
✔ |  8       | Results for FOCUS D established in expertise for UBA (Ranke 2014) [7.3 s]
-
⠏ |  0       | Iteratively reweighted least squares (IRLS) fitting
⠋ |  1       | Iteratively reweighted least squares (IRLS) fitting
⠙ |  1     1 | Iteratively reweighted least squares (IRLS) fitting
✔ |  1     1 | Iteratively reweighted least squares (IRLS) fitting [8.9 s]
+
⠏ |  0       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠋ |  1       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠙ |  2       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠹ |  3       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠸ |  4       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠼ |  5       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠴ |  6       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠦ |  7       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠧ |  8       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠇ |  9       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠏ | 10       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠋ | 11       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠙ | 12       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠹ | 13       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
✔ | 13       | Results for FOCUS D established in expertise for UBA (Ranke 2014) [8.2 s]
+
⠏ |  0       | Iteratively reweighted least squares (IRLS) fitting
⠋ |  1       | Iteratively reweighted least squares (IRLS) fitting
⠙ |  2       | Iteratively reweighted least squares (IRLS) fitting
⠹ |  2     1 | Iteratively reweighted least squares (IRLS) fitting
✔ |  2     1 | Iteratively reweighted least squares (IRLS) fitting [16.3 s]
 ────────────────────────────────────────────────────────────────────────────────
-test_irls.R:44: skip: Reweighting method 'tc' works
+test_irls.R:48: skip: Reweighting method 'tc' works
 Too much trouble with datasets that are randomly generated
 ────────────────────────────────────────────────────────────────────────────────
 
⠏ |  0       | Fitting the logistic model
⠋ |  1       | Fitting the logistic model
⠙ |  1     1 | Fitting the logistic model
✔ |  1     1 | Fitting the logistic model [0.5 s]
@@ -15,19 +15,19 @@ Skip slow fit of logistic model using deSolve without compilation
 ────────────────────────────────────────────────────────────────────────────────
 
⠏ |  0       | Model predictions with mkinpredict
⠋ |  1       | Model predictions with mkinpredict
⠙ |  2       | Model predictions with mkinpredict
⠹ |  3       | Model predictions with mkinpredict
✔ |  3       | Model predictions with mkinpredict [0.3 s]
 
⠏ |  0       | Evaluations according to 2015 NAFTA guidance
⠋ |  1       | Evaluations according to 2015 NAFTA guidance
⠙ |  1   1   | Evaluations according to 2015 NAFTA guidance
⠙ |  2       | Evaluations according to 2015 NAFTA guidance
⠹ |  3       | Evaluations according to 2015 NAFTA guidance
⠸ |  4       | Evaluations according to 2015 NAFTA guidance
⠼ |  5       | Evaluations according to 2015 NAFTA guidance
⠴ |  6       | Evaluations according to 2015 NAFTA guidance
⠦ |  7       | Evaluations according to 2015 NAFTA guidance
⠧ |  8       | Evaluations according to 2015 NAFTA guidance
⠇ |  9       | Evaluations according to 2015 NAFTA guidance
✔ |  9       | Evaluations according to 2015 NAFTA guidance [0.9 s]
-
⠏ |  0       | Fitting of parent only models
⠋ |  1       | Fitting of parent only models
⠙ |  2       | Fitting of parent only models
⠹ |  3       | Fitting of parent only models
⠸ |  4       | Fitting of parent only models
⠼ |  5       | Fitting of parent only models
⠴ |  6       | Fitting of parent only models
⠦ |  7       | Fitting of parent only models
⠧ |  8       | Fitting of parent only models
⠇ |  9       | Fitting of parent only models
⠏ | 10       | Fitting of parent only models
⠋ | 11       | Fitting of parent only models
⠙ | 12       | Fitting of parent only models
⠹ | 13       | Fitting of parent only models
⠸ | 14       | Fitting of parent only models
⠼ | 15       | Fitting of parent only models
⠴ | 16       | Fitting of parent only models
⠦ | 17       | Fitting of parent only models
⠧ | 18       | Fitting of parent only models
⠇ | 19       | Fitting of parent only models
⠏ | 20       | Fitting of parent only models
⠋ | 21       | Fitting of parent only models
✔ | 21       | Fitting of parent only models [24.3 s]
+
⠏ |  0       | Fitting of parent only models
⠋ |  1       | Fitting of parent only models
⠙ |  2       | Fitting of parent only models
⠹ |  3       | Fitting of parent only models
⠸ |  4       | Fitting of parent only models
⠼ |  5       | Fitting of parent only models
⠴ |  6       | Fitting of parent only models
⠦ |  7       | Fitting of parent only models
⠧ |  8       | Fitting of parent only models
⠇ |  9       | Fitting of parent only models
⠏ | 10       | Fitting of parent only models
⠋ | 11       | Fitting of parent only models
⠙ | 12       | Fitting of parent only models
⠹ | 13       | Fitting of parent only models
⠸ | 14       | Fitting of parent only models
⠼ | 15       | Fitting of parent only models
⠴ | 16       | Fitting of parent only models
⠦ | 17       | Fitting of parent only models
⠧ | 18       | Fitting of parent only models
⠇ | 19       | Fitting of parent only models
⠏ | 20       | Fitting of parent only models
⠋ | 21       | Fitting of parent only models
✔ | 21       | Fitting of parent only models [24.1 s]
 
⠏ |  0       | Calculation of maximum time weighted average concentrations (TWAs)
⠋ |  1       | Calculation of maximum time weighted average concentrations (TWAs)
⠙ |  2       | Calculation of maximum time weighted average concentrations (TWAs)
⠹ |  3       | Calculation of maximum time weighted average concentrations (TWAs)
⠸ |  4       | Calculation of maximum time weighted average concentrations (TWAs)
⠼ |  5       | Calculation of maximum time weighted average concentrations (TWAs)
⠴ |  6       | Calculation of maximum time weighted average concentrations (TWAs)
⠦ |  7       | Calculation of maximum time weighted average concentrations (TWAs)
⠧ |  8       | Calculation of maximum time weighted average concentrations (TWAs)
✔ |  8       | Calculation of maximum time weighted average concentrations (TWAs) [7.3 s]
 
⠏ |  0       | Summary
⠋ |  1       | Summary
✔ |  1       | Summary
 
⠏ |  0       | Plotting
⠋ |  1       | Plotting
⠙ |  2       | Plotting
⠹ |  3       | Plotting
✔ |  3       | Plotting [0.3 s]
-
⠏ |  0       | Calculation of maximum time weighted average concentrations (TWAs)
⠋ |  1       | Calculation of maximum time weighted average concentrations (TWAs)
⠙ |  2       | Calculation of maximum time weighted average concentrations (TWAs)
⠹ |  3       | Calculation of maximum time weighted average concentrations (TWAs)
⠸ |  4       | Calculation of maximum time weighted average concentrations (TWAs)
⠼ |  5       | Calculation of maximum time weighted average concentrations (TWAs)
⠴ |  6       | Calculation of maximum time weighted average concentrations (TWAs)
⠦ |  7       | Calculation of maximum time weighted average concentrations (TWAs)
⠧ |  8       | Calculation of maximum time weighted average concentrations (TWAs)
✔ |  8       | Calculation of maximum time weighted average concentrations (TWAs) [7.4 s]
-
⠏ |  0       | Plotting
⠋ |  1       | Plotting
⠙ |  2       | Plotting
⠹ |  3       | Plotting
✔ |  3       | Plotting [0.3 s]
-
⠏ |  0       | Complex test case from Schaefer et al. (2007) Piacenza paper
⠋ |  1       | Complex test case from Schaefer et al. (2007) Piacenza paper
⠙ |  2       | Complex test case from Schaefer et al. (2007) Piacenza paper
✔ |  2       | Complex test case from Schaefer et al. (2007) Piacenza paper [5.9 s]
+
⠏ |  0       | Calculation of maximum time weighted average concentrations (TWAs)
⠋ |  1       | Calculation of maximum time weighted average concentrations (TWAs)
⠙ |  2       | Calculation of maximum time weighted average concentrations (TWAs)
⠹ |  3       | Calculation of maximum time weighted average concentrations (TWAs)
⠸ |  4       | Calculation of maximum time weighted average concentrations (TWAs)
⠼ |  5       | Calculation of maximum time weighted average concentrations (TWAs)
⠴ |  6       | Calculation of maximum time weighted average concentrations (TWAs)
⠦ |  7       | Calculation of maximum time weighted average concentrations (TWAs)
⠧ |  8       | Calculation of maximum time weighted average concentrations (TWAs)
✔ |  8       | Calculation of maximum time weighted average concentrations (TWAs) [7.2 s]
+
⠏ |  0       | Plotting
⠋ |  1       | Plotting
⠙ |  2       | Plotting
⠹ |  3       | Plotting
✔ |  3       | Plotting [0.2 s]
+
⠏ |  0       | Complex test case from Schaefer et al. (2007) Piacenza paper
⠋ |  1       | Complex test case from Schaefer et al. (2007) Piacenza paper
⠙ |  2       | Complex test case from Schaefer et al. (2007) Piacenza paper
✔ |  2       | Complex test case from Schaefer et al. (2007) Piacenza paper [6.0 s]
 
⠏ |  0       | Results for synthetic data established in expertise for UBA (Ranke 2014)
⠋ |  1       | Results for synthetic data established in expertise for UBA (Ranke 2014)
⠙ |  2       | Results for synthetic data established in expertise for UBA (Ranke 2014)
⠹ |  3       | Results for synthetic data established in expertise for UBA (Ranke 2014)
⠸ |  4       | Results for synthetic data established in expertise for UBA (Ranke 2014)
✔ |  4       | Results for synthetic data established in expertise for UBA (Ranke 2014) [7.5 s]
 
 ══ Results ═════════════════════════════════════════════════════════════════════
-Duration: 75.7 s
+Duration: 83.6 s
 
-OK:       74
+OK:       80
 Failed:   0
 Warnings: 0
 Skipped:  2
diff --git a/tests/testthat/test_irls.R b/tests/testthat/test_irls.R
index 76ee73b5..f61f793d 100644
--- a/tests/testthat/test_irls.R
+++ b/tests/testthat/test_irls.R
@@ -41,6 +41,10 @@ test_that("Reweighting method 'obs' works", {
 })
 
 test_that("Reweighting method 'tc' works", {
+  fit_irls_2 <- mkinfit(m_synth_SFO_lin, SFO_lin_a, reweight.method = "tc", quiet = TRUE)
+  parms_2 <- round(fit_irls_2$bparms.optim, c(1, 4, 4, 4, 4, 4))
+  expect_equivalent(parms_2, c(102.1, 0.7393, 0.2992, 0.0202, 0.7687, 0.7229))
+
   skip("Too much trouble with datasets that are randomly generated")
   # I need to make the tc method more robust against that
   # skip_on_cran()