Adapt tests to new algorithms and output

One of the tests exceeded the number of iterations when using the
d_3 error model algorithm, so only use "direct" in this case.

4 files changed, 14 insertions, 381 deletions

diff --git a/test.log b/test.log
index 30196966..58aa129f 100644
--- a/test.log
+++ b/test.log
@@ -2,394 +2,26 @@ Loading mkin
 Testing mkin
 ✔ |  OK F W S | Context
 
⠏ |   0       | Export dataset for reading into CAKE
✔ |   1       | Export dataset for reading into CAKE
-
⠏ |   0       | Error model fitting
⠋ |   1       | Error model fitting
⠹ |   3       | Error model fitting
⠸ |   4       | Error model fitting
⠼ |   5       | Error model fitting
⠴ |   6       | Error model fitting
⠧ |   8       | Error model fitting
⠏ |  10       | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  11       | Error model fittingSum of squared residuals at call 1: 1590.602
-Sum of squared residuals at call 3: 1590.601
-Sum of squared residuals at call 5: 999.7593
-Sum of squared residuals at call 7: 999.7513
-Sum of squared residuals at call 8: 979.5713
-Sum of squared residuals at call 9: 948.3366
-Sum of squared residuals at call 10: 855.9518
-Sum of squared residuals at call 13: 836.4547
-Sum of squared residuals at call 14: 836.4547
-Sum of squared residuals at call 16: 836.422
-Sum of squared residuals at call 19: 836.422
-Sum of squared residuals at call 23: 836.422
-Sum of squared residuals at call 24: 836.422
-Negative log-likelihood at call 30: 65.71278
-
⠹ |  13       | Error model fittingNegative log-likelihood at call 1: 4104.4
-Negative log-likelihood at call 2: 4104.4
-Negative log-likelihood at call 4: 4104.399
-Negative log-likelihood at call 6: 85.79717
-Negative log-likelihood at call 11: 72.50327
-Negative log-likelihood at call 12: 72.50327
-Negative log-likelihood at call 17: 71.79809
-Negative log-likelihood at call 22: 71.10373
-Negative log-likelihood at call 26: 71.10373
-Negative log-likelihood at call 27: 70.84093
-Negative log-likelihood at call 29: 70.84093
-Negative log-likelihood at call 32: 70.64538
-Negative log-likelihood at call 37: 70.64538
-Negative log-likelihood at call 38: 70.33707
-Negative log-likelihood at call 40: 70.33707
-Negative log-likelihood at call 42: 70.33707
-Negative log-likelihood at call 43: 69.89484
-Negative log-likelihood at call 48: 69.05915
-Negative log-likelihood at call 53: 67.99547
-Negative log-likelihood at call 56: 67.99547
-Negative log-likelihood at call 58: 66.59808
-Negative log-likelihood at call 63: 66.59808
-Negative log-likelihood at call 64: 66.2343
-Negative log-likelihood at call 65: 66.23429
-Negative log-likelihood at call 68: 66.23428
-Negative log-likelihood at call 69: 65.67228
-Negative log-likelihood at call 70: 65.67228
-Negative log-likelihood at call 73: 65.67227
-Negative log-likelihood at call 74: 65.33106
-Negative log-likelihood at call 79: 65.31005
-Negative log-likelihood at call 80: 65.31005
-Negative log-likelihood at call 81: 65.31005
-Negative log-likelihood at call 83: 65.31004
-Negative log-likelihood at call 84: 65.17731
-Negative log-likelihood at call 85: 65.17731
-Negative log-likelihood at call 89: 65.16821
-Negative log-likelihood at call 94: 65.13357
-Negative log-likelihood at call 96: 65.13357
-Negative log-likelihood at call 98: 65.13357
-Negative log-likelihood at call 99: 65.08107
-Negative log-likelihood at call 104: 64.86685
-Negative log-likelihood at call 105: 64.86685
-Negative log-likelihood at call 109: 64.50332
-Negative log-likelihood at call 112: 64.50332
-Negative log-likelihood at call 114: 64.10889
-Negative log-likelihood at call 119: 63.57448
-Negative log-likelihood at call 120: 63.57448
-Negative log-likelihood at call 123: 63.57448
-Negative log-likelihood at call 124: 63.5456
-Negative log-likelihood at call 127: 63.5456
-Negative log-likelihood at call 129: 63.48903
-Negative log-likelihood at call 131: 63.48903
-Negative log-likelihood at call 135: 63.47608
-Negative log-likelihood at call 140: 63.47181
-Negative log-likelihood at call 141: 63.47181
-Negative log-likelihood at call 145: 63.4714
-Negative log-likelihood at call 146: 63.4714
-Negative log-likelihood at call 151: 63.4714
-Negative log-likelihood at call 152: 63.4714
-Negative log-likelihood at call 160: 63.4714
-Negative log-likelihood at call 169: 63.4714
-
⠸ |  14       | Error model fittingSum of squared residuals at call 1: 1590.602
-Sum of squared residuals at call 3: 1590.601
-Sum of squared residuals at call 5: 999.7593
-Sum of squared residuals at call 7: 999.7513
-Sum of squared residuals at call 8: 979.5713
-Sum of squared residuals at call 9: 948.3366
-Sum of squared residuals at call 10: 855.9518
-Sum of squared residuals at call 13: 836.4547
-Sum of squared residuals at call 14: 836.4547
-Sum of squared residuals at call 16: 836.422
-Sum of squared residuals at call 19: 836.422
-Sum of squared residuals at call 23: 836.422
-Sum of squared residuals at call 24: 836.422
-Negative log-likelihood at call 32: 7208.014
-Negative log-likelihood at call 34: 7208.013
-Negative log-likelihood at call 36: 132.2815
-Negative log-likelihood at call 41: 75.57291
-Negative log-likelihood at call 42: 75.57291
-Negative log-likelihood at call 45: 75.57291
-Negative log-likelihood at call 47: 73.57761
-Negative log-likelihood at call 52: 70.3766
-Negative log-likelihood at call 57: 68.75449
-Negative log-likelihood at call 62: 68.50149
-Negative log-likelihood at call 64: 68.50149
-Negative log-likelihood at call 66: 68.50146
-Negative log-likelihood at call 67: 68.2035
-Negative log-likelihood at call 71: 68.2035
-Negative log-likelihood at call 72: 68.13162
-Negative log-likelihood at call 77: 67.94078
-Negative log-likelihood at call 78: 67.60889
-Negative log-likelihood at call 80: 67.60889
-Negative log-likelihood at call 83: 66.72645
-Negative log-likelihood at call 88: 65.66209
-Negative log-likelihood at call 93: 64.79703
-Negative log-likelihood at call 98: 64.6745
-Negative log-likelihood at call 101: 64.6745
-Negative log-likelihood at call 102: 64.6745
-Negative log-likelihood at call 103: 64.60902
-Negative log-likelihood at call 108: 64.56616
-Negative log-likelihood at call 113: 64.55458
-Negative log-likelihood at call 117: 64.55458
-Negative log-likelihood at call 119: 64.50796
-Negative log-likelihood at call 121: 64.50796
-Negative log-likelihood at call 124: 64.41361
-Negative log-likelihood at call 129: 64.2052
-Negative log-likelihood at call 134: 63.92264
-Negative log-likelihood at call 139: 63.66033
-Negative log-likelihood at call 140: 63.66033
-Negative log-likelihood at call 142: 63.66033
-Negative log-likelihood at call 144: 63.55606
-Negative log-likelihood at call 146: 63.55606
-Negative log-likelihood at call 149: 63.48537
-Negative log-likelihood at call 150: 63.48537
-Negative log-likelihood at call 154: 63.47183
-Negative log-likelihood at call 156: 63.47183
-Negative log-likelihood at call 157: 63.47183
-Negative log-likelihood at call 159: 63.47141
-Negative log-likelihood at call 160: 63.47141
-Negative log-likelihood at call 162: 63.47141
-Negative log-likelihood at call 164: 63.4714
-Negative log-likelihood at call 165: 63.4714
-Negative log-likelihood at call 168: 63.4714
-Negative log-likelihood at call 172: 63.4714
-Negative log-likelihood at call 173: 63.4714
-Negative log-likelihood at call 181: 63.4714
-Negative log-likelihood at call 182: 63.4714
-Negative log-likelihood at call 191: 63.4714
-
⠼ |  15       | Error model fittingSum of squared residuals at call 1: 1590.602
-Sum of squared residuals at call 3: 1590.601
-Sum of squared residuals at call 5: 999.7593
-Sum of squared residuals at call 7: 999.7513
-Sum of squared residuals at call 8: 979.5713
-Sum of squared residuals at call 9: 948.3366
-Sum of squared residuals at call 10: 855.9518
-Sum of squared residuals at call 13: 836.4547
-Sum of squared residuals at call 14: 836.4547
-Sum of squared residuals at call 16: 836.422
-Sum of squared residuals at call 19: 836.422
-Sum of squared residuals at call 23: 836.422
-Sum of squared residuals at call 24: 836.422
-Negative log-likelihood at call 32: 7208.013
-Negative log-likelihood at call 34: 164.0572
-Negative log-likelihood at call 37: 139.4622
-Negative log-likelihood at call 40: 138.9749
-Negative log-likelihood at call 43: 134.4266
-Negative log-likelihood at call 46: 108.9584
-Negative log-likelihood at call 49: 98.97929
-Negative log-likelihood at call 52: 91.49458
-Negative log-likelihood at call 55: 87.49741
-Negative log-likelihood at call 57: 87.49741
-Negative log-likelihood at call 58: 85.29177
-Negative log-likelihood at call 61: 84.23711
-Negative log-likelihood at call 64: 83.76617
-Negative log-likelihood at call 67: 83.53472
-Negative log-likelihood at call 70: 83.33848
-Negative log-likelihood at call 73: 83.00488
-Negative log-likelihood at call 76: 82.06707
-Negative log-likelihood at call 77: 82.06707
-Negative log-likelihood at call 79: 75.48058
-Negative log-likelihood at call 82: 69.27829
-Negative log-likelihood at call 85: 66.14308
-Negative log-likelihood at call 86: 66.14306
-Negative log-likelihood at call 90: 65.73421
-Negative log-likelihood at call 91: 65.73421
-Negative log-likelihood at call 94: 65.71278
-Negative log-likelihood at call 98: 65.71278
-Negative log-likelihood at call 99: 65.71278
-Negative log-likelihood at call 127: 65.71278
-
⠴ |  16       | Error model fittingSum of squared residuals at call 1: 1590.602
-Sum of squared residuals at call 3: 1590.601
-Sum of squared residuals at call 5: 999.7593
-Sum of squared residuals at call 7: 999.7513
-Sum of squared residuals at call 8: 979.5713
-Sum of squared residuals at call 9: 948.3366
-Sum of squared residuals at call 10: 855.9518
-Sum of squared residuals at call 13: 836.4547
-Sum of squared residuals at call 14: 836.4547
-Sum of squared residuals at call 16: 836.422
-Sum of squared residuals at call 19: 836.422
-Sum of squared residuals at call 23: 836.422
-Sum of squared residuals at call 24: 836.422
-Negative log-likelihood at call 32: 7208.013
-Negative log-likelihood at call 34: 164.0572
-Negative log-likelihood at call 37: 139.4622
-Negative log-likelihood at call 40: 138.9749
-Negative log-likelihood at call 43: 134.4266
-Negative log-likelihood at call 46: 108.9584
-Negative log-likelihood at call 49: 98.97929
-Negative log-likelihood at call 52: 91.49458
-Negative log-likelihood at call 55: 87.49741
-Negative log-likelihood at call 57: 87.49741
-Negative log-likelihood at call 58: 85.29177
-Negative log-likelihood at call 61: 84.23711
-Negative log-likelihood at call 64: 83.76617
-Negative log-likelihood at call 67: 83.53472
-Negative log-likelihood at call 70: 83.33848
-Negative log-likelihood at call 73: 83.00488
-Negative log-likelihood at call 76: 82.06707
-Negative log-likelihood at call 77: 82.06707
-Negative log-likelihood at call 79: 75.48058
-Negative log-likelihood at call 82: 69.27829
-Negative log-likelihood at call 85: 66.14308
-Negative log-likelihood at call 86: 66.14306
-Negative log-likelihood at call 90: 65.73421
-Negative log-likelihood at call 91: 65.73421
-Negative log-likelihood at call 94: 65.71278
-Negative log-likelihood at call 98: 65.71278
-Negative log-likelihood at call 99: 65.71278
-Negative log-likelihood at call 132: 65.71278
-
⠦ |  17       | Error model fittingSum of squared residuals at call 1: 1590.602
-Sum of squared residuals at call 3: 1590.601
-Sum of squared residuals at call 5: 999.7593
-Sum of squared residuals at call 7: 999.7513
-Sum of squared residuals at call 8: 979.5713
-Sum of squared residuals at call 9: 948.3366
-Sum of squared residuals at call 10: 855.9518
-Sum of squared residuals at call 13: 836.4547
-Sum of squared residuals at call 14: 836.4547
-Sum of squared residuals at call 16: 836.422
-Sum of squared residuals at call 19: 836.422
-Sum of squared residuals at call 23: 836.422
-Sum of squared residuals at call 24: 836.422
-Negative log-likelihood at call 32: 7208.013
-Negative log-likelihood at call 34: 164.0572
-Negative log-likelihood at call 37: 139.4622
-Negative log-likelihood at call 40: 138.9749
-Negative log-likelihood at call 43: 134.4266
-Negative log-likelihood at call 46: 108.9584
-Negative log-likelihood at call 49: 98.97929
-Negative log-likelihood at call 52: 91.49458
-Negative log-likelihood at call 55: 87.49741
-Negative log-likelihood at call 57: 87.49741
-Negative log-likelihood at call 58: 85.29177
-Negative log-likelihood at call 61: 84.23711
-Negative log-likelihood at call 64: 83.76617
-Negative log-likelihood at call 67: 83.53472
-Negative log-likelihood at call 70: 83.33848
-Negative log-likelihood at call 73: 83.00488
-Negative log-likelihood at call 76: 82.06707
-Negative log-likelihood at call 77: 82.06707
-Negative log-likelihood at call 79: 75.48058
-Negative log-likelihood at call 82: 69.27829
-Negative log-likelihood at call 85: 66.14308
-Negative log-likelihood at call 86: 66.14306
-Negative log-likelihood at call 90: 65.73421
-Negative log-likelihood at call 91: 65.73421
-Negative log-likelihood at call 94: 65.71278
-Negative log-likelihood at call 98: 65.71278
-Negative log-likelihood at call 99: 65.71278
-Negative log-likelihood at call 118: 65.71278
-Negative log-likelihood at call 134: 65.71278
-
⠧ |  18       | Error model fittingNegative log-likelihood at call 1: 4104.4
-Negative log-likelihood at call 2: 4104.4
-Negative log-likelihood at call 4: 4104.399
-Negative log-likelihood at call 6: 85.79717
-Negative log-likelihood at call 11: 72.50327
-Negative log-likelihood at call 12: 72.50327
-Negative log-likelihood at call 17: 71.79809
-Negative log-likelihood at call 22: 71.10373
-Negative log-likelihood at call 26: 71.10373
-Negative log-likelihood at call 27: 70.84093
-Negative log-likelihood at call 29: 70.84093
-Negative log-likelihood at call 32: 70.64538
-Negative log-likelihood at call 37: 70.64538
-Negative log-likelihood at call 38: 70.33707
-Negative log-likelihood at call 40: 70.33707
-Negative log-likelihood at call 42: 70.33707
-Negative log-likelihood at call 43: 69.89484
-Negative log-likelihood at call 48: 69.05915
-Negative log-likelihood at call 53: 67.99547
-Negative log-likelihood at call 56: 67.99547
-Negative log-likelihood at call 58: 66.59808
-Negative log-likelihood at call 63: 66.59808
-Negative log-likelihood at call 64: 66.2343
-Negative log-likelihood at call 65: 66.23429
-Negative log-likelihood at call 68: 66.23428
-Negative log-likelihood at call 69: 65.67228
-Negative log-likelihood at call 70: 65.67228
-Negative log-likelihood at call 73: 65.67227
-Negative log-likelihood at call 74: 65.33106
-Negative log-likelihood at call 79: 65.31005
-Negative log-likelihood at call 80: 65.31005
-Negative log-likelihood at call 81: 65.31005
-Negative log-likelihood at call 83: 65.31004
-Negative log-likelihood at call 84: 65.17731
-Negative log-likelihood at call 85: 65.17731
-Negative log-likelihood at call 89: 65.16821
-Negative log-likelihood at call 94: 65.13357
-Negative log-likelihood at call 96: 65.13357
-Negative log-likelihood at call 98: 65.13357
-Negative log-likelihood at call 99: 65.08107
-Negative log-likelihood at call 104: 64.86685
-Negative log-likelihood at call 105: 64.86685
-Negative log-likelihood at call 109: 64.50332
-Negative log-likelihood at call 112: 64.50332
-Negative log-likelihood at call 114: 64.10889
-Negative log-likelihood at call 119: 63.57448
-Negative log-likelihood at call 120: 63.57448
-Negative log-likelihood at call 123: 63.57448
-Negative log-likelihood at call 124: 63.5456
-Negative log-likelihood at call 127: 63.5456
-Negative log-likelihood at call 129: 63.48903
-Negative log-likelihood at call 131: 63.48903
-Negative log-likelihood at call 135: 63.47608
-Negative log-likelihood at call 140: 63.47181
-Negative log-likelihood at call 141: 63.47181
-Negative log-likelihood at call 145: 63.4714
-Negative log-likelihood at call 146: 63.4714
-Negative log-likelihood at call 151: 63.4714
-Negative log-likelihood at call 152: 63.4714
-Negative log-likelihood at call 160: 63.4714
-Negative log-likelihood at call 169: 63.4714
-Sum of squared residuals at call 179: 1590.602
-Sum of squared residuals at call 181: 1590.601
-Sum of squared residuals at call 183: 999.7593
-Sum of squared residuals at call 185: 999.7513
-Sum of squared residuals at call 186: 979.5713
-Sum of squared residuals at call 187: 948.3366
-Sum of squared residuals at call 188: 855.9518
-Sum of squared residuals at call 191: 836.4547
-Sum of squared residuals at call 192: 836.4547
-Sum of squared residuals at call 194: 836.422
-Sum of squared residuals at call 197: 836.422
-Sum of squared residuals at call 201: 836.422
-Sum of squared residuals at call 202: 836.422
-Negative log-likelihood at call 210: 7208.013
-Negative log-likelihood at call 212: 164.0572
-Negative log-likelihood at call 215: 139.4622
-Negative log-likelihood at call 218: 138.9749
-Negative log-likelihood at call 221: 134.4266
-Negative log-likelihood at call 224: 108.9584
-Negative log-likelihood at call 227: 98.97929
-Negative log-likelihood at call 230: 91.49458
-Negative log-likelihood at call 233: 87.49741
-Negative log-likelihood at call 235: 87.49741
-Negative log-likelihood at call 236: 85.29177
-Negative log-likelihood at call 239: 84.23711
-Negative log-likelihood at call 242: 83.76617
-Negative log-likelihood at call 245: 83.53472
-Negative log-likelihood at call 248: 83.33848
-Negative log-likelihood at call 251: 83.00488
-Negative log-likelihood at call 254: 82.06707
-Negative log-likelihood at call 255: 82.06707
-Negative log-likelihood at call 257: 75.48058
-Negative log-likelihood at call 260: 69.27829
-Negative log-likelihood at call 263: 66.14308
-Negative log-likelihood at call 264: 66.14306
-Negative log-likelihood at call 268: 65.73421
-Negative log-likelihood at call 269: 65.73421
-Negative log-likelihood at call 272: 65.71278
-Negative log-likelihood at call 276: 65.71278
-Negative log-likelihood at call 277: 65.71278
-Negative log-likelihood at call 305: 65.71278
-
⠇ |  19       | Error model fitting
⠏ |  20       | Error model fitting
✔ |  20       | Error model fitting [506.4 s]
-
⠏ |   0       | Calculation of FOCUS chi2 error levels
⠋ |   1       | Calculation of FOCUS chi2 error levels
⠹ |   3       | Calculation of FOCUS chi2 error levels
⠼ |   5       | Calculation of FOCUS chi2 error levels
✔ |   5       | Calculation of FOCUS chi2 error levels [3.6 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)
⠸ |   4       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠇ |   9       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
✔ |  13       | Results for FOCUS D established in expertise for UBA (Ranke 2014) [3.8 s]
+
⠏ |   0       | Error model fitting
⠋ |   1       | Error model fitting
⠹ |   3       | Error model fitting
⠸ |   4       | Error model fitting
⠼ |   5       | Error model fitting
⠴ |   6       | Error model fitting
⠧ |   8       | Error model fitting
⠏ |  10       | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  10   1   | Error model fitting
⠋ |  11       | Error model fitting
⠹ |  13       | Error model fitting
⠸ |  14       | Error model fitting
⠼ |  15       | Error model fitting
⠴ |  16       | Error model fitting
⠦ |  17       | Error model fitting
⠧ |  18       | Error model fitting
⠇ |  19       | Error model fitting
⠏ |  20       | Error model fitting
✔ |  20       | Error model fitting [414.2 s]
+
⠏ |   0       | Calculation of FOCUS chi2 error levels
⠋ |   1       | Calculation of FOCUS chi2 error levels
⠹ |   3       | Calculation of FOCUS chi2 error levels
⠼ |   5       | Calculation of FOCUS chi2 error levels
✔ |   5       | Calculation of FOCUS chi2 error levels [3.5 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)
⠸ |   4       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
⠇ |   9       | Results for FOCUS D established in expertise for UBA (Ranke 2014)
✔ |  13       | Results for FOCUS D established in expertise for UBA (Ranke 2014) [3.7 s]
 
⠏ |   0       | Test fitting the decline of metabolites from their maximum
⠋ |   1       | Test fitting the decline of metabolites from their maximum
⠹ |   3       | Test fitting the decline of metabolites from their maximum
⠼ |   5       | Test fitting the decline of metabolites from their maximum
✔ |   6       | Test fitting the decline of metabolites from their maximum [0.9 s]
 
⠏ |   0       | Fitting the logistic model
⠋ |   1       | Fitting the logistic model
✔ |   1       | Fitting the logistic model [0.9 s]
 
⠏ |   0       | Test dataset class mkinds used in gmkin
✔ |   1       | Test dataset class mkinds used in gmkin
-
⠏ |   0       | Special cases of mkinfit calls
⠋ |   1       | Special cases of mkinfit calls
⠇ |   9       | Special cases of mkinfit calls
⠏ |  10       | Special cases of mkinfit calls
⠋ |  11       | Special cases of mkinfit calls
⠙ |  12       | Special cases of mkinfit calls
✔ |  12       | Special cases of mkinfit calls [2.7 s]
+
⠏ |   0       | Special cases of mkinfit calls
⠋ |   1       | Special cases of mkinfit calls
⠇ |   9       | Special cases of mkinfit calls
⠏ |  10       | Special cases of mkinfit calls
⠋ |  11       | Special cases of mkinfit calls
⠙ |  12       | Special cases of mkinfit calls
✔ |  12       | Special cases of mkinfit calls [2.6 s]
 
⠏ |   0       | mkinmod model generation and printing
⠇ |   9       | mkinmod model generation and printing
✔ |   9       | mkinmod model generation and printing [0.2 s]
 
⠏ |   0       | Model predictions with mkinpredict
⠋ |   1       | Model predictions with mkinpredict
✔ |   3       | Model predictions with mkinpredict [0.3 s]
-
⠏ |   0       | Evaluations according to 2015 NAFTA guidance
⠙ |   2       | Evaluations according to 2015 NAFTA guidance
⠇ |   9       | Evaluations according to 2015 NAFTA guidance
⠏ |  10       | Evaluations according to 2015 NAFTA guidance
⠴ |  16       | Evaluations according to 2015 NAFTA guidance
✔ |  16       | Evaluations according to 2015 NAFTA guidance [4.1 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
⠴ |  16       | Fitting of parent only models
⠧ |  18       | Fitting of parent only models
⠏ |  20       | Fitting of parent only models
✔ |  21       | Fitting of parent only models [40.9 s]
+
⠏ |   0       | Evaluations according to 2015 NAFTA guidance
⠙ |   2       | Evaluations according to 2015 NAFTA guidance
⠇ |   9       | Evaluations according to 2015 NAFTA guidance
⠏ |  10       | Evaluations according to 2015 NAFTA guidance
⠴ |  16       | Evaluations according to 2015 NAFTA guidance
✔ |  16       | Evaluations according to 2015 NAFTA guidance [4.0 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
⠴ |  16       | Fitting of parent only models
⠧ |  18       | Fitting of parent only models
⠏ |  20       | Fitting of parent only models
✔ |  21       | Fitting of parent only models [40.7 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)
✔ |   4       | Calculation of maximum time weighted average concentrations (TWAs) [2.2 s]
 
⠏ |   0       | Summary
✔ |   1       | Summary
 
⠏ |   0       | Plotting
⠹ |   3       | Plotting
✔ |   4       | Plotting [0.3 s]
 
⠏ |   0       | AIC calculation
✔ |   2       | AIC calculation
-
⠏ |   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 [5.4 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)
⠹ |   3       | Results for synthetic data established in expertise for UBA (Ranke 2014)
✔ |   4       | Results for synthetic data established in expertise for UBA (Ranke 2014) [7.2 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 [5.3 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)
⠹ |   3       | Results for synthetic data established in expertise for UBA (Ranke 2014)
✔ |   4       | Results for synthetic data established in expertise for UBA (Ranke 2014) [7.1 s]
 
 ══ Results ═════════════════════════════════════════════════════════════════════
-Duration: 584.3 s
+Duration: 491.4 s
 
 OK:       125
 Failed:   0
diff --git a/tests/testthat/FOCUS_2006_D.csf b/tests/testthat/FOCUS_2006_D.csf
index 43215ec4..668b1151 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: 2019-06-04
+Date: 2019-06-05
 Optimiser: IRLS
 
 [Data]
diff --git a/tests/testthat/summary_DFOP_FOCUS_C.txt b/tests/testthat/summary_DFOP_FOCUS_C.txt
index fb8051c5..5c6f4257 100644
--- a/tests/testthat/summary_DFOP_FOCUS_C.txt
+++ b/tests/testthat/summary_DFOP_FOCUS_C.txt
@@ -12,8 +12,9 @@ Model predictions using solution type analytical
 
 Fitted using test 0 model solutions performed in test time 0 s
 
-Error model:
-Constant variance 
+Error model: Constant variance 
+
+Error model algorithm: d_3 
 
 Starting values for parameters to be optimised:
              value   type
diff --git a/tests/testthat/test_error_models.R b/tests/testthat/test_error_models.R
index 404f02ab..fa1f7131 100644
--- a/tests/testthat/test_error_models.R
+++ b/tests/testthat/test_error_models.R
@@ -153,7 +153,7 @@ test_that("Reweighting method 'tc' produces reasonable variance estimates", {
   # For a single fit, we get a relative error of less than 10%  in the error
   # model components
   f_met_2_tc_e4 <- mkinfit(m_synth_DFOP_lin, d_met_2_15[[1]], quiet = TRUE,
-                          error_model = "tc")
+    error_model = "tc", error_model_algorithm = "direct")
   parm_errors_met_2_tc_e4 <- (f_met_2_tc_e4$errparms - c(0.5, 0.07)) / c(0.5, 0.07)
   expect_true(all(abs(parm_errors_met_2_tc_e4) < 0.1))