From 9cb1cebc1dcb85b1474b560210bf3939c0dc8da0 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Tue, 6 Feb 2018 17:15:22 +0100 Subject: Skip some tests on CRAN, more quiet examples --- docs/reference/test_data_from_UBA_2014-12.png | Bin 0 -> 23306 bytes docs/reference/test_data_from_UBA_2014-4.png | Bin 0 -> 17555 bytes docs/reference/test_data_from_UBA_2014.html | 212 +------------------------- 3 files changed, 6 insertions(+), 206 deletions(-) create mode 100644 docs/reference/test_data_from_UBA_2014-12.png create mode 100644 docs/reference/test_data_from_UBA_2014-4.png (limited to 'docs/reference') diff --git a/docs/reference/test_data_from_UBA_2014-12.png b/docs/reference/test_data_from_UBA_2014-12.png new file mode 100644 index 00000000..6738f3a0 Binary files /dev/null and b/docs/reference/test_data_from_UBA_2014-12.png differ diff --git a/docs/reference/test_data_from_UBA_2014-4.png b/docs/reference/test_data_from_UBA_2014-4.png new file mode 100644 index 00000000..8c65e604 Binary files /dev/null and b/docs/reference/test_data_from_UBA_2014-4.png differ diff --git a/docs/reference/test_data_from_UBA_2014.html b/docs/reference/test_data_from_UBA_2014.html index e30babc4..ed2ccd9c 100644 --- a/docs/reference/test_data_from_UBA_2014.html +++ b/docs/reference/test_data_from_UBA_2014.html @@ -131,109 +131,8 @@ # large parameter correlations, among other reasons (e.g. the adequacy of the # model). m_ws <- mkinmod(parent_w = mkinsub("SFO", "parent_s"), - parent_s = mkinsub("SFO", "parent_w"))
#> Successfully compiled differential equation model from auto-generated C code.
f_river <- mkinfit(m_ws, test_data_from_UBA_2014[[1]]$data)
#> Model cost at call 1 : 2371.755 -#> Model cost at call 3 : 2371.755 -#> Model cost at call 7 : 457.5705 -#> Model cost at call 10 : 457.5608 -#> Model cost at call 14 : 297.2882 -#> Model cost at call 16 : 297.2882 -#> Model cost at call 18 : 297.2881 -#> Model cost at call 21 : 275.6034 -#> Model cost at call 23 : 275.6034 -#> Model cost at call 27 : 268.2102 -#> Model cost at call 29 : 268.2101 -#> Model cost at call 33 : 255.941 -#> Model cost at call 35 : 255.941 -#> Model cost at call 39 : 246.486 -#> Model cost at call 41 : 246.486 -#> Model cost at call 45 : 231.4275 -#> Model cost at call 47 : 231.4275 -#> Model cost at call 51 : 212.4338 -#> Model cost at call 52 : 212.4338 -#> Model cost at call 53 : 212.4337 -#> Model cost at call 57 : 203.7185 -#> Model cost at call 58 : 203.7185 -#> Model cost at call 63 : 198.3304 -#> Model cost at call 69 : 198.3304 -#> Model cost at call 70 : 195.794 -#> Model cost at call 72 : 195.7939 -#> Model cost at call 76 : 195.2477 -#> Model cost at call 77 : 195.2477 -#> Model cost at call 82 : 191.6184 -#> Model cost at call 84 : 191.6184 -#> Model cost at call 88 : 189.9011 -#> Model cost at call 90 : 189.9011 -#> Model cost at call 91 : 189.9011 -#> Model cost at call 94 : 189.223 -#> Model cost at call 95 : 189.223 -#> Model cost at call 100 : 188.8728 -#> Model cost at call 101 : 188.8728 -#> Model cost at call 103 : 188.8728 -#> Model cost at call 106 : 188.2057 -#> Model cost at call 107 : 188.2057 -#> Model cost at call 112 : 187.8429 -#> Model cost at call 118 : 187.6219 -#> Model cost at call 119 : 187.3931 -#> Model cost at call 121 : 187.3931 -#> Model cost at call 125 : 187.1236 -#> Model cost at call 126 : 187.1236 -#> Model cost at call 131 : 186.9995 -#> Model cost at call 137 : 186.927 -#> Model cost at call 139 : 186.927 -#> Model cost at call 143 : 186.8909 -#> Model cost at call 146 : 186.8909 -#> Model cost at call 150 : 186.8708 -#> Model cost at call 152 : 186.8708 -#> Model cost at call 157 : 186.8606 -#> Model cost at call 159 : 186.8606 -#> Model cost at call 161 : 186.8606 -#> Model cost at call 162 : 186.8606 -#> Model cost at call 167 : 186.8551 -#> Model cost at call 169 : 186.8551 -#> Model cost at call 176 : 186.8519 -#> Model cost at call 177 : 186.8519 -#> Model cost at call 180 : 186.8519 -#> Model cost at call 181 : 186.8519 -#> Model cost at call 186 : 186.8504 -#> Model cost at call 187 : 186.8504 -#> Model cost at call 196 : 186.8496 -#> Model cost at call 197 : 186.8496 -#> Model cost at call 200 : 186.8496 -#> Model cost at call 206 : 186.8493 -#> Model cost at call 211 : 186.8493 -#> Model cost at call 215 : 186.8493 -#> Model cost at call 216 : 186.8491 -#> Model cost at call 225 : 186.8491 -#> Model cost at call 226 : 186.849 -#> Model cost at call 236 : 186.8489 -#> Model cost at call 246 : 186.8489 -#> Model cost at call 254 : 186.8489 -#> Model cost at call 257 : 186.8489 -#> Model cost at call 265 : 186.8489 -#> Model cost at call 268 : 186.8489 -#> Model cost at call 276 : 186.8489 -#> Model cost at call 279 : 186.8489 -#> Model cost at call 287 : 186.8489 -#> Model cost at call 290 : 186.8489 -#> Model cost at call 298 : 186.8489 -#> Model cost at call 301 : 186.8489 -#> Model cost at call 309 : 186.8489 -#> Model cost at call 312 : 186.8489 -#> Model cost at call 320 : 186.8489 -#> Model cost at call 323 : 186.8489 -#> Model cost at call 331 : 186.8489 -#> Model cost at call 334 : 186.8489 -#> Model cost at call 342 : 186.8489 -#> Model cost at call 345 : 186.8489 -#> Model cost at call 353 : 186.8489 -#> Model cost at call 356 : 186.8489 -#> Model cost at call 367 : 186.8489 -#> Model cost at call 374 : 186.8489 -#> Model cost at call 375 : 186.8489 -#> Model cost at call 380 : 186.8489 -#> Model cost at call 382 : 186.8489 -#> Model cost at call 383 : 186.8489 -#> Optimisation by method Port successfully terminated.
plot_sep(f_river)
+ parent_s = mkinsub("SFO", "parent_w"))
#> Successfully compiled differential equation model from auto-generated C code.
f_river <- mkinfit(m_ws, test_data_from_UBA_2014[[1]]$data, quiet = TRUE) + plot_sep(f_river)
summary(f_river)$bpar
#> Estimate se_notrans t value Pr(>t) Lower #> parent_w_0 9.598567e+01 2.33959810 4.102657e+01 9.568973e-19 NA #> k_parent_w_sink 3.603743e-01 0.03497716 1.030313e+01 4.988281e-09 NA @@ -249,7 +148,6 @@ #> All data 0.09246946 5 6 #> parent_w 0.06377096 3 3 #> parent_s 0.20882324 2 3
- # This is the evaluation used for the validation of software packages # in the expertise from 2014 m_soil <- mkinmod(parent = mkinsub("SFO", c("M1", "M2")), @@ -257,107 +155,8 @@ M2 = mkinsub("SFO", "M3"), M3 = mkinsub("SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
- f_soil <- mkinfit(m_soil, test_data_from_UBA_2014[[3]]$data)
#> Model cost at call 1 : 340.115 -#> Model cost at call 3 : 340.115 -#> Model cost at call 12 : 278.5521 -#> Model cost at call 14 : 278.5499 -#> Model cost at call 22 : 244.4153 -#> Model cost at call 24 : 244.4152 -#> Model cost at call 32 : 211.0249 -#> Model cost at call 34 : 211.0247 -#> Model cost at call 42 : 151.2576 -#> Model cost at call 44 : 151.2575 -#> Model cost at call 46 : 151.2574 -#> Model cost at call 52 : 109.7633 -#> Model cost at call 53 : 100.8415 -#> Model cost at call 58 : 100.8412 -#> Model cost at call 61 : 100.8412 -#> Model cost at call 62 : 100.8411 -#> Model cost at call 64 : 70.07576 -#> Model cost at call 66 : 70.07568 -#> Model cost at call 76 : 64.29488 -#> Model cost at call 78 : 64.29487 -#> Model cost at call 86 : 61.39756 -#> Model cost at call 88 : 61.39755 -#> Model cost at call 96 : 57.47933 -#> Model cost at call 98 : 57.47932 -#> Model cost at call 106 : 52.46647 -#> Model cost at call 108 : 52.46646 -#> Model cost at call 116 : 48.17301 -#> Model cost at call 118 : 48.173 -#> Model cost at call 126 : 45.15666 -#> Model cost at call 128 : 45.15665 -#> Model cost at call 137 : 44.55574 -#> Model cost at call 139 : 44.55573 -#> Model cost at call 143 : 44.55573 -#> Model cost at call 147 : 43.13847 -#> Model cost at call 149 : 43.13847 -#> Model cost at call 151 : 43.13847 -#> Model cost at call 158 : 43.11922 -#> Model cost at call 160 : 43.11922 -#> Model cost at call 168 : 42.29535 -#> Model cost at call 170 : 42.29535 -#> Model cost at call 178 : 42.03979 -#> Model cost at call 180 : 42.03979 -#> Model cost at call 189 : 41.56286 -#> Model cost at call 190 : 41.12187 -#> Model cost at call 191 : 39.73019 -#> Model cost at call 192 : 39.31762 -#> Model cost at call 193 : 39.31762 -#> Model cost at call 196 : 39.31762 -#> Model cost at call 203 : 38.6346 -#> Model cost at call 204 : 38.6346 -#> Model cost at call 205 : 38.63459 -#> Model cost at call 209 : 38.63459 -#> Model cost at call 210 : 38.63459 -#> Model cost at call 211 : 38.63459 -#> Model cost at call 213 : 38.12767 -#> Model cost at call 215 : 38.12767 -#> Model cost at call 223 : 38.04349 -#> Model cost at call 225 : 38.04349 -#> Model cost at call 229 : 38.04349 -#> Model cost at call 233 : 37.93963 -#> Model cost at call 236 : 37.93963 -#> Model cost at call 243 : 37.87645 -#> Model cost at call 244 : 37.87645 -#> Model cost at call 254 : 37.79144 -#> Model cost at call 256 : 37.79144 -#> Model cost at call 264 : 37.7493 -#> Model cost at call 269 : 37.7493 -#> Model cost at call 274 : 37.72466 -#> Model cost at call 275 : 37.72466 -#> Model cost at call 279 : 37.72466 -#> Model cost at call 283 : 37.72466 -#> Model cost at call 284 : 37.71402 -#> Model cost at call 285 : 37.71402 -#> Model cost at call 287 : 37.71402 -#> Model cost at call 294 : 37.70366 -#> Model cost at call 295 : 37.70366 -#> Model cost at call 296 : 37.70366 -#> Model cost at call 305 : 37.69553 -#> Model cost at call 306 : 37.69553 -#> Model cost at call 307 : 37.69553 -#> Model cost at call 315 : 37.6936 -#> Model cost at call 319 : 37.6936 -#> Model cost at call 321 : 37.6936 -#> Model cost at call 326 : 37.6924 -#> Model cost at call 328 : 37.6924 -#> Model cost at call 329 : 37.6924 -#> Model cost at call 336 : 37.69198 -#> Model cost at call 338 : 37.69198 -#> Model cost at call 344 : 37.69198 -#> Model cost at call 348 : 37.69197 -#> Model cost at call 350 : 37.69197 -#> Model cost at call 363 : 37.69197 -#> Model cost at call 364 : 37.69197 -#> Model cost at call 367 : 37.69197 -#> Model cost at call 382 : 37.69197 -#> Model cost at call 384 : 37.69197 -#> Model cost at call 387 : 37.69197 -#> Model cost at call 401 : 37.69197 -#> Model cost at call 420 : 37.69197 -#> Model cost at call 441 : 37.69197 -#> Optimisation by method Port successfully terminated.
plot_sep(f_soil, lpos = c("topright", "topright", "topright", "bottomright"))
summary(f_soil)$bpar
#> Estimate se_notrans t value Pr(>t) Lower + f_soil <- mkinfit(m_soil, test_data_from_UBA_2014[[3]]$data, quiet = TRUE) + plot_sep(f_soil, lpos = c("topright", "topright", "topright", "bottomright"))
summary(f_soil)$bpar
#> Estimate se_notrans t value Pr(>t) Lower #> parent_0 76.55425583 0.943443834 81.1434164 4.422340e-30 74.602593306 #> k_parent 0.12081956 0.004815515 25.0896457 1.639665e-18 0.111257526 #> k_M1 0.84258650 0.930121206 0.9058889 1.871937e-01 0.085876305 @@ -381,7 +180,8 @@ #> parent 0.04721283 2 6 #> M1 0.26551209 2 5 #> M2 0.20327575 2 5 -#> M3 0.05196549 3 4
+#> M3 0.05196549 3 4
+