Unpack state. You will see state come out of dust2 systems in several places, for example dust_system_state, but it will typically be an unstructured vector with no names; this is not very useful! However, your model knows what each element, or group of elements "means". You can unpack your state from this unstructured array into a named list using this function. The same idea applies to the higher-dimensional arrays that you might get if your system has multiple particles, multiple parameter groups or has been run for multiple time steps.
Arguments
- obj
A
dust_systemobject (from dust_system_create) ordust_likelihoodobject (from dust_filter_create or dust_unfilter_create).- state
A state vector, matrix or array. This might have come from dust_system_state, dust_likelihood_last_trajectories, or dust_likelihood_last_state.
See also
monty::monty_packer, and within that especially
documentation for $unpack(), which powers this function.
Examples
sir <- dust_example("sir")
sys <- dust_system_create(sir, list(), n_particles = 10, dt = 0.25)
dust_system_set_state_initial(sys)
t <- seq(0, 100, by = 5)
y <- dust_system_simulate(sys, t)
# The result here is a 5 x 10 x 21 matrix: 5 states by 10 particles by
# 21 times.
dim(y)
#> [1] 5 10 21
# The 10 particles and 21 times (following t) are simple enough, but
# what are our 5 compartments?
# You can use dust_unpack_state() to reshape your output as a
# list:
dust_unpack_state(sys, y)
#> $S
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 990 972 938 888 826 751 658 576 472 402 350 304 270
#> [2,] 990 979 956 923 873 798 713 623 530 423 359 311 275
#> [3,] 990 985 965 938 871 794 720 647 549 470 390 328 287
#> [4,] 990 984 961 928 882 817 732 640 552 476 415 373 335
#> [5,] 990 983 967 949 936 913 880 840 791 733 681 621 571
#> [6,] 990 979 958 935 897 817 718 605 515 433 364 319 276
#> [7,] 990 979 951 924 872 802 705 597 503 417 350 286 253
#> [8,] 990 981 966 943 911 869 836 784 700 626 546 471 420
#> [9,] 990 978 961 936 890 815 731 644 552 460 391 344 309
#> [10,] 990 974 935 881 818 744 662 560 477 422 370 313 288
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21]
#> [1,] 249 236 230 221 219 218 217 216
#> [2,] 245 227 217 212 209 205 202 198
#> [3,] 256 238 216 204 195 188 187 186
#> [4,] 306 294 274 259 253 242 240 238
#> [5,] 507 441 402 367 351 334 315 286
#> [6,] 244 212 197 190 174 168 166 163
#> [7,] 230 203 189 175 164 160 159 155
#> [8,] 378 350 316 289 259 245 230 220
#> [9,] 275 260 250 243 236 228 218 210
#> [10,] 262 243 228 221 211 208 207 207
#>
#> $I
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 10 24 37 62 86 119 155 170 195 172 133 121 103
#> [2,] 10 13 26 48 77 100 126 157 170 186 158 134 108
#> [3,] 10 9 25 36 77 114 113 136 162 158 156 148 129
#> [4,] 10 10 28 41 67 95 121 140 165 155 133 120 107
#> [5,] 10 8 21 26 19 30 46 52 67 84 99 102 102
#> [6,] 10 16 22 33 53 98 152 176 190 180 166 140 118
#> [7,] 10 14 37 47 76 104 147 190 182 184 162 148 113
#> [8,] 10 12 22 30 37 59 62 79 118 124 132 145 129
#> [9,] 10 15 26 36 62 106 134 153 165 184 149 132 103
#> [10,] 10 25 46 69 89 115 140 167 161 149 130 121 95
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21]
#> [1,] 74 61 35 29 19 12 7 4
#> [2,] 90 60 47 26 18 12 7 6
#> [3,] 110 93 72 53 36 26 12 8
#> [4,] 78 55 47 40 27 26 16 10
#> [5,] 117 113 99 84 59 52 49 57
#> [6,] 104 91 67 47 40 28 17 12
#> [7,] 92 77 61 52 42 30 22 15
#> [8,] 114 93 93 82 76 63 56 43
#> [9,] 80 63 44 24 23 26 29 21
#> [10,] 79 64 51 40 24 15 8 3
#>
#> $R
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 0 4 25 50 88 130 187 254 333 426 517 575 627
#> [2,] 0 8 18 29 50 102 161 220 300 391 483 555 617
#> [3,] 0 6 10 26 52 92 167 217 289 372 454 524 584
#> [4,] 0 6 11 31 51 88 147 220 283 369 452 507 558
#> [5,] 0 9 12 25 45 57 74 108 142 183 220 277 327
#> [6,] 0 5 20 32 50 85 130 219 295 387 470 541 606
#> [7,] 0 7 12 29 52 94 148 213 315 399 488 566 634
#> [8,] 0 7 12 27 52 72 102 137 182 250 322 384 451
#> [9,] 0 7 13 28 48 79 135 203 283 356 460 524 588
#> [10,] 0 1 19 50 93 141 198 273 362 429 500 566 617
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21]
#> [1,] 677 703 735 750 762 770 776 780
#> [2,] 665 713 736 762 773 783 791 796
#> [3,] 634 669 712 743 769 786 801 806
#> [4,] 616 651 679 701 720 732 744 752
#> [5,] 376 446 499 549 590 614 636 657
#> [6,] 652 697 736 763 786 804 817 825
#> [7,] 678 720 750 773 794 810 819 830
#> [8,] 508 557 591 629 665 692 714 737
#> [9,] 645 677 706 733 741 746 753 769
#> [10,] 659 693 721 739 765 777 785 790
#>
#> $cases_cumul
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 0 18 52 102 164 239 332 414 518 588 640 686 720
#> [2,] 0 11 34 67 117 192 277 367 460 567 631 679 715
#> [3,] 0 5 25 52 119 196 270 343 441 520 600 662 703
#> [4,] 0 6 29 62 108 173 258 350 438 514 575 617 655
#> [5,] 0 7 23 41 54 77 110 150 199 257 309 369 419
#> [6,] 0 11 32 55 93 173 272 385 475 557 626 671 714
#> [7,] 0 11 39 66 118 188 285 393 487 573 640 704 737
#> [8,] 0 9 24 47 79 121 154 206 290 364 444 519 570
#> [9,] 0 12 29 54 100 175 259 346 438 530 599 646 681
#> [10,] 0 16 55 109 172 246 328 430 513 568 620 677 702
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21]
#> [1,] 741 754 760 769 771 772 773 774
#> [2,] 745 763 773 778 781 785 788 792
#> [3,] 734 752 774 786 795 802 803 804
#> [4,] 684 696 716 731 737 748 750 752
#> [5,] 483 549 588 623 639 656 675 704
#> [6,] 746 778 793 800 816 822 824 827
#> [7,] 760 787 801 815 826 830 831 835
#> [8,] 612 640 674 701 731 745 760 770
#> [9,] 715 730 740 747 754 762 772 780
#> [10,] 728 747 762 769 779 782 783 783
#>
#> $cases_inc
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
#> [1,] 0 4 11 12 15 19 23 21 17 11 8 9 5
#> [2,] 0 2 6 9 14 13 22 26 26 19 10 6 9
#> [3,] 0 2 6 5 12 20 12 19 21 10 17 12 6
#> [4,] 0 1 4 9 9 18 18 21 25 14 9 5 6
#> [5,] 0 2 4 7 2 3 5 6 9 11 12 11 13
#> [6,] 0 3 6 8 12 18 25 17 23 13 8 6 10
#> [7,] 0 4 11 9 11 19 24 26 16 12 10 13 6
#> [8,] 0 1 4 7 6 9 9 12 19 16 13 17 6
#> [9,] 0 2 3 6 11 19 17 14 17 19 8 13 5
#> [10,] 0 2 14 12 18 18 12 16 16 16 11 6 4
#> [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21]
#> [1,] 4 3 2 2 1 0 0 0
#> [2,] 7 2 2 2 0 2 0 0
#> [3,] 6 3 6 0 1 1 0 0
#> [4,] 3 2 4 2 1 3 0 0
#> [5,] 19 13 10 7 3 1 2 4
#> [6,] 8 7 1 4 1 2 0 0
#> [7,] 1 6 2 2 3 1 0 1
#> [8,] 10 7 9 5 7 3 1 2
#> [9,] 7 1 3 1 2 4 3 2
#> [10,] 3 4 5 2 1 0 0 0
#>
# Here, the list is named following the compartments (S, I, R,
# etc) and is a 10 x 21 matrix (i.e., the remaining dimensions
# from y)
# We could apply this to the final state, which converts a 5 x 10
# matrix of state into a 5 element list of vectors, each with
# length 10:
s <- dust_system_state(sys)
dim(s)
#> [1] 5 10
dust_unpack_state(sys, s)
#> $S
#> [1] 216 198 186 238 286 163 155 220 210 207
#>
#> $I
#> [1] 4 6 8 10 57 12 15 43 21 3
#>
#> $R
#> [1] 780 796 806 752 657 825 830 737 769 790
#>
#> $cases_cumul
#> [1] 774 792 804 752 704 827 835 770 780 783
#>
#> $cases_inc
#> [1] 0 0 0 0 4 0 1 2 2 0
#>
# If you need more control, you can use 'dust_unpack_index' to map
# names to positions within the state dimension of this array
dust_unpack_index(sys)
#> $S
#> [1] 1
#>
#> $I
#> [1] 2
#>
#> $R
#> [1] 3
#>
#> $cases_cumul
#> [1] 4
#>
#> $cases_inc
#> [1] 5
#>