Extract changepoints
changepoints.RdRetrieve the indices of the changepoints identified by an algorithm or model.
Usage
changepoints(x, ...)
# Default S3 method
changepoints(x, ...)
# S3 method for class 'mod_cpt'
changepoints(x, ...)
# S3 method for class 'seg_basket'
changepoints(x, ...)
# S3 method for class 'seg_cpt'
changepoints(x, ...)
# S3 method for class 'tidycpt'
changepoints(x, use_labels = FALSE, ...)
# S3 method for class 'ga'
changepoints(x, ...)
# S3 method for class 'cpt'
changepoints(x, ...)
# S3 method for class 'cga'
changepoints(x, ...)
# S3 method for class 'segmented'
changepoints(x, ...)
# S3 method for class 'wbs'
changepoints(x, ...)Value
a numeric vector of changepoint indices, or, if use_labels is
TRUE, a character of time labels.
Details
tidycpt objects, as well as their segmenter and model components,
implement changepoints() methods.
Note that this function is not to be confused with wbs::changepoints(),
which returns different information.
For the default method, changepoints() will attempt to return the
cpt_true attribute, which is set by test_set().
See also
Other tidycpt-generics:
as.model(),
as.segmenter(),
diagnose(),
fitness(),
model_name()
Examples
cpts <- segment(DataCPSim, method = "ga", maxiter = 5)
changepoints(cpts$segmenter)
#> x3 x6 x12 x18 x19 x22 x23 x24 x25 x26 x27 x28 x30
#> 3 6 12 18 19 22 23 24 25 26 27 28 30
#> x31 x37 x38 x39 x41 x46 x47 x48 x50 x53 x56 x57 x58
#> 31 37 38 39 41 46 47 48 50 53 56 57 58
#> x66 x71 x72 x75 x76 x77 x81 x83 x84 x86 x90 x91 x92
#> 66 71 72 75 76 77 81 83 84 86 90 91 92
#> x93 x97 x101 x103 x105 x107 x108 x111 x112 x114 x117 x121 x123
#> 93 97 101 103 105 107 108 111 112 114 117 121 123
#> x124 x132 x133 x135 x137 x140 x141 x144 x145 x153 x157 x160 x162
#> 124 132 133 135 137 140 141 144 145 153 157 160 162
#> x163 x164 x165 x166 x169 x170 x171 x173 x177 x181 x182 x184 x186
#> 163 164 165 166 169 170 171 173 177 181 182 184 186
#> x187 x189 x190 x194 x195 x196 x198 x199 x201 x204 x206 x209 x212
#> 187 189 190 194 195 196 198 199 201 204 206 209 212
#> x213 x215 x218 x224 x229 x230 x235 x239 x241 x242 x246 x252 x253
#> 213 215 218 224 229 230 235 239 241 242 246 252 253
#> x254 x258 x259 x261 x262 x264 x265 x267 x268 x269 x270 x271 x274
#> 254 258 259 261 262 264 265 267 268 269 270 271 274
#> x277 x278 x279 x280 x281 x282 x284 x286 x287 x288 x289 x290 x292
#> 277 278 279 280 281 282 284 286 287 288 289 290 292
#> x293 x294 x299 x301 x304 x311 x313 x314 x315 x317 x318 x320 x325
#> 293 294 299 301 304 311 313 314 315 317 318 320 325
#> x326 x327 x328 x329 x330 x332 x334 x335 x337 x338 x346 x347 x349
#> 326 327 328 329 330 332 334 335 337 338 346 347 349
#> x350 x353 x355 x356 x361 x363 x365 x368 x369 x370 x371 x375 x376
#> 350 353 355 356 361 363 365 368 369 370 371 375 376
#> x381 x382 x384 x385 x387 x388 x389 x390 x393 x394 x396 x397 x398
#> 381 382 384 385 387 388 389 390 393 394 396 397 398
#> x400 x401 x404 x405 x407 x408 x409 x410 x413 x415 x418 x419 x422
#> 400 401 404 405 407 408 409 410 413 415 418 419 422
#> x424 x425 x426 x430 x431 x432 x433 x434 x435 x436 x440 x441 x443
#> 424 425 426 430 431 432 433 434 435 436 440 441 443
#> x444 x445 x446 x447 x449 x450 x451 x452 x453 x454 x457 x458 x460
#> 444 445 446 447 449 450 451 452 453 454 457 458 460
#> x462 x467 x468 x472 x474 x475 x480 x482 x486 x487 x488 x489 x490
#> 462 467 468 472 474 475 480 482 486 487 488 489 490
#> x491 x492 x493 x495 x496 x499 x501 x503 x506 x507 x508 x510 x511
#> 491 492 493 495 496 499 501 503 506 507 508 510 511
#> x513 x514 x520 x525 x526 x529 x531 x532 x534 x535 x537 x539 x540
#> 513 514 520 525 526 529 531 532 534 535 537 539 540
#> x541 x542 x543 x549 x551 x553 x555 x557 x559 x560 x561 x562 x570
#> 541 542 543 549 551 553 555 557 559 560 561 562 570
#> x571 x574 x576 x577 x578 x579 x580 x581 x582 x586 x587 x588 x589
#> 571 574 576 577 578 579 580 581 582 586 587 588 589
#> x591 x592 x593 x594 x595 x598 x604 x608 x610 x611 x616 x617 x621
#> 591 592 593 594 595 598 604 608 610 611 616 617 621
#> x622 x623 x624 x626 x627 x630 x633 x634 x636 x639 x640 x641 x643
#> 622 623 624 626 627 630 633 634 636 639 640 641 643
#> x646 x649 x652 x655 x658 x659 x660 x662 x665 x666 x667 x669 x671
#> 646 649 652 655 658 659 660 662 665 666 667 669 671
#> x672 x673 x674 x675 x676 x678 x680 x682 x686 x687 x688 x690 x691
#> 672 673 674 675 676 678 680 682 686 687 688 690 691
#> x692 x693 x695 x696 x698 x700 x703 x706 x708 x709 x715 x716 x723
#> 692 693 695 696 698 700 703 706 708 709 715 716 723
#> x724 x726 x727 x728 x729 x730 x731 x732 x733 x735 x737 x739 x740
#> 724 726 727 728 729 730 731 732 733 735 737 739 740
#> x741 x742 x744 x746 x747 x748 x749 x753 x754 x755 x756 x757 x758
#> 741 742 744 746 747 748 749 753 754 755 756 757 758
#> x762 x767 x768 x773 x778 x780 x782 x785 x786 x794 x797 x798 x804
#> 762 767 768 773 778 780 782 785 786 794 797 798 804
#> x805 x808 x813 x815 x818 x821 x823 x825 x826 x827 x828 x829 x832
#> 805 808 813 815 818 821 823 825 826 827 828 829 832
#> x833 x834 x835 x836 x837 x838 x839 x840 x842 x843 x846 x847 x849
#> 833 834 835 836 837 838 839 840 842 843 846 847 849
#> x852 x853 x854 x857 x858 x862 x863 x865 x868 x871 x874 x875 x880
#> 852 853 854 857 858 862 863 865 868 871 874 875 880
#> x881 x884 x885 x889 x891 x898 x899 x900 x901 x906 x911 x916 x918
#> 881 884 885 889 891 898 899 900 901 906 911 916 918
#> x919 x920 x921 x923 x924 x929 x931 x933 x934 x936 x938 x941 x942
#> 919 920 921 923 924 929 931 933 934 936 938 941 942
#> x945 x946 x947 x948 x950 x954 x957 x958 x959 x961 x962 x964 x966
#> 945 946 947 948 950 954 957 958 959 961 962 964 966
#> x967 x968 x969 x970 x972 x973 x974 x979 x980 x981 x983 x984 x985
#> 967 968 969 970 972 973 974 979 980 981 983 984 985
#> x989 x990 x992 x994 x995 x996 x997 x999 x1000 x1003 x1004 x1007 x1008
#> 989 990 992 994 995 996 997 999 1000 1003 1004 1007 1008
#> x1010 x1012 x1013 x1017 x1018 x1019 x1021 x1022 x1026 x1029 x1030 x1034 x1036
#> 1010 1012 1013 1017 1018 1019 1021 1022 1026 1029 1030 1034 1036
#> x1037 x1039 x1040 x1041 x1042 x1043 x1044 x1049 x1056 x1057 x1060 x1061 x1062
#> 1037 1039 1040 1041 1042 1043 1044 1049 1056 1057 1060 1061 1062
#> x1063 x1064 x1069 x1071 x1076 x1084 x1086 x1087 x1088 x1089 x1092 x1094
#> 1063 1064 1069 1071 1076 1084 1086 1087 1088 1089 1092 1094
# \donttest{
# Segment a times series using a genetic algorithm
cpts <- segment(DataCPSim, method = "cga")
changepoints(cpts$segmenter)
#> [1] 545 820 939 968 979
# }
cpts <- segment(DataCPSim, method = "segmented")
changepoints(cpts$segmenter)
#> [1] 776
cpts <- segment(DataCPSim, method = "wbs")
changepoints(cpts$segmenter)
#> [1] 547 809 810 822 823 939 952 953 972 976 980 982 997 999 1031
#> [16] 1032 1040 1041 1046 1063 1064 1065 1066 1086