tests/testthat/_snaps/spatial_block_cv.md

In tidymodels/spatialsample: Spatial Resampling Infrastructure

erroring when no S2

Code
  spatial_block_cv(ames_sf)
Condition
  Error in `spatial_block_cv()`:
  ! `spatial_block_cv()` can only process geographic coordinates when using the s2 geometry library.
  i Reproject your data into a projected coordinate reference system using `sf::st_transform()`.
  i Or install the `s2` package and enable it using `sf::sf_use_s2(TRUE)`.

systematic assignment -- snake

Code
  boston_snake
Output
  #  10-fold spatial block cross-validation 
  # A tibble: 10 x 2
     splits            id    
     <list>            <chr> 
   1 <split [662/20]>  Fold01
   2 <split [617/65]>  Fold02
   3 <split [604/78]>  Fold03
   4 <split [597/85]>  Fold04
   5 <split [580/102]> Fold05
   6 <split [577/105]> Fold06
   7 <split [602/80]>  Fold07
   8 <split [614/68]>  Fold08
   9 <split [630/52]>  Fold09
  10 <split [655/27]>  Fold10

Code
  as.integer(boston_snake$splits[[1]])
Output
    [1]   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18
   [19]  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36
   [37]  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54
   [55]  55  56  57  58  59  60  62  63  64  65  66  67  68  69  70  71  72  73
   [73]  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89  91  93
   [91]  94  95  96  97  98  99 100 101 102 103 104 106 107 108 109 110 112 113
  [109] 114 115 116 117 118 119 120 122 123 124 125 126 127 128 129 130 131 132
  [127] 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150
  [145] 151 152 153 154 155 156 157 158 160 161 162 163 164 165 166 167 168 169
  [163] 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187
  [181] 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205
  [199] 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223
  [217] 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241
  [235] 242 244 245 246 247 248 249 250 251 252 253 254 255 257 258 259 260 261
  [253] 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279
  [271] 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297
  [289] 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315
  [307] 316 317 318 319 321 322 324 325 326 327 328 329 330 331 332 333 334 335
  [325] 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353
  [343] 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371
  [361] 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 390
  [379] 391 392 393 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409
  [397] 410 412 413 414 415 416 417 418 419 420 421 422 424 425 426 427 428 430
  [415] 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448
  [433] 449 450 451 452 453 454 455 457 458 459 460 461 462 463 465 466 467 468
  [451] 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486
  [469] 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504
  [487] 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522
  [505] 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540
  [523] 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558
  [541] 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576
  [559] 577 578 579 580 581 582 583 584 585 586 587 588 590 591 592 593 594 595
  [577] 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613
  [595] 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631
  [613] 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649
  [631] 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667
  [649] 668 670 671 672 673 674 675 676 677 678 679 680 681 682

duplicated observations in assessment sets throws an error

Some observations fell exactly on block boundaries, meaning they were assigned to multiple assessment sets unexpectedly.
i Try setting a different `expand_bbox` value, an `offset`, or use a different number of folds.

bad args

Code
  spatial_block_cv(ames)
Condition
  Error in `spatial_block_cv()`:
  ! `spatial_block_cv()` currently only supports `sf` objects.
  i Try converting `data` to an `sf` object via `sf::st_as_sf()`.

Code
  spatial_block_cv(ames_sf, v = c(5, 10))
Condition
  Error in `spatial_block_cv()`:
  ! `v` must be a single positive integer.

Code
  spatial_block_cv(ames_sf, v = c(5, 10), method = "snake")
Condition
  Error in `spatial_block_cv()`:
  ! `v` must be a single positive integer.

Code
  spatial_block_cv(ames_sf, method = "snake", relevant_only = FALSE, v = 28)
Condition
  Warning:
  Not all folds contained blocks with data:
  x 28 folds were requested, but only 27 contain any data.
  x Empty folds were dropped.
  i To avoid this, set `relevant_only = TRUE`.
Output
  #  27-fold spatial block cross-validation 
  # A tibble: 27 x 2
     splits             id    
     <list>             <chr> 
   1 <split [2790/140]> Fold01
   2 <split [2726/204]> Fold02
   3 <split [2820/110]> Fold03
   4 <split [2877/53]>  Fold04
   5 <split [2851/79]>  Fold05
   6 <split [2877/53]>  Fold06
   7 <split [2886/44]>  Fold07
   8 <split [2736/194]> Fold08
   9 <split [2919/11]>  Fold09
  10 <split [2855/75]>  Fold10
  # i 17 more rows

Code
  spatial_block_cv(ames_sf, method = "snake", v = 60)
Condition
  Warning in `spatial_block_cv()`:
  Fewer than 60 blocks available for sampling
  i Setting `v` to 54
Output
  #  54-fold spatial block cross-validation 
  # A tibble: 54 x 2
     splits             id    
     <list>             <chr> 
   1 <split [2917/13]>  Fold01
   2 <split [2818/112]> Fold02
   3 <split [2926/4]>   Fold03
   4 <split [2929/1]>   Fold04
   5 <split [2896/34]>  Fold05
   6 <split [2905/25]>  Fold06
   7 <split [2900/30]>  Fold07
   8 <split [2928/2]>   Fold08
   9 <split [2929/1]>   Fold09
  10 <split [2923/7]>   Fold10
  # i 44 more rows

Code
  spatial_block_cv(sf::st_set_crs(ames_sf, sf::NA_crs_))
Condition
  Warning in `spatial_block_cv()`:
  `spatial_block_cv()` expects your data to have an appropriate coordinate reference system (CRS).
  i If possible, try setting a CRS using `sf::st_set_crs()`.
  i Otherwise, `spatial_block_cv()` will assume your data is in projected coordinates.
Output
  #  10-fold spatial block cross-validation 
  # A tibble: 10 x 2
     splits             id    
     <list>             <chr> 
   1 <split [2524/406]> Fold01
   2 <split [2656/274]> Fold02
   3 <split [2476/454]> Fold03
   4 <split [2771/159]> Fold04
   5 <split [2607/323]> Fold05
   6 <split [2762/168]> Fold06
   7 <split [2718/212]> Fold07
   8 <split [2665/265]> Fold08
   9 <split [2642/288]> Fold09
  10 <split [2549/381]> Fold10

Code
  spatial_block_cv(ames_sf, v = 60)
Condition
  Warning in `spatial_block_cv()`:
  Fewer than 60 blocks available for sampling
  i Setting `v` to 54
Output
  #  54-fold spatial block cross-validation 
  # A tibble: 54 x 2
     splits             id    
     <list>             <chr> 
   1 <split [2745/185]> Fold01
   2 <split [2803/127]> Fold02
   3 <split [2900/30]>  Fold03
   4 <split [2927/3]>   Fold04
   5 <split [2915/15]>  Fold05
   6 <split [2918/12]>  Fold06
   7 <split [2887/43]>  Fold07
   8 <split [2854/76]>  Fold08
   9 <split [2927/3]>   Fold09
  10 <split [2870/60]>  Fold10
  # i 44 more rows

Code
  spatial_block_cv(boston_canopy, n = 200)
Message
  Only 1.7% of blocks contain any data
  i Check that your block sizes make sense for your data
Output
  #  10-fold spatial block cross-validation 
  # A tibble: 10 x 2
     splits           id    
     <list>           <chr> 
   1 <split [613/69]> Fold01
   2 <split [613/69]> Fold02
   3 <split [614/68]> Fold03
   4 <split [614/68]> Fold04
   5 <split [614/68]> Fold05
   6 <split [614/68]> Fold06
   7 <split [614/68]> Fold07
   8 <split [614/68]> Fold08
   9 <split [614/68]> Fold09
  10 <split [614/68]> Fold10

Repeated cross-validation doesn't make sense when `method = 'continuous'`.
i Set `method = 'random'`.
i Or set `repeats = 1`.

Repeated cross-validation doesn't make sense when `method = 'snake'`.
i Set `method = 'random'`.
i Or set `repeats = 1`.

printing

#  10-fold spatial block cross-validation 
# A tibble: 10 x 2
   splits             id    
   <list>             <chr> 
 1 <split [2524/406]> Fold01
 2 <split [2656/274]> Fold02
 3 <split [2476/454]> Fold03
 4 <split [2771/159]> Fold04
 5 <split [2607/323]> Fold05
 6 <split [2762/168]> Fold06
 7 <split [2718/212]> Fold07
 8 <split [2665/265]> Fold08
 9 <split [2642/288]> Fold09
10 <split [2549/381]> Fold10

tidymodels/spatialsample documentation built on Oct. 13, 2024, 3:35 p.m.