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| == Particle Box Size and Speed == Various algorithms in EMAN2 will depend non-linearly on the box size of the particle. Sometimes (such as the case with FFTs), this behavior will appear bizzare. For example refinements with a box size of 45 pixels will run roughly twice as fast as those with a box size of 47, and 44 is about 20% faster than 45. |
== Particle Box Size == ''Warning:'' For single particle analysis '''the particle box-size must be 1.5-2x the size of the largest axis of your particle'''. The size should also be selected from the list below. There are several important reasons for this, including proper CTF correction, good centering, and other issues. If you are stuck with data which was boxed with an insufficient size, the --extrapad option in e2ctf.py will help mitigate the problem, but will still not produce results as good as data that was properly boxed with sufficient padding. |
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| The following plot shows how long it takes to compute one similarity matrix element for a noisy particle aligned to a noise-free reference with the rotate-translate-flip aligner, refine alignment enabled with the dot comparator, and a phase residual for a similarity metric. ie - typical options for a real refinement: | ''Reminder:'' The appropriate sampling for images for single particle reconstruction is ~2/3 Nyquist. That is, take the best resolution you hope to achieve, and divide by 3. This is close to the optimal A/pix value for your project. If your sampling is worse than this (A/pix larger), then you are not using a high enough magnification on the microscope. If your data is significantly oversampled (smaller A/pix than needed), e2ctf_auto will automatically generate downsampled versions of your data for more efficient processing. ---- ''For those who don't like to read (a detailed discussion is below), here is the list of good box sizes:'' : * updated on 6/17/2016: '''32, 36, 40, 48, 52, 56, 64, 66, 70, 72, 80, 84, 88, 100, 104, 108, 112, 120, 128, 130, 132, 140, 144, 150, 160, 162, 168, 176, 180, 182, 192, 200, 208, 216, 220, 224, 240, 256, 264, 288, 300, 308, 320, 324, 336, 338, 352, 364, 384, 400, 420, 432, 448, 450, 462, 480, 486, 500, 504, 512, 520, 528, 546, 560, 576, 588, 600, 640, 648, 650, 660, 672, 686, 700, 702, 704, 720, 726, 728, 750, 768, 770, 784, 800, 810, 840, 882, 896, 910, 924, 936, 972, 980, 1008, 1014, 1020, 1024''' for traditional single particle analysis. If you were to pick a size not on this list, moving up to the next number on the list would make your refinement FASTER, sometimes MUCH faster. For example, refinements would take almost 2x longer with a box size of 134 as compared to 136 These sizes are less well tested, but also probably good: 1080, 1125, 1152, 1200, 1215, 1250, 1280, 1296, 1350, 1440, 1458, 1500, 1536, 1600, 1620, 1728, 1800, 1875, 1920, 1944, 2000, 2025, 2048, 2160, 2187, 2250, 2304, 2400, 2430, 2500, 2560, 2592, 2700, 2880, 2916, 3000, 3072, 3125, 3200, 3240, 3375, 3456, 3600, 3645, 3750, 3840, 3888, 4000, 4050, 4320, 4374, 4500, 4608, 4800, 4860, 5000, 5120, 5184, 5400, 5625, 5760, 5832, 6000, 6075, 6144, 6250, 6400, 6480, 6750, 6912, 7200, 7290, 7500, 7680, 7776, 8000, 8100, ---- Various algorithms in EMAN2 will depend non-linearly on the box size of the particle. Sometimes (such as the case with FFTs), this behavior will appear bizzare. For example refinements with a box size of 128 will run almost 2x faster than a box size of 122. For several important reasons including accurate CTF correction and proper centering, box sizes in EMAN must be 1.5-2x larger than the longest axis of your particle. Sometimes for large viruses, this is reduced to 1.25x due to the very large box sizes involved, but the chance of artifacts at the edge of the box will be increased. The following plot is a section of the timing tests used to produce the above list (only even numbers shown). This is the time required for a typical set of operations used in 3-D refinement at each size: |
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| Clearly there are some good box sizes, and some very bad box sizes. | The complete timing table is also available: |
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| A better way to plot this is with respect to anticipated speed for an N^2 algorithm. This is the reciprocal of the same plot divided by box size squared, normalized so 512 is 1. That is, larger values indicate better relative speeds. Of course, 103 is still faster than 512, but if you look in a local neighborhood for a peak, that will correspond to a good box size to use. {{attachment:rel_speed.jpg}} Of course, that plot is very difficult to read actual values off of. The original timing data can be downloaded as [[attachment:profile.txt]] From this plot, we can compute when using a larger box-size is better. ie - if you have a box size of 482, your refinement would actually run faster with a box size of 512, even though it's larger. So, when picking a box size, you can optimize your speed by rounding up to a value from this list : 32, 33, 36, 40, 42, 44, 48, 50, 52, 54, 56, 60, 64, 66, 70, 72, 81, 84, 96, 98, 100, 104, 105, 112, 120, 128, 130, 132, 140, 150, 154, 168, 180, 182, 192, 196, 208, 210, 220, 224, 240, 250, 256, 260, 288, 300, 330, 352, 360, 384, 416, 440, 448, 450, 480, 512 Also note that if you are using shrink= it's a good idea to also confirm that your box size divided by the shrink value is in this list. |
{{attachment:time_vs_size.txt}} |
Particle Box Size
Warning: For single particle analysis the particle box-size must be 1.5-2x the size of the largest axis of your particle. The size should also be selected from the list below. There are several important reasons for this, including proper CTF correction, good centering, and other issues. If you are stuck with data which was boxed with an insufficient size, the --extrapad option in e2ctf.py will help mitigate the problem, but will still not produce results as good as data that was properly boxed with sufficient padding.
Reminder: The appropriate sampling for images for single particle reconstruction is ~2/3 Nyquist. That is, take the best resolution you hope to achieve, and divide by 3. This is close to the optimal A/pix value for your project. If your sampling is worse than this (A/pix larger), then you are not using a high enough magnification on the microscope. If your data is significantly oversampled (smaller A/pix than needed), e2ctf_auto will automatically generate downsampled versions of your data for more efficient processing.
For those who don't like to read (a detailed discussion is below), here is the list of good box sizes: :
- updated on 6/17/2016:
32, 36, 40, 48, 52, 56, 64, 66, 70, 72, 80, 84, 88, 100, 104, 108, 112, 120, 128, 130, 132, 140, 144, 150, 160, 162, 168, 176, 180, 182, 192, 200, 208, 216, 220, 224, 240, 256, 264, 288, 300, 308, 320, 324, 336, 338, 352, 364, 384, 400, 420, 432, 448, 450, 462, 480, 486, 500, 504, 512, 520, 528, 546, 560, 576, 588, 600, 640, 648, 650, 660, 672, 686, 700, 702, 704, 720, 726, 728, 750, 768, 770, 784, 800, 810, 840, 882, 896, 910, 924, 936, 972, 980, 1008, 1014, 1020, 1024
for traditional single particle analysis. If you were to pick a size not on this list, moving up to the next number on the list would make your refinement FASTER, sometimes MUCH faster. For example, refinements would take almost 2x longer with a box size of 134 as compared to 136
These sizes are less well tested, but also probably good: 1080, 1125, 1152, 1200, 1215, 1250, 1280, 1296, 1350, 1440, 1458, 1500, 1536, 1600, 1620, 1728, 1800, 1875, 1920, 1944, 2000, 2025, 2048, 2160, 2187, 2250, 2304, 2400, 2430, 2500, 2560, 2592, 2700, 2880, 2916, 3000, 3072, 3125, 3200, 3240, 3375, 3456, 3600, 3645, 3750, 3840, 3888, 4000, 4050, 4320, 4374, 4500, 4608, 4800, 4860, 5000, 5120, 5184, 5400, 5625, 5760, 5832, 6000, 6075, 6144, 6250, 6400, 6480, 6750, 6912, 7200, 7290, 7500, 7680, 7776, 8000, 8100,
Various algorithms in EMAN2 will depend non-linearly on the box size of the particle. Sometimes (such as the case with FFTs), this behavior will appear bizzare. For example refinements with a box size of 128 will run almost 2x faster than a box size of 122.
For several important reasons including accurate CTF correction and proper centering, box sizes in EMAN must be 1.5-2x larger than the longest axis of your particle. Sometimes for large viruses, this is reduced to 1.25x due to the very large box sizes involved, but the chance of artifacts at the edge of the box will be increased.
The following plot is a section of the timing tests used to produce the above list (only even numbers shown). This is the time required for a typical set of operations used in 3-D refinement at each size:
The complete timing table is also available:
1 32 0.988
2 33 1.069
3 34 1.106
4 35 1.094
5 36 1.165
6 37 1.424
7 38 1.265
8 39 1.179
9 40 1.276
10 41 1.600
11 42 1.343
12 43 1.535
13 44 1.332
14 45 1.320
15 46 1.494
16 47 1.801
17 48 1.377
18 49 1.419
19 50 1.615
20 51 1.705
21 52 1.554
22 53 2.138
23 54 1.690
24 55 1.638
25 56 1.718
26 57 1.879
27 58 2.003
28 59 2.365
29 60 2.006
30 61 2.862
31 62 2.210
32 63 1.896
33 64 1.786
34 65 2.006
35 66 2.079
36 67 3.201
37 68 2.474
38 69 2.545
39 70 2.287
40 71 3.430
41 72 2.432
42 73 3.909
43 74 4.244
44 75 2.471
45 76 3.115
46 77 2.531
47 78 2.632
48 79 4.350
49 80 2.551
50 81 2.667
51 82 4.882
52 83 4.789
53 84 2.807
54 85 3.225
55 86 3.853
56 87 3.695
57 88 3.092
58 89 5.365
59 90 3.250
60 91 3.182
61 92 3.990
62 93 4.177
63 94 5.320
64 95 3.984
65 96 3.698
66 97 6.917
67 98 3.580
68 99 3.776
69 100 3.479
70 101 7.398
71 102 4.518
72 103 7.277
73 104 4.011
74 105 4.163
75 106 6.586
76 107 7.681
77 108 4.165
78 109 8.548
79 110 4.390
80 111 7.136
81 112 4.195
82 113 9.037
83 114 5.347
84 115 5.656
85 116 6.363
86 117 4.773
87 118 7.127
88 119 5.843
89 120 4.996
90 121 5.381
91 122 9.775
92 123 8.919
93 124 6.940
94 125 5.361
95 126 5.498
96 127 10.793
97 128 5.262
98 129 8.172
99 130 5.772
100 131 13.207
101 132 6.145
102 133 7.136
103 134 11.406
104 135 6.177
105 136 7.235
106 137 13.460
107 138 7.750
108 139 13.445
109 140 6.413
110 141 10.361
111 142 10.080
112 143 7.249
113 144 6.479
114 145 9.548
115 146 14.477
116 147 7.912
117 148 15.151
118 149 15.361
119 150 7.076
120 151 17.844
121 152 8.839
122 153 9.007
123 154 7.642
124 155 10.283
125 156 7.919
126 157 17.080
127 158 12.018
128 159 13.628
129 160 7.590
130 161 10.389
131 162 8.826
132 163 21.548
133 164 17.547
134 165 9.322
135 166 16.076
136 167 21.025
137 168 9.276
138 169 9.698
139 170 11.327
140 171 11.459
141 172 13.966
142 173 30.264
143 174 12.970
144 175 9.918
145 176 9.464
146 177 15.912
147 178 17.130
148 179 29.904
149 180 9.749
150 181 27.213
151 182 10.466
152 183 19.676
153 184 13.238
154 185 19.103
155 186 14.855
156 187 13.501
157 188 19.260
158 189 12.914
159 190 14.059
160 191 29.577
161 192 10.762
162 193 30.683
163 194 22.662
164 195 12.734
165 196 11.653
166 197 28.955
167 198 12.531
168 199 30.151
169 200 11.476
170 201 24.117
171 202 25.374
172 203 17.047
173 204 14.878
174 205 23.362
175 206 23.263
176 207 16.795
177 208 13.418
178 209 17.106
179 210 14.108
180 211 33.806
181 212 24.339
182 213 25.485
183 214 24.089
184 215 21.590
185 216 14.002
186 217 19.506
187 218 28.885
188 219 30.216
189 220 14.976
190 221 20.136
191 222 31.080
192 223 46.027
193 224 15.144
194 225 16.064
195 226 28.599
196 227 46.237
197 228 18.853
198 229 41.577
199 230 20.160
200 231 17.638
201 232 21.303
202 233 45.457
203 234 17.581
204 235 27.343
205 236 25.852
206 237 32.117
207 238 20.241
208 239 46.253
209 240 16.172
210 241 46.068
211 242 18.771
212 243 19.281
213 244 37.050
214 245 19.471
215 246 37.249
216 247 23.412
217 248 24.636
218 249 37.858
219 250 19.071
220 251 51.429
221 252 18.430
222 253 25.778
223 254 28.485
224 255 24.604
225 256 18.041
226 257 50.685
227 258 29.540
228 259 36.156
229 260 20.860
230 261 28.165
231 262 41.947
232 263 61.513
233 264 20.543
234 265 37.414
235 266 25.715
236 267 44.078
237 268 42.174
238 269 63.978
239 270 23.082
240 271 60.436
241 272 27.103
242 273 24.942
243 274 36.982
244 275 25.017
245 276 28.259
246 277 61.920
247 278 38.480
248 279 32.352
249 280 23.059
250 281 57.747
251 282 40.768
252 283 68.900
253 284 38.690
254 285 31.115
255 286 25.449
256 287 44.558
257 288 23.006
258 289 36.072
259 290 35.098
260 291 57.207
261 292 52.831
262 293 77.769
263 294 26.132
264 295 43.840
265 296 57.136
266 297 31.309
267 298 39.686
268 299 36.080
269 300 24.802
270 301 42.340
271 302 56.261
272 303 62.274
273 304 32.674
274 305 57.124
275 306 35.903
276 307 84.012
277 308 27.843
278 309 67.110
279 310 38.245
280 311 86.697
281 312 30.523
282 313 84.909
283 314 42.817
284 315 32.813
285 316 50.789
286 317 79.510
287 318 67.386
288 319 43.672
289 320 28.212
290 321 66.876
291 322 39.774
292 323 46.617
293 324 31.656
294 325 36.138
295 326 67.898
296 327 73.863
297 328 66.484
298 329 55.413
299 330 34.495
300 331 87.178
301 332 60.054
302 333 66.211
303 334 57.758
304 335 68.357
305 336 33.411
306 337 91.447
307 338 36.933
308 339 77.641
309 340 42.280
310 341 50.504
311 342 42.828
312 343 38.739
313 344 54.348
314 345 47.889
315 346 60.307
316 347 105.448
317 348 48.453
318 349 101.230
319 350 39.074
320 351 41.096
321 352 37.043
322 353 92.030
323 354 58.770
324 355 70.667
325 356 67.151
326 357 48.228
327 358 62.838
328 359 111.903
329 360 40.466
330 361 57.183
331 362 78.888
332 363 45.242
333 364 39.407
334 365 83.464
335 366 83.931
336 367 123.511
337 368 50.523
338 369 82.153
339 370 85.348
340 371 72.424
341 372 55.863
342 373 117.396
343 374 51.904
344 375 46.613
345 376 72.811
346 377 60.640
347 378 44.486
348 379 105.228
349 380 53.382
350 381 92.783
351 382 63.294
352 383 123.405
353 384 40.457
354 385 49.395
355 386 93.434
356 387 69.715
357 388 91.087
358 389 127.701
359 390 50.157
360 391 75.241
361 392 44.931
362 393 118.510
363 394 69.480
364 395 88.236
365 396 46.810
366 397 118.600
367 398 68.979
368 399 62.579
369 400 44.363
370 401 125.374
371 402 96.598
372 403 69.694
373 404 99.999
374 405 54.688
375 406 67.573
376 407 92.638
377 408 60.926
378 409 132.781
379 410 104.240
380 411 118.139
381 412 102.776
382 413 86.827
383 414 65.660
384 415 109.193
385 416 54.635
386 417 121.890
387 418 65.289
388 419 151.173
389 420 54.048
390 421 134.402
391 422 86.580
392 423 91.213
393 424 101.401
394 425 73.722
395 426 89.963
396 427 107.451
397 428 107.638
398 429 71.417
399 430 84.187
400 431 157.732
401 432 56.324
402 433 154.611
403 434 79.417
404 435 84.714
405 436 118.875
406 437 89.299
407 438 118.344
408 439 174.658
409 440 60.033
410 441 65.057
411 442 72.630
412 443 176.987
413 444 123.458
414 445 123.737
415 446 122.932
416 447 137.403
417 448 58.830
418 449 147.018
419 450 63.747
420 451 123.394
421 452 116.389
422 453 155.775
423 454 107.286
424 455 68.251
425 456 77.851
426 457 165.939
427 458 104.730
428 459 82.244
429 460 81.521
430 461 171.054
431 462 66.177
432 463 158.183
433 464 90.208
434 465 93.799
435 466 108.231
436 467 188.789
437 468 70.604
438 469 131.209
439 470 116.811
440 471 155.312
441 472 105.408
442 473 107.924
443 474 108.081
444 475 93.973
445 476 83.038
446 477 122.316
447 478 111.616
448 479 191.065
449 480 69.295
450 481 130.147
451 482 140.476
452 483 94.583
453 484 77.935
454 485 159.745
455 486 73.585
456 487 199.120
457 488 147.830
458 489 188.132
459 490 74.887
460 491 176.537
461 492 149.911
462 493 114.195
463 494 102.512
464 495 82.737
465 496 99.834
466 497 141.685
467 498 140.787
468 499 226.361
469 500 74.323
470 501 193.394
471 502 155.905
472 503 201.679
473 504 76.870
474 505 176.594
475 506 100.391
476 507 90.270
477 508 119.061
478 509 208.389
479 510 108.512
480 511 163.683
481 512 78.000
482 513 105.036
483 514 157.365
484 515 171.946
485 516 121.556
486 517 141.721
487 518 172.717
488 519 251.635
489 520 85.008
490 521 203.125
491 522 110.759
492 523 221.999
493 524 168.590
494 525 100.535
495 526 129.827
496 527 133.870
497 528 86.281
498 529 133.910
499 530 155.531
500 531 144.458
501 532 106.503
502 533 164.880
503 534 154.343
504 535 186.231
505 536 169.630
506 537 263.638
507 538 134.501
508 539 97.087
509 540 100.199
510 541 239.638
511 542 182.515
512 543 240.795
513 544 106.521
514 545 206.043
515 546 91.294
516 547 234.968
517 548 153.393
518 549 177.863
519 550 94.760
520 551 144.243
521 552 115.947
522 553 171.186
523 554 153.582
524 555 172.391
525 556 160.164
526 557 278.700
527 558 124.360
528 559 149.214
529 560 94.480
530 561 122.862
531 562 153.803
532 563 283.362
533 564 162.851
534 565 210.885
535 566 153.972
536 567 105.127
537 568 157.666
538 569 273.579
539 570 120.927
540 571 256.017
541 572 104.716
542 573 252.664
543 574 206.647
544 575 132.231
545 576 97.024
546 577 267.934
547 578 143.500
548 579 277.816
549 580 139.508
550 581 211.386
551 582 207.168
552 583 190.759
553 584 210.818
554 585 116.378
555 586 162.733
556 587 298.773
557 588 105.581
558 589 167.884
559 590 168.385
560 591 259.621
561 592 225.937
562 593 291.268
563 594 116.274
564 595 139.465
565 596 162.815
566 597 267.667
567 598 143.039
568 599 318.942
569 600 107.888
570 601 295.118
571 602 158.595
572 603 206.049
573 604 217.217
574 605 131.870
575 606 224.605
576 607 348.720
577 608 136.711
578 609 154.157
579 610 234.696
580 611 195.034
581 612 135.860
582 613 295.572
583 614 220.933
584 615 213.438
585 616 117.220
586 617 291.460
587 618 213.886
588 619 349.504
589 620 162.969
590 621 159.786
591 622 228.185
592 623 248.117
593 624 120.481
594 625 140.241
595 626 237.735
596 627 160.212
597 628 179.104
598 629 256.517
599 630 130.181
600 631 281.144
601 632 195.939
602 633 308.937
603 634 199.870
604 635 256.142
605 636 225.719
606 637 138.252
607 638 172.975
608 639 236.053
609 640 116.936
610 641 325.857
611 642 226.565
612 643 360.283
613 644 165.745
614 645 194.336
615 646 186.138
616 647 364.676
617 648 127.066
618 649 223.882
619 650 135.507
620 651 181.139
621 652 280.019
622 653 404.535
623 654 265.261
624 655 305.316
625 656 269.406
626 657 270.952
627 658 224.733
628 659 398.392
629 660 136.995
630 661 353.602
631 662 255.246
632 663 176.276
633 664 245.797
634 665 167.083
635 666 285.963
636 667 222.216
637 668 233.071
638 669 411.615
639 670 263.849
640 671 280.817
641 672 137.914
642 673 352.575
643 674 263.570
644 675 154.794
645 676 150.296
646 677 407.891
647 678 268.740
648 679 324.868
649 680 174.219
650 681 425.389
651 682 201.343
652 683 414.254
653 684 176.306
654 685 326.359
655 686 139.765
656 687 373.343
657 688 215.741
658 689 262.834
659 690 190.270
660 691 390.865
661 692 242.687
662 693 168.351
663 694 233.300
664 695 331.825
665 696 196.289
666 697 308.773
667 698 239.844
668 699 413.173
669 700 146.902
670 701 369.469
671 702 153.204
672 703 320.200
673 704 156.467
674 705 259.661
675 706 266.475
676 707 342.449
677 708 245.385
678 709 433.539
679 710 255.794
680 711 285.337
681 712 273.271
682 713 253.732
683 714 178.364
684 715 179.974
685 716 258.582
686 717 417.582
687 718 252.111
688 719 444.624
689 720 158.981
690 721 342.927
691 722 230.335
692 723 423.340
693 724 322.972
694 725 219.587
695 726 161.653
696 727 500.954
697 728 163.257
698 729 178.240
699 730 330.089
700 731 274.648
701 732 338.492
702 733 472.237
703 734 279.485
704 735 181.017
705 736 206.861
706 737 324.813
707 738 341.441
708 739 459.635
709 740 351.049
710 741 217.086
711 742 304.326
712 743 482.695
713 744 230.257
714 745 373.296
715 746 286.336
716 747 343.257
717 748 224.399
718 749 366.234
719 750 170.058
720 751 455.766
721 752 290.530
722 753 450.205
723 754 228.560
724 755 429.061
725 756 175.303
726 757 415.059
727 758 267.228
728 759 248.500
729 760 227.134
730 761 453.005
731 762 270.256
732 763 412.221
733 764 265.518
734 765 224.447
735 766 278.946
736 767 327.301
737 768 173.421
738 769 485.746
739 770 198.074
740 771 481.700
741 772 400.485
742 773 515.885
743 774 285.750
744 775 265.985
745 776 389.467
746 777 360.299
747 778 294.484
748 779 405.545
749 780 205.262
750 781 374.422
751 782 294.383
752 783 272.748
753 784 198.409
754 785 447.660
755 786 416.965
756 787 540.348
757 788 297.964
758 789 576.315
759 790 329.444
760 791 426.524
761 792 214.535
762 793 404.383
763 794 318.287
764 795 360.978
765 796 304.767
766 797 546.087
767 798 247.913
768 799 402.409
769 800 213.451
770 801 432.729
771 802 418.684
772 803 453.097
773 804 410.355
774 805 280.332
775 806 297.535
776 807 603.353
777 808 432.620
778 809 602.677
779 810 228.858
780 811 566.766
781 812 285.659
782 813 562.294
783 814 469.205
784 815 539.961
785 816 276.719
786 817 375.781
787 818 337.721
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789 820 445.796
790 821 597.919
791 822 379.863
792 823 599.584
793 824 388.805
794 825 259.694
795 826 356.439
796 827 612.754
797 828 285.057
798 829 559.433
799 830 413.020
800 831 593.672
801 832 249.909
802 833 282.154
803 834 391.591
804 835 548.075
805 836 300.995
806 837 327.528
807 838 357.640
808 839 630.147
809 840 240.085
810 841 385.622
811 842 361.051
812 843 556.864
813 844 385.684
814 845 280.992
815 846 397.956
816 847 273.946
817 848 422.667
818 849 660.911
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820 851 505.192
821 852 382.088
822 853 649.869
823 854 489.156
824 855 308.867
825 856 425.056
826 857 668.227
827 858 268.006
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830 861 452.340
831 862 368.684
832 863 656.103
833 864 261.988
834 865 729.809
835 866 489.096
836 867 351.880
837 868 334.404
838 869 474.241
839 870 338.563
840 871 459.033
841 872 497.209
842 873 534.065
843 874 372.299
844 875 279.762
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846 877 710.078
847 878 413.449
848 879 696.140
849 880 272.079
850 881 609.093
851 882 258.467
852 883 596.331
853 884 322.056
854 885 437.682
855 886 417.652
856 887 731.995
857 888 521.343
858 889 530.866
859 890 465.394
860 891 299.056
861 892 527.770
862 893 504.228
863 894 409.203
864 895 766.884
865 896 285.538
866 897 393.334
867 898 447.089
868 899 470.546
869 900 301.585
870 901 540.807
871 902 578.301
872 903 422.965
873 904 522.254
874 905 713.056
875 906 532.494
876 907 804.016
877 908 470.847
878 909 615.902
879 910 296.275
880 911 738.584
881 912 349.982
882 913 567.343
883 914 427.959
884 915 558.470
885 916 486.113
886 917 653.222
887 918 354.391
888 919 753.502
889 920 384.491
890 921 783.713
891 922 444.425
892 923 555.907
893 924 315.381
894 925 534.025
895 926 457.225
896 927 612.445
897 928 415.432
898 929 810.883
899 930 412.462
900 931 374.656
901 932 496.908
902 933 857.887
903 934 469.074
904 935 401.654
905 936 321.207
906 937 750.433
907 938 555.843
908 939 760.428
909 940 511.905
910 941 810.391
911 942 453.356
912 943 632.770
913 944 475.663
914 945 355.380
915 946 443.771
916 947 802.638
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918 949 636.489
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920 951 786.818
921 952 400.448
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923 954 562.524
924 955 770.668
925 956 520.002
926 957 448.112
927 958 477.560
928 959 696.611
929 960 342.631
930 961 538.857
931 962 667.437
932 963 669.039
933 964 646.306
934 965 839.498
935 966 421.424
936 967 826.907
937 968 379.094
938 969 490.814
939 970 646.570
940 971 925.122
941 972 338.900
942 973 713.960
943 974 648.768
944 975 395.063
945 976 678.834
946 977 892.736
947 978 686.564
948 979 710.641
949 980 344.891
950 981 725.068
951 982 535.355
952 983 905.818
953 984 669.426
954 985 770.775
955 986 516.285
956 987 576.764
957 988 438.111
958 989 601.620
959 990 378.879
960 991 803.100
961 992 502.742
962 993 849.541
963 994 570.375
964 995 815.114
965 996 623.462
966 997 945.200
967 998 563.641
968 999 642.479
969 1000 370.964
970 1001 432.790
971 1002 600.533
972 1003 661.045
973 1004 683.520
974 1005 660.095
975 1006 505.568
976 1007 697.578
977 1008 363.957
978 1009 866.210
979 1010 711.547
980 1011 886.800
981 1012 483.252
982 1013 975.738
983 1014 397.548
984 1015 497.066
985 1016 543.594
986 1017 750.302
987 1018 521.405
988 1019 910.082
989 1020 466.539
990 1021 880.295
991 1022 727.429
992 1023 572.192