5형질 multple trait animal model - same model but different leve.
산유량 1산에서 5산까지를 다형질로 분석하는 프로그램
2개의 고정효과 : 1 - 분만 월령 : 같은 번호일지라도 산차에 따라 아무 상관없는 번호 2 - 동기우 그룹 : 산차에 상관없이 같은 번호이면 같은 동기우 그룹임
분석자료
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7 170 4 174 1 178 0 0 0 0 340 7521 6784 8417 0 0
11 171 9 175 0 0 0 0 0 0 347 6793 8005 0 0 0
15 173 0 0 0 0 0 0 0 0 348 6223 0 0 0 0
10 171 14 178 0 0 0 0 0 0 334 8823 9359 0 0 0
15 173 0 0 0 0 0 0 0 0 349 9036 0 0 0 0
9 172 8 176 0 0 0 0 0 0 323 8236 10997 0 0 0
11 172 14 178 0 0 0 0 0 0 326 9336 10567 0 0 0
7 171 0 0 0 0 0 0 0 0 325 8208 0 0 0 0
7 171 5 175 3 179 0 0 0 0 327 8004 9977 10568 0 0
8 172 10 177 0 0 0 0 0 0 317 8236 10122 0 0 0
11 173 14 178 0 0 0 0 0 0 321 9139 11362 0 0 0
11 173 10 177 0 0 0 0 0 0 318 6235 8198 0 0 0
15 101 0 0 0 0 0 0 0 0 304 7886 0 0 0 0
8 98 9 103 0 0 0 0 0 0 302 11271 10710 0 0 0
8 98 15 105 0 0 0 0 0 0 300 10561 10378 0 0 0
11 99 0 0 0 0 0 0 0 0 299 7546 0 0 0 0
9 98 14 104 0 0 0 0 0 0 298 11623 12036 0 0 0
15 101 15 105 0 0 0 0 0 0 295 10786 10398 0 0 0
11 99 10 103 0 0 0 0 0 0 294 7664 7333 0 0 0
9 98 13 104 0 0 0 0 0 0 293 10509 13111 0 0 0
11 99 0 0 0 0 0 0 0 0 291 9597 0 0 0 0
15 104 0 0 0 0 0 0 0 0 289 8026 0 0 0 0
15 102 0 0 0 0 0 0 0 0 284 7489 0 0 0 0
15 101 12 105 0 0 0 0 0 0 283 8774 10537 0 0 0
9 99 10 104 0 0 0 0 0 0 282 9906 11157 0 0 0
10 99 10 104 0 0 0 0 0 0 280 9758 13542 0 0 0
9 99 6 103 0 0 0 0 0 0 277 8766 8426 0 0 0
10 99 8 103 0 0 0 0 0 0 276 6649 8019 0 0 0
8 99 10 104 0 0 0 0 0 0 275 7164 11444 0 0 0
9 99 6 103 0 0 0 0 0 0 274 8217 7624 0 0 0
11 100 0 0 0 0 0 0 0 0 272 13235 0 0 0 0
8 99 5 103 0 0 0 0 0 0 271 10962 9720 0 0 0
8 99 12 105 0 0 0 0 0 0 270 11166 10274 0 0 0
8 100 5 103 0 0 0 0 0 0 265 9799 9467 0 0 0
15 105 0 0 0 0 0 0 0 0 263 8724 0 0 0 0
15 102 0 0 0 0 0 0 0 0 261 11371 0 0 0 0
10 101 0 0 0 0 0 0 0 0 257 12292 0 0 0 0
8 100 0 0 0 0 0 0 0 0 255 10404 0 0 0 0
10 101 0 0 0 0 0 0 0 0 254 10962 0 0 0 0
8 101 0 0 0 0 0 0 0 0 250 10891 0 0 0 0
8 101 6 104 0 0 0 0 0 0 252 9139 10575 0 0 0
9 101 0 0 0 0 0 0 0 0 253 9063 0 0 0 0
13 102 0 0 0 0 0 0 0 0 249 10725 0 0 0 0
10 102 0 0 0 0 0 0 0 0 245 9591 0 0 0 0
8 101 0 0 0 0 0 0 0 0 248 8825 0 0 0 0
7 101 6 105 0 0 0 0 0 0 242 9655 9892 0 0 0
7 101 7 105 0 0 0 0 0 0 243 9665 10371 0 0 0
11 102 0 0 0 0 0 0 0 0 241 7882 0 0 0 0
12 103 0 0 0 0 0 0 0 0 235 10480 0 0 0 0
15 105 0 0 0 0 0 0 0 0 237 9029 0 0 0 0
15 105 0 0 0 0 0 0 0 0 233 8779 0 0 0 0
11 103 0 0 0 0 0 0 0 0 231 8926 0 0 0 0
14 104 0 0 0 0 0 0 0 0 229 6888 0 0 0 0
10 103 0 0 0 0 0 0 0 0 226 8975 0 0 0 0
11 103 0 0 0 0 0 0 0 0 224 10109 0 0 0 0
7 102 0 0 0 0 0 0 0 0 223 8742 0 0 0 0
10 103 0 0 0 0 0 0 0 0 222 9132 0 0 0 0
8 173 0 0 0 0 0 0 0 0 301 7720 0 0 0 0
9 174 7 178 0 0 0 0 0 0 288 8201 10372 0 0 0
8 173 6 177 0 0 0 0 0 0 296 8488 10792 0 0 0
7 173 5 177 0 0 0 0 0 0 287 7094 8514 0 0 0
9 174 11 179 0 0 0 0 0 0 279 8350 11495 0 0 0
6 173 0 0 0 0 0 0 0 0 290 5792 0 0 0 0
9 175 0 0 0 0 0 0 0 0 268 8539 0 0 0 0
9 174 5 177 0 0 0 0 0 0 278 7258 9715 0 0 0
9 175 0 0 0 0 0 0 0 0 267 7930 0 0 0 0
11 175 0 0 0 0 0 0 0 0 269 7580 0 0 0 0
11 174 8 177 0 0 0 0 0 0 297 8146 9192 0 0 0
9 174 0 0 0 0 0 0 0 0 286 8418 0 0 0 0
7 174 3 177 0 0 0 0 0 0 266 7319 7921 0 0 0
7 174 0 0 0 0 0 0 0 0 273 7810 0 0 0 0
12 174 11 179 0 0 0 0 0 0 292 8314 10436 0 0 0
9 174 5 177 0 0 0 0 0 0 281 6611 8135 0 0 0
8 174 7 178 0 0 0 0 0 0 285 7231 7585 0 0 0
10 174 14 179 0 0 0 0 0 0 303 8887 10236 0 0 0
11 173 9 177 0 0 0 0 0 0 310 8724 10037 0 0 0
10 169 9 174 7 178 0 0 0 0 366 7780 9168 8206 0 0
11 104 0 0 0 0 0 0 0 0 213 9160 0 0 0 0
11 105 0 0 0 0 0 0 0 0 211 9064 0 0 0 0
12 105 0 0 0 0 0 0 0 0 210 10260 0 0 0 0
9 104 0 0 0 0 0 0 0 0 209 8824 0 0 0 0
10 105 0 0 0 0 0 0 0 0 208 8270 0 0 0 0
9 104 0 0 0 0 0 0 0 0 207 9502 0 0 0 0
8 104 0 0 0 0 0 0 0 0 205 7673 0 0 0 0
8 104 0 0 0 0 0 0 0 0 204 9137 0 0 0 0
12 106 0 0 0 0 0 0 0 0 200 9632 0 0 0 0
9 105 0 0 0 0 0 0 0 0 201 8804 0 0 0 0
9 105 0 0 0 0 0 0 0 0 199 7848 0 0 0 0
12 176 9 180 0 0 0 0 0 0 260 6685 9398 0 0 0
11 176 7 179 0 0 0 0 0 0 259 8478 9691 0 0 0
9 175 11 181 0 0 0 0 0 0 256 8860 9417 0 0 0
11 176 10 180 0 0 0 0 0 0 258 6483 7938 0 0 0
7 174 0 0 0 0 0 0 0 0 264 8823 0 0 0 0
8 176 0 0 0 0 0 0 0 0 247 7407 0 0 0 0
9 177 0 0 0 0 0 0 0 0 238 6666 0 0 0 0
7 176 3 179 0 0 0 0 0 0 246 7319 8041 0 0 0
9 176 9 181 0 0 0 0 0 0 251 5613 8288 0 0 0
7 176 0 0 0 0 0 0 0 0 239 7069 0 0 0 0
12 178 0 0 0 0 0 0 0 0 240 7183 0 0 0 0
9 176 0 0 0 0 0 0 0 0 244 7162 0 0 0 0
8 177 0 0 0 0 0 0 0 0 227 9474 0 0 0 0
10 178 0 0 0 0 0 0 0 0 232 6238 0 0 0 0
12 178 0 0 0 0 0 0 0 0 230 7828 0 0 0 0
8 177 0 0 0 0 0 0 0 0 221 8019 0 0 0 0
8 177 5 180 0 0 0 0 0 0 236 6642 7522 0 0 0
11 179 0 0 0 0 0 0 0 0 220 5842 0 0 0 0
11 178 0 0 0 0 0 0 0 0 228 6256 0 0 0 0
9 178 0 0 0 0 0 0 0 0 225 6066 0 0 0 0
11 179 0 0 0 0 0 0 0 0 218 5697 0 0 0 0
9 178 0 0 0 0 0 0 0 0 219 5985 0 0 0 0
9 179 0 0 0 0 0 0 0 0 217 6309 0 0 0 0
8 100 0 0 0 0 0 0 0 0 262 11092 0 0 0 0
15 171 12 174 11 179 0 0 0 0 370 7091 8813 9057 0 0
10 179 0 0 0 0 0 0 0 0 216 7522 0 0 0 0
8 178 0 0 0 0 0 0 0 0 215 6768 0 0 0 0
13 180 0 0 0 0 0 0 0 0 214 7223 0 0 0 0
10 179 0 0 0 0 0 0 0 0 212 6584 0 0 0 0
15 179 0 0 0 0 0 0 0 0 206 6081 0 0 0 0
15 179 0 0 0 0 0 0 0 0 202 7717 0 0 0 0
10 180 0 0 0 0 0 0 0 0 203 5946 0 0 0 0
11 181 0 0 0 0 0 0 0 0 198 8087 0 0 0 0
9 180 0 0 0 0 0 0 0 0 194 5877 0 0 0 0
10 181 0 0 0 0 0 0 0 0 195 6461 0 0 0 0
8 181 0 0 0 0 0 0 0 0 192 6204 0 0 0 0
10 180 0 0 0 0 0 0 0 0 197 6293 0 0 0 0
8 181 0 0 0 0 0 0 0 0 191 5689 0 0 0 0
8 180 0 0 0 0 0 0 0 0 193 6154 0 0 0 0
9 180 0 0 0 0 0 0 0 0 196 6137 0 0 0 0
14 179 0 0 0 0 0 0 0 0 234 6128 0 0 0 0
1st col : 1st trait 분만월령 고정효과2nd col : 1st trait 동기우 그룹
~~~~
9th col : 5th trait 분만월령 고정효과10th col : 5th trait 동기우 그룹11th col : cow number12th ~ 16th : 1st ~ 5th lactation milk yield
위 자료를 dairy_5tr.dat로 저장
혈통자료
191 587 301
192 587 318
193 594 326
194 594 401
195 587 330
196 587 323
197 690 317
198 690 345
199 571 311
200 571 406
201 618 496
202 594 455
203 690 315
204 618 534
205 571 402
206 690 347
207 571 408
208 618 548
209 666 427
210 618 429
211 618 447
212 594 420
213 680 391
214 594 583
215 690 344
216 594 376
217 594 476
218 658 535
219 594 544
220 658 465
221 690 409
222 839 591
223 680 424
224 839 380
225 690 716
226 839 421
227 658 691
228 690 363
229 666 526
230 658 454
231 666 492
232 658 598
233 666 505
234 690 426
235 839 460
236 690 365
237 666 581
238 711 419
239 690 453
240 690 371
241 666 396
242 666 393
243 666 1036
244 690 401
245 839 392
246 690 385
247 740 445
248 666 390
249 706 556
250 666 404
251 740 446
252 666 399
253 666 509
254 639 616
255 671 428
256 658 449
257 671 566
258 658 483
259 658 520
260 740 431
261 744 429
262 744 402
263 744 578
264 740 398
265 706 502
266 740 415
267 740 420
268 740 557
269 658 489
270 744 655
271 744 532
272 706 757
273 769 561
274 744 753
275 744 533
276 744 518
277 671 883
278 658 538
279 658 691
280 744 546
281 740 464
282 706 421
283 744 437
284 744 477
285 740 486
286 769 433
287 658 638
288 769 465
289 744 511
290 740 426
291 744 699
292 658 603
293 744 647
294 671 674
295 744 646
296 740 596
297 740 409
298 671 665
299 744 444
300 744 447
301 658 716
302 793 496
303 658 689
304 744 443
305 793 442
306 793 439
307 671 785
308 793 568
309 793 461
310 658 660
311 774 668
312 793 560
313 793 709
314 834 504
315 769 435
316 834 777
317 769 436
318 740 519
319 831 441
320 834 505
321 740 445
322 834 573
323 740 454
324 774 526
325 789 717
326 740 446
327 740 598
328 793 494
329 831 586
330 769 528
331 793 682
332 831 749
333 742 579
334 769 449
335 793 548
336 0 0
337 1480 0
338 831 715
339 769 457
340 769 452
341 0 0
342 0 0
343 831 636
344 742 520
345 742 557
346 789 606
347 789 704
348 742 536
349 789 489
350 834 883
351 742 621
352 725 471
353 953 518
354 953 518
355 834 533
356 742 487
357 953 631
358 742 524
359 742 673
360 953 633
361 834 578
362 789 525
363 789 663
364 953 527
365 789 602
366 789 603
367 789 700
368 786 559
369 953 498
370 786 499
371 789 608
372 786 856
373 953 970
374 953 884
375 953 721
376 742 558
377 953 626
378 742 567
379 953 521
380 953 746
381 786 791
382 742 901
383 786 575
384 742 902
385 742 562
386 953 647
387 953 514
388 953 938
389 834 685
390 953 505
391 953 591
392 953 826
393 834 565
394 834 825
395 953 593
396 834 770
397 953 540
398 786 643
399 953 573
400 786 598
401 892 515
402 834 655
403 786 667
404 953 695
405 892 750
406 953 1056
407 953 1122
408 953 715
409 789 743
410 953 564
411 953 529
412 834 549
413 953 874
414 789 705
415 786 606
416 834 533
417 816 876
418 789 716
419 786 603
420 786 714
421 838 785
422 786 539
423 816 676
424 816 847
425 838 697
426 789 755
427 838 694
428 834 625
429 834 637
430 786 537
431 786 621
432 786 672
433 789 656
434 789 634
435 943 554
436 943 562
437 831 563
438 892 630
439 831 619
440 831 565
441 928 674
442 834 733
443 831 958
444 831 702
445 786 822
446 943 569
447 831 668
448 831 647
449 892 644
450 834 766
451 834 626
452 843 738
453 892 661
454 943 649
455 786 635
456 831 642
457 892 662
458 892 645
459 831 593
460 915 712
461 915 768
462 786 791
463 943 601
464 786 650
465 943 584
466 943 585
467 943 592
468 915 797
469 861 716
470 928 720
471 868 727
472 786 773
473 831 699
474 831 597
475 834 771
476 892 782
477 868 970
478 831 676
479 834 697
480 831 617
481 831 798
482 834 753
483 928 678
484 928 595
485 831 628
486 892 663
487 861 705
488 786 610
489 786 947
490 786 606
491 786 814
492 928 688
493 892 607
494 831 619
495 875 616
496 875 758
497 786 878
498 928 702
499 786 634
500 786 608
501 934 856
502 875 694
503 786 649
504 879 632
505 928 766
506 928 762
507 934 722
508 934 686
509 928 642
510 879 693
511 879 653
512 879 715
513 928 665
514 914 874
515 786 643
516 879 655
517 786 906
518 879 646
519 934 805
520 786 638
521 831 695
522 879 827
523 786 817
524 934 661
525 934 728
526 879 659
527 879 866
528 934 645
529 914 730
530 786 822
531 879 727
532 914 798
533 879 865
534 1180 1152
535 952 660
536 948 782
537 948 761
538 928 657
539 928 689
540 914 899
541 967 795
542 952 970
543 914 726
544 967 717
545 914 753
546 1048 767
547 924 876
548 924 807
549 924 862
550 914 859
551 924 758
552 967 814
553 967 894
554 967 799
555 924 754
556 924 870
557 967 903
558 967 738
559 967 724
560 914 682
561 900 835
562 967 737
563 933 880
564 1048 790
565 882 677
566 891 698
567 900 704
568 890 703
569 1050 959
570 890 763
571 881 0
572 890 766
573 890 876
574 952 686
575 952 760
576 1050 808
577 952 805
578 890 866
579 900 714
580 1050 731
581 1048 770
582 952 817
583 1050 791
584 900 710
585 900 783
586 933 777
587 0 0
588 1007 780
589 982 723
590 1007 707
591 933 1122
592 982 752
593 951 865
594 925 0
595 982 801
596 982 906
597 933 0
598 982 716
599 951 927
600 951 771
601 982 728
602 982 717
603 982 886
604 951 785
605 951 730
606 1007 1106
607 1007 887
608 0 0
609 951 733
610 982 732
611 933 862
612 951 949
613 1404 0
614 1007 820
615 933 758
616 983 1152
617 983 1011
618 0 0
619 983 818
620 983 1006
621 1007 729
622 983 849
623 983 749
624 983 970
625 940 1038
626 1064 826
627 1481 0
628 940 958
629 982 734
630 1007 810
631 940 764
632 940 837
633 1064 859
634 982 894
635 982 835
636 1080 756
637 1007 768
638 982 903
639 935 0
640 1007 866
641 982 817
642 982 770
643 982 936
644 1050 871
645 1050 878
646 1007 1036
647 982 870
648 982 807
649 982 0
650 1050 824
651 982 800
652 1368 0
653 982 812
654 1050 929
655 982 773
656 1050 829
657 1076 856
658 1026 0
659 0 1002
660 1076 845
661 1076 806
662 1066 904
663 1076 889
664 613 920
665 1080 779
666 1003 0
667 613 778
668 1080 777
669 1071 947
670 613 895
671 1142 0
672 613 795
673 613 780
674 1080 1122
675 1071 1106
676 1001 1011
677 1068 958
678 1071 894
679 1071 980
680 881 0
681 1066 901
682 652 860
683 652 784
684 1328 0
685 652 847
686 1066 819
687 1084 852
688 652 794
689 1084 913
690 1026 0
691 1084 903
692 652 804
693 1068 1006
694 652 957
695 652 796
696 684 988
697 1027 1036
698 1068 0
699 1068 897
700 1084 1162
701 1130 984
702 1027 1005
703 1068 885
704 1130 921
705 1084 1072
706 1015 981
707 1130 805
708 1068 876
709 1180 827
710 1084 806
711 1015 0
712 1081 941
713 1081 883
714 1130 871
715 1081 809
716 1084 823
717 1130 919
718 1084 829
719 1128 986
720 1128 850
721 1027 1038
722 1084 902
723 1084 878
724 1084 833
725 0 0
726 1182 993
727 1082 1002
728 1265 1013
729 1084 894
730 0 836
731 1130 939
732 1084 906
733 1127 899
734 1084 841
735 1265 1049
736 1265 974
737 1265 1106
738 1265 844
739 1082 1000
740 0 0
741 1127 1033
742 1054 0
743 1084 848
744 1039 0
745 1127 893
746 1127 862
747 1084 903
748 1265 961
749 1123 0
750 1084 854
751 1265 1162
752 1084 962
753 1127 1188
754 1127 1300
755 1265 947
756 1082 1156
757 1082 1156
758 1127 1122
759 1027 1005
760 1084 858
761 1084 932
762 1082 1150
763 1182 1062
764 1082 910
765 1084 873
766 1127 0
767 1182 917
768 1119 897
769 0 0
770 1182 1022
771 1082 1086
772 1082 999
773 1082 941
774 1048 0
775 1119 883
776 1328 946
777 1119 884
778 1124 889
779 1082 1092
780 1084 888
781 1265 1072
782 1191 894
783 1265 1013
784 1177 1038
785 1182 989
786 1328 0
787 1177 893
788 1182 1152
789 1067 0
790 1182 963
791 1135 1209
792 1182 917
793 1095 0
794 1177 1151
795 1200 902
796 1177 1146
797 1177 1188
798 1182 0
799 1200 895
800 1177 899
801 1265 1031
802 1177 911
803 1265 1043
804 1177 897
805 1200 1102
806 1265 956
807 1177 0
808 1265 920
809 1182 986
810 1200 905
811 1135 996
812 1326 957
813 1299 1011
814 1265 923
815 1255 1024
816 1168 0
817 1200 918
818 1255 1086
819 1200 1044
820 0 0
821 1200 929
822 1200 921
823 1265 1051
824 1265 909
825 1328 976
826 1328 1022
827 1182 927
828 1328 946
829 1200 1010
830 1255 1035
831 1127 0
832 1177 949
833 1265 979
834 1286 0
835 1265 978
836 1328 965
837 1182 1025
838 1112 0
839 1132 0
840 1265 1094
841 1265 1055
842 1177 1167
843 1127 0
844 1200 942
845 1200 939
846 1265 1083
847 1328 993
848 1200 1126
849 1200 986
850 1328 1137
851 1328 1310
852 1265 1153
853 1200 996
854 1200 1162
855 1182 1075
856 1200 1078
857 1265 1016
858 1200 954
859 1328 1301
860 1328 1042
861 1154 0
862 1328 1179
863 1200 956
864 1200 975
865 1329 1111
866 1289 1150
867 1200 959
868 1136 0
869 1200 1145
870 1177 1061
871 1200 961
872 1265 1087
873 1200 969
874 1328 1062
875 1127 0
876 1275 971
877 1275 976
878 1424 1106
879 0 0
880 1232 1020
881 0 0
882 1172 0
883 1317 0
884 1232 1227
885 1232 1169
886 1265 1040
887 1247 984
888 1265 1072
889 1247 994
890 1344 0
891 1213 0
892 1208 0
893 1232 1092
894 1293 995
895 1265 1215
896 1299 1100
897 1232 1273
898 1312 1157
899 1308 993
900 1241 0
901 1265 1233
902 1293 1102
903 1293 1055
904 1293 1004
905 1293 1004
906 1265 1144
907 1308 1062
908 1312 1199
909 1265 1113
910 1308 1165
911 1308 1137
912 1265 1051
913 1324 1063
914 1216 0
915 1216 0
916 1308 1111
917 1308 1116
918 1265 1008
919 1265 1008
920 1232 1013
921 1265 1060
922 1265 1087
923 1232 1262
924 1204 0
925 0 0
926 1308 1014
927 1308 1187
928 1281 0
929 1324 1017
930 1329 1160
931 1329 1033
932 1277 1023
933 1271 0
934 1253 0
935 0 0
936 1335 1029
937 1329 1203
938 1333 1222
939 1274 1072
940 1281 0
941 1333 1089
942 1274 1103
943 1197 0
944 1335 1258
945 1274 1205
946 1337 1085
947 1335 1037
948 1281 0
949 1337 1179
950 1335 1034
951 1281 0
952 1281 0
953 1280 0
954 1274 1162
955 1335 1045
956 336 1091
957 1337 1092
958 1337 1189
959 1335 1113
960 1369 1043
961 1369 1063
962 1274 1098
963 1294 1150
964 1323 1111
965 1323 1157
966 1359 1262
967 1271 0
968 1323 1109
969 1274 1263
970 0 0
971 1323 1159
972 1369 1079
973 1359 1264
974 1359 1162
975 1359 1260
976 1323 1167
977 627 1073
978 1359 1330
979 1359 1304
980 1359 1133
981 0 0
982 1281 0
983 1286 0
984 1359 1252
985 1338 1077
986 627 1110
987 1340 1088
988 1292 1085
989 337 1206
990 1292 1155
991 1366 1218
992 627 1093
993 627 1140
994 1387 1229
995 1387 1266
996 1387 1193
997 1369 1098
998 1369 1105
999 1391 1198
1000 1414 1092
1001 1276 0
1002 1333 1096
1003 0 0
1004 1387 1205
1005 1414 1150
1006 1391 1231
1007 1286 0
1008 1387 1262
1009 1387 1190
1010 1387 1307
1011 1414 1151
1012 1369 1104
1013 1369 1162
1014 1333 1169
1015 0 0
1016 0 1170
1017 0 0
1018 1374 1147
1019 1374 1264
1020 1414 1146
1021 1391 1355
1022 1414 1137
1023 1359 1304
1024 1366 1321
1025 1336 1272
1026 0 0
1027 1331 0
1028 1489 1159
1029 0 0
1030 1340 1209
1031 1362 1236
1032 1359 1318
1033 1366 1189
1034 1359 1221
1035 1429 1152
1036 1448 1310
1037 1359 1249
1038 1448 1287
1039 0 0
1040 1374 1143
1041 1340 1201
1042 1336 1242
1043 1374 1193
1044 1374 1259
1045 1374 1251
1046 1374 1144
1047 1392 1291
1048 1328 0
1049 1374 1158
1050 1331 0
1051 1341 1315
1052 1340 1207
1053 1341 1266
1054 0 0
1055 1341 1400
1056 1392 1283
1057 1385 1421
1058 1392 1358
1059 1392 1408
1060 1341 1330
1061 1415 1164
1062 1392 1283
1063 1345 1233
1064 1336 0
1065 1412 1165
1066 1331 0
1067 0 0
1068 1328 0
1069 1345 1269
1070 1333 1388
1071 1328 0
1072 1341 1185
1073 1448 1256
1074 1345 1170
1075 1415 1174
1076 1331 0
1077 1448 1305
1078 1386 1250
1079 1345 1178
1080 1331 0
1081 1368 0
1082 1368 0
1083 1379 1237
1084 1331 0
1085 1429 0
1086 1448 1319
1087 1379 1248
1088 1340 1261
1089 1448 1184
1090 1379 1306
1091 0 0
1092 1389 1242
1093 1366 1231
1094 1379 1229
1095 0 0
1096 1396 1298
1097 1360 1249
1098 1387 1190
1099 1387 1251
1100 1390 1295
1101 1371 1347
1102 0 0
1103 1384 1239
1104 1384 1257
1105 1394 1207
1106 1384 1217
1107 1390 1211
1108 1406 1400
1109 1389 1218
1110 1396 1348
1111 1396 1240
1112 0 0
1113 1444 1330
1114 1440 1243
1115 1444 1269
1116 1390 1220
1117 1390 1245
1118 1444 1297
1119 1368 0
1120 337 1223
1121 1462 1402
1122 1389 1287
1123 0 0
1124 1368 0
1125 1409 1225
1126 1409 1399
1127 1368 0
1128 1368 0
1129 1352 1307
1130 1368 0
1131 1438 1221
1132 0 0
1133 1398 1219
1134 1398 1267
1135 1368 0
1136 0 0
1137 1389 1242
1138 1462 1229
1139 1445 1282
1140 1389 1397
1141 1417 1314
1142 0 0
1143 1438 1228
1144 1462 1246
1145 1413 1262
1146 337 0
1147 1474 1303
1148 1389 1319
1149 1389 1284
1150 337 0
1151 1389 0
1152 1445 1431
1153 0 1244
1154 0 0
1155 1395 1243
1156 1389 1245
1157 1395 1302
1158 1457 1330
1159 1389 1287
1160 1389 1348
1161 1475 1425
1162 1430 1266
1163 1445 1427
1164 1445 1279
1165 1445 1327
1166 1417 1272
1167 1417 1272
1168 0 0
1169 1417 1393
1170 1411 1269
1171 1417 1301
1172 0 0
1173 1417 1365
1174 0 0
1175 1405 1397
1176 1444 1304
1177 1419 0
1178 1430 1307
1179 1445 1422
1180 1410 0
1181 1416 1283
1182 1410 0
1183 1417 1350
1184 1416 1455
1185 1430 1303
1186 1416 1284
1187 1416 1284
1188 1417 0
1189 1416 1454
1190 1444 1309
1191 1410 0
1192 1416 1372
1193 1462 1315
1194 1417 1380
1195 1445 1353
1196 1445 1376
1197 0 0
1198 1416 1288
1199 1416 1288
1200 1466 0
1201 1450 1403
1202 1416 1332
1203 1416 1332
1204 0 0
1205 0 0
1206 1416 1287
1207 1470 1290
1208 0 0
1209 342 1432
1210 1416 1356
1211 1466 1348
1212 1416 1313
1213 0 0
1214 1416 1296
1215 1420 1375
1216 0 0
1217 0 0
1218 0 1397
1219 0 0
1220 0 0
1221 0 0
1222 0 0
1223 0 0
1224 1468 1311
1225 0 0
1226 1446 1373
1227 1446 1349
1228 1462 1437
1229 0 0
1230 1468 1316
1231 1446 1321
1232 1439 0
1233 0 0
1234 1468 1376
1235 1468 1423
1236 0 0
1237 0 0
1238 1468 1350
1239 1462 1330
1240 1461 1322
1241 0 0
1242 1461 1325
1243 1461 1332
1244 0 0
1245 1461 1348
1246 0 1346
1247 1447 0
1248 0 1342
1249 0 1370
1250 1448 1339
1251 0 1351
1252 0 1364
1253 0 0
1254 1461 1372
1255 1458 0
1256 1461 1433
1257 0 0
1258 0 1418
1259 0 0
1260 0 0
1261 1464 0
1262 0 1434
1263 0 1443
1264 0 1442
1265 1458 0
1266 0 1334
1267 0 0
1268 1461 1353
1269 0 0
1270 1461 1357
1271 0 0
1272 1461 1355
1273 1461 1355
1274 1458 0
1275 1451 0
1276 0 0
1277 1458 0
1278 1467 1361
1279 1467 1354
1280 0 0
1281 0 0
1282 1483 1363
1283 1483 1436
1284 1485 1426
1285 1485 1423
1286 0 0
1287 1483 1427
1288 1469 1460
1289 1453 0
1290 0 0
1291 341 1428
1292 0 0
1293 1458 0
1294 0 0
1295 341 1422
1296 1469 1380
1297 0 0
1298 341 1367
1299 1458 0
1300 1476 0
1301 1476 0
1302 1467 1353
1303 0 0
1304 0 0
1305 341 1373
1306 0 0
1307 0 0
1308 1463 0
1309 0 0
1310 341 1354
1311 341 1383
1312 1478 0
1313 1486 1365
1314 341 1381
1315 0 0
1316 341 1436
1317 0 0
1318 0 0
1319 1468 1454
1320 341 1421
1321 1446 0
1322 1461 1378
1323 1481 0
1324 1477 0
1325 1467 1449
1326 1458 0
1327 1469 1382
1328 1451 0
1329 1481 0
1330 0 0
1331 0 0
1332 1469 1377
1333 1471 0
1334 0 0
1335 1481 0
1336 1480 0
1337 1473 0
1338 1473 0
1339 0 0
1340 1472 0
1341 1478 0
1342 0 0
1343 1441 1393
1344 0 0
1345 1463 0
1346 0 0
1347 1452 1435
1348 1479 0
1349 1479 0
1350 1488 0
1351 0 0
1352 0 0
1353 1479 0
1354 0 0
1355 1479 1422
1356 1479 0
1357 1479 1401
1358 1479 1407
1359 1478 0
1360 1466 0
1361 1486 1465
1362 0 0
1363 1486 0
1364 0 0
1365 1486 0
1366 0 0
1367 0 0
1368 0 0
1369 1480 0
1370 0 0
1371 1473 0
1372 1479 0
1373 0 0
1374 1471 0
1375 0 0
1376 1486 0
1377 0 0
1378 1486 1459
1379 1471 0
1380 0 0
1381 0 0
1382 0 0
1383 0 0
1384 1480 0
1385 1482 0
1386 1482 0
1387 1482 0
1388 0 0
1389 1480 0
1390 0 0
1391 0 0
1392 1480 0
1393 0 0
1394 0 0
1395 0 0
1396 0 0
1397 0 0
1398 1480 0
1399 0 0
1400 0 0
1401 0 0
1402 0 0
1403 0 0
1404 0 0
1405 1480 0
1406 1480 0
1407 0 0
1408 0 0
1409 1482 0
1410 0 0
1411 1480 0
1412 1480 0
1413 1490 0
1414 1484 0
1415 1482 0
1416 0 0
1417 1480 0
1418 0 0
1419 0 0
1420 0 0
1421 0 0
1422 0 0
1423 0 0
1424 1482 0
1425 0 0
1426 0 0
1427 0 0
1428 0 0
1429 1482 0
1430 1456 0
1431 0 0
1432 0 0
1433 0 0
1434 0 0
1435 0 0
1436 0 0
1437 0 0
1438 1487 0
1439 0 0
1440 0 0
1441 0 0
1442 0 0
1443 0 0
1444 1482 0
1445 0 0
1446 0 0
1447 0 0
1448 0 0
1449 0 0
1450 0 0
1451 0 0
1452 0 0
1453 0 0
1454 0 0
1455 0 0
1456 0 0
1457 0 0
1458 0 0
1459 0 0
1460 0 0
1461 0 0
1462 0 0
1463 0 0
1464 0 0
1465 0 0
1466 0 0
1467 0 0
1468 0 0
1469 0 0
1470 0 0
1471 0 0
1472 0 0
1473 0 0
1474 0 0
1475 0 0
1476 0 0
1477 0 0
1478 0 0
1479 0 0
1480 0 0
1481 0 0
1482 0 0
1483 1490 0
1484 0 0
1485 0 0
1486 0 0
1487 0 0
1488 0 0
1489 1482 0
1490 0 0
animal sire dam
위 자료를 pedi_5tr.dat로 저장
파라미터 파일
23000.0 14921.0 13885.0 12434.8 11213.9 32000.0 17007.9 14966.6 14403.0 31000.0 15614.8 14465.5 28000.0 14297.6 27000.0
12385.0 10947.8 10137.1 8924.0 8657.3 13715.0 12318.4 9617.2 9221.4 11759.0 9428.9 8641.4 9334.0 7790.7 9000.0
1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
0 0 0 0 0 1 0 0 0 0 0 0 0 0 0
1 1 0 0 0 1 0 0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
1 0 1 0 0 0 0 0 0 1 0 0 0 0 0
0 0 0 0 0 1 1 0 0 1 0 0 0 0 0
1 1 1 0 0 1 1 0 0 1 0 0 0 0 0
0 0 0 0 0 0 0 0 0 0 0 0 1 0 0
1 0 0 1 0 0 0 0 0 0 0 0 1 0 0
0 0 0 0 0 1 0 1 0 0 0 0 1 0 0
1 1 0 1 0 1 0 1 0 0 0 0 1 0 0
0 0 0 0 0 0 0 0 0 1 1 0 1 0 0
1 0 1 1 0 0 0 0 0 1 1 0 1 0 0
0 0 0 0 0 1 1 1 0 1 1 0 1 0 0
1 1 1 1 0 1 1 1 0 1 1 0 1 0 0
0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
1 0 0 0 1 0 0 0 0 0 0 0 0 0 1
0 0 0 0 0 1 0 0 1 0 0 0 0 0 1
1 1 0 0 1 1 0 0 1 0 0 0 0 0 1
0 0 0 0 0 0 0 0 0 1 0 1 0 0 1
1 0 1 0 1 0 0 0 0 1 0 1 0 0 1
0 0 0 0 0 1 1 0 1 1 0 1 0 0 1
1 1 1 0 1 1 1 0 1 1 0 1 0 0 1
0 0 0 0 0 0 0 0 0 0 0 0 1 1 1
1 0 0 1 1 0 0 0 0 0 0 0 1 1 1
0 0 0 0 0 1 0 1 1 0 0 0 1 1 1
1 1 0 1 1 1 0 1 1 0 0 0 1 1 1
0 0 0 0 0 0 0 0 0 1 1 1 1 1 1
1 0 1 1 1 0 0 0 0 1 1 1 1 1 1
0 0 0 0 0 1 1 1 1 1 1 1 1 1 1
1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
1st row : residual variance-covariance2nd row : genetic variance-covariance
위 자료를 vcvtrt_5tr.par 저장
left hand side와 right hand side를 준비하는 프로그램
PROGRAM mt_dl_animal_model3_5tr_setup
! program name - multiple trait, different fixed level, animal model setup
! same model but different fixed level
! programmer - Park Byoungho
! usage - mt_df_animal_model3_5tr_setup
! purpose : read data file and write left-hand side and right-hand side
! Date - 2009.10.9.
! update
USE gi
IMPLICIT NONE
! data dictionary
INTEGER, PARAMETER :: no_of_trait = 5 ! number of trait
INTEGER, PARAMETER :: no_of_fixed = 2 ! number of fixed effects
INTEGER, PARAMETER :: no_of_eq = 1490 ! number of equation CHARACTER(LEN = 256) :: data_filename ! data file name
CHARACTER(LEN = 256) :: pedi_filename ! pedigree file name
CHARACTER(LEN = 256) :: par_filename ! parameter file name INTEGER :: no_of_ud ! number of upper digonal
INTEGER :: no_of_tc ! number of trait combination
REAL(KIND = 8), ALLOCATABLE :: gvcv(:) ! upper diagonal part of genetic variance-covariance, (no_of_trait)*(no_of_trait + 1) / 2 dimension
REAL(KIND = 8), ALLOCATABLE :: rvcv(:) ! upper diagonal part of residual variance-covariance, (no_of_trait)*(no_of_trait + 1) / 2 dimension
REAL(KIND = 8), ALLOCATABLE :: temp_rvcv(:) ! temporary rvcv
REAL(KIND = 8), ALLOCATABLE :: rvcv_tc(:,:) ! rvcv according to trait combination and then inverse
REAL(KIND = 8), ALLOCATABLE :: rvcv_tc_m(:,:,:) ! rvcv matrix according to trait combination and then inverse
INTEGER, ALLOCATABLE :: trait_combi(:) ! trait combination
INTEGER :: tc_no ! trait combination number INTEGER, ALLOCATABLE :: temp_effects(:) ! temporary animal and fixed effect
REAL(KIND = 8) :: milk1, milk2, r1, r2 ! data of trait for each line
INTEGER, ALLOCATABLE :: effects(:,:) ! array for fixed and animal effects
REAL(KINd = 8), ALLOCATABLE :: observations(:) ! array for observations
REAL(KINd = 8), ALLOCATABLE :: observations_mbr(:) ! array for observations multiplied by rvcv
INTEGER :: animal, sire, dam ! animal, sire, dam name for pedigree file
REAL(KIND = 8), ALLOCATABLE :: xpy(:,:) ! right-hand side
INTEGER, ALLOCATABLE :: nobs(:,:) ! number of observations
INTEGER :: i, j, k, l ! do loop
!REAL :: temp_value ! temporary storate for swap
INTEGER, DIMENSION(99) :: iw ! for inverse
REAL(KIND = 8) :: z ! for inverse
INTEGER :: mr ! for inverse
INTEGER :: status ! I/O status
CHARACTER(LEN = 40) :: error_msg ! error message
INTEGER :: zero = 0
! get data file name
data_filename = 'dairy_5tr.dat'
! get pedigree file name
pedi_filename = 'pedi_5tr.dat'
! get parameter file name
par_filename = 'vcvtrt_5tr.par' no_of_ud = (no_of_trait)*(no_of_trait + 1) / 2 ! number of upper diagonal of variance-covariance
no_of_tc = 0 ! number of trait combination
DO i = 1, no_of_trait
no_of_tc = no_of_tc + 2 ** (i - 1)
END DO ALLOCATE(gvcv(no_of_ud)) ! genetic variance-covariance
ALLOCATE(rvcv(no_of_ud)) ! residual variance-covariance
ALLOCATE(temp_rvcv(no_of_ud)) ! temporary residual variance-covariance
ALLOCATE(rvcv_tc(no_of_tc, no_of_ud)) ! residual variance-covariance according to trait combination
ALLOCATE(rvcv_tc_m(no_of_tc, no_of_trait, no_of_trait)) ! residual variance-covariance matrix according to trait combination
ALLOCATE(trait_combi(no_of_ud)) ! trait combination
ALLOCATE(xpy(no_of_eq, no_of_trait)) ! right hand side
ALLOCATE(nobs(no_of_eq, no_of_trait)) ! number of observations
ALLOCATE(temp_effects(no_of_trait * no_of_fixed + 1)) ! temporary array for fixed and animal effects
ALLOCATE(effects(no_of_trait, no_of_fixed + 1)) ! array for processing fixed and animal effects
ALLOCATE(observations(no_of_trait)) ! array for observations
ALLOCATE(observations_mbr(no_of_trait)) ! array for observations multiplied by rvcv
xpy = 0
nobs = 0 ! open file for data processing procedure
OPEN(UNIT = 31, FILE = 'ongoing.dat', STATUS = 'REPLACE', ACTION = 'WRITE')
! open parameter file
OPEN(UNIT = 21, FILE = par_filename, STATUS = 'OLD', ACTION = 'READ', IOSTAT = status, IOMSG = error_msg)
IF (status /= 0) THEN ! file open failed
WRITE (*,'(1X, A, A)') 'parameter file open failed -- error message : ', error_msg
STOP
END IF ! residual variance-covariance
READ(UNIT = 21, FMT = *) rvcv
WRITE(31,*) 'residual variance-covariance = ', rvcv
! genetic variance-covariance
READ(UNIT = 21, FMT = *) gvcv
WRITE(31,*) 'genetic variance-covariance = ', gvcv
! trait combination
DO k = 1, no_of_tc
READ(UNIT = 21, FMT = *) trait_combi
WRITE(31,*) 'trait combination ', k , '=', trait_combi
temp_rvcv = rvcv * trait_combi
WRITE(31,*) 'trati combination residual vcv', temp_rvcv
z = 0.0
CALL DJNVHF(temp_rvcv,no_of_trait,iw,z,mr) ! inverse of upper diagonal matrix(residual)
WRITE(31,*) 'inverse of trait combination rvcv', temp_rvcv
rvcv_tc(k,:) = temp_rvcv ! sotre the inverse of upper diagonal matrix(residual)
DO i = 1, no_of_trait
DO j = 1, no_of_trait
rvcv_tc_m(k,i,j) = temp_rvcv(IHMSSF(i,j,no_of_trait))
END DO
END DO
END DO ! open data file
OPEN(UNIT = 11, FILE = data_filename, STATUS = 'OLD', ACTION = 'READ', IOSTAT = status, IOMSG = error_msg)
IF (status /= 0) THEN ! file open failed
WRITE (*,'(1X, A, A)') 'Data file open failed -- error message : ', error_msg
STOP
END IF ! open data file for writing left-hand side
OPEN(UNIT = 12, FILE = 'lhs.dat', STATUS = 'REPLACE', ACTION = 'WRITE') ! read each line
DO
READ(UNIT = 11, FMT = *, IOSTAT = status) temp_effects, observations
IF (status /= 0) EXIT ! end of file ! copy temp_effects(fixed) to effects
DO i = 1, no_of_trait
effects(i,1:no_of_fixed) = temp_effects((i-1) * no_of_fixed + 1 : i * no_of_fixed)
END DO
! copy temp_effects(animal) to effects
DO i = 1, no_of_trait
effects(i,no_of_fixed + 1) = temp_effects(no_of_trait * no_of_fixed + 1)
END DO
! find trait combination number
tc_no = 0
DO i = 1, no_of_trait
IF (observations(i) /= 0.0) tc_no = tc_no + 2 ** (i - 1)
END DO observations_mbr = MATMUL(rvcv_tc_m(tc_no,:,:), observations) ! left hand side
DO i = 1, no_of_trait
IF (effects(i,1) /= 0) THEN
DO j = 1, no_of_fixed + 1
IF (j < no_of_fixed + 1) THEN
WRITE(UNIT = 12, FMT = *) effects(i,j), i, ((effects(k,l),l = 1, no_of_fixed + 1), k = 1, no_of_trait), '1', tc_no
ELSE
WRITE(UNIT = 12, FMT = *) effects(i,j), i, ((effects(k,l),l = 1, no_of_fixed + 1), k = 1, no_of_trait), '2', tc_no
END IF
END DO
END IF
END DO
! right hand side
DO i = 1, no_of_trait
IF (effects(i,1) /= 0) THEN
DO j = 1, no_of_fixed + 1
xpy(effects(i,j),i) = xpy(effects(i,j),i) + observations_mbr(i)
nobs(effects(i,j),i) = nobs(effects(i,j),i) + 1
END DO
END IF
END DO END DO CLOSE(11) ! close data file
! open pedigree file
OPEN(UNIT = 13, FILE = pedi_filename, STATUS = 'OLD', ACTION = 'READ', IOSTAT = status, IOMSG = error_msg)
IF (status /= 0) THEN ! file open failed
WRITE (*,'(1X, A, A)') 'pedigree file open failed -- error message : ', error_msg
STOP
END IF ! read each line
DO
READ(UNIT = 13, FMT = *, IOSTAT = status) animal, sire, dam
IF (status /= 0) EXIT ! end of file ! write animal effect
! DO i = 1, no_of_trait
IF ( sire /= 0 .AND. dam /= 0) THEN
WRITE(UNIT = 12, FMT = *) animal, zero, animal, sire, dam, (zero,k=1,no_of_trait*(no_of_fixed+1)-3), '1001', zero
WRITE(UNIT = 12, FMT = *) sire, zero, animal, dam, sire, (zero,k=1,no_of_trait*(no_of_fixed+1)-3), '1002', zero
WRITE(UNIT = 12, FMT = *) dam, zero, animal, sire, dam, (zero,k=1,no_of_trait*(no_of_fixed+1)-3), '1002', zero
ELSE IF (sire /= 0 .AND. dam == 0) THEN
WRITE(UNIT = 12, FMT = *) animal, zero, animal, sire, dam, (zero,k=1,no_of_trait*(no_of_fixed+1)-3), '1003', zero
WRITE(UNIT = 12, FMT = *) sire, zero, animal, sire, dam, (zero,k=1,no_of_trait*(no_of_fixed+1)-3), '1004', zero
ELSE IF (sire == 0 .AND. dam /= 0) THEN
WRITE(UNIT = 12, FMT = *) animal, zero, animal, dam, sire, (zero,k=1,no_of_trait*(no_of_fixed+1)-3), '1003', zero
WRITE(UNIT = 12, FMT = *) dam, zero, animal, dam, sire, (zero,k=1,no_of_trait*(no_of_fixed+1)-3), '1004', zero
ELSE
WRITE(UNIT = 12, FMT = *) animal, zero, animal, sire, dam, (zero,k=1,no_of_trait*(no_of_fixed+1)-3), '1005', zero
END IF
! END DO
END DO ! end of reading datas CLOSE(13) ! close animal file
CLOSE(12) ! close file for left-hand side ! open file for right hand side
OPEN(UNIT = 14, FILE = 'rhs.dat', STATUS = 'REPLACE', ACTION = 'WRITE') ! write xpy
DO i = 1, no_of_eq
WRITE(UNIT = 14, FMT = *) xpy(i,:), nobs(i,:)
END DO
CLOSE(14) ! close file for right-hand sideEND PROGRAM mt_dl_animal_model3_5tr_setup
위 프로그램을 mt_dl_animal_model3_5tr_setup.f95로 저장
Left hand side 정렬 명령어 sort -m -o sorted_lhs.dat lhs.dat
해를 구하는 프로그램
PROGRAM mt_dl_animal_model3_5tr_solve ! program name - multiple trait, different fixed level, animal_model_solve
! programmer - Park Byoungho
! usage - mt_dl_animal_model3_solve
! purpose : read sorted_lhs.dat and rhs.dat which are made in animal_model_setup.exe and are sorted
! find a solution using Gauss-Seidel iteration
! Date - 2009.7.7
! update - 209.7.14. inv_diag_ele(2,2) -> allocate(inv_diag_ele(no_of_trait,no_of_trait))
! data_type(i,9) -> data_type = lhs(i,2+no_of_trait*(no_of_fixed+1)+1)
! tc_no(i,10) -> tc_no = lhs(i,2+no_of_trait*(no_of_fixed+1)+2) USE gi IMPLICIT NONE
! data dictionary
INTEGER, PARAMETER :: no_of_trait = 5 ! number of trait
INTEGER, PARAMETER :: no_of_fixed = 2 ! number of fixed effects
INTEGER, PARAMETER :: no_of_eq = 1490 ! number of equation INTEGER :: no_of_ud ! number of upper digonal
INTEGER :: no_of_tc ! number of trait combination REAL(KIND = 8), ALLOCATABLE :: gvcv(:) ! upper diagonal part of genetic variance-covariance, (no_of_trait)*(no_of_trait + 1) / 2 dimension
REAL(KIND = 8), ALLOCATABLE :: gvcv_m(:,:)
REAL(KIND = 8), ALLOCATABLE :: rvcv(:) ! upper diagonal part of residual variance-covariance, (no_of_trait)*(no_of_trait + 1) / 2 dimension
REAL(KIND = 8), ALLOCATABLE :: temp_rvcv(:) ! temporary rvcv
REAL(KIND = 8), ALLOCATABLE :: rvcv_tc(:,:) ! rvcv according to trait combination and then inverse
REAL(KIND = 8), ALLOCATABLE :: rvcv_tc_m(:,:,:) ! rvcv matrix according to trait combination and then inverse
INTEGER, ALLOCATABLE :: trait_combi(:) ! trait combination
INTEGER :: tc_no ! trait combination number INTEGER, DIMENSION(99) :: iw ! for inverse
REAL(KIND = 8) :: z ! for inverse
INTEGER :: mr ! for inverse
INTEGER :: pre_eq_no ! previous equation number
INTEGER :: cur_eq_no ! current equation number
INTEGER :: pre_trait_no ! previous trait number
INTEGER :: cur_trait_no ! current trati number
INTEGER, ALLOCATABLE :: loc_of_nz(:,:) ! location of none-zero element
INTEGER, ALLOCATABLE :: loc_of_nz_a(:,:) ! location of none-zero element
INTEGER :: data_type ! data type : 1:fixed, 2-6:animal
REAL(KIND = 8), ALLOCATABLE :: diag_ele(:,:) ! diagonal element of lhs
REAL(KIND = 8), ALLOCATABLE :: inv_diag_ele(:,:) ! inverse of diagonal
INTEGER :: no_of_lhs ! number of lhs lines
INTEGER, ALLOCATABLE :: lhs(:,:) ! left-hand side
REAL(KIND = 8), ALLOCATABLE :: rhs(:,:) ! right-hand side, x'y
REAL(KIND = 8), ALLOCATABLE :: temp_rhs(:) ! right-hand side one element
REAL(KIND = 8), ALLOCATABLE :: solutions(:,:) ! solutions
REAL(KIND = 8), ALLOCATABLE :: pre_sol(:) ! previous solution
REAL(KIND = 8), ALLOCATABLE :: sum_sol(:) ! sum solution
INTEGER :: iteration ! iteration
REAL(KIND = 8) :: epsilon ! sum of squares between old and new solutions
INTEGER :: i,j,k ! loop
INTEGER :: status ! i/o status
CHARACTER(LEN = 40) :: error_msg ! error message
INTEGER, PARAMETER :: MAX_ITER = 1000 ! maximum number of iteration
REAL(KIND = 8), PARAMETER :: criteria = 1.E-12 ! criteria for stopping
no_of_ud = (no_of_trait)*(no_of_trait + 1) / 2 ! number of upper diagonal of variance-covariance
no_of_tc = 0 ! number of trait combination
DO i = 1, no_of_trait
no_of_tc = no_of_tc + 2 ** (i - 1)
END DO
ALLOCATE(gvcv(no_of_ud)) ! genetic variance-covariance
ALLOCATE(gvcv_m(no_of_trait, no_of_trait)) ! genetic variance-covariance
ALLOCATE(rvcv(no_of_ud)) ! residual variance-covariance
ALLOCATE(temp_rvcv(no_of_ud)) ! temporary residual variance-covariance
ALLOCATE(rvcv_tc(no_of_tc, no_of_ud)) ! residual variance-covariance according to trait combination
ALLOCATE(rvcv_tc_m(no_of_tc, no_of_trait, no_of_trait)) ! residual variance-covariance matrix according to trait combination
ALLOCATE(trait_combi(no_of_ud)) ! trait combination
ALLOCATE(rhs(no_of_eq, no_of_trait * 2)) ! right hand side
ALLOCATE(loc_of_nz(no_of_trait,no_of_fixed + 1)) ! location of none-zero element
ALLOCATE(loc_of_nz_a(no_of_trait,no_of_fixed))
ALLOCATE(sum_sol(no_of_trait)) ! temporary solution
ALLOCATE(solutions(no_of_eq, no_of_trait)) ! solution
ALLOCATE(pre_sol(no_of_trait))
ALLOCATE(diag_ele(no_of_trait,no_of_trait))
ALLOCATE(inv_diag_ele(no_of_trait,no_of_trait))
ALLOCATE(temp_rhs(no_of_trait))
! initialiaze solutions to zero
solutions = 0
! open file for data processing procedure
OPEN(UNIT = 31, FILE = 'ongoing_solve.dat', STATUS = 'REPLACE', ACTION = 'WRITE')
! open parameter file
OPEN(UNIT = 21, FILE = 'vcvtrt_5tr.par', STATUS = 'OLD', ACTION = 'READ', IOSTAT = status, IOMSG = error_msg)
IF (status /= 0) THEN ! file open failed
WRITE (*,'(1X, A, A)') 'parameter file open failed -- error message : ', error_msg
STOP
END IF
! residual variance-covariance
READ(UNIT = 21, FMT = *) rvcv
write(31,*) 'residual variance-covariance = ', rvcv
! genetic variance-covariance
READ(UNIT = 21, FMT = *) gvcv
write(31,*) 'genetic variance-covariance = ', gvcv
! inverse of genetic variance-covariance
z = 0.0
CALL DJNVHF(gvcv,no_of_trait,iw,z,mr)
DO i = 1, no_of_trait
DO j = 1, no_of_trait
gvcv_m(i,j) = gvcv(IHMSSF(i,j,no_of_trait))
END DO
END DO
write(31,*) 'inverse of genetic variance-covariance', ((gvcv_m(i,j),i = 1, no_of_trait),j = 1, no_of_trait)
! trait combination
DO k = 1, no_of_tc
READ(UNIT = 21, FMT = *) trait_combi
write(31,*) 'trait combination ', k , '=', trait_combi
temp_rvcv = rvcv * trait_combi
write(31,*) 'trati combination residual vcv', temp_rvcv
z = 0.0
CALL DJNVHF(temp_rvcv,no_of_trait,iw,z,mr) ! inverse of upper diagonal matrix(residual)
write(31,*) 'inverse of trait combination rvcv', temp_rvcv
rvcv_tc(k,:) = temp_rvcv ! sotre the inverse of upper diagonal matrix(residual)
DO i = 1, no_of_trait
DO j = 1, no_of_trait
rvcv_tc_m(k,i,j) = temp_rvcv(IHMSSF(i,j,no_of_trait))
END DO
END DO
END DO
!open left-han side file
OPEN(UNIT = 11, FILE = 'sorted_lhs.dat', STATUS = 'OLD', ACTION = 'READ', IOSTAT = status, IOMSG = error_msg)
IF (status /= 0) THEN ! file open failed
WRITE (*,'(1X, A, A)') 'Sorted lhs file open failed -- error message : ', error_msg
STOP
END IF
! count the lines of lhs
no_of_lhs = 0
DO
READ(UNIT = 11, FMT = *, IOSTAT = status)
IF (status /= 0) EXIT ! reach end of file
no_of_lhs = no_of_lhs + 1
END DO
ALLOCATE(lhs(no_of_lhs, no_of_trait * (no_of_fixed + 1) + 4))
write(31,*) 'number of lines of left hand side = ', no_of_lhs
! store lhs to array
REWIND(11)
DO i = 1, no_of_lhs
READ(UNIT = 11, FMT = *, IOSTAT = status) lhs(i,:)
IF (status /= 0) EXIT ! reach end of file
END DO
CLOSE(11)
write(31,*) 'left hand side, lines = ', no_of_lhs
DO i = 1, no_of_lhs
write(31,*) lhs(i,:)
END DO
!open right-hand side file
OPEN(UNIT = 12, FILE = 'rhs.dat', STATUS = 'OLD', ACTION = 'READ', IOSTAT = status, IOMSG = error_msg)
IF (status /= 0) THEN ! file open failed
WRITE (*,'(1X, A, A)') 'RHS file open failed -- error message : ', error_msg
STOP
END IF
! read and store right-hand side
DO i = 1, no_of_eq
READ(UNIT = 12,FMT = *) rhs(i,:)
END DO
close(12)
write(31,*) 'right hand side, number of equations = ', no_of_eq
DO i = 1, no_of_eq
write(31,*) i, rhs(i,:)
END DO
! start iteration
DO iteration = 1, MAX_ITER
pre_eq_no = 1
diag_ele = 0.0
temp_rhs = rhs(lhs(1,1),1:no_of_trait)
epsilon = 0.0
! start reading and processing each line of lhs
DO i = 1, no_of_lhs
cur_eq_no = lhs(i,1)
cur_trait_no = lhs(i,2)
data_type = lhs(i,2+no_of_trait*(no_of_fixed+1)+1)
tc_no = lhs(i,2+no_of_trait*(no_of_fixed+1)+2)
! if new equation, calculate solution
IF (pre_eq_no /= cur_eq_no) THEN
pre_sol = solutions(pre_eq_no, :)
CALL geninv(diag_ele, inv_diag_ele)
write(31,*) 'calculate solutions'
write(31,*) 'diag_ele = ', diag_ele
write(31,*) 'inv_diag_ele = ', inv_diag_ele
write(31,*) 'temp_rhs = ', temp_rhs
solutions(pre_eq_no, :) = MATMUL(inv_diag_ele, temp_rhs)
epsilon = epsilon + SUM((pre_sol - solutions(pre_eq_no, :))**2)
write(31,*) 'new sol =', MATMUL(inv_diag_ele, temp_rhs)
diag_ele = 0.0
temp_rhs = rhs(lhs(i,1), 1:no_of_trait)
pre_eq_no = cur_eq_no
END IF
! adjust rhs and add diag_ele
SELECT CASE(data_type)
CASE(1) ! fixed effect
DO k = 1, no_of_trait
loc_of_nz(k,:) = lhs(i,(k-1)*(no_of_fixed + 1)+ 3 : k * (no_of_fixed + 1) + 2)
END DO
sum_sol = 0
DO k = 1, no_of_trait
If (loc_of_nz(k,1) /= 0) THEN
sum_sol(k) = SUM(solutions(loc_of_nz(k,:),k))
END IF
END DO
temp_rhs(cur_trait_no) = temp_rhs(cur_trait_no) &
- SUM(rvcv_tc_m(tc_no,cur_trait_no,:) * sum_sol) &
+ rvcv_tc_m(tc_no,cur_trait_no,cur_trait_no) * solutions(cur_eq_no, cur_trait_no)
diag_ele(cur_trait_no,cur_trait_no) = diag_ele(cur_trait_no,cur_trait_no) + rvcv_tc_m(tc_no, cur_trait_no, cur_trait_no)
CASE(2) ! animal as a fixed effect
DO k = 1, no_of_trait
loc_of_nz_a(k,:) = lhs(i,(k-1)*(no_of_fixed + 1)+ 3 : k * (no_of_fixed + 1) + 1)
END DO
sum_sol = 0
DO k = 1, no_of_trait
If (loc_of_nz_a(k,1) /= 0) THEN
sum_sol(k) = SUM(solutions(loc_of_nz_a(k,:),k))
END IF
END DO
temp_rhs(cur_trait_no) = temp_rhs(cur_trait_no) &
- SUM(rvcv_tc_m(tc_no,cur_trait_no,:) * sum_sol)
diag_ele(cur_trait_no,:) = diag_ele(cur_trait_no,:) + rvcv_tc_m(tc_no, cur_trait_no,:)
CASE(1001) ! animal, both parents are known, animal is diagonal
temp_rhs = temp_rhs - (-1.) * MATMUL(gvcv_m,solutions(lhs(i,4),:)) &
- (-1.) * MATMUL(gvcv_m,solutions(lhs(i,5),:))
diag_ele = diag_ele + 2.0 * gvcv_m
CASE(1002) ! animal, both parents are known, sire or dam is diagonal
write(31,*) 'temp_rhs = ', temp_rhs
write(31,*) 'diag_ele = ', diag_ele
write(31,*) 'lhs(i,3) = ', lhs(i,3)
write(31,*) 'solutions(lhs(i,3) =', solutions(lhs(i,3),:)
temp_rhs = temp_rhs - (-1.0) * MATMUL(gvcv_m,solutions(lhs(i,3),:)) &
- ( 0.5) * MATMUL(gvcv_m,solutions(lhs(i,4),:))
diag_ele = diag_ele + ( 0.5) * gvcv_m
write(31,*) 'temp_rhs = ', temp_rhs
write(31,*) 'diag_ele = ', diag_ele
CASE(1003) ! animal, one parent is known, animal is diagonal
temp_rhs = temp_rhs - (-2.0/3.0) * MATMUL(gvcv_m,solutions(lhs(i,4),:))
diag_ele = diag_ele + (4.0/3.0) * gvcv_m
CASE(1004) ! animal effect, one parents is known, parent is diagonal
temp_rhs = temp_rhs - (-2.0/3.0) * MATMUL(gvcv_m,solutions(lhs(i,3),:))
diag_ele = diag_ele + (1.0/3.0) * gvcv_m
CASE(1005) ! animal effect, no parents is known
diag_ele = diag_ele + 1.0 * gvcv_m
write(31,*) 'case 1005, diag_ele = ', diag_ele
CASE DEFAULT
WRITE(31,*) cur_eq_no, 'equation number has a ', data_type,' Invalid data_type. ', i,'th line of lhs'
END SELECT
END DO
! end reading lhs
! calculate last solution
pre_sol = solutions(pre_eq_no, :)
CALL geninv(diag_ele, inv_diag_ele)
solutions(pre_eq_no, :) = MATMUL(inv_diag_ele, temp_rhs)
epsilon = (epsilon + SUM((pre_sol - solutions(pre_eq_no, :))**2))/(no_of_eq * no_of_trait)
WRITE(31,*) iteration,'th iteration''s solutions'
DO k = 1, no_of_eq
WRITE(31,*) k, solutions(k,:)
END DO
! write iteration number and epsilon
write(*,*) 'iteration = ', iteration , ', epsilon = ', epsilon
IF (epsilon < criteria) THEN
EXIT
END IF
END DO
! end iteration
CLOSE(31)
! open file for writing solution
OPEN(UNIT=13, FILE='sol.dat', STATUS='REPLACE', ACTION='WRITE', IOSTAT=status)
DO i = 1, no_of_eq
WRITE(13,*) i, solutions(i,:)
END DO
CLOSE(13)
END PROGRAM mt_dl_animal_model3_5tr_solve
위 프로그램을 mt_dlanimal_model3_5tr_solve.f95로 저장
LHS, RHS 및 solution은 첨부파일로 대체
컴파일 및 실행화면
관련 파일
1255084814_dairy_5tr.dat
1255084814_pedi_5tr.dat
1255084814_vcvtrt_5tr.par
1255084814_mt_dl_animal_model3_5tr_setup.f95
1255084814_inverse.f95
1255084814_lhs.dat
1255084814_rhs.dat
1255084814_sorted_lhs.dat
1255084814_mt_dl_animal_model3_5tr_solve.f95
1255084814_sol.dat
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