Shuffle matrix based on column elements

3 次查看（过去 30 天）
EK
EK 2023-10-7
评论： Voss 2023-10-8
Hi,
I have matrices like in the file attached below. The 4 columns log for stimuli representation in time. The rows are time and the columns are events. The first column logs stimuli id in time. (No stimulus =0, stimulus : 1 2 3 4 5 or 6) The second column logs the stimulus presentation time and its duration (0= No stimulus, 2=Stimulus); column 3 logs duration and ID of each trial. Trial 1 ==1; Trial trial 2 ==2; etc . I need to shuffle trials Ids (column3). Can anyone help with it?

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采纳的回答

Voss
Voss 2023-10-8
Ran in:
Here's one way:
data = readmatrix('logfile_example-30-09-23.xlsx')
data = 1820×4
0 1 1 1 0 1 1 2 0 1 1 3 0 1 1 4 0 1 1 5 0 1 1 6 0 1 1 7 0 1 1 8 0 1 1 9 0 1 1 10
[trial_idx,trial_id] = findgroups(data(:,3));
n_trials = numel(trial_id);
order = randperm(n_trials)
order = 1×10
4 9 3 2 1 6 10 8 7 5
result = [];
for ii = 1:n_trials
result = [result; data(trial_idx == order(ii),:)];
end
disp(result);
0 1 4 547 0 1 4 548 0 1 4 549 0 1 4 550 0 1 4 551 0 1 4 552 0 1 4 553 0 1 4 554 0 1 4 555 0 1 4 556 0 1 4 557 0 1 4 558 0 1 4 559 0 1 4 560 0 1 4 561 0 1 4 562 0 1 4 563 0 1 4 564 0 1 4 565 0 1 4 566 0 1 4 567 0 1 4 568 0 1 4 569 0 1 4 570 0 1 4 571 0 1 4 572 0 1 4 573 0 1 4 574 0 1 4 575 0 1 4 576 0 1 4 577 0 1 4 578 0 1 4 579 0 1 4 580 0 1 4 581 0 1 4 582 0 1 4 583 0 1 4 584 0 1 4 585 0 1 4 586 0 1 4 587 0 1 4 588 0 1 4 589 0 1 4 590 0 1 4 591 0 1 4 592 0 1 4 593 0 1 4 594 0 1 4 595 0 1 4 596 0 1 4 597 0 1 4 598 0 1 4 599 0 1 4 600 0 1 4 601 0 1 4 602 0 1 4 603 0 1 4 604 0 1 4 605 0 1 4 606 0 1 4 607 0 1 4 608 0 1 4 609 0 1 4 610 0 1 4 611 0 1 4 612 0 1 4 613 0 1 4 614 0 1 4 615 0 1 4 616 2 2 4 617 2 2 4 618 2 2 4 619 2 2 4 620 2 2 4 621 2 2 4 622 2 2 4 623 2 2 4 624 2 2 4 625 2 2 4 626 2 2 4 627 2 2 4 628 2 2 4 629 2 2 4 630 2 2 4 631 2 2 4 632 2 2 4 633 2 2 4 634 2 2 4 635 2 2 4 636 2 2 4 637 2 2 4 638 2 2 4 639 2 2 4 640 2 2 4 641 2 2 4 642 2 2 4 643 2 2 4 644 2 2 4 645 2 2 4 646 2 2 4 647 2 2 4 648 2 2 4 649 2 2 4 650 2 2 4 651 2 2 4 652 2 2 4 653 2 2 4 654 2 2 4 655 2 2 4 656 2 2 4 657 2 2 4 658 0 3 4 659 0 3 4 660 0 3 4 661 0 3 4 662 0 3 4 663 0 3 4 664 0 3 4 665 0 3 4 666 0 3 4 667 0 3 4 668 0 3 4 669 0 3 4 670 0 3 4 671 0 3 4 672 0 3 4 673 0 3 4 674 0 3 4 675 0 3 4 676 0 3 4 677 0 3 4 678 0 3 4 679 0 3 4 680 0 3 4 681 0 3 4 682 0 3 4 683 0 3 4 684 0 3 4 685 0 3 4 686 0 3 4 687 0 3 4 688 0 3 4 689 0 3 4 690 0 3 4 691 0 3 4 692 0 3 4 693 0 3 4 694 0 3 4 695 0 3 4 696 0 3 4 697 0 3 4 698 0 3 4 699 0 3 4 700 0 3 4 701 0 3 4 702 0 3 4 703 0 3 4 704 0 3 4 705 0 3 4 706 0 3 4 707 0 3 4 708 0 3 4 709 0 3 4 710 0 3 4 711 0 3 4 712 0 3 4 713 0 3 4 714 0 3 4 715 0 3 4 716 0 3 4 717 0 3 4 718 0 3 4 719 0 3 4 720 0 3 4 721 0 3 4 722 0 3 4 723 0 3 4 724 0 3 4 725 0 3 4 726 0 3 4 727 0 3 4 728 0 1 9 1457 0 1 9 1458 0 1 9 1459 0 1 9 1460 0 1 9 1461 0 1 9 1462 0 1 9 1463 0 1 9 1464 0 1 9 1465 0 1 9 1466 0 1 9 1467 0 1 9 1468 0 1 9 1469 0 1 9 1470 0 1 9 1471 0 1 9 1472 0 1 9 1473 0 1 9 1474 0 1 9 1475 0 1 9 1476 0 1 9 1477 0 1 9 1478 0 1 9 1479 0 1 9 1480 0 1 9 1481 0 1 9 1482 0 1 9 1483 0 1 9 1484 0 1 9 1485 0 1 9 1486 0 1 9 1487 0 1 9 1488 0 1 9 1489 0 1 9 1490 0 1 9 1491 0 1 9 1492 0 1 9 1493 0 1 9 1494 0 1 9 1495 0 1 9 1496 0 1 9 1497 0 1 9 1498 0 1 9 1499 0 1 9 1500 0 1 9 1501 0 1 9 1502 0 1 9 1503 0 1 9 1504 0 1 9 1505 0 1 9 1506 0 1 9 1507 0 1 9 1508 0 1 9 1509 0 1 9 1510 0 1 9 1511 0 1 9 1512 0 1 9 1513 0 1 9 1514 0 1 9 1515 0 1 9 1516 0 1 9 1517 0 1 9 1518 0 1 9 1519 0 1 9 1520 0 1 9 1521 0 1 9 1522 0 1 9 1523 0 1 9 1524 0 1 9 1525 0 1 9 1526 2 2 9 1527 2 2 9 1528 2 2 9 1529 2 2 9 1530 2 2 9 1531 2 2 9 1532 2 2 9 1533 2 2 9 1534 2 2 9 1535 2 2 9 1536 2 2 9 1537 2 2 9 1538 2 2 9 1539 2 2 9 1540 2 2 9 1541 2 2 9 1542 2 2 9 1543 2 2 9 1544 2 2 9 1545 2 2 9 1546 2 2 9 1547 2 2 9 1548 2 2 9 1549 2 2 9 1550 2 2 9 1551 2 2 9 1552 2 2 9 1553 2 2 9 1554 2 2 9 1555 2 2 9 1556 2 2 9 1557 2 2 9 1558 2 2 9 1559 2 2 9 1560 2 2 9 1561 2 2 9 1562 2 2 9 1563 2 2 9 1564 2 2 9 1565 2 2 9 1566 2 2 9 1567 2 2 9 1568 0 3 9 1569 0 3 9 1570 0 3 9 1571 0 3 9 1572 0 3 9 1573 0 3 9 1574 0 3 9 1575 0 3 9 1576 0 3 9 1577 0 3 9 1578 0 3 9 1579 0 3 9 1580 0 3 9 1581 0 3 9 1582 0 3 9 1583 0 3 9 1584 0 3 9 1585 0 3 9 1586 0 3 9 1587 0 3 9 1588 0 3 9 1589 0 3 9 1590 0 3 9 1591 0 3 9 1592 0 3 9 1593 0 3 9 1594 0 3 9 1595 0 3 9 1596 0 3 9 1597 0 3 9 1598 0 3 9 1599 0 3 9 1600 0 3 9 1601 0 3 9 1602 0 3 9 1603 0 3 9 1604 0 3 9 1605 0 3 9 1606 0 3 9 1607 0 3 9 1608 0 3 9 1609 0 3 9 1610 0 3 9 1611 0 3 9 1612 0 3 9 1613 0 3 9 1614 0 3 9 1615 0 3 9 1616 0 3 9 1617 0 3 9 1618 0 3 9 1619 0 3 9 1620 0 3 9 1621 0 3 9 1622 0 3 9 1623 0 3 9 1624 0 3 9 1625 0 3 9 1626 0 3 9 1627 0 3 9 1628 0 3 9 1629 0 3 9 1630 0 3 9 1631 0 3 9 1632 0 3 9 1633 0 3 9 1634 0 3 9 1635 0 3 9 1636 0 3 9 1637 0 3 9 1638 0 1 3 365 0 1 3 366 0 1 3 367 0 1 3 368 0 1 3 369 0 1 3 370 0 1 3 371 0 1 3 372 0 1 3 373 0 1 3 374 0 1 3 375 0 1 3 376 0 1 3 377 0 1 3 378 0 1 3 379 0 1 3 380 0 1 3 381 0 1 3 382 0 1 3 383 0 1 3 384 0 1 3 385 0 1 3 386 0 1 3 387 0 1 3 388 0 1 3 389 0 1 3 390 0 1 3 391 0 1 3 392 0 1 3 393 0 1 3 394 0 1 3 395 0 1 3 396 0 1 3 397 0 1 3 398 0 1 3 399 0 1 3 400 0 1 3 401 0 1 3 402 0 1 3 403 0 1 3 404 0 1 3 405 0 1 3 406 0 1 3 407 0 1 3 408 0 1 3 409 0 1 3 410 0 1 3 411 0 1 3 412 0 1 3 413 0 1 3 414 0 1 3 415 0 1 3 416 0 1 3 417 0 1 3 418 0 1 3 419 0 1 3 420 0 1 3 421 0 1 3 422 0 1 3 423 0 1 3 424 0 1 3 425 0 1 3 426 0 1 3 427 0 1 3 428 0 1 3 429 0 1 3 430 0 1 3 431 0 1 3 432 0 1 3 433 0 1 3 434 1 2 3 435 1 2 3 436 1 2 3 437 1 2 3 438 1 2 3 439 1 2 3 440 1 2 3 441 1 2 3 442 1 2 3 443 1 2 3 444 1 2 3 445 1 2 3 446 1 2 3 447 1 2 3 448 1 2 3 449 1 2 3 450 1 2 3 451 1 2 3 452 1 2 3 453 1 2 3 454 1 2 3 455 1 2 3 456 1 2 3 457 1 2 3 458 1 2 3 459 1 2 3 460 1 2 3 461 1 2 3 462 1 2 3 463 1 2 3 464 1 2 3 465 1 2 3 466 1 2 3 467 1 2 3 468 1 2 3 469 1 2 3 470 1 2 3 471 1 2 3 472 1 2 3 473 1 2 3 474 1 2 3 475 1 2 3 476 0 3 3 477 0 3 3 478 0 3 3 479 0 3 3 480 0 3 3 481 0 3 3 482 0 3 3 483 0 3 3 484 0 3 3 485 0 3 3 486 0 3 3 487 0 3 3 488 0 3 3 489 0 3 3 490 0 3 3 491 0 3 3 492 0 3 3 493 0 3 3 494 0 3 3 495 0 3 3 496 0 3 3 497 0 3 3 498 0 3 3 499 0 3 3 500 0 3 3 501 0 3 3 502 0 3 3 503 0 3 3 504 0 3 3 505 0 3 3 506 0 3 3 507 0 3 3 508 0 3 3 509 0 3 3 510 0 3 3 511 0 3 3 512 0 3 3 513 0 3 3 514 0 3 3 515 0 3 3 516 0 3 3 517 0 3 3 518 0 3 3 519 0 3 3 520 0 3 3 521 0 3 3 522 0 3 3 523 0 3 3 524 0 3 3 525 0 3 3 526 0 3 3 527 0 3 3 528 0 3 3 529 0 3 3 530 0 3 3 531 0 3 3 532 0 3 3 533 0 3 3 534 0 3 3 535 0 3 3 536 0 3 3 537 0 3 3 538 0 3 3 539 0 3 3 540 0 3 3 541 0 3 3 542 0 3 3 543 0 3 3 544 0 3 3 545 0 3 3 546 0 1 2 183 0 1 2 184 0 1 2 185 0 1 2 186 0 1 2 187 0 1 2 188 0 1 2 189 0 1 2 190 0 1 2 191 0 1 2 192 0 1 2 193 0 1 2 194 0 1 2 195 0 1 2 196 0 1 2 197 0 1 2 198 0 1 2 199 0 1 2 200 0 1 2 201 0 1 2 202 0 1 2 203 0 1 2 204 0 1 2 205 0 1 2 206 0 1 2 207 0 1 2 208 0 1 2 209 0 1 2 210 0 1 2 211 0 1 2 212 0 1 2 213 0 1 2 214 0 1 2 215 0 1 2 216 0 1 2 217 0 1 2 218 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更多回答（1 个）

Walter Roberson
Walter Roberson 2023-10-7
sortrows specifying column 3 to sort on. The resulting matrix will group together all of the entries with the same trial-ID
  5 个评论
显示 3更早的评论
EK
EK 2023-10-8
column 3 logs Trials Ids. Trial 1==1, Trial 2==2, etc. I need to shaffle the trials.
Dyuman Joshi
Dyuman Joshi 2023-10-8
@EK, Bruno's question was that in what way randomizing column 3 matters? What is the idea/logic behind randomizing?

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