python - 从 Numpy 3D 数组到 2D 数组的转换

Question

具有以下 3D 数组 (9,9,9):

>>> np.arange(729).reshape((9,9,9))
array([[[  0   1   2   3   4   5   6   7   8]
        [  9  10  11  12  13  14  15  16  17]
        [ 18  19  20  21  22  23  24  25  26]
        [ 27  28  29  30  31  32  33  34  35]
        [ 36  37  38  39  40  41  42  43  44]
        [ 45  46  47  48  49  50  51  52  53]
        [ 54  55  56  57  58  59  60  61  62]
        [ 63  64  65  66  67  68  69  70  71]
        [ 72  73  74  75  76  77  78  79  80]]
      ...
       [[648 649 650 651 652 653 654 655 656]
        [657 658 659 660 661 662 663 664 665]
        [666 667 668 669 670 671 672 673 674]
        [675 676 677 678 679 680 681 682 683]
        [684 685 686 687 688 689 690 691 692]
        [693 694 695 696 697 698 699 700 701]
        [702 703 704 705 706 707 708 709 710]
        [711 712 713 714 715 716 717 718 719]
        [720 721 722 723 724 725 726 727 728]]])

我如何将它 reshape 为看起来像这个二维数组 (27,27):

Answer 1

您需要进行 6D 一次 reshape ，基本上将每个轴一分为二，然后转置以推回偶数轴(第 2、4 和 6)到最后并最终 reshape 回 2D -

a.reshape(-1,3,3,3,3,3).transpose(0,2,4,1,3,5).reshape(27,27)

sample 运行-

In [28]: a = np.arange(729).reshape((9,9,9))

In [29]: out = a.reshape(-1,3,3,3,3,3).transpose(0,2,4,1,3,5).reshape(27,27)

In [30]: out[0]
Out[30]: 
array([  0,   1,   2,   9,  10,  11,  18,  19,  20,  81,  82,  83,  90,
        91,  92,  99, 100, 101, 162, 163, 164, 171, 172, 173, 180, 181, 182])

In [31]: out[1]
Out[31]: 
array([  3,   4,   5,  12,  13,  14,  21,  22,  23,  84,  85,  86,  93,
        94,  95, 102, 103, 104, 165, 166, 167, 174, 175, 176, 183, 184, 185])

In [32]: out[2]
Out[32]: 
array([  6,   7,   8,  15,  16,  17,  24,  25,  26,  87,  88,  89,  96,
        97,  98, 105, 106, 107, 168, 169, 170, 177, 178, 179, 186, 187, 188])

In [33]: out[3]
Out[33]: 
array([ 27,  28,  29,  36,  37,  38,  45,  46,  47, 108, 109, 110, 117,
       118, 119, 126, 127, 128, 189, 190, 191, 198, 199, 200, 207, 208, 209])

In [34]: out[-1]
Out[34]: 
array([546, 547, 548, 555, 556, 557, 564, 565, 566, 627, 628, 629, 636,
       637, 638, 645, 646, 647, 708, 709, 710, 717, 718, 719, 726, 727, 728])

通用案例解决方案

BSZ = [3,3] # Block size
p,q = BSZ
out = a.reshape(p,q,p,q,p,q).transpose(0,2,4,1,3,5).reshape(p**3,q**3)