【三维张量的展开和折叠 python】

测试张量，模态展开和折叠函数

tensor = np.array([[[0, 3, 6, 9],
                    [1, 4, 7, 10],
                    [2, 5, 8, 11]],

                   [[12, 15, 18, 21],
                    [13, 16, 19, 22],
                    [14, 17, 20, 23]]])

def mode_k_folding(mat, k, dim):
    # Folding a matrix into a tensor
    # dim = (n1,n2,n3)
    # k=1,2,3
    dim0 = list(dim[:k-1]) + list(dim[k:])
    dim0.append(dim[k-1])
    mat = mat.transpose()  # Transpose the matrix
    ten = np.reshape(mat, dim0, order='F')
    ten = np.moveaxis(ten, -1, k-1)
    return ten

def mode_k_unfolding(tensor, mode):
    """
    tensor: 输入的张量
    mode: 展开的模态 1,2,3
    测试完成！
    """
    mode -= 1
    return np.reshape(np.moveaxis(tensor, mode, 0), (tensor.shape[mode], -1), order = 'F')

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测试结果

a = TQB.get_tensor()
print(a)
# print(a[0,:,:])
b = TQB.mode_k_unfolding(a, 3)
print(b)
c = TQB.mode_k_folding(b, 3, a.shape)
print(c)
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[[[ 1 13]
  [ 4 16]
  [ 7 19]
  [10 22]]

 [[ 2 14]
  [ 5 17]
  [ 8 20]
  [11 23]]

 [[ 3 15]
  [ 6 18]
  [ 9 21]
  [12 24]]]
[[ 1  2  3  4  5  6  7  8  9 10 11 12]
 [13 14 15 16 17 18 19 20 21 22 23 24]]
[[[ 1 13]
  [ 4 16]
  [ 7 19]
  [10 22]]

 [[ 2 14]
  [ 5 17]
  [ 8 20]
  [11 23]]

 [[ 3 15]
  [ 6 18]
  [ 9 21]
  [12 24]]]
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