unstack

t3toolbox.backend.stacking.unstack(S, axes)

def unstack(
        S,                              # tree of arrays (or single array) carrying stack axes to split out
        axes: typ.Sequence[int],        # len=num stacking levels; array axes to unstack into tree levels
):

Unstack nested sequence of arrays along specificed array axes.

Examples

>>> import numpy as np
>>> import t3toolbox.backend.stacking as stacking
>>> A = np.random.randn(4, 2,3, 5,6)
>>> B = np.random.randn(7, 2,3, 8)
>>> C = np.random.randn(9, 2,3)
>>> S = ((A, B), C)
>>> T = stacking.unstack(S, axes=(1,2))
>>> ii, jj = 1, 2
>>> ((Aij, Bij), Cij) = T[ii][jj]
>>> print(np.linalg.norm(Aij - A[:,ii,jj,:,:]))
0.0
>>> print(np.linalg.norm(Bij - B[:,ii,jj,:]))
0.0
>>> print(np.linalg.norm(Cij - C[:,ii,jj]))
0.0

Stack then unstack:

>>> import numpy as np
>>> import t3toolbox.backend.stacking as stacking
>>> import t3toolbox.corewise as cw
>>> randn = np.random.randn
>>> a00, a01, a10, a11 = randn(3,2), randn(3,2), randn(3,2), randn(3,2)
>>> b00, b01, b10, b11 = randn(4,5), randn(4,5), randn(4,5), randn(4,5)
>>> c00, c01, c10, c11 = randn(7), randn(7), randn(7), randn(7)
>>> T00 = (a00, (b00, c00))
>>> T01 = (a01, (b01, c01))
>>> T10 = (a10, (b10, c10))
>>> T11 = (a11, (b11, c11))
>>> T = ((T00, T01), (T10, T11))
>>> S = stacking.stack(T, axes=(0,2))
>>> T2 = stacking.unstack(S, axes=(0,2))
>>> print(cw.corewise_norm(cw.corewise_sub(T, T2)))
0.0

Unstack then stack:

>>> import numpy as np
>>> import t3toolbox.backend.stacking as stacking
>>> A = np.random.randn(4, 2,3, 5,6)
>>> B = np.random.randn(7, 2,3, 8)
>>> C = np.random.randn(9, 2,3)
>>> S = ((A, B), C)
>>> T = stacking.unstack(S, axes=(1,2))
>>> ii, jj = 1, 2
>>> S2 = stacking.stack(T, axes=(1,2))
>>> ((A2, B2), C2) = S2
>>> print(np.linalg.norm(A - A2))
0.0
>>> print(np.linalg.norm(B - B2))
0.0
>>> print(np.linalg.norm(C - C2))
0.0

When there are no axes to unstack:

>>> import numpy as np
>>> import t3toolbox.backend.stacking as stacking
>>> A = np.random.randn(4, 5, 6)
>>> B = np.random.randn(7, 8)
>>> C = np.random.randn(9)
>>> S = ((A, B), C)
>>> T = stacking.unstack(S, axes=())
>>> ((A2, B2), C2) = T
>>> print(np.linalg.norm(A2 - A))
0.0
>>> print(np.linalg.norm(B2 - B))
0.0
>>> print(np.linalg.norm(C2 - C))
0.0

When the tree is a single object:

>>> import numpy as np
>>> import t3toolbox.backend.stacking as stacking
>>> A = np.random.randn(4, 2,3, 5,6)
>>> T = stacking.unstack(A, axes=(1,2))
>>> ii, jj = 1, 2
>>> Aij = T[ii][jj]
>>> print(np.linalg.norm(Aij - A[:, ii, jj, :]))
0.0

When the tree is a single object and there are no objects to unstack

>>> import numpy as np
>>> import t3toolbox.backend.stacking as stacking
>>> A = np.random.randn(4, 5,6)
>>> T = stacking.unstack(A, axes=())
>>> print(np.linalg.norm(A - T))
0.0

Parameters:

axes (t3toolbox.backend.common.typ.Sequence[int])