For Consideration

docs/source/gcp/fg.rst

@@ -1,7 +1,7 @@
-pyttb.gcp.fg
-====================
+pyttb.decompositions.cp.gcp.fg
+==============================
 
-.. automodule:: pyttb.gcp.fg
+.. automodule:: pyttb.decompositions.cp.gcp.fg
     :members:
     :undoc-members:
     :show-inheritance:

docs/source/gcp/fg_est.rst

@@ -1,7 +1,7 @@
-pyttb.gcp.fg_est
-====================
+pyttb.decompositions.cp.gcp.fg_est
+==================================
 
-.. automodule:: pyttb.gcp.fg_est
+.. automodule:: pyttb.decompositions.cp.gcp.fg_est
     :members:
     :undoc-members:
     :show-inheritance:

docs/source/gcp/fg_setup.rst

@@ -1,7 +1,7 @@
-pyttb.gcp.fg_setup
-====================
+pyttb.decompositions.cp.gcp.fg_setup
+====================================
 
-.. automodule:: pyttb.gcp.fg_setup
+.. automodule:: pyttb.decompositions.cp.gcp.fg_setup
     :members:
     :undoc-members:
     :show-inheritance:

docs/source/gcp/handles.rst

@@ -1,7 +1,7 @@
-pyttb.gcp.handles
-====================
+pyttb.decompositions.cp.gcp.handles
+===================================
 
-.. automodule:: pyttb.gcp.handles
+.. automodule:: pyttb.decompositions.cp.gcp.handles
     :members:
     :undoc-members:
     :show-inheritance:

docs/source/gcp/optimizers.rst

@@ -1,7 +1,7 @@
-pyttb.gcp.optimizers
-====================
+pyttb.decompositions.cp.gcp.optimizers
+======================================
 
-.. automodule:: pyttb.gcp.optimizers
+.. automodule:: pyttb.decompositions.cp.gcp.optimizers
     :members:
     :undoc-members:
     :special-members: __init__

docs/source/gcp/samplers.rst

@@ -1,7 +1,7 @@
-pyttb.gcp.samplers
-====================
+pyttb.decompositions.cp.gcp.samplers
+====================================
 
-.. automodule:: pyttb.gcp.samplers
+.. automodule:: pyttb.decompositions.cp.gcp.samplers
     :members:
     :undoc-members:
     :special-members: __init__

docs/source/tutorial/algorithm_gcp_opt.ipynb

@@ -163,10 +163,10 @@
     "import numpy as np\n",
     "\n",
     "import pyttb as ttb\n",
-    "from pyttb.gcp.fg_setup import function_type, setup\n",
-    "from pyttb.gcp.handles import Objectives\n",
-    "from pyttb.gcp.optimizers import LBFGSB, SGD, Adagrad, Adam\n",
-    "from pyttb.gcp.samplers import GCPSampler"
+    "from pyttb.decompositions.cp.gcp.fg_setup import function_type, setup\n",
+    "from pyttb.decompositions.cp.gcp.handles import Objectives\n",
+    "from pyttb.decompositions.cp.gcp.optimizers import LBFGSB, SGD, Adagrad, Adam\n",
+    "from pyttb.decompositions.cp.gcp.samplers import GCPSampler"
    ]
   },
   {

pyttb/__init__.py

@@ -11,22 +11,23 @@
 
 import warnings
 
-from pyttb.cp_als import cp_als
-from pyttb.cp_apr import cp_apr
+from pyttb.decompositions.cp import cp_als, cp_apr, gcp_opt
+from pyttb.decompositions.tucker import hosvd, tucker_als
 from pyttb.export_data import export_data
-from pyttb.gcp_opt import gcp_opt
-from pyttb.hosvd import hosvd
 from pyttb.import_data import import_data
 from pyttb.khatrirao import khatrirao
-from pyttb.ktensor import ktensor
 from pyttb.matlab import matlab_support
-from pyttb.sptenmat import sptenmat
-from pyttb.sptensor import sptendiag, sptenrand, sptensor
-from pyttb.sumtensor import sumtensor
-from pyttb.tenmat import tenmat
-from pyttb.tensor import tendiag, teneye, tenones, tenrand, tensor, tenzeros
-from pyttb.ttensor import ttensor
-from pyttb.tucker_als import tucker_als
+from pyttb.tensors import (
+    ktensor,
+    sptenmat,
+    sptensor,
+    sumtensor,
+    tenmat,
+    tensor,
+    ttensor,
+)
+from pyttb.tensors.dense import tendiag, teneye, tenones, tenrand, tenzeros
+from pyttb.tensors.sparse import sptendiag, sptenrand
 
 
 def ignore_warnings(ignore=True):

pyttb/decompositions/__init__.py

@@ -0,0 +1 @@
+"""Tensor Decompositions."""

pyttb/decompositions/cp/__init__.py

@@ -0,0 +1,13 @@
+"""CP Decompositions."""
+
+from __future__ import annotations
+
+from .als import cp_als
+from .apr import cp_apr
+from .general import gcp_opt
+
+__all__ = [
+    "cp_als",
+    "cp_apr",
+    "gcp_opt",
+]

pyttb/cp_als.py → pyttb/decompositions/cp/als.py

@@ -12,19 +12,20 @@
 
 import pyttb as ttb
 from pyttb.pyttb_utils import OneDArray, parse_one_d
+from pyttb.tensors import ktensor, sptensor, tensor, ttensor
 
 
 def cp_als(  # noqa: PLR0912,PLR0913,PLR0915
-    input_tensor: ttb.tensor | ttb.sptensor | ttb.ttensor | ttb.sumtensor,
+    input_tensor: tensor | sptensor | ttensor | ttb.sumtensor,
     rank: int,
     stoptol: float = 1e-4,
     maxiters: int = 1000,
     dimorder: OneDArray | None = None,
     optdims: OneDArray | None = None,
-    init: Literal["random"] | Literal["nvecs"] | ttb.ktensor = "random",
+    init: Literal["random"] | Literal["nvecs"] | ktensor = "random",
     printitn: int = 1,
     fixsigns: bool = True,
-) -> tuple[ttb.ktensor, ttb.ktensor, dict]:
+) -> tuple[ktensor, ktensor, dict]:
     """Compute CP decomposition with alternating least squares.
 
     Parameters
@@ -150,7 +151,7 @@ def cp_als(  # noqa: PLR0912,PLR0913,PLR0915
     assert rank > 0, "Number of components requested must be positive"
 
     # Set up and error checking on initial guess
-    if isinstance(init, ttb.ktensor):
+    if isinstance(init, ktensor):
         # User provided an initial ktensor; validate it
         assert init.ndims == N, f"Initial guess does not have {N} modes"
         assert init.ncomponents == rank, (
@@ -165,15 +166,15 @@ def cp_als(  # noqa: PLR0912,PLR0913,PLR0915
             factor_matrices.append(
                 np.random.uniform(0, 1, (input_tensor.shape[n], rank))
             )
-        init = ttb.ktensor(factor_matrices)
+        init = ktensor(factor_matrices)
     elif isinstance(init, str) and init.lower() == "nvecs":
         assert not isinstance(input_tensor, ttb.sumtensor), (
             "Sumtensor doesn't support nvecs"
         )
         factor_matrices = []
         for n in range(N):
             factor_matrices.append(input_tensor.nvecs(n, rank))
-        init = ttb.ktensor(factor_matrices)
+        init = ktensor(factor_matrices)
     else:
         assert False, "The selected initialization method is not supported"
 
@@ -234,7 +235,7 @@ def cp_als(  # noqa: PLR0912,PLR0913,PLR0915
             U[n] = Unew
             UtU[:, :, n] = U[n].T @ U[n]
 
-        M = ttb.ktensor(U, weights)
+        M = ktensor(U, weights)
 
         # This is equivalent to innerprod(X,P).
         iprod = np.sum(

pyttb/gcp/fg.py → pyttb/decompositions/cp/gcp/fg.py

@@ -13,7 +13,7 @@
 import pyttb as ttb
 
 if TYPE_CHECKING:
-    from pyttb.gcp.fg_setup import function_type
+    from pyttb.decompositions.cp.gcp.fg_setup import function_type
 
 
 @overload

pyttb/gcp/fg_est.py → pyttb/decompositions/cp/gcp/fg_est.py

@@ -14,7 +14,7 @@
 
 if TYPE_CHECKING:
     import pyttb as ttb
-    from pyttb.gcp.fg_setup import function_type
+    from pyttb.decompositions.cp.gcp.fg_setup import function_type
 
 
 @overload

pyttb/gcp/fg_setup.py → pyttb/decompositions/cp/gcp/fg_setup.py

@@ -7,21 +7,24 @@
 from __future__ import annotations
 
 from functools import partial
-from typing import Callable
+from typing import TYPE_CHECKING, Callable
 
 import numpy as np
 
-import pyttb as ttb
-from pyttb.gcp import handles
-from pyttb.gcp.handles import Objectives
+from pyttb.decompositions.cp.gcp import handles
+from pyttb.decompositions.cp.gcp.handles import Objectives
+from pyttb.tensors.sparse import sptensor
+
+if TYPE_CHECKING:
+    from pyttb.tensors.dense import tensor
 
 function_type = Callable[[np.ndarray, np.ndarray], np.ndarray]
 fg_return = tuple[function_type, function_type, float]
 
 
 def setup(  # noqa: PLR0912,PLR0915
     objective: Objectives,
-    data: ttb.tensor | ttb.sptensor | None = None,
+    data: tensor | sptensor | None = None,
     additional_parameter: float | None = None,
 ) -> fg_return:
     """Collect the function and gradient handles for GCP.
@@ -121,23 +124,23 @@ def setup(  # noqa: PLR0912,PLR0915
     return function_handle, gradient_handle, lower_bound
 
 
-def valid_nonneg(data: ttb.tensor | ttb.sptensor) -> bool:
+def valid_nonneg(data: tensor | sptensor) -> bool:
     """Check if provided data is valid non-negative tensor."""
-    if isinstance(data, ttb.sptensor):
+    if isinstance(data, sptensor):
         return bool(np.all(data.vals > 0))
     return bool(np.all(data.data > 0))
 
 
-def valid_binary(data: ttb.tensor | ttb.sptensor) -> bool:
+def valid_binary(data: tensor | sptensor) -> bool:
     """Check if provided data is valid binary tensor."""
-    if isinstance(data, ttb.sptensor):
+    if isinstance(data, sptensor):
         return bool(np.all(data.vals == 1))
     return bool(np.all(np.isin(np.unique(data.data), [0, 1])))
 
 
-def valid_natural(data: ttb.tensor | ttb.sptensor) -> bool:
+def valid_natural(data: tensor | sptensor) -> bool:
     """Check if provided data is valid natural number tensor."""
-    if isinstance(data, ttb.sptensor):
+    if isinstance(data, sptensor):
         vals = data.vals
     else:
         vals = data.data

pyttb/gcp/optimizers.py → pyttb/decompositions/cp/gcp/optimizers.py

@@ -16,12 +16,12 @@
 from scipy.optimize import fmin_l_bfgs_b
 
 import pyttb as ttb
-from pyttb.gcp.fg import evaluate
-from pyttb.gcp.fg_est import estimate
-from pyttb.gcp.samplers import GCPSampler
+from pyttb.decompositions.cp.gcp.fg import evaluate
+from pyttb.decompositions.cp.gcp.fg_est import estimate
+from pyttb.decompositions.cp.gcp.samplers import GCPSampler
 
 if TYPE_CHECKING:
-    from pyttb.gcp.fg_setup import function_type
+    from pyttb.decompositions.cp.gcp.fg_setup import function_type
 
 
 class StochasticSolver(ABC):

pyttb/gcp/samplers.py → pyttb/decompositions/cp/gcp/samplers.py

@@ -17,8 +17,8 @@
 
 import pyttb as ttb
 from pyttb.pyttb_utils import tt_sub2ind
-from pyttb.sptensor import sptensor
-from pyttb.tensor import tensor
+from pyttb.tensors.dense import tensor
+from pyttb.tensors.sparse import sptensor
 
 sample_type = tuple[np.ndarray, np.ndarray, np.ndarray]
 sampler_type = Callable[[Union[tensor, sptensor]], sample_type]

pyttb/gcp_opt.py → pyttb/decompositions/cp/general.py

@@ -15,12 +15,12 @@
 import numpy as np
 
 import pyttb as ttb
-from pyttb.gcp.fg_setup import function_type, setup
-from pyttb.gcp.handles import Objectives
-from pyttb.gcp.optimizers import LBFGSB, StochasticSolver
+from pyttb.decompositions.cp.gcp.fg_setup import function_type, setup
+from pyttb.decompositions.cp.gcp.handles import Objectives
+from pyttb.decompositions.cp.gcp.optimizers import LBFGSB, StochasticSolver
 
 if TYPE_CHECKING:
-    from pyttb.gcp.samplers import GCPSampler
+    from pyttb.decompositions.cp.gcp.samplers import GCPSampler
 
 
 def gcp_opt(  # noqa:  PLR0912,PLR0913

pyttb/decompositions/tucker/__init__.py

@@ -0,0 +1,11 @@
+"""Tucker Decompositions."""
+
+from __future__ import annotations
+
+from .als import tucker_als
+from .svd import hosvd
+
+__all__ = [
+    "hosvd",
+    "tucker_als",
+]

pyttb/tucker_als.py → pyttb/decompositions/tucker/als.py

@@ -12,7 +12,7 @@
 import numpy as np
 
 from pyttb.pyttb_utils import OneDArray, parse_one_d
-from pyttb.ttensor import ttensor
+from pyttb.tensors.tucker import ttensor
 
 if TYPE_CHECKING:
     import pyttb as ttb

pyttb/matlab/matlab_support.py

@@ -9,7 +9,7 @@
 
 import numpy as np
 
-from pyttb.tensor import tensor
+from pyttb.tensors.dense import tensor
 
 from .matlab_utilities import _matlab_array_str
 

pyttb/tensors/__init__.py

@@ -0,0 +1,21 @@
+"""Tensor Classes."""
+
+from __future__ import annotations
+
+from .dense import tensor
+from .kruskal import ktensor
+from .matricized import tenmat
+from .sparse import sptensor
+from .sparse_matricized import sptenmat
+from .sum import sumtensor
+from .tucker import ttensor
+
+__all__ = [
+    "ktensor",
+    "sptenmat",
+    "sptensor",
+    "sumtensor",
+    "tenmat",
+    "tensor",
+    "ttensor",
+]

tests/gcp/test_fg.py

@@ -8,9 +8,9 @@
 import pytest
 
 import pyttb as ttb
-from pyttb.gcp import fg_setup
-from pyttb.gcp.fg import evaluate
-from pyttb.gcp.handles import Objectives
+from pyttb.decompositions.cp.gcp import fg_setup
+from pyttb.decompositions.cp.gcp.fg import evaluate
+from pyttb.decompositions.cp.gcp.handles import Objectives
 
 
 def test_evaluate():

tests/gcp/test_fg_est.py

@@ -8,7 +8,7 @@
 import pytest
 
 import pyttb as ttb
-from pyttb.gcp.fg_est import estimate, estimate_helper
+from pyttb.decompositions.cp.gcp.fg_est import estimate, estimate_helper
 
 
 def test_estimate_helper():