Add copy constructor for tenmat.

pyttb/sptenmat.py

@@ -94,7 +94,9 @@ def from_data( # noqa: PLR0913
  newsubs, loc = np.unique(subs, axis=0, return_inverse=True)
  # Sum the corresponding values
  # Squeeze to convert from column vector to row vector
- newvals = accumarray(loc, np.squeeze(vals), size=newsubs.shape[0], func=sum)
+ newvals = accumarray(
+ loc, np.squeeze(vals, axis=1), size=newsubs.shape[0], func=sum
+ )
 
  # Find the nonzero indices of the new values
  nzidx = np.nonzero(newvals)
@@ -115,27 +117,16 @@ def from_data( # noqa: PLR0913
  @classmethod
  def from_tensor_type( # noqa: PLR0912
  cls,
- source: Union[ttb.sptensor, ttb.sptenmat],
+ source: Union[ttb.sptensor],
  rdims: Optional[np.ndarray] = None,
  cdims: Optional[np.ndarray] = None,
  cdims_cyclic: Optional[
  Union[Literal["fc"], Literal["bc"], Literal["t"]]
  ] = None,
  ):
- valid_sources = (sptenmat, ttb.sptensor)
- assert isinstance(source, valid_sources), (
- "Can only generate sptenmat from "
- f"{[src.__name__ for src in valid_sources]} but received {type(source)}."
+ assert isinstance(source, ttb.sptensor), (
+ "Can only generate sptenmat from " f"sptensor but received {type(source)}."
  )
- # Copy Constructor
- if isinstance(source, sptenmat):
- return cls().from_data(
- source.subs.copy(),
- source.vals.copy(),
- source.rdims.copy(),
- source.cdims.copy(),
- source.tshape,
- )
 
  if isinstance(source, ttb.sptensor):
  n = source.ndims
@@ -242,6 +233,37 @@ def from_array(
  subs = np.vstack(array.nonzero()).transpose()
  return ttb.sptenmat.from_data(subs, vals, rdims, cdims, tshape)
 
+ def copy(self) -> sptenmat:
+ """
+ Return a deep copy of the :class:`pyttb.sptenmat`.
+
+ Examples
+ --------
+ Create a :class:`pyttb.sptenmat` (ST1) and make a deep copy. Verify
+ the deep copy (ST3) is not just a reference (like ST2) to the original.
+
+ >>> S1 = ttb.sptensor(shape=(2,2))
+ >>> S1[0,0] = 1
+ >>> ST1 = ttb.sptenmat.from_tensor_type(S1, np.array([0]))
+ >>> ST2 = ST1
+ >>> ST3 = ST1.copy()
+ >>> ST1[0,0] = 3
+ >>> ST1.to_sptensor().isequal(ST2.to_sptensor())
+ True
+ >>> ST1.to_sptensor().isequal(ST3.to_sptensor())
+ False
+ """
+ return sptenmat().from_data(
+ self.subs.copy(),
+ self.vals.copy(),
+ self.rdims.copy(),
+ self.cdims.copy(),
+ self.tshape,
+ )
+
+ def __deepcopy__(self, memo):
+ return self.copy()
+
  def to_sptensor(self) -> ttb.sptensor:
  """
  Contruct a :class:`pyttb.sptensor` from `:class:pyttb.sptenmat`
@@ -312,13 +334,13 @@ def __pos__(self):
  """
  Unary plus operator (+).
  """
- return self.from_tensor_type(self)
+ return self.copy()
 
  def __neg__(self):
  """
  Unary minus operator (-).
  """
- result = self.from_tensor_type(self)
+ result = self.copy()
  result.vals *= -1
  return result
 

pyttb/tenmat.py

@@ -131,16 +131,6 @@ def from_tensor_type( # noqa: PLR0912
  -------
  Constructed tenmat
  """
- # Case 0b: Copy Constructor
- if isinstance(source, tenmat):
- # Create tenmat
- tenmatInstance = cls()
- tenmatInstance.tshape = source.tshape
- tenmatInstance.rindices = source.rindices.copy()
- tenmatInstance.cindices = source.cindices.copy()
- tenmatInstance.data = source.data.copy()
- return tenmatInstance
-
  # Case III: Convert a tensor to a tenmat
  if isinstance(source, ttb.tensor):
  n = source.ndims
@@ -210,9 +200,39 @@ def from_tensor_type( # noqa: PLR0912
  tenmatInstance.data = data.copy()
  return tenmatInstance
  raise ValueError(
- f"Can only create tenmat from tensor or tenmat but recieved {type(source)}"
+ f"Can only create tenmat from tensor but recieved {type(source)}"
  )
 
+ def copy(self) -> tenmat:
+ """
+ Return a deep copy of the :class:`pyttb.tenmat`.
+
+ Examples
+ --------
+ Create a :class:`pyttb.tenmat` (TM1) and make a deep copy. Verify
+ the deep copy (TM3) is not just a reference (like TM2) to the original.
+
+ >>> T1 = ttb.tensor(np.ones((3,2)))
+ >>> TM1 = ttb.tenmat.from_tensor_type(T1, np.array([0]))
+ >>> TM2 = TM1
+ >>> TM3 = TM1.copy()
+ >>> TM1[0,0] = 3
+ >>> TM1[0,0] == TM2[0,0]
+ True
+ >>> TM1[0,0] == TM3[0,0]
+ False
+ """
+ # Create tenmat
+ tenmatInstance = tenmat()
+ tenmatInstance.tshape = self.tshape
+ tenmatInstance.rindices = self.rindices.copy()
+ tenmatInstance.cindices = self.cindices.copy()
+ tenmatInstance.data = self.data.copy()
+ return tenmatInstance
+
+ def __deepcopy__(self, memo):
+ return self.copy()
+
  def to_tensor(self) -> ttb.tensor:
  """Return copy of tenmat data as a tensor"""
  # RESHAPE TENSOR-AS-MATRIX
@@ -309,7 +329,7 @@ def __mul__(self, other):
  """
  # One argument is a scalar
  if np.isscalar(other):
- Z = ttb.tenmat.from_tensor_type(self)
+ Z = self.copy()
  Z.data = Z.data * other
  return Z
  if isinstance(other, tenmat):
@@ -370,15 +390,15 @@ def __add__(self, other):
 
  # One argument is a scalar
  if np.isscalar(other):
- Z = ttb.tenmat.from_tensor_type(self)
+ Z = self.copy()
  Z.data = Z.data + other
  return Z
  if isinstance(other, tenmat):
  # Check that data shapes agree
  if not self.shape == other.shape:
  assert False, "tenmat shape mismatch."
 
- Z = ttb.tenmat.from_tensor_type(self)
+ Z = self.copy()
  Z.data = Z.data + other.data
  return Z
  assert False, "tenmat addition only valid with scalar or tenmat objects."
@@ -412,15 +432,15 @@ def __sub__(self, other):
 
  # One argument is a scalar
  if np.isscalar(other):
- Z = ttb.tenmat.from_tensor_type(self)
+ Z = self.copy()
  Z.data = Z.data - other
  return Z
  if isinstance(other, tenmat):
  # Check that data shapes agree
  if not self.shape == other.shape:
  assert False, "tenmat shape mismatch."
 
- Z = ttb.tenmat.from_tensor_type(self)
+ Z = self.copy()
  Z.data = Z.data - other.data
  return Z
  assert False, "tenmat subtraction only valid with scalar or tenmat objects."
@@ -440,15 +460,15 @@ def __rsub__(self, other):
 
  # One argument is a scalar
  if np.isscalar(other):
- Z = ttb.tenmat.from_tensor_type(self)
+ Z = self.copy()
  Z.data = other - Z.data
  return Z
  if isinstance(other, tenmat):
  # Check that data shapes agree
  if not self.shape == other.shape:
  assert False, "tenmat shape mismatch."
 
- Z = ttb.tenmat.from_tensor_type(self)
+ Z = self.copy()
  Z.data = other.data - Z.data
  return Z
  assert False, "tenmat subtraction only valid with scalar or tenmat objects."
@@ -463,7 +483,7 @@ def __pos__(self):
  copy of tenmat
  """
 
- T = ttb.tenmat.from_tensor_type(self)
+ T = self.copy()
 
  return T
 
@@ -477,7 +497,7 @@ def __neg__(self):
  copy of tenmat
  """
 
- T = ttb.tenmat.from_tensor_type(self)
+ T = self.copy()
  T.data = -1 * T.data
 
  return T

tests/test_sptenmat.py

@@ -2,6 +2,8 @@
 # LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the
 # U.S. Government retains certain rights in this software.
 
+from copy import deepcopy
+
 import numpy as np
 import pytest
 from scipy import sparse
@@ -134,7 +136,15 @@ def test_sptenmat_initialization_from_tensor_type(
  params, sptenmatInstance = sample_sptenmat
  params3, sptensorInstance = sample_sptensor_3way
  # Copy constructor
- S = ttb.sptenmat.from_tensor_type(sptenmatInstance)
+ S = sptenmatInstance.copy()
+ assert S is not sptenmatInstance
+ np.testing.assert_array_equal(S.subs, sptenmatInstance.subs)
+ np.testing.assert_array_equal(S.vals, sptenmatInstance.vals)
+ np.testing.assert_array_equal(S.rdims, sptenmatInstance.rdims)
+ np.testing.assert_array_equal(S.cdims, sptenmatInstance.cdims)
+ np.testing.assert_array_equal(S.tshape, sptenmatInstance.tshape)
+
+ S = deepcopy(sptenmatInstance)
  assert S is not sptenmatInstance
  np.testing.assert_array_equal(S.subs, sptenmatInstance.subs)
  np.testing.assert_array_equal(S.vals, sptenmatInstance.vals)

tests/test_tenmat.py

@@ -2,6 +2,8 @@
 # LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the
 # U.S. Government retains certain rights in this software.
 
+from copy import deepcopy
+
 import numpy as np
 import pytest
 
@@ -231,7 +233,14 @@ def test_tenmat_initialization_from_tensor_type(
  data = params["data"]
 
  # Copy Constructor
- tenmatCopy = ttb.tenmat.from_tensor_type(tenmatInstance)
+ tenmatCopy = tenmatInstance.copy()
+ assert (tenmatCopy.data == data).all()
+ assert (tenmatCopy.rindices == rdims).all()
+ assert (tenmatCopy.cindices == cdims).all()
+ assert tenmatCopy.shape == data.shape
+ assert tenmatCopy.tshape == tshape
+
+ tenmatCopy = deepcopy(tenmatInstance)
  assert (tenmatCopy.data == data).all()
  assert (tenmatCopy.rindices == rdims).all()
  assert (tenmatCopy.cindices == cdims).all()
@@ -427,7 +436,7 @@ def test_tenmat__setitem__():
  tenmatInstance = ttb.tenmat.from_tensor_type(tensorInstance, rdims=np.array([0, 1]))
 
  # single element -> scalar
- tenmatInstance2 = ttb.tenmat.from_tensor_type(tenmatInstance)
+ tenmatInstance2 = tenmatInstance.copy()
  for i in range(4):
  for j in range(4):
  tenmatInstance2[i, j] = i * 4 + j + 10