SPTENMAT: Remove from_data. Merge with __init__

pyttb/sptenmat.py

@@ -23,19 +23,8 @@ class sptenmat(object):
 
  __slots__ = ("tshape", "rdims", "cdims", "subs", "vals")
 
- def __init__(self):
- """
- Construct an empty :class:`pyttb.sptenmat`
- """
- self.tshape = ()
- self.rdims = np.array([])
- self.cdims = np.array([])
- self.subs = np.array([], ndmin=2, dtype=int)
- self.vals = np.array([], ndmin=2)
-
- @classmethod
- def from_data( # noqa: PLR0913
- cls,
+ def __init__( # noqa: PLR0913
+ self,
  subs: Optional[np.ndarray] = None,
  vals: Optional[np.ndarray] = None,
  rdims: Optional[np.ndarray] = None,
@@ -50,15 +39,45 @@ def from_data( # noqa: PLR0913
  Parameters
  ----------
  subs:
- Location of non-zero entries
+ Location of non-zero entries, in sptenmat.
  vals:
- Values for non-zero entries
+ Values for non-zero entries, in sptenmat.
  rdims:
- Mapping of row indices
+ Mapping of row indices.
  cdims:
- Mapping of column indices
+ Mapping of column indices.
  tshape:
- Shape of the original tensor
+ Shape of the original tensor.
+
+ Examples
+ --------
+ Create an empty :class:`pyttb.sptenmat`:
+
+ >>> S = ttb.sptenmat()
+ >>> S # doctest: +NORMALIZE_WHITESPACE
+ sptenmat corresponding to a sptensor of shape () with 0 nonzeros
+ rdims = [ ] (modes of sptensor corresponding to rows)
+ cdims = [ ] (modes of sptensor corresponding to columns)
+
+ Create a :class:`pyttb.sptenmat` from subscripts, values, and unwrapping
+ dimensions:
+
+ >>> subs = np.array([[1, 6], [1, 7]])
+ >>> vals = np.array([[6], [7]])
+ >>> tshape = (4, 4, 4)
+ >>> S = ttb.sptenmat(\
+ subs,\
+ vals,\
+ rdims=np.array([0]),\
+ cdims=np.array([1,2]),\
+ tshape=tshape\
+ )
+ >>> S # doctest: +NORMALIZE_WHITESPACE
+ sptenmat corresponding to a sptensor of shape (4, 4, 4) with 2 nonzeros
+ rdims = [ 0 ] (modes of sptensor corresponding to rows)
+ cdims = [ 1, 2 ] (modes of sptensor corresponding to columns)
+ [1, 6] = 6
+ [1, 7] = 7
  """
  if subs is None:
  subs = np.array([], ndmin=2, dtype=int)
@@ -106,13 +125,11 @@ def from_data( # noqa: PLR0913
  if newvals.size > 0:
  newvals = newvals[:, None]
 
- sptenmatInstance = cls()
- sptenmatInstance.tshape = tshape
- sptenmatInstance.rdims = rdims.copy().astype(int)
- sptenmatInstance.cdims = cdims.copy().astype(int)
- sptenmatInstance.subs = newsubs
- sptenmatInstance.vals = newvals
- return sptenmatInstance
+ self.tshape = tshape
+ self.rdims = rdims.copy().astype(int)
+ self.cdims = cdims.copy().astype(int)
+ self.subs = newsubs
+ self.vals = newvals
 
  @classmethod
  def from_tensor_type( # noqa: PLR0912
@@ -189,7 +206,7 @@ def from_tensor_type( # noqa: PLR0912
  cidx = tt_sub2ind(csize, source.subs[:, cdims])
  cidx = cidx.reshape((cidx.size, 1)).astype(int)
 
- return cls().from_data(
+ return cls(
  np.hstack([ridx, cidx], dtype=int),
  source.vals.copy(),
  rdims.astype(int),
@@ -231,7 +248,7 @@ def from_array(
  f"Expected sparse matrix or array but received: {type(array)}"
  )
  subs = np.vstack(array.nonzero()).transpose()
- return ttb.sptenmat.from_data(subs, vals, rdims, cdims, tshape)
+ return ttb.sptenmat(subs, vals, rdims, cdims, tshape)
 
  def copy(self) -> sptenmat:
  """
@@ -253,7 +270,7 @@ def copy(self) -> sptenmat:
  >>> ST1.to_sptensor().isequal(ST3.to_sptensor())
  False
  """
- return sptenmat().from_data(
+ return sptenmat(
  self.subs.copy(),
  self.vals.copy(),
  self.rdims.copy(),

tests/test_sptenmat.py

@@ -61,7 +61,7 @@ def sample_sptenmat():
  "cdims": cdims,
  "tshape": tshape,
  }
- sptenmatInstance = ttb.sptenmat.from_data(subs, vals, rdims, cdims, tshape)
+ sptenmatInstance = ttb.sptenmat(subs, vals, rdims, cdims, tshape)
  return data, sptenmatInstance
 
 
@@ -90,7 +90,7 @@ def test_sptenmat_initialization_from_data(sample_sptenmat):
  shape = (np.prod(np.array(tshape)[rdims]), np.prod(np.array(tshape)[cdims]))
 
  # Constructor from data: subs, vals, rdims, cdims, and tshape
- S = ttb.sptenmat.from_data(subs, vals, rdims, cdims, tshape)
+ S = ttb.sptenmat(subs, vals, rdims, cdims, tshape)
  np.testing.assert_array_equal(S.subs, subs)
  np.testing.assert_array_equal(S.vals, vals)
  np.testing.assert_array_equal(S.rdims, rdims)
@@ -99,7 +99,7 @@ def test_sptenmat_initialization_from_data(sample_sptenmat):
  np.testing.assert_array_equal(S.shape, shape)
 
  # Constructor from data: rdims, cdims, and tshape
- S = ttb.sptenmat.from_data(rdims=rdims, cdims=cdims, tshape=tshape)
+ S = ttb.sptenmat(rdims=rdims, cdims=cdims, tshape=tshape)
  np.testing.assert_array_equal(S.subs, np.array([]))
  np.testing.assert_array_equal(S.vals, np.array([]))
  np.testing.assert_array_equal(S.rdims, rdims)
@@ -110,7 +110,7 @@ def test_sptenmat_initialization_from_data(sample_sptenmat):
  # Constructor from data: rdims, and tshape
  all_rdims = np.arange(len(tshape))
  rdims_shape = (np.prod(tshape), 1)
- S = ttb.sptenmat.from_data(rdims=all_rdims, tshape=tshape)
+ S = ttb.sptenmat(rdims=all_rdims, tshape=tshape)
  np.testing.assert_array_equal(S.subs, np.array([]))
  np.testing.assert_array_equal(S.vals, np.array([]))
  np.testing.assert_array_equal(S.rdims, all_rdims)
@@ -120,7 +120,7 @@ def test_sptenmat_initialization_from_data(sample_sptenmat):
 
  # Constructor from data: cdims, and tshape
  cdims_shape = (1, np.prod(tshape))
- S = ttb.sptenmat.from_data(cdims=all_rdims, tshape=tshape)
+ S = ttb.sptenmat(cdims=all_rdims, tshape=tshape)
  np.testing.assert_array_equal(S.subs, np.array([]))
  np.testing.assert_array_equal(S.vals, np.array([]))
  np.testing.assert_array_equal(S.rdims, np.array([]))