ENH: transition to SciPy sparse arrays from matrices

Author: lucascolley

docs/construct.md

@@ -229,9 +229,9 @@ methods:
 * [`sparse.COO.todense`][]: Converts to a [`numpy.ndarray`][] unconditionally.
 * [`sparse.COO.maybe_densify`][]: Converts to a [`numpy.ndarray`][] based on
    certain constraints.
-* [`sparse.COO.to_scipy_sparse`][]: Converts to a [`scipy.sparse.coo_matrix`][] if
+* [`sparse.COO.to_scipy_sparse`][]: Converts to a [`scipy.sparse.coo_array`][] if
    the array is two dimensional.
-* [`sparse.COO.tocsr`][]: Converts to a [`scipy.sparse.csr_matrix`][] if
+* [`sparse.COO.tocsr`][]: Converts to a [`scipy.sparse.csr_array`][] if
    the array is two dimensional.
-* [`sparse.COO.tocsc`][]: Converts to a [`scipy.sparse.csc_matrix`][] if
+* [`sparse.COO.tocsc`][]: Converts to a [`scipy.sparse.csc_array`][] if
    the array is two dimensional.

sparse/numba_backend/_compressed/compressed.py

@@ -239,7 +239,7 @@ def dtype(self):
         See Also
         --------
         - [`numpy.ndarray.dtype`][] : Numpy equivalent property.
-        - [`scipy.sparse.csr_matrix.dtype`][] : Scipy equivalent property.
+        - [`scipy.sparse.csr_array.dtype`][] : Scipy equivalent property.
         """
         return self.data.dtype
 
@@ -258,7 +258,7 @@ def nnz(self):
         - [`sparse.COO.nnz`][] : Equivalent [`sparse.COO`][] array property.
         - [`sparse.DOK.nnz`][] : Equivalent [`sparse.DOK`][] array property.
         - [`numpy.count_nonzero`][] : A similar Numpy function.
-        - [`scipy.sparse.coo_matrix.nnz`][] : The Scipy equivalent property.
+        - [`scipy.sparse.coo_array.nnz`][] : The Scipy equivalent property.
         """
         return self.data.shape[0]
 
@@ -388,7 +388,7 @@ def _reduce_return(self, data, arr_attrs, result_fill_value):
     def change_compressed_axes(self, new_compressed_axes):
         """
         Returns a new array with specified compressed axes. This operation is similar to converting
-        a scipy.sparse.csc_matrix to a scipy.sparse.csr_matrix.
+        a scipy.sparse.csc_array to a scipy.sparse.csr_array.
 
         Returns
         -------
@@ -474,7 +474,7 @@ def todense(self):
         --------
         - [`sparse.DOK.todense`][] : Equivalent [`sparse.DOK`][] array method.
         - [`sparse.COO.todense`][] : Equivalent [`sparse.COO`][] array method.
-        - [`scipy.sparse.coo_matrix.todense`][] : Equivalent Scipy method.
+        - [`scipy.sparse.coo_array.todense`][] : Equivalent Scipy method.
 
         """
         if self.compressed_axes is None:
@@ -494,7 +494,7 @@ def todok(self):
 
     def to_scipy_sparse(self, accept_fv=None):
         """
-        Converts this [`sparse.GCXS`][] object into a [`scipy.sparse.csr_matrix`][] or [`scipy.sparse.csc_matrix`][].
+        Converts this [`sparse.GCXS`][] object into a [`scipy.sparse.csr_array`][] or [`scipy.sparse.csc_array`][].
 
         Parameters
         ----------
@@ -503,7 +503,7 @@ def to_scipy_sparse(self, accept_fv=None):
 
         Returns
         -------
-        scipy.sparse.csr_matrix or scipy.sparse.csc_matrix
+        scipy.sparse.csr_array or scipy.sparse.csc_array
             The converted Scipy sparse matrix.
 
         Raises
@@ -520,9 +520,9 @@ def to_scipy_sparse(self, accept_fv=None):
             raise ValueError("Can only convert a 2-dimensional array to a Scipy sparse matrix.")
 
         if 0 in self.compressed_axes:
-            return scipy.sparse.csr_matrix((self.data, self.indices, self.indptr), shape=self.shape)
+            return scipy.sparse.csr_array((self.data, self.indices, self.indptr), shape=self.shape)
 
-        return scipy.sparse.csc_matrix((self.data, self.indices, self.indptr), shape=self.shape)
+        return scipy.sparse.csc_array((self.data, self.indices, self.indptr), shape=self.shape)
 
     def asformat(self, format, **kwargs):
         """
@@ -751,8 +751,8 @@ def _2d_transpose(self):
 
         See Also
         --------
-        scipy.sparse.csr_matrix.transpose : Scipy equivalent function.
-        scipy.sparse.csc_matrix.transpose : Scipy equivalent function.
+        scipy.sparse.csr_array.transpose : Scipy equivalent function.
+        scipy.sparse.csc_array.transpose : Scipy equivalent function.
         numpy.ndarray.transpose : Numpy equivalent function.
         """
         if self.ndim != 2:
@@ -791,7 +791,7 @@ def dot(self, other):
         --------
         - [`sparse.dot`][] : Equivalent function for two arguments.
         - [`numpy.dot`][] : Numpy equivalent function.
-        - [`scipy.sparse.coo_matrix.dot`][] : Scipy equivalent function.
+        - [`scipy.sparse.coo_array.dot`][] : Scipy equivalent function.
         """
         from .._common import dot
 

sparse/numba_backend/_coo/core.py

@@ -397,7 +397,7 @@ def todense(self):
         See Also
         --------
         - [`sparse.DOK.todense`][] : Equivalent `DOK` array method.
-        - [`scipy.sparse.coo_matrix.todense`][] : Equivalent Scipy method.
+        - [`scipy.sparse.coo_array.todense`][] : Equivalent Scipy method.
 
         Examples
         --------
@@ -451,11 +451,14 @@ def from_scipy_sparse(cls, x, /, *, fill_value=None):
             x.eliminate_zeros()
             x.sum_duplicates()
 
-        coords = np.empty((2, x.nnz), dtype=x.row.dtype)
-        coords[0, :] = x.row
-        coords[1, :] = x.col
+        def _coords(x):
+            c = getattr(x, "coords", None)
+            if c is None: # legacy support for SciPy sparse matrices
+                c = (x.row, x.col)
+            return c
+
         return COO(
-            coords,
+            _coords(x),
             x.data,
             shape=x.shape,
             has_duplicates=not x.has_canonical_format,
@@ -562,7 +565,7 @@ def dtype(self):
         See Also
         --------
         - [`numpy.ndarray.dtype`][] : Numpy equivalent property.
-        - [`scipy.sparse.coo_matrix.dtype`][] : Scipy equivalent property.
+        - [`scipy.sparse.coo_array.dtype`][] : Scipy equivalent property.
 
         Examples
         --------
@@ -590,7 +593,7 @@ def nnz(self):
         --------
         - [`sparse.DOK.nnz`][] : Equivalent [`sparse.DOK`][] array property.
         - [`numpy.count_nonzero`][] : A similar Numpy function.
-        - [`scipy.sparse.coo_matrix.nnz`][] : The Scipy equivalent property.
+        - [`scipy.sparse.coo_array.nnz`][] : The Scipy equivalent property.
 
         Examples
         --------
@@ -945,7 +948,7 @@ def dot(self, other):
         --------
         - [`sparse.dot`][] : Equivalent function for two arguments.
         - [`numpy.dot`][] : Numpy equivalent function.
-        - [`scipy.sparse.coo_matrix.dot`][] : Scipy equivalent function.
+        - [`scipy.sparse.coo_array.dot`][] : Scipy equivalent function.
 
         Examples
         --------
@@ -1160,7 +1163,7 @@ def squeeze(self, axis=None):
 
     def to_scipy_sparse(self, /, *, accept_fv=None):
         """
-        Converts this [`sparse.COO`][] object into a [`scipy.sparse.coo_matrix`][].
+        Converts this [`sparse.COO`][] object into a [`scipy.sparse.coo_array`][].
 
         Parameters
         ----------
@@ -1169,7 +1172,7 @@ def to_scipy_sparse(self, /, *, accept_fv=None):
 
         Returns
         -------
-        scipy.sparse.coo_matrix
+        scipy.sparse.coo_array
             The converted Scipy sparse matrix.
 
         Raises
@@ -1181,17 +1184,14 @@ def to_scipy_sparse(self, /, *, accept_fv=None):
 
         See Also
         --------
-        - [`sparse.COO.tocsr`][] : Convert to a [`scipy.sparse.csr_matrix`][].
-        - [`sparse.COO.tocsc`][] : Convert to a [`scipy.sparse.csc_matrix`][].
+        - [`sparse.COO.tocsr`][] : Convert to a [`scipy.sparse.csr_array`][].
+        - [`sparse.COO.tocsc`][] : Convert to a [`scipy.sparse.csc_array`][].
         """
         import scipy.sparse
 
         check_fill_value(self, accept_fv=accept_fv)
 
-        if self.ndim != 2:
-            raise ValueError("Can only convert a 2-dimensional array to a Scipy sparse matrix.")
-
-        result = scipy.sparse.coo_matrix((self.data, (self.coords[0], self.coords[1])), shape=self.shape)
+        result = scipy.sparse.coo_array((self.data, self.coords), shape=self.shape)
         result.has_canonical_format = True
         return result
 
@@ -1206,15 +1206,15 @@ def _tocsr(self):
         indptr = np.zeros(self.shape[0] + 1, dtype=np.int64)
         np.cumsum(np.bincount(row, minlength=self.shape[0]), out=indptr[1:])
 
-        return scipy.sparse.csr_matrix((self.data, col, indptr), shape=self.shape)
+        return scipy.sparse.csr_array((self.data, col, indptr), shape=self.shape)
 
     def tocsr(self):
         """
-        Converts this array to a [`scipy.sparse.csr_matrix`][].
+        Converts this array to a [`scipy.sparse.csr_array`][].
 
         Returns
         -------
-        scipy.sparse.csr_matrix
+        scipy.sparse.csr_array
             The result of the conversion.
 
         Raises
@@ -1226,9 +1226,9 @@ def tocsr(self):
 
         See Also
         --------
-        - [`sparse.COO.tocsc`][] : Convert to a [`scipy.sparse.csc_matrix`][].
-        - [`sparse.COO.to_scipy_sparse`][] : Convert to a [`scipy.sparse.coo_matrix`][].
-        - [`scipy.sparse.coo_matrix.tocsr`][] : Equivalent Scipy function.
+        - [`sparse.COO.tocsc`][] : Convert to a [`scipy.sparse.csc_array`][].
+        - [`sparse.COO.to_scipy_sparse`][] : Convert to a [`scipy.sparse.coo_array`][].
+        - [`scipy.sparse.coo_array.tocsr`][] : Equivalent Scipy function.
         """
         check_zero_fill_value(self)
 
@@ -1250,11 +1250,11 @@ def tocsr(self):
 
     def tocsc(self):
         """
-        Converts this array to a [`scipy.sparse.csc_matrix`][].
+        Converts this array to a [`scipy.sparse.csc_array`][].
 
         Returns
         -------
-        scipy.sparse.csc_matrix
+        scipy.sparse.csc_array
             The result of the conversion.
 
         Raises
@@ -1266,9 +1266,9 @@ def tocsc(self):
 
         See Also
         --------
-        - [`sparse.COO.tocsr`][] : Convert to a [`scipy.sparse.csr_matrix`][].
-        - [`sparse.COO.to_scipy_sparse`][] : Convert to a [`scipy.sparse.coo_matrix`][].
-        - [`scipy.sparse.coo_matrix.tocsc`][] : Equivalent Scipy function.
+        - [`sparse.COO.tocsr`][] : Convert to a [`scipy.sparse.csr_array`][].
+        - [`sparse.COO.to_scipy_sparse`][] : Convert to a [`scipy.sparse.coo_array`][].
+        - [`scipy.sparse.coo_array.tocsc`][] : Equivalent Scipy function.
         """
         check_zero_fill_value(self)
 
@@ -1320,7 +1320,7 @@ def _sum_duplicates(self):
 
         See Also
         --------
-        scipy.sparse.coo_matrix.sum_duplicates : Equivalent Scipy function.
+        scipy.sparse.coo_array.sum_duplicates : Equivalent Scipy function.
 
         Examples
         --------

sparse/numba_backend/_dok.py

@@ -258,7 +258,7 @@ def nnz(self):
         --------
         - [`sparse.COO.nnz`][] : Equivalent [`sparse.COO`][] array property.
         - [`numpy.count_nonzero`][] : A similar Numpy function.
-        - [`scipy.sparse.coo_matrix.nnz`][] : The Scipy equivalent property.
+        - [`scipy.sparse.coo_array.nnz`][] : The Scipy equivalent property.
 
         Examples
         --------
@@ -450,7 +450,7 @@ def todense(self):
         See Also
         --------
         - [`sparse.COO.todense`][] : Equivalent `COO` array method.
-        - [`scipy.sparse.coo_matrix.todense`][] : Equivalent Scipy method.
+        - [`scipy.sparse.coo_array.todense`][] : Equivalent Scipy method.
 
         Examples
         --------

sparse/numba_backend/_sparse_array.py

@@ -74,7 +74,7 @@ def nnz(self):
         --------
         - [`sparse.DOK.nnz`][] : Equivalent [`sparse.DOK`][] array property.
         - [`numpy.count_nonzero`][] : A similar Numpy function.
-        - [`scipy.sparse.coo_matrix.nnz`][] : The Scipy equivalent property.
+        - [`scipy.sparse.coo_array.nnz`][] : The Scipy equivalent property.
 
         Examples
         --------
@@ -254,7 +254,7 @@ def todense(self):
         --------
         - [`sparse.DOK.todense`][] : Equivalent `DOK` array method.
         - [`sparse.COO.todense`][] : Equivalent `COO` array method.
-        - [`scipy.sparse.coo_matrix.todense`][] : Equivalent Scipy method.
+        - [`scipy.sparse.coo_array.todense`][] : Equivalent Scipy method.
 
         Examples
         --------
@@ -453,7 +453,7 @@ def sum(self, axis=None, keepdims=False, dtype=None, out=None):
         See Also
         --------
         - [`numpy.sum`][] : Equivalent numpy function.
-        - [`scipy.sparse.coo_matrix.sum`][] : Equivalent Scipy function.
+        - [`scipy.sparse.coo_array.sum`][] : Equivalent Scipy function.
         """
         return np.add.reduce(self, out=out, axis=axis, keepdims=keepdims, dtype=dtype)
 
@@ -478,7 +478,7 @@ def max(self, axis=None, keepdims=False, out=None):
         See Also
         --------
         - [`numpy.max`][] : Equivalent numpy function.
-        - [`scipy.sparse.coo_matrix.max`][] : Equivalent Scipy function.
+        - [`scipy.sparse.coo_array.max`][] : Equivalent Scipy function.
         """
         return np.maximum.reduce(self, out=out, axis=axis, keepdims=keepdims)
 
@@ -549,7 +549,7 @@ def min(self, axis=None, keepdims=False, out=None):
         See Also
         --------
         - [`numpy.min`][] : Equivalent numpy function.
-        - [`scipy.sparse.coo_matrix.min`][] : Equivalent Scipy function.
+        - [`scipy.sparse.coo_array.min`][] : Equivalent Scipy function.
         """
         return np.minimum.reduce(self, out=out, axis=axis, keepdims=keepdims)
 
@@ -619,7 +619,7 @@ def astype(self, dtype, casting="unsafe", copy=True):
 
         See Also
         --------
-        - [`scipy.sparse.coo_matrix.astype`][] :
+        - [`scipy.sparse.coo_array.astype`][] :
             SciPy sparse equivalent function
         - [`numpy.ndarray.astype`][] :
             NumPy equivalent ufunc.
@@ -653,7 +653,7 @@ def mean(self, axis=None, keepdims=False, dtype=None, out=None):
         See Also
         --------
         - [`numpy.ndarray.mean`][] : Equivalent numpy method.
-        - [`scipy.sparse.coo_matrix.mean`][] : Equivalent Scipy method.
+        - [`scipy.sparse.coo_array.mean`][] : Equivalent Scipy method.
 
         Notes
         -----

sparse/numba_backend/tests/test_array_function.py

@@ -110,8 +110,8 @@ class TestAsarray:
         "input",
         [
             np_eye,
-            scipy.sparse.csr_matrix(np_eye),
-            scipy.sparse.csc_matrix(np_eye),
+            scipy.sparse.csr_array(np_eye),
+            scipy.sparse.csc_array(np_eye),
             4,
             np.array(5),
             np.arange(12).reshape((2, 3, 2)),

sparse/numba_backend/tests/test_compressed_2d.py

@@ -74,7 +74,7 @@ def test_from_sparse(cls, source_type):
 @pytest.mark.parametrize("scipy_type", ["coo", "csr", "csc", "lil"])
 @pytest.mark.parametrize("CLS", [CSR, CSC, GCXS])
 def test_from_scipy_sparse(scipy_type, CLS, dtype):
-    orig = scipy.sparse.random(20, 30, density=0.2, format=scipy_type, dtype=dtype)
+    orig = scipy.sparse.random_array((20, 30), density=0.2, format=scipy_type, dtype=dtype)
     ref = COO.from_scipy_sparse(orig)
     result = CLS.from_scipy_sparse(orig)
 

sparse/numba_backend/tests/test_conversion.py

@@ -53,7 +53,7 @@ def test_non_canonical_conversion():
     indices = np.array((1, 0, 0, 1, 1), dtype=int)
     indptr = np.array((0, 2, 5), dtype=int)
 
-    x = sps.csr_matrix((data, indices, indptr), shape=(2, 2))
+    x = sps.csr_array((data, indices, indptr), shape=(2, 2))
     ref = np.array(((1.0, 2.0), (3.0, 4.0)))
 
     gcxs_check = sparse.GCXS(x)