Add order parameter to {zero, ones, full}[_like].

Fixes #514.

Author: hameerabbasi

sparse/_common.py

@@ -1348,7 +1348,7 @@ def eye(N, M=None, k=0, dtype=float, format="coo", **kwargs):
     ).asformat(format, **kwargs)
 
 
-def full(shape, fill_value, dtype=None, format="coo", **kwargs):
+def full(shape, fill_value, dtype=None, format="coo", order="C", **kwargs):
     """Return a SparseArray of given shape and type, filled with `fill_value`.
 
     Parameters
@@ -1364,6 +1364,9 @@ def full(shape, fill_value, dtype=None, format="coo", **kwargs):
         A format string.
     compressed_axes : iterable, optional
         The axes to compress if returning a GCXS array.
+    order : {'C', None}
+        Values except these are not currently supported and raise a
+        NotImplementedError.
 
     Returns
     -------
@@ -1385,6 +1388,8 @@ def full(shape, fill_value, dtype=None, format="coo", **kwargs):
         dtype = np.array(fill_value).dtype
     if not isinstance(shape, tuple):
         shape = (shape,)
+    if order not in {"C", None}:
+        raise NotImplementedError("Currently, only 'C' and None are supported.")
     data = np.empty(0, dtype=dtype)
     coords = np.empty((len(shape), 0), dtype=np.intp)
     return COO(

sparse/tests/test_array_function.py

@@ -78,4 +78,17 @@ def test_property(func):
 
 def test_broadcast_to_scalar():
     s = sparse.COO.from_numpy([0, 0, 1, 2])
-    np.broadcast_to(np.zeros_like(s, shape=()), (3,))
+    actual = np.broadcast_to(np.zeros_like(s, shape=()), (3,))
+    expected = np.broadcast_to(np.zeros_like(s.todense(), shape=()), (3,))
+
+    assert isinstance(actual, sparse.COO)
+    assert_eq(actual, expected)
+
+
+def test_zeros_like_order():
+    s = sparse.COO.from_numpy([0, 0, 1, 2])
+    actual = np.zeros_like(s, order="C")
+    expected = np.zeros_like(s.todense(), order="C")
+
+    assert isinstance(actual, sparse.COO)
+    assert_eq(actual, expected)