Merge pull request #423 from hameerabbasi/add-shape-kwarg-full-like

Add shape= kwarg in {zeros, ones, full}_like.

azure-pipelines.yml

@@ -14,9 +14,6 @@ jobs:
           python_version: '3.7'
         Python36:
           python_version: '3.6'
-        ArrayFunction:
-          NUMPY_EXPERIMENTAL_ARRAY_FUNCTION: '1'
-          NUMPY_VERSION: '==1.16.2'
 - job: MacOS
   variables:
     python_version: '3.6'

requirements.txt

@@ -1,3 +1,3 @@
-numpy
+numpy>=1.17
 scipy>=0.19
 numba>=0.49

sparse/_common.py

@@ -1375,7 +1375,7 @@ def full(shape, fill_value, dtype=None, format="coo", compressed_axes=None):
     ).asformat(format, compressed_axes=compressed_axes)
 
 
-def full_like(a, fill_value, dtype=None, format=None, compressed_axes=None):
+def full_like(a, fill_value, dtype=None, shape=None, format=None, compressed_axes=None):
     """Return a full array with the same shape and type as a given array.
 
     Parameters
@@ -1403,12 +1403,12 @@ def full_like(a, fill_value, dtype=None, format=None, compressed_axes=None):
     """
     if format is None and not isinstance(a, np.ndarray):
         format = type(a).__name__.lower()
-    else:
+    elif format is None:
         format = "coo"
     if hasattr(a, "compressed_axes") and compressed_axes is None:
         compressed_axes = a.compressed_axes
     return full(
-        a.shape,
+        a.shape if shape is None else shape,
         fill_value,
         dtype=(a.dtype if dtype is None else dtype),
         format=format,
@@ -1452,7 +1452,7 @@ def zeros(shape, dtype=float, format="coo", compressed_axes=None):
     )
 
 
-def zeros_like(a, dtype=None, format=None, compressed_axes=None):
+def zeros_like(a, dtype=None, shape=None, format=None, compressed_axes=None):
     """Return a SparseArray of zeros with the same shape and type as ``a``.
 
     Parameters
@@ -1478,17 +1478,8 @@ def zeros_like(a, dtype=None, format=None, compressed_axes=None):
     array([[0, 0, 0],
            [0, 0, 0]])
     """
-    if format is None and not isinstance(a, np.ndarray):
-        format = type(a).__name__.lower()
-    elif format is None:
-        format = "coo"
-    if hasattr(a, "compressed_axes") and compressed_axes is None:
-        compressed_axes = a.compressed_axes
-    return zeros(
-        a.shape,
-        dtype=(a.dtype if dtype is None else dtype),
-        format=format,
-        compressed_axes=compressed_axes,
+    return full_like(
+        a, 0, dtype=dtype, shape=shape, format=format, compressed_axes=compressed_axes
     )
 
 
@@ -1528,7 +1519,7 @@ def ones(shape, dtype=float, format="coo", compressed_axes=None):
     )
 
 
-def ones_like(a, dtype=None, format=None, compressed_axes=None):
+def ones_like(a, dtype=None, shape=None, format=None, compressed_axes=None):
     """Return a SparseArray of ones with the same shape and type as ``a``.
 
     Parameters
@@ -1554,17 +1545,8 @@ def ones_like(a, dtype=None, format=None, compressed_axes=None):
     array([[1, 1, 1],
            [1, 1, 1]])
     """
-    if format is None and not isinstance(a, np.ndarray):
-        format = type(a).__name__.lower()
-    else:
-        format = "coo"
-    if hasattr(a, "compressed_axes") and compressed_axes is None:
-        compressed_axes = a.compressed_axes
-    return ones(
-        a.shape,
-        dtype=(a.dtype if dtype is None else dtype),
-        format=format,
-        compressed_axes=compressed_axes,
+    return full_like(
+        a, 1, dtype=dtype, shape=shape, format=format, compressed_axes=compressed_axes
     )
 
 

sparse/tests/test_coo.py

@@ -1307,6 +1307,7 @@ def test_ones_zeros_like(funcname):
     assert_eq(sp_func(x), np_func(x))
     assert_eq(sp_func(x, dtype="f8"), np_func(x, dtype="f8"))
     assert_eq(sp_func(x, dtype=None), np_func(x, dtype=None))
+    assert_eq(sp_func(x, shape=(2, 2)), np_func(x, shape=(2, 2)))
 
 
 def test_full():
@@ -1320,6 +1321,9 @@ def test_full_like():
     x = np.zeros((5, 5), dtype="i8")
     assert_eq(sparse.full_like(x, 9.5), np.full_like(x, 9.5))
     assert_eq(sparse.full_like(x, 9.5, dtype="f8"), np.full_like(x, 9.5, dtype="f8"))
+    assert_eq(
+        sparse.full_like(x, 9.5, shape=(2, 2)), np.full_like(x, 9.5, shape=(2, 2))
+    )
 
 
 @pytest.mark.parametrize("complex", [True, False])