Match ufunc.reduce behavior. (pydata#108)

setup.py

@@ -33,7 +33,6 @@
             'sphinx',
             'sphinxcontrib-napoleon',
             'sphinx_rtd_theme',
-            'numpydoc',
         ],
     },
     zip_safe=False

sparse/coo.py

@@ -632,7 +632,7 @@ def nanreduce(self, method, identity=None, axis=None, keepdims=False, **kwargs):
         arr = _replace_nan(self, method.identity if identity is None else identity)
         return arr.reduce(method, axis, keepdims, **kwargs)
 
-    def reduce(self, method, axis=None, keepdims=False, **kwargs):
+    def reduce(self, method, axis=(0,), keepdims=False, **kwargs):
         """
         Performs a reduction operation on this array.
 
@@ -692,10 +692,10 @@ def reduce(self, method, axis=None, keepdims=False, **kwargs):
         >>> s4.dtype
         dtype('float16')
 
-        By default, this reduces the array down to one number, reducing along all axes.
+        By default, this reduces the array by only the first axis.
 
         >>> s.reduce(np.add)
-        25
+        <COO: shape=(5,), dtype=int64, nnz=5, sorted=True, duplicates=False>
         """
         zero_reduce_result = method.reduce([_zero_of_dtype(self.dtype)], **kwargs)
 
@@ -730,10 +730,16 @@ def reduce(self, method, axis=None, keepdims=False, **kwargs):
             result[missing_counts] = method(result[missing_counts],
                                             _zero_of_dtype(self.dtype), **kwargs)
             coords = a.coords[0:1, inv_idx]
+
+            # Filter out zeros
+            mask = result != _zero_of_dtype(result.dtype)
+            coords = coords[:, mask]
+            result = result[mask]
+
             a = COO(coords, result, shape=(a.shape[0],),
                     has_duplicates=False, sorted=True)
 
-            a = a.reshape([self.shape[d] for d in neg_axis])
+            a = a.reshape(tuple(self.shape[d] for d in neg_axis))
             result = a
 
         if keepdims:

sparse/tests/test_coo.py

@@ -25,7 +25,7 @@ def test_reductions(reduction, axis, keepdims, kwargs, eqkwargs):
     y = x.todense()
     xx = getattr(x, reduction)(axis=axis, keepdims=keepdims, **kwargs)
     yy = getattr(y, reduction)(axis=axis, keepdims=keepdims, **kwargs)
-    assert_eq(xx, yy, check_nnz=False, **eqkwargs)
+    assert_eq(xx, yy, **eqkwargs)
 
 
 @pytest.mark.parametrize('reduction,kwargs,eqkwargs', [
@@ -42,7 +42,23 @@ def test_ufunc_reductions(reduction, axis, keepdims, kwargs, eqkwargs):
     y = x.todense()
     xx = reduction(x, axis=axis, keepdims=keepdims, **kwargs)
     yy = reduction(y, axis=axis, keepdims=keepdims, **kwargs)
-    assert_eq(xx, yy, check_nnz=False, **eqkwargs)
+    assert_eq(xx, yy, **eqkwargs)
+
+
+@pytest.mark.parametrize('reduction,kwargs', [
+    (np.max, {}),
+    (np.sum, {'axis': 0}),
+    (np.prod, {'keepdims': True}),
+    (np.add.reduce, {}),
+    (np.add.reduce, {'keepdims': True}),
+    (np.minimum.reduce, {'axis': 0}),
+])
+def test_ufunc_reductions_kwargs(reduction, kwargs):
+    x = sparse.random((2, 3, 4), density=.5)
+    y = x.todense()
+    xx = reduction(x, **kwargs)
+    yy = reduction(y, **kwargs)
+    assert_eq(xx, yy)
 
 
 @pytest.mark.parametrize('reduction', [