BUG: modfy(SparseArray) (#26947)

Closes #26946

(cherry picked from commit 430f664ddbb4dab542b34b2c75b6d086fdef4934)

Author: TomAugspurger

doc/source/whatsnew/v0.25.0.rst

@@ -769,6 +769,7 @@ Sparse
 - Bug in :class:`SparseFrame` constructor where passing ``None`` as the data would cause ``default_fill_value`` to be ignored (:issue:`16807`)
 - Bug in :class:`SparseDataFrame` when adding a column in which the length of values does not match length of index, ``AssertionError`` is raised instead of raising ``ValueError`` (:issue:`25484`)
 - Introduce a better error message in :meth:`Series.sparse.from_coo` so it returns a ``TypeError`` for inputs that are not coo matrices (:issue:`26554`)
+- Bug in :func:`numpy.modf` on a :class:`SparseArray`. Now a tuple of :class:`SparseArray` is returned.
 
 Other
 ^^^^^

pandas/core/arrays/sparse.py

@@ -1697,6 +1697,17 @@ def __array_ufunc__(self, ufunc, method, *inputs, **kwargs):
             # No alignment necessary.
             sp_values = getattr(ufunc, method)(self.sp_values, **kwargs)
             fill_value = getattr(ufunc, method)(self.fill_value, **kwargs)
+
+            if isinstance(sp_values, tuple):
+                # multiple outputs. e.g. modf
+                arrays = tuple(
+                    self._simple_new(sp_value,
+                                     self.sp_index,
+                                     SparseDtype(sp_value.dtype, fv))
+                    for sp_value, fv in zip(sp_values, fill_value)
+                )
+                return arrays
+
             return self._simple_new(sp_values,
                                     self.sp_index,
                                     SparseDtype(sp_values.dtype, fill_value))

pandas/tests/arrays/sparse/test_array.py

@@ -1071,6 +1071,16 @@ def test_ufunc_args(self):
         result = SparseArray([2, 0, 1, -1], fill_value=1)
         tm.assert_sp_array_equal(np.add(sparse, 1), result)
 
+    @pytest.mark.parametrize('fill_value', [0.0, np.nan])
+    def test_modf(self, fill_value):
+        # https://github.com/pandas-dev/pandas/issues/26946
+        sparse = pd.SparseArray([fill_value] * 10 + [1.1, 2.2],
+                                fill_value=fill_value)
+        r1, r2 = np.modf(sparse)
+        e1, e2 = np.modf(np.asarray(sparse))
+        tm.assert_sp_array_equal(r1, pd.SparseArray(e1, fill_value=fill_value))
+        tm.assert_sp_array_equal(r2, pd.SparseArray(e2, fill_value=fill_value))
+
     def test_nbytes_integer(self):
         arr = SparseArray([1, 0, 0, 0, 2], kind='integer')
         result = arr.nbytes