BUG: ufunc is not applied to sparse.fill_value

doc/source/sparse.rst

@@ -130,6 +130,28 @@ keeps an arrays of all of the locations where the data are not equal to the
 fill value. The ``block`` format tracks only the locations and sizes of blocks
 of data.
 
+.. _sparse.calculation:
+
+Sparse Calculation
+------------------
+
+You can apply NumPy ufuncs to ``SparseArray`` and get ``SparseArray`` result.
+
+.. ipython:: python
+
+   arr = pd.SparseArray([1., np.nan, np.nan, -2., np.nan])
+   np.abs(arr)
+
+
+Note that ufunc is also applied to ``fill_value``. This is needed to get
+the correct dense result.
+
+.. ipython:: python
+
+   arr = pd.SparseArray([1., -1, -1, -2., -1], fill_value=-1)
+   np.abs(arr)
+   np.abs(arr).to_dense()
+
 .. _sparse.scipysparse:
 
 Interaction with scipy.sparse

doc/source/whatsnew/v0.19.0.txt

@@ -759,6 +759,8 @@ Bug Fixes
 - Bug in ``SparseDataFrame`` in which ``axis=None`` did not default to ``axis=0`` (:issue:`13048`)
 - Bug in ``SparseSeries`` and ``SparseDataFrame`` creation with ``object`` dtype may raise ``TypeError`` (:issue:`11633`)
 - Bug in ``SparseDataFrame`` doesn't respect passed ``SparseArray`` or ``SparseSeries`` 's dtype and ``fill_value``  (:issue:`13866`)
+- Bug in ``SparseArray`` and ``SparseSeries`` don't apply ufunc to ``fill_value`` (:issue:`13853`)
+- Bug in ``SparseSeries.abs`` incorrectly keeps negative ``fill_value`` (:issue:`13853`)
 - Bug when passing a not-default-indexed ``Series`` as ``xerr`` or ``yerr`` in ``.plot()`` (:issue:`11858`)
 - Bug in matplotlib ``AutoDataFormatter``; this restores the second scaled formatting and re-adds micro-second scaled formatting (:issue:`13131`)
 - Bug in selection from a ``HDFStore`` with a fixed format and ``start`` and/or ``stop`` specified will now return the selected range (:issue:`8287`)

pandas/sparse/array.py

@@ -212,6 +212,34 @@ def kind(self):
         elif isinstance(self.sp_index, IntIndex):
             return 'integer'
 
+    def __array_wrap__(self, out_arr, context=None):
+        """
+        NumPy calls this method when ufunc is applied
+
+        Parameters
+        ----------
+
+        out_arr : ndarray
+            ufunc result (note that ufunc is only applied to sp_values)
+        context : tuple of 3 elements (ufunc, signature, domain)
+            for example, following is a context when np.sin is applied to
+            SparseArray,
+
+            (<ufunc 'sin'>, (SparseArray,), 0))
+
+        See http://docs.scipy.org/doc/numpy/user/basics.subclassing.html
+        """
+        if isinstance(context, tuple) and len(context) == 3:
+            ufunc, args, domain = context
+            # to apply ufunc only to fill_value (to avoid recursive call)
+            args = [getattr(a, 'fill_value', a) for a in args]
+            fill_value = ufunc(self.fill_value, *args[1:])
+        else:
+            fill_value = self.fill_value
+
+        return self._simple_new(out_arr, sp_index=self.sp_index,
+                                fill_value=fill_value)
+
     def __array_finalize__(self, obj):
         """
         Gets called after any ufunc or other array operations, necessary

pandas/sparse/frame.py

@@ -706,7 +706,7 @@ def apply(self, func, axis=0, broadcast=False, reduce=False):
             new_series = {}
             for k, v in compat.iteritems(self):
                 applied = func(v)
-                applied.fill_value = func(applied.fill_value)
+                applied.fill_value = func(v.fill_value)
                 new_series[k] = applied
             return self._constructor(
                 new_series, index=self.index, columns=self.columns,

pandas/sparse/series.py

@@ -307,13 +307,22 @@ def __unicode__(self):
         rep = '%s\n%s' % (series_rep, repr(self.sp_index))
         return rep
 
-    def __array_wrap__(self, result):
+    def __array_wrap__(self, result, context=None):
         """
         Gets called prior to a ufunc (and after)
+
+        See SparseArray.__array_wrap__ for detail.
         """
+        if isinstance(context, tuple) and len(context) == 3:
+            ufunc, args, domain = context
+            args = [getattr(a, 'fill_value', a) for a in args]
+            fill_value = ufunc(self.fill_value, *args[1:])
+        else:
+            fill_value = self.fill_value
+
         return self._constructor(result, index=self.index,
                                  sparse_index=self.sp_index,
-                                 fill_value=self.fill_value,
+                                 fill_value=fill_value,
                                  copy=False).__finalize__(self)
 
     def __array_finalize__(self, obj):
@@ -434,10 +443,8 @@ def abs(self):
         -------
         abs: type of caller
         """
-        res_sp_values = np.abs(self.sp_values)
-        return self._constructor(res_sp_values, index=self.index,
-                                 sparse_index=self.sp_index,
-                                 fill_value=self.fill_value).__finalize__(self)
+        return self._constructor(np.abs(self.values),
+                                 index=self.index).__finalize__(self)
 
     def get(self, label, default=None):
         """

pandas/sparse/tests/test_array.py

@@ -829,6 +829,52 @@ def test_numpy_mean(self):
         tm.assertRaisesRegexp(ValueError, msg, np.mean,
                               SparseArray(data), out=out)
 
+    def test_ufunc(self):
+        # GH 13853 make sure ufunc is applied to fill_value
+        sparse = SparseArray([1, np.nan, 2, np.nan, -2])
+        result = SparseArray([1, np.nan, 2, np.nan, 2])
+        tm.assert_sp_array_equal(abs(sparse), result)
+        tm.assert_sp_array_equal(np.abs(sparse), result)
+
+        sparse = SparseArray([1, -1, 2, -2], fill_value=1)
+        result = SparseArray([1, 2, 2], sparse_index=sparse.sp_index,
+                             fill_value=1)
+        tm.assert_sp_array_equal(abs(sparse), result)
+        tm.assert_sp_array_equal(np.abs(sparse), result)
+
+        sparse = SparseArray([1, -1, 2, -2], fill_value=-1)
+        result = SparseArray([1, 2, 2], sparse_index=sparse.sp_index,
+                             fill_value=1)
+        tm.assert_sp_array_equal(abs(sparse), result)
+        tm.assert_sp_array_equal(np.abs(sparse), result)
+
+        sparse = SparseArray([1, np.nan, 2, np.nan, -2])
+        result = SparseArray(np.sin([1, np.nan, 2, np.nan, -2]))
+        tm.assert_sp_array_equal(np.sin(sparse), result)
+
+        sparse = SparseArray([1, -1, 2, -2], fill_value=1)
+        result = SparseArray(np.sin([1, -1, 2, -2]), fill_value=np.sin(1))
+        tm.assert_sp_array_equal(np.sin(sparse), result)
+
+        sparse = SparseArray([1, -1, 0, -2], fill_value=0)
+        result = SparseArray(np.sin([1, -1, 0, -2]), fill_value=np.sin(0))
+        tm.assert_sp_array_equal(np.sin(sparse), result)
+
+    def test_ufunc_args(self):
+        # GH 13853 make sure ufunc is applied to fill_value, including its arg
+        sparse = SparseArray([1, np.nan, 2, np.nan, -2])
+        result = SparseArray([2, np.nan, 3, np.nan, -1])
+        tm.assert_sp_array_equal(np.add(sparse, 1), result)
+
+        sparse = SparseArray([1, -1, 2, -2], fill_value=1)
+        result = SparseArray([2, 0, 3, -1], fill_value=2)
+        tm.assert_sp_array_equal(np.add(sparse, 1), result)
+
+        sparse = SparseArray([1, -1, 0, -2], fill_value=0)
+        result = SparseArray([2, 0, 1, -1], fill_value=1)
+        tm.assert_sp_array_equal(np.add(sparse, 1), result)
+
+
 if __name__ == '__main__':
     import nose
     nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],

pandas/sparse/tests/test_series.py

@@ -589,6 +589,21 @@ def test_abs(self):
         tm.assert_sp_series_equal(result, expected)
         self.assertEqual(result.name, 'x')
 
+        s = SparseSeries([1, -2, 2, -3], fill_value=-2, name='x')
+        expected = SparseSeries([1, 2, 3], sparse_index=s.sp_index,
+                                fill_value=2, name='x')
+        result = s.abs()
+        tm.assert_sp_series_equal(result, expected)
+        self.assertEqual(result.name, 'x')
+
+        result = abs(s)
+        tm.assert_sp_series_equal(result, expected)
+        self.assertEqual(result.name, 'x')
+
+        result = np.abs(s)
+        tm.assert_sp_series_equal(result, expected)
+        self.assertEqual(result.name, 'x')
+
     def test_reindex(self):
         def _compare_with_series(sps, new_index):
             spsre = sps.reindex(new_index)
@@ -1288,6 +1303,7 @@ def test_numpy_func_call(self):
             for series in ('bseries', 'zbseries'):
                 getattr(np, func)(getattr(self, series))
 
+
 if __name__ == '__main__':
     import nose
     nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],