BUG: SparseArray numeric ops misc fixes

doc/source/whatsnew/v0.18.1.txt

@@ -114,6 +114,9 @@ These changes conform sparse handling to return the correct types and work to ma
 - Bug in ``SparseSeries.iloc[]`` with scalar input may raise ``IndexError`` (:issue:`10560`)
 - Bug in ``SparseSeries.loc[]``, ``.iloc[]`` with ``slice`` returns ``SparseArray``, rather than ``SparseSeries`` (:issue:`10560`)
 - Bug in ``SparseDataFrame.loc[]``, ``.iloc[]`` may results in dense ``Series``, rather than ``SparseSeries`` (:issue:`12787`)
+- Bug in ``SparseArray`` addition ignores ``fill_value`` of right hand side (:issue:`12910`)
+- Bug in ``SparseArray`` mod raises ``AttributeError (:issue:`12910`)
+- Bug in ``SparseArray`` pow calculates ``1 ** np.nan`` as ``np.nan`` which must be 1 (:issue:`12910`)
 - Bug in ``SparseSeries.__repr__`` raises ``TypeError`` when it is longer than ``max_rows`` (:issue:`10560`)
 - Bug in ``SparseSeries.shape`` ignores ``fill_value`` (:issue:`10452`)
 - Bug in ``SparseSeries.reindex`` incorrectly handle ``fill_value`` (:issue:`12797`)

pandas/sparse/array.py

@@ -59,10 +59,7 @@ def wrapper(self, other):
 
 
 def _sparse_array_op(left, right, op, name):
-    if np.isnan(left.fill_value):
-        sparse_op = lambda a, b: _sparse_nanop(a, b, name)
-    else:
-        sparse_op = lambda a, b: _sparse_fillop(a, b, name)
+    sparse_op = lambda a, b: _sparse_op(a, b, name)
 
     if left.sp_index.equals(right.sp_index):
         result = op(left.sp_values, right.sp_values)
@@ -79,15 +76,7 @@ def _sparse_array_op(left, right, op, name):
                        fill_value=fill_value)
 
 
-def _sparse_nanop(this, other, name):
-    sparse_op = getattr(splib, 'sparse_nan%s' % name)
-    result, result_index = sparse_op(this.sp_values, this.sp_index,
-                                     other.sp_values, other.sp_index)
-
-    return result, result_index
-
-
-def _sparse_fillop(this, other, name):
+def _sparse_op(this, other, name):
     sparse_op = getattr(splib, 'sparse_%s' % name)
     result, result_index = sparse_op(this.sp_values, this.sp_index,
                                      this.fill_value, other.sp_values,

pandas/sparse/tests/test_array.py

@@ -543,6 +543,69 @@ def test_fillna_overlap(self):
         tm.assert_sp_array_equal(res, exp)
 
 
+class TestSparseArrayArithmetic(tm.TestCase):
+
+    _multiprocess_can_split_ = True
+
+    def _check_numeric_ops(self, a, b, a_dense, b_dense):
+        tm.assert_numpy_array_equal((a + b).to_dense(), a_dense + b_dense)
+        tm.assert_numpy_array_equal((b + a).to_dense(), b_dense + a_dense)
+
+        tm.assert_numpy_array_equal((a - b).to_dense(), a_dense - b_dense)
+        tm.assert_numpy_array_equal((b - a).to_dense(), b_dense - a_dense)
+
+        tm.assert_numpy_array_equal((a * b).to_dense(), a_dense * b_dense)
+        tm.assert_numpy_array_equal((b * a).to_dense(), b_dense * a_dense)
+
+        tm.assert_numpy_array_equal((a / b).to_dense(), a_dense / b_dense)
+        tm.assert_numpy_array_equal((b / a).to_dense(), b_dense / a_dense)
+
+        tm.assert_numpy_array_equal((a // b).to_dense(), a_dense // b_dense)
+        tm.assert_numpy_array_equal((b // a).to_dense(), b_dense // a_dense)
+
+        tm.assert_numpy_array_equal((a % b).to_dense(), a_dense % b_dense)
+        tm.assert_numpy_array_equal((b % a).to_dense(), b_dense % a_dense)
+
+        tm.assert_numpy_array_equal((a ** b).to_dense(), a_dense ** b_dense)
+        tm.assert_numpy_array_equal((b ** a).to_dense(), b_dense ** a_dense)
+
+    def test_float_scalar(self):
+        values = np.array([np.nan, 1, 2, 0, np.nan, 0, 1, 2, 1, np.nan])
+
+        a = SparseArray(values)
+        self._check_numeric_ops(a, 1, values, 1)
+        self._check_numeric_ops(a, 0, values, 0)
+
+        a = SparseArray(values, fill_value=0)
+        self._check_numeric_ops(a, 1, values, 1)
+        self._check_numeric_ops(a, 0, values, 0)
+
+        a = SparseArray(values, fill_value=2)
+        self._check_numeric_ops(a, 1, values, 1)
+        self._check_numeric_ops(a, 0, values, 0)
+
+    def test_float_array(self):
+        values = np.array([np.nan, 1, 2, 0, np.nan, 0, 1, 2, 1, np.nan])
+        rvalues = np.array([2, np.nan, 2, 3, np.nan, 0, 1, 5, 2, np.nan])
+
+        a = SparseArray(values)
+        b = SparseArray(rvalues)
+        self._check_numeric_ops(a, b, values, rvalues)
+        self._check_numeric_ops(a, b * 0, values, rvalues * 0)
+
+        a = SparseArray(values, fill_value=0)
+        b = SparseArray(rvalues)
+        self._check_numeric_ops(a, b, values, rvalues)
+
+        a = SparseArray(values, fill_value=0)
+        b = SparseArray(rvalues, fill_value=0)
+        self._check_numeric_ops(a, b, values, rvalues)
+
+        a = SparseArray(values, fill_value=1)
+        b = SparseArray(rvalues, fill_value=2)
+        self._check_numeric_ops(a, b, values, rvalues)
+
+
 if __name__ == '__main__':
     import nose
     nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],

pandas/sparse/tests/test_libsparse.py

@@ -269,31 +269,6 @@ def test_to_int_index(self):
 
 
 class TestSparseOperators(tm.TestCase):
-    def _nan_op_tests(self, sparse_op, python_op):
-        def _check_case(xloc, xlen, yloc, ylen, eloc, elen):
-            xindex = BlockIndex(TEST_LENGTH, xloc, xlen)
-            yindex = BlockIndex(TEST_LENGTH, yloc, ylen)
-
-            xdindex = xindex.to_int_index()
-            ydindex = yindex.to_int_index()
-
-            x = np.arange(xindex.npoints) * 10. + 1
-            y = np.arange(yindex.npoints) * 100. + 1
-
-            result_block_vals, rb_index = sparse_op(x, xindex, y, yindex)
-            result_int_vals, ri_index = sparse_op(x, xdindex, y, ydindex)
-
-            self.assertTrue(rb_index.to_int_index().equals(ri_index))
-            assert_equal(result_block_vals, result_int_vals)
-
-            # check versus Series...
-            xseries = Series(x, xdindex.indices)
-            yseries = Series(y, ydindex.indices)
-            series_result = python_op(xseries, yseries).valid()
-            assert_equal(result_block_vals, series_result.values)
-            assert_equal(result_int_vals, series_result.values)
-
-        check_cases(_check_case)
 
     def _op_tests(self, sparse_op, python_op):
         def _check_case(xloc, xlen, yloc, ylen, eloc, elen):
@@ -337,16 +312,6 @@ def _check_case(xloc, xlen, yloc, ylen, eloc, elen):
 check_ops = ['add', 'sub', 'mul', 'truediv', 'floordiv']
 
 
-def make_nanoptestf(op):
-    def f(self):
-        sparse_op = getattr(splib, 'sparse_nan%s' % op)
-        python_op = getattr(operator, op)
-        self._nan_op_tests(sparse_op, python_op)
-
-    f.__name__ = 'test_nan%s' % op
-    return f
-
-
 def make_optestf(op):
     def f(self):
         sparse_op = getattr(splib, 'sparse_%s' % op)
@@ -358,13 +323,11 @@ def f(self):
 
 
 for op in check_ops:
-    f = make_nanoptestf(op)
     g = make_optestf(op)
-    setattr(TestSparseOperators, f.__name__, f)
     setattr(TestSparseOperators, g.__name__, g)
-    del f
     del g
 
+
 if __name__ == '__main__':
     import nose  # noqa
     nose.runmodule(argv=[__file__, '-vvs', '-x', '--pdb', '--pdb-failure'],