[POC] implement test_arithmetic.py

pandas/tests/indexes/test_numeric.py

@@ -13,7 +13,7 @@
 import pandas.util.testing as tm
 
 import pandas as pd
-from pandas._libs.tslibs import Timestamp, Timedelta
+from pandas._libs.tslibs import Timestamp
 
 from pandas.tests.indexes.common import Base
 
@@ -26,42 +26,6 @@ def full_like(array, value):
     return ret
 
 
-class TestIndexArithmeticWithTimedeltaScalar(object):
-
-    @pytest.mark.parametrize('index', [
-        Int64Index(range(1, 11)),
-        UInt64Index(range(1, 11)),
-        Float64Index(range(1, 11)),
-        RangeIndex(1, 11)])
-    @pytest.mark.parametrize('scalar_td', [Timedelta(days=1),
-                                           Timedelta(days=1).to_timedelta64(),
-                                           Timedelta(days=1).to_pytimedelta()])
-    def test_index_mul_timedelta(self, scalar_td, index):
-        # GH#19333
-        expected = pd.timedelta_range('1 days', '10 days')
-
-        result = index * scalar_td
-        tm.assert_index_equal(result, expected)
-        commute = scalar_td * index
-        tm.assert_index_equal(commute, expected)
-
-    @pytest.mark.parametrize('index', [Int64Index(range(1, 3)),
-                                       UInt64Index(range(1, 3)),
-                                       Float64Index(range(1, 3)),
-                                       RangeIndex(1, 3)])
-    @pytest.mark.parametrize('scalar_td', [Timedelta(days=1),
-                                           Timedelta(days=1).to_timedelta64(),
-                                           Timedelta(days=1).to_pytimedelta()])
-    def test_index_rdiv_timedelta(self, scalar_td, index):
-        expected = pd.TimedeltaIndex(['1 Day', '12 Hours'])
-
-        result = scalar_td / index
-        tm.assert_index_equal(result, expected)
-
-        with pytest.raises(TypeError):
-            index / scalar_td
-
-
 class Numeric(Base):
 
     def test_can_hold_identifiers(self):

pandas/tests/series/test_arithmetic.py

@@ -891,22 +891,3 @@ def test_td64series_mul_timedeltalike_invalid(self, scalar_td):
             td1 * scalar_td
         with tm.assert_raises_regex(TypeError, pattern):
             scalar_td * td1
-
-
-class TestTimedeltaSeriesInvalidArithmeticOps(object):
-    @pytest.mark.parametrize('scalar_td', [
-        timedelta(minutes=5, seconds=4),
-        Timedelta('5m4s'),
-        Timedelta('5m4s').to_timedelta64()])
-    def test_td64series_pow_invalid(self, scalar_td):
-        td1 = Series([timedelta(minutes=5, seconds=3)] * 3)
-        td1.iloc[2] = np.nan
-
-        # check that we are getting a TypeError
-        # with 'operate' (from core/ops.py) for the ops that are not
-        # defined
-        pattern = 'operate|unsupported|cannot|not supported'
-        with tm.assert_raises_regex(TypeError, pattern):
-            scalar_td ** td1
-        with tm.assert_raises_regex(TypeError, pattern):
-            td1 ** scalar_td

pandas/tests/test_arithmetic.py

@@ -0,0 +1,119 @@
+# -*- coding: utf-8 -*-
+# Arithmetc tests for DataFrame/Series/Index/Array classes that should
+# behave identically.
+from datetime import timedelta
+
+import pytest
+import numpy as np
+
+import pandas as pd
+import pandas.util.testing as tm
+
+from pandas import Timedelta
+
+
+# ------------------------------------------------------------------
+# Numeric dtypes Arithmetic with Timedelta Scalar
+
+class TestNumericArraylikeArithmeticWithTimedeltaScalar(object):
+
+    @pytest.mark.parametrize('box', [
+        pd.Index,
+        pd.Series,
+        pytest.param(pd.DataFrame,
+                     marks=pytest.mark.xfail(reason="block.eval incorrect",
+                                             strict=True))
+    ])
+    @pytest.mark.parametrize('index', [
+        pd.Int64Index(range(1, 11)),
+        pd.UInt64Index(range(1, 11)),
+        pd.Float64Index(range(1, 11)),
+        pd.RangeIndex(1, 11)],
+        ids=lambda x: type(x).__name__)
+    @pytest.mark.parametrize('scalar_td', [
+        Timedelta(days=1),
+        Timedelta(days=1).to_timedelta64(),
+        Timedelta(days=1).to_pytimedelta()],
+        ids=lambda x: type(x).__name__)
+    def test_index_mul_timedelta(self, scalar_td, index, box):
+        # GH#19333
+
+        if (box is pd.Series and
+                type(scalar_td) is timedelta and index.dtype == 'f8'):
+            raise pytest.xfail(reason="Cannot multiply timedelta by float")
+
+        expected = pd.timedelta_range('1 days', '10 days')
+
+        index = tm.box_expected(index, box)
+        expected = tm.box_expected(expected, box)
+
+        result = index * scalar_td
+        tm.assert_equal(result, expected)
+
+        commute = scalar_td * index
+        tm.assert_equal(commute, expected)
+
+    @pytest.mark.parametrize('box', [pd.Index, pd.Series, pd.DataFrame])
+    @pytest.mark.parametrize('index', [
+        pd.Int64Index(range(1, 3)),
+        pd.UInt64Index(range(1, 3)),
+        pd.Float64Index(range(1, 3)),
+        pd.RangeIndex(1, 3)],
+        ids=lambda x: type(x).__name__)
+    @pytest.mark.parametrize('scalar_td', [
+        Timedelta(days=1),
+        Timedelta(days=1).to_timedelta64(),
+        Timedelta(days=1).to_pytimedelta()],
+        ids=lambda x: type(x).__name__)
+    def test_index_rdiv_timedelta(self, scalar_td, index, box):
+
+        if box is pd.Series and type(scalar_td) is timedelta:
+            raise pytest.xfail(reason="TODO: Figure out why this case fails")
+        if box is pd.DataFrame and isinstance(scalar_td, timedelta):
+            raise pytest.xfail(reason="TODO: Figure out why this case fails")
+
+        expected = pd.TimedeltaIndex(['1 Day', '12 Hours'])
+
+        index = tm.box_expected(index, box)
+        expected = tm.box_expected(expected, box)
+
+        result = scalar_td / index
+        tm.assert_equal(result, expected)
+
+        with pytest.raises(TypeError):
+            index / scalar_td
+
+
+# ------------------------------------------------------------------
+# Timedelta64[ns] dtype Arithmetic Operations
+
+
+class TestTimedeltaArraylikeInvalidArithmeticOps(object):
+
+    @pytest.mark.parametrize('box', [
+        pd.Index,
+        pd.Series,
+        pytest.param(pd.DataFrame,
+                     marks=pytest.mark.xfail(reason="raises ValueError "
+                                                    "instead of TypeError",
+                                             strict=True))
+    ])
+    @pytest.mark.parametrize('scalar_td', [
+        timedelta(minutes=5, seconds=4),
+        Timedelta('5m4s'),
+        Timedelta('5m4s').to_timedelta64()])
+    def test_td64series_pow_invalid(self, scalar_td, box):
+        td1 = pd.Series([timedelta(minutes=5, seconds=3)] * 3)
+        td1.iloc[2] = np.nan
+
+        td1 = tm.box_expected(td1, box)
+
+        # check that we are getting a TypeError
+        # with 'operate' (from core/ops.py) for the ops that are not
+        # defined
+        pattern = 'operate|unsupported|cannot|not supported'
+        with tm.assert_raises_regex(TypeError, pattern):
+            scalar_td ** td1
+
+        with tm.assert_raises_regex(TypeError, pattern):
+            td1 ** scalar_td

pandas/util/testing.py

@@ -1478,6 +1478,50 @@ def assert_panel_equal(left, right,
             assert item in left, msg
 
 
+def assert_equal(left, right, **kwargs):
+    """
+    Wrapper for tm.assert_*_equal to dispatch to the appropriate test function.
+
+    Parameters
+    ----------
+    left : Index, Series, or DataFrame
+    right : Index, Series, or DataFrame
+    **kwargs
+    """
+    if isinstance(left, pd.Index):
+        assert_index_equal(left, right, **kwargs)
+    elif isinstance(left, pd.Series):
+        assert_series_equal(left, right, **kwargs)
+    elif isinstance(left, pd.DataFrame):
+        assert_frame_equal(left, right, **kwargs)
+    else:
+        raise NotImplementedError(type(left))
+
+
+def box_expected(expected, box_cls):
+    """
+    Helper function to wrap the expected output of a test in a given box_class.
+
+    Parameters
+    ----------
+    expected : np.ndarray, Index, Series
+    box_cls : {Index, Series, DataFrame}
+
+    Returns
+    -------
+    subclass of box_cls
+    """
+    if box_cls is pd.Index:
+        expected = pd.Index(expected)
+    elif box_cls is pd.Series:
+        expected = pd.Series(expected)
+    elif box_cls is pd.DataFrame:
+        expected = pd.Series(expected).to_frame()
+    else:
+        raise NotImplementedError(box_cls)
+    return expected
+
+
 # -----------------------------------------------------------------------------
 # Sparse