def testWithPlainValue(self):
if self.func_name in ['__and__', '__or__', '__xor__']:
# skip tests for bitwise logical operators on plain value.
return
data1 = pd.DataFrame(np.random.rand(10, 10), index=np.arange(10),
columns=[4, 1, 3, 2, 10, 5, 9, 8, 6, 7])
data1 = self.to_boolean_if_needed(data1)
df1 = from_pandas(data1, chunk_size=6)
s1 = df1[2]
r = getattr(df1, self.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], axis=0)
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1, self.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(df1, self.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10), axis=0)
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1, self.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10), axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(s1, self.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1[2], self.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
pd.testing.assert_series_equal(expected, result)
r = getattr(s1, self.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1[2], self.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
pd.testing.assert_series_equal(expected, result)
# specify index, not the default range index
data1 = pd.DataFrame(np.random.rand(10, 7), index=np.arange(5, 15),
columns=[4, 1, 3, 2, 5, 6, 7])
data1 = self.to_boolean_if_needed(data1)
df1 = from_pandas(data1, chunk_size=6)
s1 = df1[2]
r = getattr(df1, self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), axis=0)
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1, self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(df1, self.func_name)(from_array(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])), axis=0)
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1, self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(s1, self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1[2], self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
pd.testing.assert_series_equal(expected, result)
r = getattr(s1, self.func_name)(from_array(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])))
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1[2], self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
pd.testing.assert_series_equal(expected, result)
def test_with_plain_value(setup, func_name, func_opts):
if func_opts.func_name in ['__and__', '__or__', '__xor__']:
# skip tests for bitwise logical operators on plain value.
return
data1 = pd.DataFrame(np.random.rand(10, 10), index=np.arange(10),
columns=[4, 1, 3, 2, 10, 5, 9, 8, 6, 7])
data1 = to_boolean_if_needed(func_opts.func_name, data1)
df1 = from_pandas(data1, chunk_size=6)
s1 = df1[2]
r = getattr(df1, func_opts.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], axis=0)
result = r.execute().fetch()
expected = getattr(data1, func_opts.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(df1, func_opts.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10), axis=0)
result = r.execute().fetch()
expected = getattr(data1, func_opts.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10), axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(s1, func_opts.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
result = r.execute().fetch()
expected = getattr(data1[2], func_opts.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
pd.testing.assert_series_equal(expected, result)
r = getattr(s1, func_opts.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
result = r.execute().fetch()
expected = getattr(data1[2], func_opts.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
pd.testing.assert_series_equal(expected, result)
# specify index, not the default range index
data1 = pd.DataFrame(np.random.rand(10, 7), index=np.arange(5, 15),
columns=[4, 1, 3, 2, 5, 6, 7])
data1 = to_boolean_if_needed(func_opts.func_name, data1)
df1 = from_pandas(data1, chunk_size=6)
s1 = df1[2]
r = getattr(df1, func_opts.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), axis=0)
result = r.execute().fetch()
expected = getattr(data1, func_opts.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(df1, func_opts.func_name)(from_array(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])), axis=0)
result = r.execute().fetch()
expected = getattr(data1, func_opts.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(s1, func_opts.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
result = r.execute().fetch()
expected = getattr(data1[2], func_opts.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
pd.testing.assert_series_equal(expected, result)
r = getattr(s1, func_opts.func_name)(from_array(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])))
result = r.execute().fetch()
expected = getattr(data1[2], func_opts.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
pd.testing.assert_series_equal(expected, result)
def testWithPlainValue(self):
data1 = pd.DataFrame(np.random.rand(10, 10), index=np.arange(10),
columns=[4, 1, 3, 2, 10, 5, 9, 8, 6, 7])
df1 = from_pandas(data1, chunk_size=6)
s1 = df1[2]
r = getattr(df1, self.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], axis=0)
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1, self.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(df1, self.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10), axis=0)
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1, self.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10), axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(s1, self.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1[2], self.func_name)([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
pd.testing.assert_series_equal(expected, result)
r = getattr(s1, self.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1[2], self.func_name)((1, 2, 3, 4, 5, 6, 7, 8, 9, 10))
pd.testing.assert_series_equal(expected, result)
# specify index, not the default range index
data1 = pd.DataFrame(np.random.rand(10, 7), index=np.arange(5, 15),
columns=[4, 1, 3, 2, 5, 6, 7])
df1 = from_pandas(data1, chunk_size=6)
s1 = df1[2]
r = getattr(df1, self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), axis=0)
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1, self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(df1, self.func_name)(from_array(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])), axis=0)
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1, self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), axis=0)
pd.testing.assert_frame_equal(expected, result)
r = getattr(s1, self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1[2], self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
pd.testing.assert_series_equal(expected, result)
r = getattr(s1, self.func_name)(from_array(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])))
result = self.executor.execute_dataframe(r, concat=True)[0]
expected = getattr(data1[2], self.func_name)(np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]))
pd.testing.assert_series_equal(expected, result)