def testFromDataFrameExecution(self):
mdf = md.DataFrame({
'angle': [0, 3, 4],
'degree': [360, 180, 360]
},
index=['circle', 'triangle', 'rectangle'])
tensor_result = self.executor.execute_tensor(from_dataframe(mdf))
tensor_expected = self.executor.execute_tensor(
mt.tensor([[0, 360], [3, 180], [4, 360]]))
np.testing.assert_equal(tensor_result, tensor_expected)
# test up-casting
mdf2 = md.DataFrame({'a': [0.1, 0.2, 0.3], 'b': [1, 2, 3]})
tensor_result2 = self.executor.execute_tensor(from_dataframe(mdf2))
np.testing.assert_equal(tensor_result2[0].dtype, np.dtype('float64'))
tensor_expected2 = self.executor.execute_tensor(
mt.tensor([[0.1, 1.0], [0.2, 2.0], [0.3, 3.0]]))
np.testing.assert_equal(tensor_result2, tensor_expected2)
raw = [[0.1, 0.2, 0.4], [0.4, 0.7, 0.3]]
mdf3 = md.DataFrame(raw, columns=list('abc'), chunk_size=2)
tensor_result3 = self.executor.execute_tensor(from_dataframe(mdf3),
concat=True)[0]
np.testing.assert_array_equal(tensor_result3, np.asarray(raw))
self.assertTrue(tensor_result3.flags['F_CONTIGUOUS'])
self.assertFalse(tensor_result3.flags['C_CONTIGUOUS'])
# test from series
series = md.Series([1, 2, 3])
tensor_result = series.to_tensor().execute()
np.testing.assert_array_equal(tensor_result, np.array([1, 2, 3]))
series = md.Series(range(10), chunk_size=3)
tensor_result = series.to_tensor().execute()
np.testing.assert_array_equal(tensor_result, np.arange(10))
def test_from_dataframe_execution(setup):
mdf = md.DataFrame({'angle': [0, 3, 4], 'degree': [360, 180, 360]},
index=['circle', 'triangle', 'rectangle'])
tensor_result = from_dataframe(mdf).execute().fetch()
tensor_expected = mt.tensor([[0, 360], [3, 180], [4, 360]]).execute().fetch()
np.testing.assert_equal(tensor_result, tensor_expected)
# test up-casting
mdf2 = md.DataFrame({'a': [0.1, 0.2, 0.3], 'b': [1, 2, 3]})
tensor_result2 = from_dataframe(mdf2).execute().fetch()
np.testing.assert_equal(tensor_result2[0].dtype, np.dtype('float64'))
tensor_expected2 = mt.tensor([[0.1, 1.0], [0.2, 2.0], [0.3, 3.0]]).execute().fetch()
np.testing.assert_equal(tensor_result2, tensor_expected2)
raw = [[0.1, 0.2, 0.4], [0.4, 0.7, 0.3]]
mdf3 = md.DataFrame(raw, columns=list('abc'), chunk_size=2)
tensor_result3 = from_dataframe(mdf3).execute().fetch()
np.testing.assert_array_equal(tensor_result3, np.asarray(raw))
assert tensor_result3.flags['F_CONTIGUOUS'] is True
assert tensor_result3.flags['C_CONTIGUOUS'] is False
# test from series
series = md.Series([1, 2, 3])
tensor_result = series.to_tensor().execute().fetch()
np.testing.assert_array_equal(tensor_result, np.array([1, 2, 3]))
series = md.Series(range(10), chunk_size=3)
tensor_result = series.to_tensor().execute().fetch()
np.testing.assert_array_equal(tensor_result, np.arange(10))
# test from index
index = md.Index(pd.MultiIndex.from_tuples([(0, 1), (2, 3), (4, 5)]))
tensor_result = index.to_tensor(extract_multi_index=True).execute().fetch()
np.testing.assert_array_equal(tensor_result, np.arange(6).reshape((3, 2)))
index = md.Index(pd.MultiIndex.from_tuples([(0, 1), (2, 3), (4, 5)]))
tensor_result = index.to_tensor(extract_multi_index=False).execute().fetch()
np.testing.assert_array_equal(tensor_result,
pd.MultiIndex.from_tuples([(0, 1), (2, 3), (4, 5)]).to_series())