def testFromTensorSerialize(self):
# test serialization and deserialization
# pb
tensor = mt.random.rand(10, 10)
df = dataframe_from_tensor(tensor)
df.tiles()
chunk = df.chunks[0]
serials = self._pb_serial(chunk)
op, pb = serials[chunk.op, chunk.data]
self.assertEqual(tuple(pb.index), chunk.index)
self.assertEqual(pb.key, chunk.key)
self.assertEqual(tuple(pb.shape), chunk.shape)
self.assertEqual(int(op.type.split('.', 1)[1]), OperandDef.DATAFRAME_FROM_TENSOR)
chunk2 = self._pb_deserial(serials)[chunk.data]
self.assertEqual(chunk.index, chunk2.index)
self.assertEqual(chunk.key, chunk2.key)
self.assertEqual(chunk.shape, chunk2.shape)
pd.testing.assert_index_equal(chunk2.index_value.to_pandas(), chunk.index_value.to_pandas())
pd.testing.assert_index_equal(chunk2.columns_value.to_pandas(), chunk.columns_value.to_pandas())
# json
chunk = df.chunks[0]
serials = self._json_serial(chunk)
chunk2 = self._json_deserial(serials)[chunk.data]
self.assertEqual(chunk.index, chunk2.index)
self.assertEqual(chunk.key, chunk2.key)
self.assertEqual(chunk.shape, chunk2.shape)
pd.testing.assert_index_equal(chunk2.index_value.to_pandas(), chunk.index_value.to_pandas())
pd.testing.assert_index_equal(chunk2.columns_value.to_pandas(), chunk.columns_value.to_pandas())
def testFromTensorExecution(self):
tensor = mt.random.rand(10, 10, chunk_size=5)
df = dataframe_from_tensor(tensor)
tensor_res = self.executor.execute_tensor(tensor, concat=True)[0]
pdf_expected = pd.DataFrame(tensor_res)
df_result = self.executor.execute_dataframe(df, concat=True)[0]
pd.testing.assert_index_equal(df_result.index, pd.RangeIndex(0, 10))
pd.testing.assert_index_equal(df_result.columns, pd.RangeIndex(0, 10))
pd.testing.assert_frame_equal(df_result, pdf_expected)
# test converted with specified index_value and columns
tensor2 = mt.random.rand(2, 2, chunk_size=1)
df2 = dataframe_from_tensor(tensor2,
index=pd.Index(['a', 'b']),
columns=pd.Index([3, 4]))
df_result = self.executor.execute_dataframe(df2, concat=True)[0]
pd.testing.assert_index_equal(df_result.index, pd.Index(['a', 'b']))
pd.testing.assert_index_equal(df_result.columns, pd.Index([3, 4]))
# test converted from 1-d tensor
tensor3 = mt.array([1, 2, 3])
df3 = dataframe_from_tensor(tensor3)
result3 = self.executor.execute_dataframe(df3, concat=True)[0]
pdf_expected = pd.DataFrame(np.array([1, 2, 3]))
pd.testing.assert_frame_equal(pdf_expected, result3)
# test converted from identical chunks
tensor4 = mt.ones((10, 10), chunk_size=3)
df4 = dataframe_from_tensor(tensor4)
result4 = self.executor.execute_dataframe(df4, concat=True)[0]
pdf_expected = pd.DataFrame(
self.executor.execute_tensor(tensor4, concat=True)[0])
pd.testing.assert_frame_equal(pdf_expected, result4)
# from tensor with given index
tensor5 = mt.ones((10, 10), chunk_size=3)
df5 = dataframe_from_tensor(tensor5, index=np.arange(0, 20, 2))
result5 = self.executor.execute_dataframe(df5, concat=True)[0]
pdf_expected = pd.DataFrame(self.executor.execute_tensor(
tensor5, concat=True)[0],
index=np.arange(0, 20, 2))
pd.testing.assert_frame_equal(pdf_expected, result5)
# from tensor with given columns
tensor6 = mt.ones((10, 10), chunk_size=3)
df6 = dataframe_from_tensor(tensor6, columns=list('abcdefghij'))
result6 = self.executor.execute_dataframe(df6, concat=True)[0]
pdf_expected = pd.DataFrame(self.executor.execute_tensor(
tensor6, concat=True)[0],
columns=list('abcdefghij'))
pd.testing.assert_frame_equal(pdf_expected, result6)
def testFromTensor(self):
tensor = mt.random.rand(10, 10, chunk_size=5)
df = dataframe_from_tensor(tensor)
self.assertIsInstance(df.index_value._index_value, IndexValue.RangeIndex)
self.assertEqual(df.op.dtypes[0], tensor.dtype, 'DataFrame converted from tensor have the wrong dtype')
df.tiles()
self.assertEqual(len(df.chunks), 4)
self.assertIsInstance(df.chunks[0].index_value._index_value, IndexValue.RangeIndex)
self.assertIsInstance(df.chunks[0].index_value, IndexValue)
# test converted from 1-d tensor
tensor2 = mt.array([1, 2, 3])
# in fact, tensor3 is (3,1)
tensor3 = mt.array([tensor2]).T
df2 = dataframe_from_tensor(tensor2)
df3 = dataframe_from_tensor(tensor3)
df2.tiles()
df3.tiles()
np.testing.assert_equal(df2.chunks[0].index, (0, 0))
np.testing.assert_equal(df3.chunks[0].index, (0, 0))
# test converted from scalar
scalar = mt.array(1)
np.testing.assert_equal(scalar.ndim, 0)
with self.assertRaises(TypeError):
dataframe_from_tensor(scalar)
# from tensor with given index
df = dataframe_from_tensor(tensor, index=np.arange(0, 20, 2))
df.tiles()
pd.testing.assert_index_equal(df.chunks[0].index_value.to_pandas(), pd.Index(np.arange(0, 10, 2)))
pd.testing.assert_index_equal(df.chunks[1].index_value.to_pandas(), pd.Index(np.arange(0, 10, 2)))
pd.testing.assert_index_equal(df.chunks[2].index_value.to_pandas(), pd.Index(np.arange(10, 20, 2)))
pd.testing.assert_index_equal(df.chunks[3].index_value.to_pandas(), pd.Index(np.arange(10, 20, 2)))
# from tensor with given columns
df = dataframe_from_tensor(tensor, columns=list('abcdefghij'))
df.tiles()
pd.testing.assert_index_equal(df.chunks[0].columns_value.to_pandas(), pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[1].columns_value.to_pandas(), pd.Index(['f', 'g', 'h', 'i', 'j']))
pd.testing.assert_index_equal(df.chunks[2].columns_value.to_pandas(), pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[3].columns_value.to_pandas(), pd.Index(['f', 'g', 'h', 'i', 'j']))
# test series from tensor
tensor = mt.random.rand(10, chunk_size=4)
series = series_from_tensor(tensor, name='a')
self.assertEqual(series.dtype, tensor.dtype)
self.assertEqual(series.name, 'a')
pd.testing.assert_index_equal(series.index_value.to_pandas(), pd.RangeIndex(10))
series.tiles()
self.assertEqual(len(series.chunks), 3)
pd.testing.assert_index_equal(series.chunks[0].index_value.to_pandas(), pd.RangeIndex(0, 4))
self.assertEqual(series.chunks[0].name, 'a')
pd.testing.assert_index_equal(series.chunks[1].index_value.to_pandas(), pd.RangeIndex(4, 8))
self.assertEqual(series.chunks[1].name, 'a')
pd.testing.assert_index_equal(series.chunks[2].index_value.to_pandas(), pd.RangeIndex(8, 10))
self.assertEqual(series.chunks[2].name, 'a')
with self.assertRaises(TypeError):
series_from_tensor(mt.ones((10, 10)))
def testFromTensorExecution(self):
tensor = mt.random.rand(10, 10, chunk_size=5)
df = dataframe_from_tensor(tensor)
tensor_res = self.executor.execute_tensor(tensor, concat=True)[0]
pdf_expected = pd.DataFrame(tensor_res)
df_result = self.executor.execute_dataframe(df, concat=True)[0]
pd.testing.assert_index_equal(df_result.index, pd.RangeIndex(0, 10))
pd.testing.assert_index_equal(df_result.columns, pd.RangeIndex(0, 10))
pd.testing.assert_frame_equal(df_result, pdf_expected)
# test converted with specified index_value and columns
tensor2 = mt.random.rand(2, 2, chunk_size=1)
df2 = dataframe_from_tensor(tensor2,
index=pd.Index(['a', 'b']),
columns=pd.Index([3, 4]))
df_result = self.executor.execute_dataframe(df2, concat=True)[0]
pd.testing.assert_index_equal(df_result.index, pd.Index(['a', 'b']))
pd.testing.assert_index_equal(df_result.columns, pd.Index([3, 4]))
# test converted from 1-d tensor
tensor3 = mt.array([1, 2, 3])
df3 = dataframe_from_tensor(tensor3)
result3 = self.executor.execute_dataframe(df3, concat=True)[0]
pdf_expected = pd.DataFrame(np.array([1, 2, 3]))
pd.testing.assert_frame_equal(pdf_expected, result3)
# test converted from identical chunks
tensor4 = mt.ones((10, 10), chunk_size=3)
df4 = dataframe_from_tensor(tensor4)
result4 = self.executor.execute_dataframe(df4, concat=True)[0]
pdf_expected = pd.DataFrame(
self.executor.execute_tensor(tensor4, concat=True)[0])
pd.testing.assert_frame_equal(pdf_expected, result4)
# from tensor with given index
tensor5 = mt.ones((10, 10), chunk_size=3)
df5 = dataframe_from_tensor(tensor5, index=np.arange(0, 20, 2))
result5 = self.executor.execute_dataframe(df5, concat=True)[0]
pdf_expected = pd.DataFrame(self.executor.execute_tensor(
tensor5, concat=True)[0],
index=np.arange(0, 20, 2))
pd.testing.assert_frame_equal(pdf_expected, result5)
# from tensor with given index that is a tensor
raw7 = np.random.rand(10, 10)
tensor7 = mt.tensor(raw7, chunk_size=3)
index_raw7 = np.random.rand(10)
index7 = mt.tensor(index_raw7, chunk_size=4)
df7 = dataframe_from_tensor(tensor7, index=index7)
result7 = self.executor.execute_dataframe(df7, concat=True)[0]
pdf_expected = pd.DataFrame(raw7, index=index_raw7)
pd.testing.assert_frame_equal(pdf_expected, result7)
# from tensor with given index is a md.Index
raw10 = np.random.rand(10, 10)
tensor10 = mt.tensor(raw10, chunk_size=3)
index10 = md.date_range('2020-1-1', periods=10, chunk_size=3)
df10 = dataframe_from_tensor(tensor10, index=index10)
result10 = self.executor.execute_dataframe(df10, concat=True)[0]
pdf_expected = pd.DataFrame(raw10,
index=pd.date_range('2020-1-1',
periods=10))
pd.testing.assert_frame_equal(pdf_expected, result10)
# from tensor with given columns
tensor6 = mt.ones((10, 10), chunk_size=3)
df6 = dataframe_from_tensor(tensor6, columns=list('abcdefghij'))
result6 = self.executor.execute_dataframe(df6, concat=True)[0]
pdf_expected = pd.DataFrame(self.executor.execute_tensor(
tensor6, concat=True)[0],
columns=list('abcdefghij'))
pd.testing.assert_frame_equal(pdf_expected, result6)
# from 1d tensors
raws8 = [('a', np.random.rand(8)), ('b', np.random.randint(10,
size=8)),
('c', [
''.join(np.random.choice(list(printable), size=6))
for _ in range(8)
])]
tensors8 = OrderedDict(
(r[0], mt.tensor(r[1], chunk_size=3)) for r in raws8)
raws8.append(('d', 1))
raws8.append(('e', pd.date_range('2020-1-1', periods=8)))
tensors8['d'] = 1
tensors8['e'] = raws8[-1][1]
df8 = dataframe_from_1d_tileables(tensors8,
columns=[r[0] for r in raws8])
result = self.executor.execute_dataframe(df8, concat=True)[0]
pdf_expected = pd.DataFrame(OrderedDict(raws8))
pd.testing.assert_frame_equal(result, pdf_expected)
# from 1d tensors and specify index with a tensor
index_raw9 = np.random.rand(8)
index9 = mt.tensor(index_raw9, chunk_size=4)
df9 = dataframe_from_1d_tileables(tensors8,
columns=[r[0] for r in raws8],
index=index9)
result = self.executor.execute_dataframe(df9, concat=True)[0]
pdf_expected = pd.DataFrame(OrderedDict(raws8), index=index_raw9)
pd.testing.assert_frame_equal(result, pdf_expected)
# from 1d tensors and specify index
df11 = dataframe_from_1d_tileables(tensors8,
columns=[r[0] for r in raws8],
index=md.date_range('2020-1-1',
periods=8))
result = self.executor.execute_dataframe(df11, concat=True)[0]
pdf_expected = pd.DataFrame(OrderedDict(raws8),
index=pd.date_range('2020-1-1', periods=8))
pd.testing.assert_frame_equal(result, pdf_expected)
def testFromTensor(self):
tensor = mt.random.rand(10, 10, chunk_size=5)
df = dataframe_from_tensor(tensor)
self.assertIsInstance(df.index_value._index_value,
IndexValue.RangeIndex)
self.assertEqual(
df.op.dtypes[0], tensor.dtype,
'DataFrame converted from tensor have the wrong dtype')
df = df.tiles()
self.assertEqual(len(df.chunks), 4)
self.assertIsInstance(df.chunks[0].index_value._index_value,
IndexValue.RangeIndex)
self.assertIsInstance(df.chunks[0].index_value, IndexValue)
# test converted from 1-d tensor
tensor2 = mt.array([1, 2, 3])
# in fact, tensor3 is (3,1)
tensor3 = mt.array([tensor2]).T
df2 = dataframe_from_tensor(tensor2)
df3 = dataframe_from_tensor(tensor3)
df2 = df2.tiles()
df3 = df3.tiles()
np.testing.assert_equal(df2.chunks[0].index, (0, 0))
np.testing.assert_equal(df3.chunks[0].index, (0, 0))
# test converted from scalar
scalar = mt.array(1)
np.testing.assert_equal(scalar.ndim, 0)
with self.assertRaises(TypeError):
dataframe_from_tensor(scalar)
# from tensor with given index
df = dataframe_from_tensor(tensor, index=np.arange(0, 20, 2))
df = df.tiles()
pd.testing.assert_index_equal(df.chunks[0].index_value.to_pandas(),
pd.Index(np.arange(0, 10, 2)))
pd.testing.assert_index_equal(df.chunks[1].index_value.to_pandas(),
pd.Index(np.arange(0, 10, 2)))
pd.testing.assert_index_equal(df.chunks[2].index_value.to_pandas(),
pd.Index(np.arange(10, 20, 2)))
pd.testing.assert_index_equal(df.chunks[3].index_value.to_pandas(),
pd.Index(np.arange(10, 20, 2)))
# from tensor with index that is a tensor as well
df = dataframe_from_tensor(tensor, index=mt.arange(0, 20, 2))
df = df.tiles()
self.assertEqual(len(df.chunks[0].inputs), 2)
self.assertFalse(df.chunks[0].index_value.has_value())
# from tensor with given columns
df = dataframe_from_tensor(tensor, columns=list('abcdefghij'))
df = df.tiles()
pd.testing.assert_index_equal(df.dtypes.index,
pd.Index(list('abcdefghij')))
pd.testing.assert_index_equal(df.chunks[0].columns_value.to_pandas(),
pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[0].dtypes.index,
pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[1].columns_value.to_pandas(),
pd.Index(['f', 'g', 'h', 'i', 'j']))
pd.testing.assert_index_equal(df.chunks[1].dtypes.index,
pd.Index(['f', 'g', 'h', 'i', 'j']))
pd.testing.assert_index_equal(df.chunks[2].columns_value.to_pandas(),
pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[2].dtypes.index,
pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[3].columns_value.to_pandas(),
pd.Index(['f', 'g', 'h', 'i', 'j']))
pd.testing.assert_index_equal(df.chunks[3].dtypes.index,
pd.Index(['f', 'g', 'h', 'i', 'j']))
# test series from tensor
tensor = mt.random.rand(10, chunk_size=4)
series = series_from_tensor(tensor, name='a')
self.assertEqual(series.dtype, tensor.dtype)
self.assertEqual(series.name, 'a')
pd.testing.assert_index_equal(series.index_value.to_pandas(),
pd.RangeIndex(10))
series = series.tiles()
self.assertEqual(len(series.chunks), 3)
pd.testing.assert_index_equal(series.chunks[0].index_value.to_pandas(),
pd.RangeIndex(0, 4))
self.assertEqual(series.chunks[0].name, 'a')
pd.testing.assert_index_equal(series.chunks[1].index_value.to_pandas(),
pd.RangeIndex(4, 8))
self.assertEqual(series.chunks[1].name, 'a')
pd.testing.assert_index_equal(series.chunks[2].index_value.to_pandas(),
pd.RangeIndex(8, 10))
self.assertEqual(series.chunks[2].name, 'a')
df = dataframe_from_1d_tensors(
[mt.tensor(np.random.rand(4)),
mt.tensor(np.random.rand(4))])
pd.testing.assert_index_equal(df.columns_value.to_pandas(),
pd.RangeIndex(2))
df = df.tiles()
pd.testing.assert_index_equal(df.chunks[0].index_value.to_pandas(),
pd.RangeIndex(4))
series = series_from_tensor(mt.random.rand(4))
pd.testing.assert_index_equal(series.index_value.to_pandas(),
pd.RangeIndex(4))
series = series_from_tensor(mt.random.rand(4), index=[1, 2, 3])
pd.testing.assert_index_equal(series.index_value.to_pandas(),
pd.Index([1, 2, 3]))
series = series_from_tensor(mt.random.rand(4),
index=pd.Index([1, 2, 3], name='my_index'))
pd.testing.assert_index_equal(series.index_value.to_pandas(),
pd.Index([1, 2, 3], name='my_index'))
self.assertEqual(series.index_value.name, 'my_index')
with self.assertRaises(TypeError):
series_from_tensor(mt.ones((10, 10)))
# index has wrong shape
with self.assertRaises(ValueError):
dataframe_from_tensor(mt.random.rand(4, 3),
index=mt.random.rand(5))
# columns have wrong shape
with self.assertRaises(ValueError):
dataframe_from_tensor(mt.random.rand(4, 3), columns=['a', 'b'])
# index should be 1-d
with self.assertRaises(ValueError):
dataframe_from_tensor(mt.tensor(np.random.rand(3, 2)),
index=mt.tensor(np.random.rand(3, 2)))
# 1-d tensors should have same shapen
with self.assertRaises(ValueError):
dataframe_from_1d_tensors(
[mt.tensor(np.random.rand(3)),
mt.tensor(np.random.rand(2))])
# index has wrong shape
with self.assertRaises(ValueError):
dataframe_from_1d_tensors([mt.tensor(np.random.rand(3))],
index=mt.tensor(np.random.rand(2)))
# columns have wrong shape
with self.assertRaises(ValueError):
dataframe_from_1d_tensors([mt.tensor(np.random.rand(3))],
columns=['a', 'b'])
# index should be 1-d
with self.assertRaises(ValueError):
series_from_tensor(mt.random.rand(4), index=mt.random.rand(4, 3))
def test_from_tensor():
tensor = mt.random.rand(10, 10, chunk_size=5)
df = dataframe_from_tensor(tensor)
assert isinstance(df.index_value._index_value, IndexValue.RangeIndex)
assert df.op.dtypes[0] == tensor.dtype
df = tile(df)
assert len(df.chunks) == 4
assert isinstance(df.chunks[0].index_value._index_value, IndexValue.RangeIndex)
assert isinstance(df.chunks[0].index_value, IndexValue)
# test converted from 1-d tensor
tensor2 = mt.array([1, 2, 3])
# in fact, tensor3 is (3,1)
tensor3 = mt.array([tensor2]).T
df2 = dataframe_from_tensor(tensor2)
df3 = dataframe_from_tensor(tensor3)
df2 = tile(df2)
df3 = tile(df3)
np.testing.assert_equal(df2.chunks[0].index, (0, 0))
np.testing.assert_equal(df3.chunks[0].index, (0, 0))
# test converted from scalar
scalar = mt.array(1)
np.testing.assert_equal(scalar.ndim, 0)
with pytest.raises(TypeError):
dataframe_from_tensor(scalar)
# from tensor with given index
df = dataframe_from_tensor(tensor, index=np.arange(0, 20, 2))
df = tile(df)
pd.testing.assert_index_equal(df.chunks[0].index_value.to_pandas(), pd.Index(np.arange(0, 10, 2)))
pd.testing.assert_index_equal(df.chunks[1].index_value.to_pandas(), pd.Index(np.arange(0, 10, 2)))
pd.testing.assert_index_equal(df.chunks[2].index_value.to_pandas(), pd.Index(np.arange(10, 20, 2)))
pd.testing.assert_index_equal(df.chunks[3].index_value.to_pandas(), pd.Index(np.arange(10, 20, 2)))
# from tensor with index that is a tensor as well
df = dataframe_from_tensor(tensor, index=mt.arange(0, 20, 2))
df = tile(df)
assert len(df.chunks[0].inputs) == 2
assert df.chunks[0].index_value.has_value() is False
# from tensor with given columns
df = dataframe_from_tensor(tensor, columns=list('abcdefghij'))
df = tile(df)
pd.testing.assert_index_equal(df.dtypes.index, pd.Index(list('abcdefghij')))
pd.testing.assert_index_equal(df.chunks[0].columns_value.to_pandas(), pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[0].dtypes.index, pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[1].columns_value.to_pandas(), pd.Index(['f', 'g', 'h', 'i', 'j']))
pd.testing.assert_index_equal(df.chunks[1].dtypes.index, pd.Index(['f', 'g', 'h', 'i', 'j']))
pd.testing.assert_index_equal(df.chunks[2].columns_value.to_pandas(), pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[2].dtypes.index, pd.Index(['a', 'b', 'c', 'd', 'e']))
pd.testing.assert_index_equal(df.chunks[3].columns_value.to_pandas(), pd.Index(['f', 'g', 'h', 'i', 'j']))
pd.testing.assert_index_equal(df.chunks[3].dtypes.index, pd.Index(['f', 'g', 'h', 'i', 'j']))
# test series from tensor
tensor = mt.random.rand(10, chunk_size=4)
series = series_from_tensor(tensor, name='a')
assert series.dtype == tensor.dtype
assert series.name == 'a'
pd.testing.assert_index_equal(series.index_value.to_pandas(), pd.RangeIndex(10))
series = tile(series)
assert len(series.chunks) == 3
pd.testing.assert_index_equal(series.chunks[0].index_value.to_pandas(), pd.RangeIndex(0, 4))
assert series.chunks[0].name == 'a'
pd.testing.assert_index_equal(series.chunks[1].index_value.to_pandas(), pd.RangeIndex(4, 8))
assert series.chunks[1].name == 'a'
pd.testing.assert_index_equal(series.chunks[2].index_value.to_pandas(), pd.RangeIndex(8, 10))
assert series.chunks[2].name == 'a'
d = OrderedDict([(0, mt.tensor(np.random.rand(4))),
(1, mt.tensor(np.random.rand(4)))])
df = dataframe_from_1d_tileables(d)
pd.testing.assert_index_equal(df.columns_value.to_pandas(), pd.RangeIndex(2))
df = tile(df)
pd.testing.assert_index_equal(df.chunks[0].index_value.to_pandas(), pd.RangeIndex(4))
series = series_from_tensor(mt.random.rand(4))
pd.testing.assert_index_equal(series.index_value.to_pandas(), pd.RangeIndex(4))
series = series_from_tensor(mt.random.rand(4), index=[1, 2, 3])
pd.testing.assert_index_equal(series.index_value.to_pandas(), pd.Index([1, 2, 3]))
series = series_from_tensor(mt.random.rand(4), index=pd.Index([1, 2, 3], name='my_index'))
pd.testing.assert_index_equal(series.index_value.to_pandas(), pd.Index([1, 2, 3], name='my_index'))
assert series.index_value.name == 'my_index'
with pytest.raises(TypeError):
series_from_tensor(mt.ones((10, 10)))
# index has wrong shape
with pytest.raises(ValueError):
dataframe_from_tensor(mt.random.rand(4, 3), index=mt.random.rand(5))
# columns have wrong shape
with pytest.raises(ValueError):
dataframe_from_tensor(mt.random.rand(4, 3), columns=['a', 'b'])
# index should be 1-d
with pytest.raises(ValueError):
dataframe_from_tensor(mt.tensor(np.random.rand(3, 2)),
index=mt.tensor(np.random.rand(3, 2)))
# 1-d tensors should have same shape
with pytest.raises(ValueError):
dataframe_from_1d_tileables(OrderedDict([(0, mt.tensor(np.random.rand(3))),
(1, mt.tensor(np.random.rand(2)))]))
# index has wrong shape
with pytest.raises(ValueError):
dataframe_from_1d_tileables({0: mt.tensor(np.random.rand(3))},
index=mt.tensor(np.random.rand(2)))
# columns have wrong shape
with pytest.raises(ValueError):
dataframe_from_1d_tileables({0: mt.tensor(np.random.rand(3))},
columns=['a', 'b'])
# index should be 1-d
with pytest.raises(ValueError):
series_from_tensor(mt.random.rand(4), index=mt.random.rand(4, 3))
