def test_geometric_types(postgres):
adapter = PostgresAdapter(postgres.url(), 'geometric_test')
adapter.field_shapes = {'path': 5}
adapter.field_names = {4: 'path2'}
expected = np.array([((1.1, 2.2),
[1, 2, 3],
[1, 2, 3, 4],
[3, 4, 1, 2],
[(1, 2), (3, 4), (5, 6), (0, 0), (0, 0)],
[(1.0, 2.0), (3.0, 4.0), (5.0, 6.0)],
[1, 2, 3])],
dtype=[(str('point'), 'f8', 2),
(str('line'), 'f8', 3),
(str('lseg'), 'f8', 4),
(str('box'), 'f8', 4),
(str('path2'), 'f8', (5, 2)),
(str('polygon'), 'O'),
(str('circle'), 'f8', 3)])
result = adapter[:]
np.testing.assert_array_equal(expected, result)
adapter.field_shapes = {'path2': 5}
result = adapter[:]
np.testing.assert_array_equal(expected, result)
adapter.field_shapes = {4: 5}
result = adapter[:]
np.testing.assert_array_equal(expected, result)
def test_multipolygons(self):
adapter = PostgresAdapter(self.postgresql.url(),
query='select polygon2d, polygon3d, polygon4d from multipolygons')
adapter.field_shapes = {'polygon3d': (2, 4, 5), 'polygon4d': (2, 3, 4)}
result = adapter[:]
expected = np.array([('MULTIPOLYGON (((0.000000 1.000000, 2.000000 3.000000, 4.000000 5.000000, 0.000000 1.000000), '
'(0.000000 1.000000, 2.000000 3.000000, 4.000000 5.000000, 0.000000 1.000000), '
'(0.000000 1.000000, 2.000000 3.000000, 4.000000 5.000000, 0.000000 1.000000)), '
'((0.000000 1.000000, 2.000000 3.000000, 4.000000 5.000000, 0.000000 1.000000), '
'(0.000000 1.000000, 2.000000 3.000000, 4.000000 5.000000, 0.000000 1.000000), '
'(0.000000 1.000000, 2.000000 3.000000, 4.000000 5.000000, 0.000000 1.000000)))',
[[[[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 1, 2], [0, 0, 0]],
[[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 1, 2], [0, 0, 0]],
[[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 1, 2], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]],
[[[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 1, 2], [0, 0, 0]],
[[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 1, 2], [0, 0, 0]],
[[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 1, 2], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]]],
[[[(0, 1, 2, 3), (4, 5, 6, 7), (8, 9, 10, 11), (0, 1, 2, 3)],
[(0, 1, 2, 3), (4, 5, 6, 7), (8, 9, 10, 11), (0, 1, 2, 3)],
[(0, 1, 2, 3), (4, 5, 6, 7), (8, 9, 10, 11), (0, 1, 2, 3)]],
[[(0, 1, 2, 3), (4, 5, 6, 7), (8, 9, 10, 11), (0, 1, 2, 3)],
[(0, 1, 2, 3), (4, 5, 6, 7), (8, 9, 10, 11), (0, 1, 2, 3)],
[(0, 1, 2, 3), (4, 5, 6, 7), (8, 9, 10, 11), (0, 1, 2, 3)]]])],
dtype=[('polygon2d', 'O'),
('polygon3d', 'f8', (2, 4, 5, 3)),
('polygon4d', 'f8', (2, 3, 4, 4))])
np.testing.assert_array_equal(expected, result)
def test_multilines(self):
adapter = PostgresAdapter(self.postgresql.url(),
query='select line2d, line3d, line4d from multilines')
adapter.field_shapes = {'line3d': (2, 3), 'line4d': (2, 2)}
result = adapter[:]
expected = np.array([('MULTILINESTRING ((0.000000 1.000000, 2.000000 3.000000), '
'(4.000000 5.000000, 6.000000 7.000000))',
[[[0, 1, 2], [3, 4, 5], [0, 0, 0]], [[6, 7, 8], [9, 10, 11], [12, 13, 14]]],
[[(0, 1, 2, 3), (4, 5, 6, 7)], [(8, 9, 10, 11), (12, 13, 14, 15)]])],
dtype=[('line2d', 'O'),
('line3d', 'f8', (2, 3, 3)),
('line4d', 'f8', (2, 2, 4))])
np.testing.assert_array_equal(expected, result)
def test_multipoints(self):
adapter = PostgresAdapter(self.postgresql.url(),
query='select point2d, point3d, point4d from multipoints')
adapter.field_shapes = {'point2d': 1, 'point3d': 4}
result = adapter[:]
expected = np.array([([[0, 1]],
[[0, 1, 2], [3, 4, 5], [0, 0, 0], [0, 0, 0]],
'MULTIPOINT ((0.000000 1.000000 2.000000 3.000000), '
'(4.000000 5.000000 6.000000 7.000000))')],
dtype=[('point2d', 'f8', (1, 2)),
('point3d', 'f8', (4, 3)),
('point4d', 'O')])
np.testing.assert_array_equal(expected, result)
def test_lines(self):
adapter = PostgresAdapter(self.postgresql.url(),
query='select line2d, line3d, line4d from lines')
adapter.field_shapes = {'line2d': 1, 'line3d': 3}
result = adapter[:]
expected = np.array([([[0.0, 1.0]],
[[0.0, 1.0, 2.0], [3.0, 4.0, 5.0], [0.0, 0.0, 0.0]],
'LINESTRING (0.000000 1.000000 2.000000 3.000000, '
'4.000000 5.000000 6.000000 7.000000)'),
([[0.0, 1.0]],
[[0.0, 1.0, 2.0], [3.0, 4.0, 5.0], [6.0, 7.0, 8.0]],
'LINESTRING (0.000000 1.000000 2.000000 3.000000, '
'4.000000 5.000000 6.000000 7.000000)')],
dtype=[('line2d', 'f8', (1,2)),
('line3d', 'f8', (3,3)),
('line4d', 'O')])
np.testing.assert_array_equal(expected, result)
def test_polygons(postgres):
adapter = PostgresAdapter(postgres.url(),
query='select polygon2d, polygon3d, polygon4d from polygons')
adapter.field_shapes = {'polygon3d': (4, 5), 'polygon4d': (3, 4)}
result = adapter[:]
expected = np.array([('POLYGON ((0.000000 1.000000, 2.000000 3.000000, 4.000000 5.000000, 0.000000 1.000000), '
'(0.000000 1.000000, 2.000000 3.000000, 4.000000 5.000000, 0.000000 1.000000), '
'(0.000000 1.000000, 2.000000 3.000000, 4.000000 5.000000, 0.000000 1.000000))',
[[[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 1, 2], [0, 0, 0]],
[[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 1, 2], [0, 0, 0]],
[[0, 1, 2], [3, 4, 5], [6, 7, 8], [0, 1, 2], [0, 0, 0]],
[[0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 0]]],
[[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [0, 1, 2, 3]],
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [0, 1, 2, 3]],
[[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11], [0, 1, 2, 3]]])],
dtype=[('polygon2d', 'O'),
('polygon3d', 'f8', (4, 5, 3)),
('polygon4d', 'f8', (3, 4, 4))])
np.testing.assert_array_equal(expected, result)
def test_dataframe(postgres):
adapter = PostgresAdapter(postgres.url(), table='ints_test', dataframe=True)
expected = pd.DataFrame({'int2': np.array([np.iinfo(np.int16).min, 0, np.iinfo(np.int16).max], dtype='i2'),
'int4': np.array([np.iinfo(np.int32).min, 0, np.iinfo(np.int32).max], dtype='i4'),
'int8': np.array([np.iinfo(np.int64).min, 0, np.iinfo(np.int64).max], dtype='i8')})
result = adapter[:]
np.testing.assert_array_equal(expected, result)
adapter = PostgresAdapter(postgres.url(), 'casts_test', dataframe=True)
expected = np.zeros((CASTS_TEST_NUM_RECORDS,), dtype=[(str('char'), str('O')),
(str('int4'), str('i4')),
(str('float8'), str('f8'))])
for i in range(CASTS_TEST_NUM_RECORDS):
expected[i] = (str(i).ljust(10), i, float('{0}.{0}'.format(i)))
expected = pd.DataFrame.from_records(expected, index=np.arange(CASTS_TEST_NUM_RECORDS, dtype='u8'))
result = adapter[:]
assert_frame_equal(expected, result)
adapter = PostgresAdapter(postgres.url(), 'casts_test', dataframe=True, field_filter=['int4', 'float8'])
adapter.field_types = ['i2', 'f4']
adapter.field_names = ['a', 'b']
expected = np.zeros((CASTS_TEST_NUM_RECORDS,), dtype=[(str('a'), str('i2')), (str('b'), str('f4'))])
for i in range(CASTS_TEST_NUM_RECORDS):
expected[i] = (i, float('{0}.{0}'.format(i)))
expected = pd.DataFrame.from_records(expected, index=np.arange(CASTS_TEST_NUM_RECORDS, dtype='u8'))
result = adapter[:]
assert_frame_equal(expected, result)
adapter.field_types = {'a': 'f4'}
expected = np.zeros((CASTS_TEST_NUM_RECORDS,), dtype=[(str('a'), str('f4')), (str('b'), str('f8'))])
for i in range(CASTS_TEST_NUM_RECORDS):
expected[i] = (i, float('{0}.{0}'.format(i)))
expected = pd.DataFrame.from_records(expected, index=np.arange(CASTS_TEST_NUM_RECORDS, dtype='u8'))
result = adapter[:]
assert_frame_equal(expected, result)
adapter = PostgresAdapter(postgres.url(),
'geometric_test',
dataframe=True,
field_filter=['point', 'line', 'polygon'])
result = adapter[:]
point_data = np.empty(1, dtype='O')
point_data[0] = [1.1, 2.2]
line_data = np.empty(1, dtype='O')
line_data[0] = [1.0, 2.0, 3.0]
polygon_data = np.empty(1, dtype='O')
polygon_data[0] = [(1.0, 2.0), (3.0, 4.0), (5.0, 6.0)]
expected = pd.DataFrame(OrderedDict([('point', point_data),
('line', line_data),
('polygon', polygon_data)]),
index=np.array([0], dtype='u8'))
assert_frame_equal(expected, result)
adapter = PostgresAdapter(postgres.url(), 'fixed_strings_test', dataframe=True)
result = adapter[:]
expected = pd.DataFrame(['aaa ', 'bbb ', 'ccc '],
columns=['fixed'],
index=np.array([0, 1, 2], dtype='u8'))
assert_frame_equal(expected, result)
with pytest.raises(RuntimeError):
adapter.field_shapes = {'fixed': 2}
adapter.field_shapes = {'fixed': 2}
def test_missing_values(postgres):
# Don't test missing values for PostGIS types for now. Since PostGIS type metadata
# is stored by postgresql as actual data in the record, an empty or missing
# value in a PostGIS column contains no metadata about what type it
# actually is (and postgresql doesn't know about GIS types so doesn't
# store that column metadata anywhere). In order to handle missing data
# for PostGIS types, we'll probably need to come up with some sort of
<<<<<<< HEAD
# generic PostGIS object or dtype which can be set to NULL for ***REMOVED***
=======
# generic PostGIS object or dtype which can be set to NULL for missing data.
>>>>>>> 14dcbb9542f8d05344fd4a2cc4ef07c47528a8f1
adapter = PostgresAdapter(postgres.url(), table='missing_values_test')
adapter.field_shapes = {'path': 2}
result = adapter[:]
expected = np.array([('', 0, np.nan, [np.nan, np.nan], [(np.nan, np.nan), (np.nan, np.nan)], [])],
dtype=[(str('char'), str('U5')),
(str('int4'), str('i4')),
(str('float4'), str('f4')),
(str('point'), str('f8'), 2),
(str('path'), str('f8'), (2, 2)),
(str('polygon'), str('O'))])
assert expected.dtype == result.dtype
assert result[0][0] == ''
assert result[0][1] == 0
assert np.isnan(result[0][2])
assert np.isnan(result[0][3][0])
assert np.isnan(result[0][3][1])
assert np.isnan(result[0][4][0][0])