/usr/lib/python3/dist-packages/pydap/tests/test_iter_data.py is in python3-pydap 3.2.2+ds1-1ubuntu1.
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import numpy as np
from pydap.handlers.lib import IterData
from pydap.model import DatasetType, SequenceType, BaseType
import sys
import pytest
@pytest.fixture
def simple_array():
arr = np.array([
(0, 1, 10.),
(1, 2, 20.),
(2, 3, 30.),
(3, 4, 40.),
(4, 5, 50.),
(5, 6, 60.),
(6, 7, 70.),
(7, 8, 80.),
], dtype=[('byte', 'b'), ('int', 'i4'), ('float', 'f4')])
return arr
@pytest.fixture
def simple_object(simple_array):
# add sequence and children for each column
name = 'nameless'
dataset = DatasetType(name)
seq = dataset['sequence'] = SequenceType('sequence')
for var in simple_array.dtype.names:
seq[var] = BaseType(var)
obj = IterData([(0, 1, 10.),
(1, 2, 20.),
(2, 3, 30.),
(3, 4, 40.),
(4, 5, 50.),
(5, 6, 60.),
(6, 7, 70.),
(7, 8, 80.)],
seq)
return obj
def test_iter(simple_array, simple_object):
assert ([tuple(row)
for row in simple_array] ==
[(0, 1, 10.), (1, 2, 20.),
(2, 3, 30.), (3, 4, 40.),
(4, 5, 50.), (5, 6, 60.),
(6, 7, 70.), (7, 8, 80.)])
assert (list(simple_array["byte"]) ==
[0, 1, 2, 3, 4, 5, 6, 7])
assert ([tuple(row) for row in simple_object] ==
[(0, 1, 10.), (1, 2, 20.),
(2, 3, 30.), (3, 4, 40.),
(4, 5, 50.), (5, 6, 60.),
(6, 7, 70.), (7, 8, 80.)])
assert (list(simple_object["byte"]) ==
[0, 1, 2, 3, 4, 5, 6, 7])
little_endian = pytest.mark.skipif(sys.byteorder != 'little', reason="assumes little endian")
intfour = pytest.mark.skipif(sys.int_info[1] != 4, reason="assumes sizeof_digit is four")
@little_endian
@intfour
def test_dtype(simple_array, simple_object):
assert (
simple_array.dtype ==
np.dtype([('byte', 'i1'), ('int', '<i4'), ('float', '<f4')]))
assert (simple_array["int"].dtype == "<i4")
assert (
simple_object.dtype ==
np.dtype([('byte', '<i8'), ('int', '<i8'), ('float', '<f8')]))
assert (simple_object["int"].dtype == "<i8")
def test_selection(simple_array, simple_object):
selection = simple_array[simple_array["byte"] > 3]
assert ([tuple(row) for row in selection] ==
[(4, 5, 50.), (5, 6, 60.),
(6, 7, 70.), (7, 8, 80.)])
selection = simple_object[simple_object["byte"] > 3]
assert ([tuple(row) for row in selection] ==
[(4, 5, 50.), (5, 6, 60.),
(6, 7, 70.), (7, 8, 80.)])
def test_projection(simple_array, simple_object):
projection = simple_array[1::2]
assert ([tuple(row) for row in projection] ==
[(1, 2, 20.), (3, 4, 40.),
(5, 6, 60.), (7, 8, 80.)])
assert (
list(simple_array["byte"][1::2]) == [1, 3, 5, 7])
assert (
list(simple_array[1::2]["byte"]) == [1, 3, 5, 7])
projection = simple_object[1::2]
assert ([tuple(row) for row in projection] ==
[(1, 2, 20.), (3, 4, 40.),
(5, 6, 60.), (7, 8, 80.)])
assert (
list(simple_object["byte"][1::2]) == [1, 3, 5, 7])
assert (
list(simple_object[1::2]["byte"]) == [1, 3, 5, 7])
def test_combined(simple_array, simple_object):
filtered = simple_array[simple_array["byte"] > 1]
filtered = filtered[filtered["byte"] < 6]
filtered = filtered[::2]
assert ([tuple(row) for row in filtered] ==
[(2, 3, 30.), (4, 5, 50.)])
filtered = simple_object[simple_object["byte"] > 1]
filtered = filtered[filtered["byte"] < 6]
filtered = filtered[::2]
assert ([tuple(row) for row in filtered] ==
[(2, 3, 30.), (4, 5, 50.)])
@pytest.fixture
def nested_data():
shallow_data = [(1, 1, 1), (2, 4, 4),
(3, 6, 9), (4, 8, 16)]
deep_data = [[(10, 11, 12), (21, 22, 23)],
[(15, 16, 17)],
[],
[(31, 32, 33), (41, 42, 43),
(51, 52, 53), (61, 62, 63)]]
nested = [x + (deep_data[x_id],)
for x_id, x
in enumerate(shallow_data)]
return nested
@pytest.fixture
def nested_dtype():
dtype = np.dtype([('a', '<i8'), ('b', '<i8'),
('c', '<i8'),
('d', np.dtype([('e', '<i8'),
('f', '<i8'),
('g', '<i8')]))])
return dtype
@pytest.fixture
def nested_object(nested_data):
name = 'nameless'
dataset = DatasetType(name)
seq = dataset['nested'] = SequenceType('nested')
for var in ['a', 'b', 'c']:
seq[var] = BaseType(var)
seq['d'] = SequenceType('d')
for var in ['e', 'f', 'g']:
seq['d'][var] = BaseType(var)
nested = IterData(nested_data, seq)
return nested
def test_nested_iter(nested_data, nested_object):
assert ([tuple(row) for row in nested_object] ==
nested_data)
def test_nested_iter_child(nested_data, nested_object):
expected = [row[0] for row in nested_data]
assert list(nested_object["a"]) == expected
def test_nested_iter_nested_sequence(nested_data, nested_object):
expected = [row[3] for row in nested_data]
assert list(nested_object["d"]) == expected
def test_nested_iter_nested_deep_child(nested_data, nested_object):
expected = [[col[0] for col in row[3]]
for row in nested_data]
assert list(nested_object['d']['e']) == expected
@little_endian
@intfour
def test_nested_dtype(nested_dtype, nested_object):
assert nested_object.dtype == nested_dtype
def test_nested_selection(nested_data, nested_object):
selection = nested_object[nested_object["a"] > 2]
expected = [tuple(row) for row in nested_data
if row[0] > 2]
assert [tuple(row) for row in selection] == expected
def test_nested_projection(nested_data, nested_object):
projection = nested_data[1::2]
expected = [tuple(row) for row_id, row
in enumerate(nested_data)
if row_id in range(1, len(nested_data), 2)]
assert [tuple(row) for row in projection] == expected
projection = nested_object[1::2]
expected = [tuple(row) for row_id, row
in enumerate(nested_data)
if row_id in range(1, len(nested_data), 2)]
assert [tuple(row) for row in projection] == expected
def test_nested_combined(nested_data, nested_object):
filtered = [tuple(row) for row in nested_data
if row[0] > 2]
filtered = [tuple(row) for row in filtered
if row[0] < 4]
filtered = filtered[::2]
assert ([tuple(row) for row in filtered] ==
[(3, 6, 9, [])])
filtered = nested_object[nested_object["a"] > 2]
filtered = filtered[filtered["a"] < 4]
filtered = filtered[::2]
assert ([tuple(row) for row in filtered] ==
[(3, 6, 9, [])])
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