def test_regexp(self):
sequence = SequenceType("sequence")
sequence["name"] = BaseType("name")
sequence.data = IterData([
("John", "Paul", "George", "Ringo"),
], sequence)
filtered = sequence[ConstraintExpression('sequence.name=~"J.*"')]
self.assertEqual(list(filtered.iterdata()), [("John", )])
def setUp(self):
self.nested_object = IterData(
("nested", ("a", "b", "c",
("d", ("e", "f", "g")))), [(1, 1, 1, [(10, 11, 12),
(21, 22, 23)]),
(2, 4, 4, [(15, 16, 17)]),
(3, 6, 9, []),
(4, 8, 16, [(31, 32, 33),
(41, 42, 43),
(51, 52, 53),
(61, 62, 63)])])
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 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 setUp(self):
"""Create a flat IterData."""
template = SequenceType("a")
template["b"] = BaseType("b")
template["c"] = BaseType("c")
template["d"] = BaseType("d")
self.data = IterData([(1, 2, 3), (4, 5, 6)], template)
self.array = np.array(
np.rec.fromrecords([
(1, 2, 3),
(4, 5, 6),
], names=["b", "c", "d"]))
def unpack_children(stream, template):
"""Unpack children from a structure, returning their data."""
cols = list(template.children()) or [template]
out = []
for col in cols:
# sequences and other structures
if isinstance(col, SequenceType):
out.append(IterData(list(unpack_sequence(stream, col)), col))
elif isinstance(col, StructureType):
out.append(tuple(unpack_children(stream, col)))
# unpack arrays
elif col.shape:
n = np.fromstring(stream.read(4), ">I")[0]
count = col.dtype.itemsize * n
if col.dtype.char in "SU":
data = []
for _ in range(n):
k = np.fromstring(stream.read(4), ">I")[0]
data.append(stream.read(k))
stream.read(-k % 4)
out.append(np.array(text_type(data), dtype='S'))
else:
stream.read(4) # read additional length
out.append(
np.fromstring(stream.read(count),
col.dtype).reshape(col.shape))
if col.dtype.char == "B":
stream.read(-n % 4)
# special types: strings and bytes
elif col.dtype.char in 'SU':
n = np.fromstring(stream.read(4), '>I')[0]
out.append(stream.read(n).decode('ascii'))
stream.read(-n % 4)
elif col.dtype.char == 'B':
data = np.fromstring(stream.read(1), col.dtype)[0]
stream.read(3)
out.append(data)
# usual data
else:
out.append(
np.fromstring(stream.read(col.dtype.itemsize), col.dtype)[0])
return out
def setUp(self):
self.simple_array = 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')])
self.simple_object = IterData(("simple", ("byte", "int", "float")),
[(0, 1, 10.), (1, 2, 20.), (2, 3, 30.),
(3, 4, 40.), (4, 5, 50.), (5, 6, 60.),
(6, 7, 70.), (7, 8, 80.)])
('int', 'i4'),
('float', 'f4')])
# A nested sequence.
NestedSequence = DatasetType("NestedSequence")
NestedSequence["location"] = SequenceType("location")
NestedSequence["location"]["lat"] = BaseType("lat")
NestedSequence["location"]["lon"] = BaseType("lon")
NestedSequence["location"]["elev"] = BaseType("elev")
NestedSequence["location"]["time_series"] = SequenceType("time_series")
NestedSequence["location"]["time_series"]["time"] = BaseType("time")
NestedSequence["location"]["time_series"]["slp"] = BaseType("slp")
NestedSequence["location"]["time_series"]["wind"] = BaseType("wind")
NestedSequence["location"].data = IterData([
(1, 1, 1, [(10, 11, 12), (21, 22, 23)]),
(2, 4, 4, [(15, 16, 17)]),
(3, 6, 9, []),
(4, 8, 16, [(31, 32, 33), (41, 42, 43), (51, 52, 53), (61, 62, 63)]),
], NestedSequence.location)
# A simple array with bytes, strings and shorts. These types require special
# encoding for the DODS response.
SimpleArray = DatasetType("SimpleArray")
SimpleArray["byte"] = BaseType("byte", np.arange(5, dtype="b"))
SimpleArray["string"] = BaseType("string", np.array(["one", "two"]))
SimpleArray["short"] = BaseType("short", np.array(1, dtype="h"))
DODS = os.path.join(os.path.dirname(__file__),
'rainfall_time_malaysia.cdp.dods')
DAS = os.path.join(os.path.dirname(__file__), 'rainfall_time_malaysia.cdp.das')
dapper = open_file(DODS, DAS)