def test_append_restricted_type(self):
v = TimeSeriesReferenceVectorData(name='a', description='a')
with self.assertRaisesWith(
TypeError,
"TimeSeriesReferenceVectorData.append: incorrect type for "
"'arg' (got 'float', expected 'TimeSeriesReference')"):
v.append(2.0)
def test_get_length1_invalid_data(self):
"""Get data from a TimeSeriesReferenceVectorData with one element and invalid data"""
temp = TimeSeriesReferenceVectorData()
value = TimeSeriesReference(
-1, -1,
TimeSeries(name='test',
description='test',
data=np.arange(10),
unit='unit',
starting_time=5.0,
rate=0.1))
temp.append(value)
# test index slicing
re = temp[0]
self.assertTrue(
isinstance(
re, TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_TUPLE))
self.assertTupleEqual(
re, TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_NONE_TYPE)
# test array slicing and list slicing
selection = [slice(None), [
0,
]]
for s in selection:
re = temp[s]
self.assertTrue(isinstance(re, list))
self.assertTrue(len(re), 1)
self.assertTrue(
isinstance(
re[0],
TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_TUPLE))
self.assertTupleEqual(
re[0],
TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_NONE_TYPE)
def test_add_row_restricted_type(self):
v = TimeSeriesReferenceVectorData(name='a', description='a')
with self.assertRaisesWith(
TypeError,
"TimeSeriesReferenceVectorData.add_row: incorrect type for "
"'val' (got 'int', expected 'TimeSeriesReference')"):
v.add_row(1)
def test_init(self):
temp = TimeSeriesReferenceVectorData()
self.assertEqual(temp.name, 'timeseries')
self.assertEqual(
temp.description,
"Column storing references to a TimeSeries (rows). For each TimeSeries this "
"VectorData column stores the start_index and count to indicate the range in time "
"to be selected as well as an object reference to the TimeSeries.")
self.assertListEqual(temp.data, [])
temp = TimeSeriesReferenceVectorData(name='test', description='test')
self.assertEqual(temp.name, 'test')
self.assertEqual(temp.description, 'test')
def test_get_length1_valid_data(self):
"""Get data from a TimeSeriesReferenceVectorData with one element and valid data"""
temp = TimeSeriesReferenceVectorData()
value = TimeSeriesReference(
0, 5,
TimeSeries(name='test',
description='test',
data=np.arange(10),
unit='unit',
starting_time=5.0,
rate=0.1))
temp.append(value)
self.assertTupleEqual(temp[0], value)
self.assertListEqual(temp[:], [
TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_TUPLE(*value),
])
def test_get_length5_valid_data(self):
"""Get data from a TimeSeriesReferenceVectorData with 5 elements"""
temp = TimeSeriesReferenceVectorData()
num_values = 5
values = [
TimeSeriesReference(
0, 5,
TimeSeries(name='test' + str(i),
description='test',
data=np.arange(10),
unit='unit',
starting_time=5.0,
rate=0.1)) for i in range(num_values)
]
for v in values:
temp.append(v)
# Test single element selection
for i in range(num_values):
# test index slicing
re = temp[i]
self.assertTupleEqual(re, values[i])
# test slicing
re = temp[i:i + 1]
self.assertTupleEqual(
re[0],
TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_TUPLE(
*values[i]))
# Test multi element selection
re = temp[0:2]
self.assertTupleEqual(
re[0],
TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_TUPLE(
*values[0]))
self.assertTupleEqual(
re[1],
TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_TUPLE(
*values[1]))
def test_get_length5_with_invalid_data(self):
"""Get data from a TimeSeriesReferenceVectorData with 5 elements"""
temp = TimeSeriesReferenceVectorData()
num_values = 5
values = [
TimeSeriesReference(
0, 5,
TimeSeries(name='test' + str(i + 1),
description='test',
data=np.arange(10),
unit='unit',
starting_time=5.0,
rate=0.1)) for i in range(num_values - 2)
]
values = ([
TimeSeriesReference(
-1, -1,
TimeSeries(name='test' + str(0),
description='test',
data=np.arange(10),
unit='unit',
starting_time=5.0,
rate=0.1)),
] + values + [
TimeSeriesReference(
-1, -1,
TimeSeries(name='test' + str(5),
description='test',
data=np.arange(10),
unit='unit',
starting_time=5.0,
rate=0.1)),
])
for v in values:
temp.append(v)
# Test single element selection
for i in range(num_values):
# test index slicing
re = temp[i]
if i in [0, 4]:
self.assertTrue(
isinstance(
re, TimeSeriesReferenceVectorData.
TIME_SERIES_REFERENCE_TUPLE))
self.assertTupleEqual(
re, TimeSeriesReferenceVectorData.
TIME_SERIES_REFERENCE_NONE_TYPE)
else:
self.assertTupleEqual(re, values[i])
# test slicing
re = temp[i:i + 1]
if i in [0, 4]:
self.assertTrue(
isinstance(
re[0], TimeSeriesReferenceVectorData.
TIME_SERIES_REFERENCE_TUPLE))
self.assertTupleEqual(
re[0], TimeSeriesReferenceVectorData.
TIME_SERIES_REFERENCE_NONE_TYPE)
else:
self.assertTupleEqual(
re[0],
TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_TUPLE(
*values[i]))
# Test multi element selection
re = temp[0:2]
self.assertTupleEqual(
re[0],
TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_NONE_TYPE)
self.assertTupleEqual(
re[1],
TimeSeriesReferenceVectorData.TIME_SERIES_REFERENCE_TUPLE(
*values[1]))
def test_get_empty(self):
"""Get data from an empty TimeSeriesReferenceVectorData"""
temp = TimeSeriesReferenceVectorData()
self.assertListEqual(temp[:], [])
with self.assertRaises(IndexError):
temp[0]