def test_write_archive(self, delete=True):
data.add_timeseries(TEST_DATA)
fname = tempfile.mktemp(suffix='.hdf', prefix='gwsumm-tests-')
try:
archive.write_data_archive(fname)
finally:
if delete and os.path.isfile(fname):
os.remove(fname)
return fname
def test_write_archive(self, delete=True):
data.add_timeseries(TEST_DATA)
fname = tempfile.mktemp(suffix='.hdf', prefix='gwsumm-tests-')
try:
archive.write_data_archive(fname)
finally:
if delete and os.path.isfile(fname):
os.remove(fname)
return fname
def test_get_timeseries(self):
# test simple get after add
a = TimeSeries([1, 2, 3, 4, 5], name='test name', epoch=0,
sample_rate=1)
data.add_timeseries(a)
b = data.get_timeseries('test name', [(0, 5)])
self.assertEqual(a, b)
# test more complicated add with a cache
a = data.get_timeseries('H1:LOSC-STRAIN', LOSC_SEGMENTS,
cache=self.FRAMES['H1:LOSC-STRAIN'])
b = data.get_timeseries('H1:LOSC-STRAIN', LOSC_SEGMENTS)
self.assertEqual(a, b)
def test_get_timeseries(self):
# test simple get after add
a = TimeSeries([1, 2, 3, 4, 5],
name='test name',
epoch=0,
sample_rate=1)
data.add_timeseries(a)
b = data.get_timeseries('test name', [(0, 5)])
self.assertEqual(a, b)
# test more complicated add with a cache
a = data.get_timeseries('H1:LOSC-STRAIN',
LOSC_SEGMENTS,
cache=self.FRAMES['H1:LOSC-STRAIN'])
b = data.get_timeseries('H1:LOSC-STRAIN', LOSC_SEGMENTS)
self.assertEqual(a, b)
def test_get_timeseries(self):
# empty globalv.DATA
globalv.DATA = type(globalv.DATA)()
# test simple get after add
a = TimeSeries([1, 2, 3, 4, 5], name='test name', epoch=0,
sample_rate=1)
data.add_timeseries(a)
b, = data.get_timeseries('test name', [(0, 5)], nproc=1)
nptest.assert_array_equal(a.value, b.value)
assert a.sample_rate.value == b.sample_rate.value
# test more complicated add with a cache
a, = data.get_timeseries('H1:LOSC-STRAIN', LOSC_SEGMENTS,
cache=self.FRAMES['H1:LOSC-STRAIN'],
nproc=1)
b, = data.get_timeseries('H1:LOSC-STRAIN', LOSC_SEGMENTS,
nproc=1)
nptest.assert_array_equal(a.value, b.value)
def test_get_timeseries(self):
# empty globalv.DATA
globalv.DATA = type(globalv.DATA)()
# test simple get after add
a = TimeSeries([1, 2, 3, 4, 5],
name='test name',
epoch=0,
sample_rate=1)
data.add_timeseries(a)
b, = data.get_timeseries('test name', [(0, 5)], nproc=1)
nptest.assert_array_equal(a.value, b.value)
assert a.sample_rate.value == b.sample_rate.value
# test more complicated add with a cache
a, = data.get_timeseries('H1:LOSC-STRAIN',
LOSC_SEGMENTS,
cache=self.FRAMES['H1:LOSC-STRAIN'],
nproc=1)
b, = data.get_timeseries('H1:LOSC-STRAIN', LOSC_SEGMENTS, nproc=1)
nptest.assert_array_equal(a.value, b.value)
def test_add_timeseries(self):
a = TimeSeries([1, 2, 3, 4, 5],
name='test name',
epoch=0,
sample_rate=1)
# test simple add using 'name'
data.add_timeseries(a)
assert 'test name' in globalv.DATA
assert len(globalv.DATA['test name']) == 1
assert globalv.DATA['test name'][0] is a
# test add using key kwarg
data.add_timeseries(a, key='test key')
assert globalv.DATA['test key'][0] is a
# test add to existing key with coalesce
b = TimeSeries([6, 7, 8, 9, 10],
name='test name 2',
epoch=5,
sample_rate=1)
data.add_timeseries(b, key='test key', coalesce=True)
assert len(globalv.DATA['test key']) == 1
nptest.assert_array_equal(globalv.DATA['test key'][0].value,
arange(1, 11))
def test_add_timeseries(self):
a = TimeSeries([1, 2, 3, 4, 5], name='test name', epoch=0,
sample_rate=1)
# test simple add using 'name'
data.add_timeseries(a)
self.assertIn('test name', globalv.DATA)
self.assertEqual(globalv.DATA['test name'], [a])
# test add using key kwarg
data.add_timeseries(a, key='test key')
self.assertIn('test key', globalv.DATA)
self.assertEqual(globalv.DATA['test key'], [a])
# test add to existing key with coalesce
b = TimeSeries([6, 7, 8, 9, 10], name='test name 2', epoch=5,
sample_rate=1)
data.add_timeseries(b, key='test key', coalesce=True)
self.assertEqual(globalv.DATA['test key'],
[a.append(b, inplace=False)])
def test_add_timeseries(self):
a = TimeSeries([1, 2, 3, 4, 5], name='test name', epoch=0,
sample_rate=1)
# test simple add using 'name'
data.add_timeseries(a)
assert 'test name' in globalv.DATA
assert len(globalv.DATA['test name']) == 1
assert globalv.DATA['test name'][0] is a
# test add using key kwarg
data.add_timeseries(a, key='test key')
assert globalv.DATA['test key'][0] is a
# test add to existing key with coalesce
b = TimeSeries([6, 7, 8, 9, 10], name='test name 2', epoch=5,
sample_rate=1)
data.add_timeseries(b, key='test key', coalesce=True)
assert len(globalv.DATA['test key']) == 1
nptest.assert_array_equal(globalv.DATA['test key'][0].value,
arange(1, 11))
def test_add_timeseries(self):
a = TimeSeries([1, 2, 3, 4, 5],
name='test name',
epoch=0,
sample_rate=1)
# test simple add using 'name'
data.add_timeseries(a)
self.assertIn('test name', globalv.DATA)
self.assertEqual(globalv.DATA['test name'], [a])
# test add using key kwarg
data.add_timeseries(a, key='test key')
self.assertIn('test key', globalv.DATA)
self.assertEqual(globalv.DATA['test key'], [a])
# test add to existing key with coalesce
b = TimeSeries([6, 7, 8, 9, 10],
name='test name 2',
epoch=5,
sample_rate=1)
data.add_timeseries(b, key='test key', coalesce=True)
self.assertEqual(globalv.DATA['test key'],
[a.append(b, inplace=False)])
def test_write_archive(delete=True):
empty_globalv()
data.add_timeseries(TEST_DATA)
data.add_timeseries(create([1, 2, 3, 4, 5],
dt=60., channel='X1:TEST-TREND.mean'))
data.add_timeseries(create([1, 2, 3, 2, 1],
series_class=StateVector,
channel='X1:TEST-STATE_VECTOR'))
data.add_spectrogram(create([[1, 2, 3], [3, 2, 1], [1, 2, 3]],
series_class=Spectrogram,
channel='X1:TEST-SPECTROGRAM'))
t = EventTable(random.random((100, 5)), names=['time', 'a', 'b', 'c', 'd'])
t.meta['segments'] = SegmentList([Segment(0, 100)])
triggers.add_triggers(t, 'X1:TEST-TABLE,testing')
fname = tempfile.mktemp(suffix='.h5', prefix='gwsumm-tests-')
try:
archive.write_data_archive(fname)
archive.write_data_archive(fname) # test again to validate backups
finally:
if delete and os.path.isfile(fname):
os.remove(fname)
return fname
def test_write_archive(delete=True):
empty_globalv()
data.add_timeseries(TEST_DATA)
data.add_timeseries(create([1, 2, 3, 4, 5],
dt=60., channel='X1:TEST-TREND.mean'))
data.add_timeseries(create([1, 2, 3, 2, 1],
series_class=StateVector,
channel='X1:TEST-STATE_VECTOR'))
data.add_spectrogram(create([[1, 2, 3], [3, 2, 1], [1, 2, 3]],
series_class=Spectrogram,
channel='X1:TEST-SPECTROGRAM'))
t = EventTable(random.random((100, 5)), names=['time', 'a', 'b', 'c', 'd'])
t.meta['segments'] = SegmentList([Segment(0, 100)])
triggers.add_triggers(t, 'X1:TEST-TABLE,testing')
fname = tempfile.mktemp(suffix='.h5', prefix='gwsumm-tests-')
try:
archive.write_data_archive(fname)
archive.write_data_archive(fname) # test again to validate backups
finally:
if delete and os.path.isfile(fname):
os.remove(fname)
return fname
