def test_veto_flag(self):
d = query_flag('L1',
'data',
1126051217,
1126051217 + 100000,
cache=True)
v1n = query_flag('L1',
'CBC_HW_INJ',
1126051217,
1126051217 + 100000,
cache=True)
v1 = query_flag('L1',
'CBC_HW_INJ',
1126051217,
1126051217 + 100000,
cache=True)
self.assertTrue(abs((v1 + v1n).coalesce() - d) == 0)
v2n = query_flag('L1',
'CBC_CAT2',
1126051217,
1126051217 + 100000,
cache=True)
v2 = query_flag('L1',
'CBC_CAT2_VETO',
1126051217,
1126051217 + 100000,
cache=True)
self.assertTrue(abs((v2 + v2n).coalesce() - d) == 0)
def test_query_str(self):
d = query_flag('H1', 'data', 1126051217, 1126051217 + 100000)
d1 = query_str('H1', '+data', 1126051217, 1126051217 + 100000)
d2 = query_str('H1', '+H1:data', 1126051217, 1126051217 + 100000)
d3 = query_str('H1', '+data[1126051217:1127051217]', 1126051217,
1126051217 + 100000)
d4 = query_str('H1', '+data<0:0>[1126051217:1127051217]', 1126051217,
1126051217 + 100000)
self.assertTrue(abs(d - d1) == 0)
self.assertTrue(abs(d - d2) == 0)
self.assertTrue(abs(d - d3) == 0)
self.assertTrue(abs(d - d4) == 0)
d5 = query_str('L1', '+data', 1126051217, 1126051217 + 100000)
d6 = query_str('H1', '+L1:data', 1126051217, 1126051217 + 100000)
self.assertTrue(abs(d5 - d6) == 0)
d7 = query_flag('H1',
'CBC_HW_INJ',
1126051217,
1126051217 + 100000,
cache=True)
d8 = query_str('H1', '+data,-CBC_HW_INJ', 1126051217,
1126051217 + 100000)
self.assertTrue(abs((d - d7) - d8) == 0)
def test_cumulative_query(self):
segs1 = query_flag('H1', 'CBC_HW_INJ',
1126051217, 1126051217 + 100000, cache=True)
segs2 = query_flag('H1', 'BURST_HW_INJ',
1126051217, 1126051217 + 100000, cache=True)
segs = query_cumulative_flags('H1', ['CBC_HW_INJ', 'BURST_HW_INJ'],
1126051217, 1126051217 + 100000, cache=True)
csegs = (segs1 + segs2).coalesce()
self.assertTrue(abs(csegs - segs) == 0)
def test_veto_flag(self):
d = query_flag('L1', 'data', 1126051217, 1126051217 + 100000, cache=True)
v1n = query_flag('L1', 'CBC_HW_INJ', 1126051217, 1126051217 + 100000, cache=True)
v1 = query_flag('L1', 'CBC_HW_INJ', 1126051217, 1126051217 + 100000, cache=True)
self.assertTrue(abs((v1 + v1n).coalesce() - d) == 0)
v2n = query_flag('L1', 'CBC_CAT2', 1126051217, 1126051217 + 100000, cache=True)
v2 = query_flag('L1', 'CBC_CAT2_VETO', 1126051217, 1126051217 + 100000, cache=True)
self.assertTrue(abs((v2 + v2n).coalesce() - d) == 0)
def test_direct_query(self):
segs = query_flag('H1',
'DATA',
1126051217,
1126051217 + 100000,
cache=True)
self.assertTrue(len(segs) > 0)
def test_direct_empty_return(self):
segs = query_flag('H1',
'DATA',
1126051217,
1126051217 + 1000,
cache=True)
self.assertTrue(len(segs) == 0)
def test_cumulative_query(self):
segs1 = query_flag('H1',
'CBC_HW_INJ',
1126051217,
1126051217 + 100000,
cache=True)
segs2 = query_flag('H1',
'BURST_HW_INJ',
1126051217,
1126051217 + 100000,
cache=True)
segs = query_cumulative_flags('H1', ['CBC_HW_INJ', 'BURST_HW_INJ'],
1126051217,
1126051217 + 100000,
cache=True)
csegs = (segs1 + segs2).coalesce()
self.assertTrue(abs(csegs - segs) == 0)
def test_query_str(self):
d = query_flag('H1', 'data', 1126051217, 1126051217 + 100000)
d1 = query_str('H1', '+data', 1126051217, 1126051217 + 100000)
d2 = query_str('H1', '+H1:data', 1126051217, 1126051217 + 100000)
d3 = query_str('H1', '+data:1', 1126051217, 1126051217 + 100000)
d4 = query_str('H1', '+data<0:0>[1126051217:1127051217]', 1126051217, 1126051217 + 100000)
self.assertTrue(abs(d - d1) == 0)
self.assertTrue(abs(d - d2) == 0)
self.assertTrue(abs(d - d3) == 0)
self.assertTrue(abs(d - d4) == 0)
d5 = query_str('L1', '+data', 1126051217, 1126051217 + 100000)
d6 = query_str('H1', '+L1:data', 1126051217, 1126051217 + 100000)
self.assertTrue(abs(d5 - d6) == 0)
d7 = query_flag('H1', 'CBC_HW_INJ',
1126051217, 1126051217 + 100000, cache=True)
d8 = query_str('H1', '+data,-CBC_HW_INJ', 1126051217, 1126051217 + 100000)
self.assertTrue(abs((d-d7) - d8) == 0)
"""This example shows how to determine when a CBC hardware injection is present
in the data from a detector.
"""
import matplotlib.pyplot as pp
from pycbc import dq
start_time = 1126051217
end_time = start_time + 10000000
# Get times that the Livingston detector has CBC injections into the data
segs = dq.query_flag('L1', 'CBC_HW_INJ', start_time, end_time)
pp.figure(figsize=[10, 2])
for seg in segs:
start, end = seg
pp.axvspan(start, end, color='blue')
pp.xlabel('Time (s)')
pp.show()
def test_direct_query(self):
segs = query_flag('H1', 'DATA', 1126051217, 1126051217 + 100000, cache=True)
self.assertTrue(len(segs) > 0)
def test_direct_empty_return(self):
segs = query_flag('H1', 'DATA', 1126051217, 1126051217 + 1000, cache=True)
self.assertTrue(len(segs) == 0)
def check_validtimes(detector,
gps_start,
gps_end,
shift_to_valid=False,
max_shift=None,
segment_name='DATA',
**kwargs):
r"""Checks DQ server to see if the given times are in a valid segment.
If the ``shift_to_valid`` flag is provided, the times will be shifted left
or right to try to find a continous valid block nearby. The shifting starts
by shifting the times left by 1 second. If that does not work, it shifts
the times right by one second. This continues, increasing the shift time by
1 second, until a valid block could be found, or until the shift size
exceeds ``max_shift``.
If the given times are not in a continuous valid segment, or a valid block
cannot be found nearby, a ``NoValidDataError`` is raised.
Parameters
----------
detector : str
The name of the detector to query; e.g., 'H1'.
gps_start : int
The GPS start time of the segment to query.
gps_end : int
The GPS end time of the segment to query.
shift_to_valid : bool, optional
If True, will try to shift the gps start and end times to the nearest
continous valid segment of data. Default is False.
max_shift : int, optional
The maximum number of seconds to try to shift left or right to find
a valid segment. Default is ``gps_end - gps_start``.
segment_name : str, optional
The status flag to query; passed to :py:func:`pycbc.dq.query_flag`.
Default is "DATA".
\**kwargs :
All other keyword arguments are passed to
:py:func:`pycbc.dq.query_flag`.
Returns
-------
use_start : int
The start time to use. If ``shift_to_valid`` is True, this may differ
from the given GPS start time.
use_end : int
The end time to use. If ``shift_to_valid`` is True, this may differ
from the given GPS end time.
"""
# expand the times checked encase we need to shift
if max_shift is None:
max_shift = int(gps_end - gps_start)
check_start = gps_start - max_shift
check_end = gps_end + max_shift
# if we're running in an mpi enviornment and we're not the parent process,
# we'll wait before quering the segment database. This will result in
# getting the segments from the cache, so as not to overload the database
if MPI is not None and (MPI.COMM_WORLD.Get_size() > 1
and MPI.COMM_WORLD.Get_rank() != 0):
# we'll wait for 2 minutes
sleep(120)
validsegs = dq.query_flag(detector,
segment_name,
check_start,
check_end,
cache=True,
**kwargs)
use_start = gps_start
use_end = gps_end
# shift if necessary
if shift_to_valid:
shiftsize = 1
while (use_start, use_end) not in validsegs and shiftsize < max_shift:
# try shifting left
use_start = gps_start - shiftsize
use_end = gps_end - shiftsize
if (use_start, use_end) not in validsegs:
# try shifting right
use_start = gps_start + shiftsize
use_end = gps_end + shiftsize
shiftsize += 1
# check that we have a valid range
if (use_start, use_end) not in validsegs:
raise NoValidDataError("Could not find a continous valid segment in "
"in detector {}".format(detector))
return use_start, use_end
"""This example shows how to determine when a detector is active."""
import matplotlib.pyplot as pp
from pycbc import dq
from pycbc.results import ifo_color
start_time = 1126051217
end_time = start_time + 100000
# Get times that the Hanford detector has data
hsegs = dq.query_flag('H1', 'DATA', start_time, end_time)
# Get times that the Livingston detector has data
lsegs = dq.query_flag('L1', 'DATA', start_time, end_time)
pp.figure(figsize=[10, 2])
for seg in lsegs:
start, end = seg
pp.axvspan(start, end, color=ifo_color('L1'), ymin=0.1, ymax=0.4)
for seg in hsegs:
start, end = seg
pp.axvspan(start, end, color=ifo_color('H1'), ymin=0.6, ymax=0.9)
pp.xlabel('Time (s)')
pp.show()
