def get_current_and_upcoming_variables(self, instrument_name):
"""
Fetches the instrument variables for:
- The next run number
- Upcoming run numbers
- Upcoming known experiments
as a tuple of (current_variables, upcoming_variables_by_run, upcoming_variables_by_experiment)
"""
instrument = InstrumentUtils().get_instrument(instrument_name)
completed_status = StatusUtils().get_completed()
# First, we find the latest run number to determine what's upcoming.
try:
latest_completed_run_number = ReductionRun.objects.filter(
instrument=instrument, run_version=0,
status=completed_status).order_by(
'-run_number').first().run_number
except AttributeError:
latest_completed_run_number = 1
# Then we find all the upcoming runs and force updating of all subsequent variables.
upcoming_run_variables = InstrumentVariable.objects.filter(
instrument=instrument,
start_run__isnull=False,
start_run__gt=latest_completed_run_number +
1).order_by('start_run')
upcoming_run_numbers = set(
[var.start_run for var in upcoming_run_variables])
[
self.show_variables_for_run(instrument_name, run_number)
for run_number in upcoming_run_numbers
]
# Get the most recent run variables.
current_variables = self.show_variables_for_run(
instrument_name, latest_completed_run_number)
if not current_variables:
# If no variables are saved, we'll use the default ones, and set them while we're at it.
current_variables = self.get_default_variables(instrument_name)
self.set_variables_for_runs(instrument_name, current_variables)
# And then select the variables for all subsequent run numbers; collect the immediate upcoming variables and all subsequent sets.
upcoming_variables_by_run = self.show_variables_for_run(
instrument_name, latest_completed_run_number + 1)
upcoming_variables_by_run += list(
InstrumentVariable.objects.filter(
instrument=instrument,
start_run__in=upcoming_run_numbers).order_by('start_run'))
# Get the upcoming experiments, and then select all variables for these experiments.
upcoming_experiments = []
with ICATCommunication() as icat:
upcoming_experiments = list(
icat.get_upcoming_experiments_for_instrument(instrument_name))
upcoming_variables_by_experiment = InstrumentVariable.objects.filter(
instrument=instrument,
experiment_reference__in=upcoming_experiments).order_by(
'experiment_reference')
return current_variables, upcoming_variables_by_run, upcoming_variables_by_experiment
def open_icat(self):
""" Try to open an ICAT session, if we don't have one already. """
try:
if self.icat is None:
self.icat = ICATCommunication(**self.kwargs)
except Exception as e:
logger.error("Failed to connect to ICAT: %s - %s" %
(type(e).__name, e))
raise ICATConnectionException()
def get_current_and_upcoming_variables(self,
instrument_name,
last_run_object=None):
"""
:param instrument_name: The name of the instrument
:param last_run_object: Optionally provide an object of the last run on the instrument
Fetches the instrument variables for:
- The next run number
- Upcoming run numbers
- Upcoming known experiments
as a tuple of
(current_variables, upcoming_variables_by_run, upcoming_variables_by_experiment)
"""
instrument = InstrumentUtils().get_instrument(instrument_name)
completed_status = StatusUtils().get_completed()
# First, we find the latest run number to determine what's upcoming.
try:
if last_run_object and last_run_object.status.value_verbose(
) == 'Completed':
latest_completed_run_number = last_run_object.run_number
else:
latest_completed_run_number = ReductionRun.objects.filter(instrument=instrument,
run_version=0,
status=completed_status)\
.order_by('-run_number').first().run_number
except AttributeError:
latest_completed_run_number = 1
# Then we find all the upcoming runs and force updating of all subsequent variables.
# pylint:disable=no-member
upcoming_run_variables = InstrumentVariable.objects.\
filter(instrument=instrument,
start_run__isnull=False,
start_run__gt=latest_completed_run_number + 1).order_by('start_run')
upcoming_run_numbers = set(
[var.start_run for var in upcoming_run_variables])
# pylint:disable=expression-not-assigned
[
self.show_variables_for_run(instrument_name, run_number)
for run_number in upcoming_run_numbers
]
# Get the most recent run variables.
current_variables = self.show_variables_for_run(
instrument_name, latest_completed_run_number)
if not current_variables:
# If no variables are saved, we'll use the default ones, and set them while we're at it.
current_variables = self.get_default_variables(instrument_name)
self.set_variables_for_runs(instrument_name, current_variables)
# And then select the variables for all subsequent run numbers;
# collect the immediate upcoming variables and all subsequent sets.
upcoming_variables_by_run = self.show_variables_for_run(
instrument_name, latest_completed_run_number + 1)
# pylint:disable=no-member
upcoming_variables_by_run += list(
InstrumentVariable.objects.filter(
instrument=instrument,
start_run__in=upcoming_run_numbers).order_by('start_run'))
# Get the upcoming experiments, and then select all variables for these experiments.
upcoming_experiments = []
with ICATCommunication() as icat:
upcoming_experiments = list(
icat.get_upcoming_experiments_for_instrument(instrument_name))
# pylint:disable=line-too-long,no-member
upcoming_variables_by_experiment = InstrumentVariable.objects.\
filter(instrument=instrument,
experiment_reference__in=upcoming_experiments).order_by('experiment_reference')
return current_variables, upcoming_variables_by_run, upcoming_variables_by_experiment
