def getRR(first=272000,
last=326000,
tkr_IN=True,
tkr_strip_status='GOOD',
tkr_pix_status='GOOD',
name='UL',
cl='Collisions'):
runs = runregistry.get_datasets(
filter={
'run_number': {
'and': [{
'>': first
}, {
'<': last
}]
},
'tracker_included': tkr_IN,
'tracker-strip': tkr_strip_status,
#'tracker-pixel': tkr_pix_status,
'class': {
'like': '%{}%'.format(cl)
},
'dataset_name': {
'like': '%{}%'.format(name)
},
})
return runs
def get_runs_by_list(self, list_of_run_numbers):
"""
Get list of run dictionaries from the Tracker workspace in the Run Registry
Example:
>>> client = TrackerRunRegistryClient()
>>> runs = client.get_runs_by_list(["323423"])
>>> runs[0]["state"]
'COMPLETED'
:param list_of_run_numbers: list of run numbers
:return: dictionary containing the queryset
"""
if not list_of_run_numbers:
return []
runs = runregistry.get_datasets(
filter={
'run_number': {
'or': list_of_run_numbers
},
'dataset_name': {
'notlike': '%online%'
}
})
return runs
def retrieve_dataset(run_number):
datasets = runregistry.get_datasets(
filter={'run_number': {
'=': run_number
}})
for dataset in datasets:
if "online" not in dataset["name"]:
if not TrackerCertification.objects.filter(
runreconstruction__run__run_number=run_number,
runreconstruction__reconstruction=get_reco_from_dataset(
dataset["name"])).exists():
return dataset["name"]
if len(datasets) != 0:
raise Exception("No available datasets for run {}".format(run_number))
else:
raise Exception("Run {} has been fully certified".format(run_number))
def get_dataset_name(run_id,
keyword=express_2017_settings.KEYWORD_FOR_PULLED_LABEL):
dataset_informations = rr.get_datasets(filter={'run_number': run_id})
if run_id not in dataset_name_cache:
try:
dataset_name_cache[run_id] = tuple(
map(
lambda x: x['name'],
filter(
lambda x: express_2017_settings.
KEYWORD_FOR_PULLED_LABEL in x['name'],
dataset_informations)))[0]
print(run_id, dataset_name_cache[run_id])
except IndexError:
print("!! There is no dataset_name for selected keywork '{}' !!".
format(express_2017_settings.KEYWORD_FOR_PULLED_LABEL))
exit()
return dataset_name_cache[run_id]
def retrieve_dataset_by_reco(run_number, reco):
datasets = runregistry.get_datasets(
filter={'run_number': {
'=': run_number
}})
for dataset in datasets:
if reco in dataset["name"].lower():
return dataset["name"]
if reco == "rereco":
if reco in dataset["name"].lower() and "UL" not in dataset["name"]:
return dataset["name"]
if reco == "rerecoul":
if "rereco" in dataset["name"].lower() and "UL" in dataset["name"]:
return dataset["name"]
raise Exception("Could not find reconstruction:{} for run {}".format(
reco, run_number))
def get_dataset_name(recon_name="PromptReco", run_id=None):
dataset_name_cache_key = "%s___%s" % (recon_name, run_id)
if dataset_name_cache_key in dataset_name_cache:
# print("Yay, found %s" % (dataset_name_cache_key))
return dataset_name_cache[dataset_name_cache_key]
if recon_name in regex_cache:
r = regex_cache[recon_name]
else:
r = re.compile(".*{}".format(recon_name))
regex_cache[recon_name] = r
dataset_informations = rr.get_datasets(filter={'run_number': int(run_id)})
dataset_names = list(map(lambda x: x['name'], dataset_informations))
prompt_reco_dataset = list(filter(r.match, dataset_names))
if len(prompt_reco_dataset) > 1:
raise PromptRecoDatasetNotUniqueError
dataset_name_cache[dataset_name_cache_key] = prompt_reco_dataset[0]
return prompt_reco_dataset[0]
def get_datasets_of_runs(runs, user):
for run in runs:
datasets = runregistry.get_datasets(
filter={
'run_number': {
'=': run["run_number"]
},
'global_state': {
'=': 'OPEN'
},
})
today = timezone.now().strftime("%Y-%m-%d")
run_check = OpenRuns.objects.filter(run_number=run["run_number"])
if not run_check.exists():
dataset_express = ""
dataset_prompt = ""
dataset_rereco = ""
dataset_rereco_ul = ""
state_express = ""
state_prompt = ""
state_rereco = ""
state_rereco_ul = ""
for dataset in datasets:
if "express" in dataset["name"].lower():
dataset_express = dataset["name"]
state_express = dataset["dataset_attributes"][
"global_state"] if "global_state" in dataset[
"dataset_attributes"] else "SIGNOFF"
elif "prompt" in dataset["name"].lower():
dataset_prompt = dataset["name"]
state_prompt = dataset["dataset_attributes"][
"global_state"] if "global_state" in dataset[
"dataset_attributes"] else "SIGNOFF"
elif "rereco" in dataset["name"].lower(
) and "UL" in dataset["name"]:
dataset_rereco_ul = dataset["name"]
state_rereco_ul = dataset["dataset_attributes"][
"global_state"] if "global_state" in dataset[
"dataset_attributes"] else "SIGNOFF"
elif "rereco" in dataset["name"].lower():
dataset_rereco = dataset["name"]
state_rereco = dataset["dataset_attributes"][
"global_state"] if "global_state" in dataset[
"dataset_attributes"] else "SIGNOFF"
if dataset_express != "" or dataset_prompt != "" or dataset_rereco != "" or dataset_rereco_ul != "":
OpenRuns.objects.create(run_number=run["run_number"],
dataset_express=dataset_express,
user=user,
state_express=state_express,
date_retrieved=today)
OpenRuns.objects.filter(run_number=run["run_number"]).update(
dataset_prompt=dataset_prompt, state_prompt=state_prompt)
OpenRuns.objects.filter(run_number=run["run_number"]).update(
dataset_rereco=dataset_rereco, state_rereco=state_rereco)
OpenRuns.objects.filter(run_number=run["run_number"]).update(
dataset_rereco_ul=dataset_rereco_ul,
state_rereco_ul=state_rereco_ul)
else:
run_check.update(date_retrieved=today)
for run in sorted_runs:
run_num = run['run_number']
dataset_str = ''
ntriggers = run['oms_attributes']['l1_triggers_counter']
ls_good = 0
ls_tot = 0
pixel_flag = 'NOTSET'
strip_flag = 'NOTSET'
tracking_flag = 'NOTSET'
datasets = runregistry.get_datasets(
filter={
'run_number': run_num,
'class': {
'like': '%Collisions%'
},
'dataset_name': {
'like': '%' + stream + '%'
}
})
ndat = len(datasets)
if ndat != 1:
if ndat == 0:
print('>> No dataset found for the run ' + str(run_num) +
' !! Skipping it.')
if ndat > 1:
print('>> Several datasets found for the run ' + str(run_num) +
' !! Skipping it.')
print('>> The list is : ')
for dataset in datasets:
print('>> ', dataset['name'])