else:
raise ValueError('catalog name not found')
if injweight is None:
injweight = llhweight
print("The llhweight is: {}".format(llhweight))
print("The injweight is: {}".format(injweight))
# get unique job id
job_id = '{0}_nixtime_{2:.0f}_job_{1}'.format(socket.gethostname(),
os.getpid(), time.time())
# set up submitter
submitter = Submitter(
job_dir=
'/data/user/brelethford/Output/stacking_sensitivity/{0}/mstacking_{1}yr/jobs/{2}_{3}'
.format(catalog, str(n), job_id, llhweight))
submitter.memory = 3
# figure out what dir we're in, and get the path to the actual job script
this_dir = os.path.dirname(os.path.abspath(__file__))
job_script = this_dir + '/background_trials.py'
# get the metaproject path
env_shell = os.getenv('I3_BUILD') + '/env-shell.sh'
# build the lists of commands and labels
commands, labels = [], []
## For this we'll need to do background trials in batches of 1000. So...
batchsize = 100
total_bckg_trials = 30000
opts, args = parser.parse_args()
llhweight = opts.llhweight
injweight = opts.injweight
print("The llhweight is: {}".format(llhweight))
print("The injweight is: {}".format(injweight))
# get unique job id
job_id = '{0}_nixtime_{2:.0f}_job_{1}_{3}inj'.format(socket.gethostname(),
os.getpid(), time.time(),
injweight)
# set up submitter
submitter = Submitter(
job_dir=
'/data/user/brelethford/Output/stacking_sensitivity/SwiftBAT70m_mc_cut/{0}/jobs/{1}'
.format(llhweight, job_id))
# figure out what dir we're in, and get the path to the actual job script
this_dir = os.path.dirname(os.path.abspath(__file__))
job_script = this_dir + '/n_inj_test_2.py'
# get the metaproject path
env_shell = os.getenv('I3_BUILD') + '/env-shell.sh'
# build the lists of commands and labels
commands, labels = [], []
## However, I don't know how I'd split this up, so I'm just gonna hope that I can do it all at once...
bins = 1
gammarange = np.linspace(2.0, 2.0, bins)
if injweight is None:
injweight = llhweight
print("The llhweight is: {}".format(llhweight))
print("The injweight is: {}".format(injweight))
# get unique job id
job_id = '{0}_nixtime_{2:.0f}_job_{1}'.format(socket.gethostname(),
os.getpid(), time.time())
jobdir = misc.ensure_dir(
'/data/user/brelethford/Output/stacking_sensitivity/{0}/jstacking_{1}year/jobs/'
.format(catalog, n_year))
# set up submitter
submitter = Submitter(job_dir=jobdir + '{0}_{1}'.format(job_id, llhweight))
submitter.memory = 3
# figure out what dir we're in, and get the path to the actual job script
this_dir = os.path.dirname(os.path.abspath(__file__))
job_script = this_dir + '/background_trials.py'
# get the metaproject path
env_shell = os.getenv('I3_BUILD') + '/env-shell.sh'
# build the lists of commands and labels
commands, labels = [], []
## For this we'll need to do background trials in batches of 1000. So...
batchsize = 100
total_bckg_trials = 10000
batches = int(np.round(total_bckg_trials / batchsize))
import os
import socket
import time
import numpy as np
from icecube.umdtools.submitter import Submitter
# get unique job id
job_id = '{0}_nixtime_{2:.0f}_job_{1}'.format(socket.gethostname(),
os.getpid(), time.time())
# set up submitter
submitter = Submitter(
job_dir=
'/data/user/brelethford/Output/all_sky_sensitivity/results/box/jobs/{0}'.
format(job_id))
# figure out what dir we're in, and get the path to the actual job script
this_dir = os.path.dirname(os.path.abspath(__file__))
job_script = this_dir + '/all_sky_sensitivity_default.py'
# get the metaproject path
env_shell = os.getenv('I3_BUILD') + '/env-shell.sh'
# build the lists of commands and labels
commands, labels = [], []
bins = 31
#sindecrange=np.linspace(np.sin(np.radians(-85.0)),np.sin(np.radians(85.0)),bins)
#degdecrange = np.degrees(np.arcsin(sindecrange))
#Note - I used to do it with equal spacing in degrees, but I think I want equal spacing in sin_dec, for the purpose of graphing.