def daemon_loop():
while True:
try:
job_queue = dismod3.get_job_queue()
except:
job_queue = []
for param_id in job_queue:
print 'processing job %d' % param_id
job_params = dismod3.remove_from_job_queue(param_id)
id = int(job_params['dm_id'])
fit_all.fit_all(id)
time.sleep(dismod3.settings.SLEEP_SECS)
def daemon_loop():
on_sge = dismod3.settings.ON_SGE
while True:
try:
job_queue = dismod3.get_job_queue()
except:
job_queue = []
for param_id in job_queue:
#tweet('processing job %d' % id)
log('processing job %d' % param_id)
job_params = dismod3.remove_from_job_queue(param_id)
id = int(job_params['dm_id'])
dm = dismod3.get_disease_model(id)
# make a working directory for the id
dir = dismod3.settings.JOB_WORKING_DIR % id
if not os.path.exists(dir):
os.makedirs(dir)
estimate_type = dm.params.get('run_status', {}).get('estimate_type', 'fit all individually')
if estimate_type.find('posterior') != -1:
#fit each region/year/sex individually for this model
regions_to_fit = dm.params.get('run_status', {}).get('regions_to_fit', [])
if regions_to_fit[0] == 'all_regions':
regions_to_fit = dismod3.gbd_regions
d = '%s/posterior' % dir
if os.path.exists(d):
rmtree(d)
os.mkdir(d)
os.mkdir('%s/stdout' % d)
os.mkdir('%s/stderr' % d)
dismod3.init_job_log(id, 'posterior', param_id)
for r in regions_to_fit:
for s in dismod3.gbd_sexes:
for y in dismod3.gbd_years:
# fit only one region, for the time being...
# TODO: make region selection a user-settable option from the gui
#if clean(r) != 'asia_southeast':
# continue
k = '%s+%s+%s' % (clean(r), s, y)
o = '%s/stdout/%s' % (d, k)
e = '%s/stderr/%s' % (d, k)
if on_sge:
call_str = dismod3.settings.GBD_FIT_STR % (o, e, '-l -r %s -s %s -y %s' % (clean(r), s, y), id)
subprocess.call(call_str, shell=True)
else:
call_str = dismod3.settings.GBD_FIT_STR % ('-l -r %s -s %s -y %s' % (clean(r), s, y), id, o, e)
subprocess.call(call_str, shell=True)
time.sleep(1.)
elif estimate_type.find('empirical priors') != -1:
# fit empirical priors (by pooling data from all regions
d = '%s/empirical_priors' % dir
if os.path.exists(d):
rmtree(d)
os.mkdir(d)
os.mkdir('%s/stdout' % d)
os.mkdir('%s/stderr' % d)
dismod3.init_job_log(id, 'empirical_priors', param_id)
for t in ['excess-mortality', 'remission', 'incidence', 'prevalence']:
o = '%s/stdout/%s' % (d, t)
e = '%s/stderr/%s' % (d, t)
if on_sge:
subprocess.call(dismod3.settings.GBD_FIT_STR % (o, e, '-l -t %s' % t, id), shell=True)
else:
subprocess.call(dismod3.settings.GBD_FIT_STR % ('-l -t %s' % t, id, o, e), shell=True)
else:
#tweet('unrecognized estimate type: %s' % estimate_type)
log('unrecognized estimate type: %s' % estimate_type)
time.sleep(dismod3.settings.SLEEP_SECS)
def daemon_loop():
on_sge = dismod3.settings.ON_SGE
while True:
try:
job_queue = dismod3.get_job_queue()
except:
job_queue = []
for param_id in job_queue:
#tweet('processing job %d' % id)
log('processing job %d' % param_id)
job_params = dismod3.remove_from_job_queue(param_id)
id = int(job_params['dm_id'])
dm = dismod3.get_disease_model(id)
# make a working directory for the id
dir = dismod3.settings.JOB_WORKING_DIR % id
if os.path.exists(dir):
dismod3.disease_json.random_rename(dir)
os.makedirs(dir)
estimate_type = dm.params.get('run_status', {}).get('estimate_type', 'fit all individually')
# sort the regions so that the data rich regions are fit first
#data_hash = GBDDataHash(dm.data)
#sorted_regions = sorted(dismod3.gbd_regions, reverse=True,
#key=lambda r: len(data_hash.get(region=r)))
if estimate_type == 'Fit continuous single parameter model':
#dismod3.disease_json.create_disease_model_dir(id)
o = '%s/continuous_spm.stdout' % dir
e = '%s/continuous_spm.stderr' % dir
if on_sge:
print o
print e
call_str = 'qsub -cwd -o %s -e %s ' % (o, e) \
+ 'run_on_cluster.sh /home/OUTPOST/abie/gbd_dev/gbd/fit_continuous_spm.py %d' % id
else:
call_str = 'python -u /home/abie/gbd/fit_continuous_spm.py %d 2>%s |tee %s' % (id, e, o)
subprocess.call(call_str, shell=True)
continue
if estimate_type.find('posterior') != -1:
#fit each region/year/sex individually for this model
regions_to_fit = dm.params.get('run_status', {}).get('regions_to_fit', [])
if regions_to_fit[0] == 'all_regions':
regions_to_fit = dismod3.gbd_regions
d = '%s/posterior' % dir
if os.path.exists(d):
rmtree(d)
os.mkdir(d)
os.mkdir('%s/stdout' % d)
os.mkdir('%s/stderr' % d)
os.mkdir('%s/pickle' % d)
dismod3.init_job_log(id, 'posterior', param_id)
for r in regions_to_fit:
for s in dismod3.gbd_sexes:
for y in dismod3.gbd_years:
# fit only one region, for the time being...
# TODO: make region selection a user-settable option from the gui
#if clean(r) != 'asia_southeast':
# continue
k = '%s+%s+%s' % (clean(r), s, y)
o = '%s/stdout/%s' % (d, k)
e = '%s/stderr/%s' % (d, k)
if on_sge:
call_str = dismod3.settings.GBD_FIT_STR % (o, e, '-l -r %s -s %s -y %s' % (clean(r), s, y), id)
subprocess.call(call_str, shell=True)
else:
call_str = dismod3.settings.GBD_FIT_STR % ('-l -r %s -s %s -y %s' % (clean(r), s, y), id, o, e)
subprocess.call(call_str, shell=True)
#time.sleep(1.)
elif estimate_type.find('empirical priors') != -1:
# fit empirical priors (by pooling data from all regions
d = '%s/empirical_priors' % dir
if os.path.exists(d):
rmtree(d)
os.mkdir(d)
os.mkdir('%s/stdout' % d)
os.mkdir('%s/stderr' % d)
os.mkdir('%s/pickle' % d)
dismod3.init_job_log(id, 'empirical_priors', param_id)
for t in ['excess-mortality', 'remission', 'incidence', 'prevalence']:
o = '%s/stdout/%s' % (d, t)
e = '%s/stderr/%s' % (d, t)
if on_sge:
subprocess.call(dismod3.settings.GBD_FIT_STR % (o, e, '-l -t %s' % t, id), shell=True)
else:
subprocess.call(dismod3.settings.GBD_FIT_STR % ('-l -t %s' % t, id, o, e), shell=True)
else:
#tweet('unrecognized estimate type: %s' % estimate_type)
log('unrecognized estimate type: %s' % estimate_type)
time.sleep(dismod3.settings.SLEEP_SECS)
