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do_signal_llhs_quick.py
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do_signal_llhs_quick.py
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import numpy as np
from astropy.io import fits
import os
import argparse
import logging, traceback
import time
from bkg_rate_estimation import rate_obj_from_sqltab
from sqlite_funcs import get_conn, write_result
from dbread_funcs import get_rate_fits_tab, guess_dbfname,\
get_seeds_tab, get_info_tab, get_files_tab
from config import EBINS0, EBINS1
from flux_models import Plaw_Flux
from minimizers import NLLH_ScipyMinimize_Wjacob, imxy_grid_miner, NLLH_ScipyMinimize
from drm_funcs import DRMs
from ray_trace_funcs import RayTraces
from LLH import LLH_webins
from models import Bkg_Model, Point_Source_Model, CompoundModel
# need to read rate fits from DB
# and read twinds
# and read/get event, dmask, and ebins
# then get bkg_llh_obj and a minimizer
# then loop over all time windows
# minimizing nllh and recording bf params
def cli():
parser = argparse.ArgumentParser()
parser.add_argument('--evfname', type=str,\
help="Event data file",
default=None)
parser.add_argument('--dmask', type=str,\
help="Detmask fname",
default=None)
parser.add_argument('--job_id', type=int,\
help="ID to tell it what seeds to do",\
default=-1)
parser.add_argument('--dbfname', type=str,\
help="Name to save the database to",\
default=None)
args = parser.parse_args()
return args
def do_analysis(seed_tab, pl_flux, drm_obj, rt_obj,\
bkg_llh_obj, sig_llh_obj, bkg_rate_obj,\
conn, db_fname, grid_width=4e-3, grid_step=1e-3):
seed_t_gs = seed_tab.groupby('timeID')
N_twinds = seed_t_gs.ngroups
ebins0 = sig_llh_obj.ebins0
ebins1 = sig_llh_obj.ebins1
bl_dmask = sig_llh_obj.bl_dmask
bkg_miner = NLLH_ScipyMinimize('')
sig_miner = NLLH_ScipyMinimize_Wjacob('')
for seed_g in seed_t_gs:
timeID = seed_g[0]
seed_tab = seed_g[1]
Nseeds = len(seed_tab)
t0 = np.nanmean(seed_tab['time'])
dt = np.nanmean(seed_tab['duration'])
t1 = t0 + dt
tmid = (t0+t1)/2.
bkg_llh_obj.set_time(t0, dt)
sig_llh_obj.set_time(t0, dt)
bkg_mod = Bkg_Model(bkg_rate_obj, bl_dmask, t=tmid,\
bkg_err_fact=2.0, use_prior=False)
logging.debug("bkg exp rates, errors")
logging.debug(bkg_mod._rates)
logging.debug(bkg_mod._errs)
bkg_llh_obj.set_model(bkg_mod)
bkg_miner.set_llh(bkg_llh_obj)
bkg_miner.set_fixed_params(bkg_llh_obj.model.param_names)
bkg_params = {pname:bkg_llh_obj.model.param_dict[pname]['val'] for\
pname in bkg_llh_obj.model.param_names}
bkg_nllh = -bkg_llh_obj.get_llh(bkg_params)
for row in seed_tab.itertuples():
try:
blipID = row.blipID
sig_mod = Point_Source_Model(row.imx, row.imy, grid_width,\
pl_flux, drm_obj,\
[ebins0,ebins1], rt_obj, bl_dmask, use_deriv=True)
comp_mod = CompoundModel([bkg_mod, sig_mod])
sig_llh_obj.set_model(comp_mod)
sig_miner.set_llh(sig_llh_obj)
fixed_pars = [pname for pname in sig_miner.param_names if\
('A' not in pname) or ('gamma' not in pname)]
sig_miner.set_fixed_params(fixed_pars)
sig_miner.set_fixed_params(['Signal_A', 'Signal_gamma'], fixed=False)
param_list, nllhs, imxs, imys = imxy_grid_miner(\
sig_miner, row.imx-grid_width/2., row.imy-grid_width/2.,\
row.imx+grid_width/2., row.imy+grid_width/2.,\
dimxy=grid_step)
best_ind = np.argmin(nllhs)
bf_params = param_list[best_ind]
sig_nllh = nllhs[best_ind]
imx = imxs[best_ind]
imy = imys[best_ind]
sig_param_dict = {}
i = 0
for pname in sig_miner.param_names:
if pname in sig_miner.fixed_params:
if 'imx' in pname:
sig_param_dict[pname] = imx
elif 'imy' in pname:
sig_param_dict[pname] = imy
else:
sig_param_dict[pname] = sig_miner.param_info_dict[pname]['val']
else:
sig_param_dict[pname] = bf_params[i]
i += 1
logging.info("sig_param_dict: ")
logging.info(str(sig_param_dict))
TS = np.sqrt(2.*(bkg_nllh - sig_nllh))
if np.isnan(TS):
TS = 0.0
try:
write_result(conn, row, sig_param_dict,\
bkg_nllh, sig_nllh, TS)
except Exception as E:
logging.error(E)
logging.error("Problem writing to DB")
conn.close()
conn = get_conn(db_fname)
try:
write_result(conn, row, sig_param_dict,\
bkg_nllh, sig_nllh, TS)
except Exception as E:
logging.error(E)
logging.error("Problem writing to DB")
logging.error("Couldn't write ")
logging.error(str(sig_param_dict))
logging.error("to DB")
except Exception as E:
logging.error(E)
logging.error(traceback.format_exc())
logging.error("Failed to minimize seed: ")
logging.error(row)
def main(args):
fname = 'llh_analysis_' + str(args.job_id)
logging.basicConfig(filename=fname+'.log', level=logging.DEBUG,\
format='%(asctime)s-' '%(levelname)s- %(message)s')
while True:
try:
if args.dbfname is None:
db_fname = guess_dbfname()
if isinstance(db_fname, list):
db_fname = db_fname[0]
else:
db_fname = args.dbfname
logging.info('Connecting to DB')
conn = get_conn(db_fname)
info_tab = get_info_tab(conn)
logging.info('Got info table')
files_tab = get_files_tab(conn)
logging.info('Got files table')
trigtime = info_tab['trigtimeMET'][0]
evfname = files_tab['evfname'][0]
ev_data = fits.open(evfname)[1].data
dmask_fname = files_tab['detmask'][0]
dmask = fits.open(dmask_fname)[0].data
bl_dmask = (dmask==0.0)
logging.debug('Opened up event and detmask files')
rate_fits_df = get_rate_fits_tab(conn)
bkg_rates_obj = rate_obj_from_sqltab(rate_fits_df, 0, 1)
break
except Exception as E:
logging.error(str(E))
logging.error(traceback.format_exc())
time.sleep(30.0)
time_starting = time.time()
proc_num = args.job_id
# init classes up here
drm_dir = files_tab['drmDir'][0]
rt_dir = files_tab['rtDir'][0]
drm_obj = DRMs(drm_dir)
rt_obj = RayTraces(rt_dir)
pl_flux = Plaw_Flux()
ebins0 = np.array(EBINS0)
ebins1 = np.array(EBINS1)
logging.debug("ebins0")
logging.debug(ebins0)
logging.debug("ebins1")
logging.debug(ebins1)
bkg_llh_obj = LLH_webins(ev_data, ebins0, ebins1, bl_dmask)
sig_llh_obj = LLH_webins(ev_data, ebins0, ebins1, bl_dmask)
while True:
conn = get_conn(db_fname)
try:
if proc_num >= 0:
seeds_tab = get_seeds_tab(conn, proc_group=proc_num)
else:
seeds_tab = get_seeds_tab(conn)
except Exception as E:
logging.error(E)
logging.error(traceback.format_exc())
logging.warning("Failed to get seed tab, will try again")
conn.close()
time.sleep(30.0)
continue
new_seeds = (seeds_tab['done']==0)
seed_tab = seeds_tab[new_seeds]
Nseeds_todo = np.sum(new_seeds)
logging.info(str(Nseeds_todo) + " new seeds")
if Nseeds_todo == 0:
conn.close()
time.sleep(30.0)
continue
#seed_prio_gs = seed_tab.groupby('priority')
#Nprio = seed_prio_gs.ngroups
min_priority = np.min(seed_tab['priority'])
logging.info("min priority is " + str(min_priority))
prio_bl = (seed_tab['priority']==min_priority)
Nmin_prio = np.sum(prio_bl)
logging.info(str(Nmin_prio) + " new seeds with priority " + str(min_priority))
seed_tab = seed_tab[prio_bl]
do_analysis(seed_tab, pl_flux, drm_obj, rt_obj,\
bkg_llh_obj, sig_llh_obj, bkg_rates_obj,\
conn, db_fname)
conn.close()
if __name__ == "__main__":
args = cli()
main(args)