#! /usr/bin/env python
# ==========================================================================
# This script illustrates how to perform an unbinned CTA analysis based on
# simulated CTA data. You may use and adapt this script to implement your
# own pipeline.
#
# Usage:
#   ./pipeline_unbinned_mem.py
#
# ==========================================================================
#
# Copyright (C) 2015 Juergen Knoedlseder
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.
#
# ==========================================================================
import gammalib
import ctools
from cscripts import obsutils


# ================== #
# Setup observations #
# ================== #
def setup_observations(pattern="four", ra=83.63, dec=22.01, offset=1.5,
                       emin=0.1, emax=100.0, rad=5.0, duration=1800.0,
                       deadc=0.95,
                       caldb="prod2", irf="South_50h"):
    """
    Returns an observation container.

    Keywords:
     pattern   - Pointing pattern, either "single" or "four"
     ra        - RA of pattern centre [deg] (default: 83.6331)
     dec       - DEC of pattern centre [deg] (default: 22.0145)
     offset    - Offset between observations of pattern [deg] (default: 1.5)
     emin      - Minimum energy [TeV] (default: 0.1)
     emax      - Maximum energy [TeV] (default: 100.0)
     rad       - ROI radius used for analysis [deg] (default: 5.0)
     duration  - Duration of one CTA observation [seconds] (default: 1800.0)
     deadc     - Deadtime correction factor (default: 0.95)
     caldb     - Calibration database path (default: "dummy")
     irf       - Instrument response function (default: cta_dummy_irf)
    """
    # Set list of observations
    obs_def_list = obsutils.set_obs_patterns(pattern,
                                             ra=ra,
                                             dec=dec,
                                             offset=offset)

    # Get observation container
    obs = obsutils.set_obs_list(obs_def_list,
                                duration=duration,
                                emin=emin,
                                emax=emax,
                                rad=rad,
                                caldb=caldb,
                                irf=irf)

    # Return observation container
    return obs


# =========== #
# Setup model #
# =========== #
def setup_model(obs, model="${CTOOLS}/share/models/crab.xml"):
    """
    Setup model for analysis.

    Keywords:
     model - Model Xml file
    """
    # Append model from file to observation container
    obs.models(gammalib.GModels(model))

    # Return observation container
    return obs


# ================================ #
# Simulation and analysis pipeline #
# ================================ #
def run_pipeline(obs, ra=83.63, dec=22.01, rad=3.0,
                 emin=0.1, emax=100.0,
                 tmin=0.0, tmax=0.0,
                 debug=False):
    """
    Simulation and unbinned analysis pipeline.

    Keywords:
     ra    - RA of cube centre [deg] (default: 83.63)
     dec   - DEC of cube centre [deg] (default: 22.01)
     rad   - Selection radius [deg] (default: 3.0)
     emin  - Minimum energy of cube [TeV] (default: 0.1)
     emax  - Maximum energy of cube [TeV] (default: 100.0)
     tmin  - Start time [MET] (default: 0.0)
     tmax  - Stop time [MET] (default: 0.0)
     debug - Enable debugging (default: False)
    """
    # Simulate events
    sim = ctools.ctobssim(obs)
    sim["debug"] = debug
    sim.run()

    # Select events
    select = ctools.ctselect(sim.obs())
    select["ra"]    = ra
    select["dec"]   = dec
    select["rad"]   = rad
    select["emin"]  = emin
    select["emax"]  = emax
    select["tmin"]  = tmin
    select["tmax"]  = tmax
    select["debug"] = debug
    select.run()

    # Perform maximum likelihood fitting
    like = ctools.ctlike(select.obs())
    like["debug"] = True # Switch this always on for results in console
    like.run()

    # Return
    return


# ======================== #
# Main routine entry point #
# ======================== #
if __name__ == '__main__':
    """
    """
    # Dump header
    print("********************************************")
    print("*      CTA unbinned analysis pipeline      *")
    print("********************************************")

    # Setup observations
    obs = setup_observations()

    # Setup model
    obs = setup_model(obs)

    # Run analysis pipeline
    run_pipeline(obs)