# Copyright (c) 2019-2020 by the parties listed in the AUTHORS file.
# All rights reserved.  Use of this source code is governed by
# a BSD-style license that can be found in the LICENSE file.

import argparse
import os

import numpy as np
from scipy.constants import h, k

from ..mpi import MPI
from ..timing import function_timer, Timer
from ..utils import Logger, Environment

from .. import qarray as qa

from ..todmap import OpSimAtmosphere, atm_available_utils

if atm_available_utils:
    from ..todmap.atm import (
        atm_atmospheric_loading,
        atm_atmospheric_loading_vec,
        atm_absorption_coefficient,
        atm_absorption_coefficient_vec,
    )


XAXIS, YAXIS, ZAXIS = np.eye(3)
TCMB = 2.725


def add_atmosphere_args(parser):
    """Add the atmospheric simulation arguments"""
    parser.add_argument(
        "--atmosphere",
        required=False,
        action="store_true",
        help="Add simulated atmoshere",
        dest="simulate_atmosphere",
    )
    parser.add_argument(
        "--simulate-atmosphere",
        required=False,
        action="store_true",
        help="Add simulated atmoshere",
        dest="simulate_atmosphere",
    )
    parser.add_argument(
        "--no-atmosphere",
        required=False,
        action="store_false",
        help="Do not add simulated atmosphere",
        dest="simulate_atmosphere",
    )
    parser.add_argument(
        "--simulate-coarse-atmosphere",
        required=False,
        action="store_true",
        help="Add simulated coarse atmoshere",
        dest="simulate_coarse_atmosphere",
    )
    parser.add_argument(
        "--no-coarse-atmosphere",
        required=False,
        action="store_false",
        help="Do not add simulated coarse atmosphere",
        dest="simulate_coarse_atmosphere",
    )
    parser.add_argument(
        "--no-simulate-atmosphere",
        required=False,
        action="store_false",
        help="Do not add simulated atmosphere",
        dest="simulate_atmosphere",
    )
    parser.set_defaults(simulate_atmosphere=False)

    parser.add_argument(
        "--focalplane-radius-deg",
        required=False,
        type=np.float64,
        help="Override focal plane radius [deg]",
    )

    parser.add_argument(
        "--atm-verbosity",
        required=False,
        default=0,
        type=np.int64,
        help="Atmospheric sim verbosity level",
    )
    parser.add_argument(
        "--atm-lmin-center",
        required=False,
        default=0.01,
        type=np.float64,
        help="Kolmogorov turbulence dissipation scale center",
    )
    parser.add_argument(
        "--atm-lmin-sigma",
        required=False,
        default=0.001,
        type=np.float64,
        help="Kolmogorov turbulence dissipation scale sigma",
    )
    parser.add_argument(
        "--atm-lmax-center",
        required=False,
        default=10.0,
        type=np.float64,
        help="Kolmogorov turbulence injection scale center",
    )
    parser.add_argument(
        "--atm-lmax-sigma",
        required=False,
        default=10.0,
        type=np.float64,
        help="Kolmogorov turbulence injection scale sigma",
    )
    parser.add_argument(
        "--atm-gain",
        required=False,
        default=2e-5,
        type=np.float64,
        help="Atmospheric gain factor.",
    )
    parser.add_argument(
        "--atm-gain-coarse",
        required=False,
        default=8e-5,
        type=np.float64,
        help="Coarse atmospheric gain factor.",
    )
    parser.add_argument(
        "--atm-zatm",
        required=False,
        default=40000.0,
        type=np.float64,
        help="atmosphere extent for temperature profile",
    )
    parser.add_argument(
        "--atm-zmax",
        required=False,
        default=200.0,
        type=np.float64,
        help="atmosphere extent for water vapor integration",
    )
    parser.add_argument(
        "--atm-xstep",
        required=False,
        default=10.0,
        type=np.float64,
        help="size of volume elements in X direction",
    )
    parser.add_argument(
        "--atm-ystep",
        required=False,
        default=10.0,
        type=np.float64,
        help="size of volume elements in Y direction",
    )
    parser.add_argument(
        "--atm-zstep",
        required=False,
        default=10.0,
        type=np.float64,
        help="size of volume elements in Z direction",
    )
    parser.add_argument(
        "--atm-nelem-sim-max",
        required=False,
        default=10000,
        type=np.int64,
        help="controls the size of the simulation slices",
    )
    parser.add_argument(
        "--atm-wind-dist",
        required=False,
        default=3000.0,
        type=np.float64,
        help="Maximum wind drift to simulate without discontinuity",
    )
    parser.add_argument(
        "--atm-z0-center",
        required=False,
        default=2000.0,
        type=np.float64,
        help="central value of the water vapor distribution",
    )
    parser.add_argument(
        "--atm-z0-sigma",
        required=False,
        default=0.0,
        type=np.float64,
        help="sigma of the water vapor distribution",
    )
    parser.add_argument(
        "--atm-T0-center",
        required=False,
        default=280.0,
        type=np.float64,
        help="central value of the temperature distribution",
    )
    parser.add_argument(
        "--atm-T0-sigma",
        required=False,
        default=10.0,
        type=np.float64,
        help="sigma of the temperature distribution",
    )
    parser.add_argument(
        "--atm-cache",
        required=False,
        default="atm_cache",
        help="Atmosphere cache directory",
    )
    parser.add_argument(
        "--atm-apply-flags",
        default=False,
        action="store_true",
        help="Only simulate unflagged samples.",
    )
    parser.add_argument(
        "--weather-pwv",
        required=False,
        type=np.float64,
        help="Override randomized PWV [mm]",
    )
    parser.add_argument(
        "--weather-temperature",
        required=False,
        type=np.float64,
        help="Override randomized air temperature [K]",
    )
    parser.add_argument(
        "--weather-pressure",
        required=False,
        type=np.float64,
        help="Override randomized surface pressure [Pa]",
    )
    parser.add_argument(
        "--weather-west-wind",
        required=False,
        type=np.float64,
        help="Override randomized West wind [m/s]",
    )
    parser.add_argument(
        "--weather-south-wind",
        required=False,
        type=np.float64,
        help="Override randomized South wind [m/s]",
    )
    # Common flag mask may already be added
    try:
        parser.add_argument(
            "--common-flag-mask",
            required=False,
            default=1,
            type=np.uint8,
            help="Common flag mask",
        )
    except argparse.ArgumentError:
        pass
    # `flush` may already be added
    try:
        parser.add_argument(
            "--flush",
            required=False,
            default=False,
            action="store_true",
            help="Flush every print statement.",
        )
    except argparse.ArgumentError:
        pass
    return


@function_timer
def simulate_atmosphere(args, comm, data, mc, cache_name=None, verbose=True):
    """Simulate atmospheric signal and add it to `cache_name`."""
    if not args.simulate_atmosphere:
        return
    log = Logger.get()
    timer = Timer()
    timer.start()
    if comm.world_rank == 0:
        log.info("Simulating atmosphere")
        if args.atm_cache and not os.path.isdir(args.atm_cache):
            try:
                os.makedirs(args.atm_cache)
            except FileExistsError:
                pass

    write_debug = False
    if args.atm_verbosity > 1:
        write_debug = True

    # Simulate the atmosphere signal

    atm = OpSimAtmosphere(
        out=cache_name,
        realization=2 * mc,
        lmin_center=args.atm_lmin_center,
        lmin_sigma=args.atm_lmin_sigma,
        lmax_center=args.atm_lmax_center,
        lmax_sigma=args.atm_lmax_sigma,
        gain=args.atm_gain,
        zatm=args.atm_zatm,
        zmax=args.atm_zmax,
        xstep=args.atm_xstep,
        ystep=args.atm_ystep,
        zstep=args.atm_zstep,
        nelem_sim_max=args.atm_nelem_sim_max,
        z0_center=args.atm_z0_center,
        z0_sigma=args.atm_z0_sigma,
        apply_flags=args.atm_apply_flags,
        common_flag_mask=args.common_flag_mask,
        cachedir=args.atm_cache,
        wind_dist=args.atm_wind_dist,
        write_debug=write_debug,
    )
    atm.exec(data)

    if args.simulate_coarse_atmosphere:
        atm = OpSimAtmosphere(
            out=cache_name,
            realization=2 * mc + 1,
            lmin_center=300,
            lmin_sigma=0,
            lmax_center=10000,
            lmax_sigma=0,
            gain=args.atm_gain_coarse,
            zatm=args.atm_zatm,
            zmax=args.atm_zmax,
            xstep=50,
            ystep=50,
            zstep=50,
            nelem_sim_max=30000,
            z0_center=args.atm_z0_center,
            z0_sigma=args.atm_z0_sigma,
            apply_flags=args.atm_apply_flags,
            common_flag_mask=args.common_flag_mask,
            cachedir=args.atm_cache,
            wind_dist=10000,
            write_debug=write_debug,
        )
        atm.exec(data)

    if comm.comm_world is not None:
        comm.comm_world.barrier()
    if comm.world_rank == 0:
        timer.report_clear("Atmosphere simulation")
    return


@function_timer
def scale_atmosphere_by_frequency(
    args, comm, data, freq=None, mc=0, cache_name=None, verbose=True
):
    """Scale atmospheric fluctuations by frequency.

    Assume that cached signal under totalname_freq is pure atmosphere
    and scale the absorption coefficient according to the frequency.

    If the focalplane is included in the observation and defines
    bandpasses for the detectors, the scaling is computed for each
    detector separately and `freq` is ignored.

    """
    if not args.simulate_atmosphere:
        return

    log = Logger.get()
    if comm.world_rank == 0 and verbose:
        log.info("Scaling atmosphere by frequency")
    timer = Timer()
    timer.start()
    for obs in data.obs:
        tod = obs["tod"]
        todcomm = tod.mpicomm
        site_id = obs["site_id"]
        weather = obs["weather"]
        if "focalplane" in obs:
            focalplane = obs["focalplane"]
        else:
            focalplane = None
        start_time = obs["start_time"]
        weather.set(site_id, mc, start_time)
        altitude = obs["altitude"]
        air_temperature = weather.air_temperature
        surface_pressure = weather.surface_pressure
        pwv = weather.pwv
        # Use the entire processing group to sample the absorption
        # coefficient as a function of frequency
        freqmin = 0
        if freq is None:
            freqmax = 1000
        else:
            freqmax = 2 * freq
        nfreq = 1001
        freqstep = (freqmax - freqmin) / (nfreq - 1)
        if todcomm is None:
            nfreq_task = nfreq
            my_ifreq_min = 0
            my_ifreq_max = nfreq
        else:
            nfreq_task = int(nfreq // todcomm.size) + 1
            my_ifreq_min = nfreq_task * todcomm.rank
            my_ifreq_max = min(nfreq, nfreq_task * (todcomm.rank + 1))
        my_nfreq = my_ifreq_max - my_ifreq_min
        if my_nfreq > 0:
            if atm_available_utils:
                my_freqs = freqmin + np.arange(my_ifreq_min, my_ifreq_max) * freqstep
                my_absorption = atm_absorption_coefficient_vec(
                    altitude,
                    air_temperature,
                    surface_pressure,
                    pwv,
                    my_freqs[0],
                    my_freqs[-1],
                    my_nfreq,
                )
                my_loading = atm_atmospheric_loading_vec(
                    altitude,
                    air_temperature,
                    surface_pressure,
                    pwv,
                    my_freqs[0],
                    my_freqs[-1],
                    my_nfreq,
                )
            else:
                raise RuntimeError(
                    "Atmosphere utilities from libaatm are not available"
                )
        else:
            my_freqs = np.array([])
            my_absorption = np.array([])
            my_loading = np.array([])
        if todcomm is None:
            freqs = my_freqs
            absorption = my_absorption
            loading = my_loading
        else:
            freqs = np.hstack(todcomm.allgather(my_freqs))
            absorption = np.hstack(todcomm.allgather(my_absorption))
            loading = np.hstack(todcomm.allgather(my_loading))
        for det in tod.local_dets:
            if "bandpass_transmission" in focalplane[det]:
                # We have full bandpasses for the detector
                bandpass_freqs = focalplane[det]["bandpass_freq_ghz"]
                bandpass = focalplane[det]["bandpass_transmission"]
            else:
                if "bandcenter_ghz" in focalplane[det]:
                    # Use detector bandpass from the focalplane
                    center = focalplane[det]["bandcenter_ghz"]
                    width = focalplane[det]["bandwidth_ghz"]
                else:
                    # Use default values for the entire focalplane
                    if freq is None:
                        raise RuntimeError(
                            "You must supply the nominal frequency if bandpasses "
                            "are not available"
                        )
                    center = freq
                    width = 0.2 * freq
                bandpass_freqs = np.array([center - width / 2, center + width / 2])
                bandpass = np.ones(2)
            # Normalize and interpolate the bandpass
            nstep = 1001
            fmin, fmax = bandpass_freqs[0], bandpass_freqs[-1]
            det_freqs = np.linspace(fmin, fmax, nstep)
            det_bandpass = np.interp(det_freqs, bandpass_freqs, bandpass)
            det_bandpass /= np.sum(det_bandpass)
            # Interpolate absorption and loading to bandpass frequencies
            absorption_det = np.interp(det_freqs, freqs, absorption)
            loading_det = np.interp(det_freqs, freqs, loading)
            # From brightness to thermodynamic units
            x = h * det_freqs * 1e9 / k / TCMB
            rj2cmb = (x / (np.exp(x / 2) - np.exp(-x / 2))) ** -2
            # Normalize to unity at 150GHz
            rj2cmb *= 0.5763279042527544
            absorption_det *= rj2cmb
            # Average across the bandpass
            absorption_det = np.sum(absorption_det * det_bandpass)
            loading_det = np.sum(loading_det * det_bandpass)
            cachename = "{}_{}".format(cache_name, det)
            ref = tod.cache.reference(cachename)
            ref *= absorption_det
            # Add loading, accounting for the observing elevation
            try:
                # Some TOD classes provide a shortcut to Az/El
                az, el = tod.read_azel(detector=det)
            except Exception as e:
                azelquat = tod.read_pntg(detector=det, azel=True)
                theta, phi = qa.to_position(azelquat)
                el = np.pi / 2 - theta
            ref += loading_det / np.sin(el)
            del ref

    if comm.comm_world is not None:
        comm.comm_world.barrier()
    timer.stop()
    if comm.world_rank == 0 and verbose:
        timer.report("Atmosphere scaling")
    return


@function_timer
def update_atmospheric_noise_weights(args, comm, data, freq, mc, verbose=False):
    """Update atmospheric noise weights.

    Estimate the atmospheric noise level from weather parameters and
    encode it as a noise_scale in the observation.  Madam will apply
    the noise_scale to the detector weights.  This approach assumes
    that the atmospheric noise dominates over detector noise.  To be
    more precise, we would have to add the squared noise weights but
    we do not have their relative calibration.

    """
    if not args.simulate_atmosphere:
        for obs in data.obs:
            obs["noise_scale"] = 1.0
        return
    log = Logger.get()
    if comm.world_rank == 0 and verbose:
        log.info("Updating atmospheric noise weights")
    timer = Timer()
    timer.start()
    if atm_available_utils:
        for obs in data.obs:
            site_id = obs["site_id"]
            weather = obs["weather"]
            start_time = obs["start_time"]
            weather.set(site_id, mc, start_time)
            altitude = obs["altitude"]
            absorption = atm_absorption_coefficient(
                altitude,
                weather.air_temperature,
                weather.surface_pressure,
                weather.pwv,
                freq,
            )
            obs["noise_scale"] = absorption * weather.air_temperature
    else:
        raise RuntimeError("Atmosphere utilities from libaatm are not available")

    if comm.comm_world is not None:
        comm.comm_world.barrier()
    timer.stop()
    if comm.world_rank == 0 and verbose:
        timer.report("Atmosphere weighting")
    return


@function_timer
def draw_weather(args, comm, data, mc=0, verbose=True):
    """ Draw the weather parameters for this Monte Carlo realization
    """
    timer = Timer()
    timer.start()

    for obs in data.obs:
        tod = obs["tod"]
        site = obs["site_id"]
        weather = obs["weather"]

        # Get the observation start and initialize the weather
        # object
        start_time = obs["start_time"]
        weather.set(site, mc, start_time)

        # Check for optional overrides
        if args.weather_pwv is not None:
            weather._pwv = args.weather_pwv
        if args.weather_temperature is not None:
            weather._air_temperature = args.weather_temperature
        if args.weather_pressure is not None:
            weather._surface_pressure = args.weather_pressure
        if args.weather_west_wind is not None:
            weather._west_wind = args.weather_west_wind
        if args.weather_south_wind is not None:
            weather._south_wind = args.weather_south_wind

    if verbose:
        if comm.comm_world is not None:
            comm.comm_world.barrier()
        timer.stop()
        if comm.world_rank == 0:
            timer.report("draw_weather")
    return
