"""Compare vis_cpu with pyuvsim visibilities."""
import pytest

import copy
import numpy as np
from astropy import units
from astropy.coordinates import Latitude, Longitude
from astropy.time import Time
from astropy.units import Quantity
from pyradiosky import SkyModel
from pyuvsim import AnalyticBeam, simsetup, uvsim
from pyuvsim.telescope import BeamList

from hera_sim import io
from hera_sim.beams import PolyBeam
from hera_sim.visibilities import MatVis, ModelData, VisibilitySimulation

nfreq = 3
ntime = 20
nants = 4


def get_uvdata(pol_array=None):
    hera_lat = -30.7215
    hera_lon = 21.4283
    hera_alt = 1073.0
    obstime = Time("2018-08-31T04:02:30.11", format="isot", scale="utc")
    if pol_array is None:
        pol_array = np.array(["XX", "YY", "XY", "YX"])
    np.random.seed(10)

    # Random antenna locations
    x = np.random.random(nants) * 400.0  # Up to 400 metres
    y = np.random.random(nants) * 400.0
    z = np.random.random(nants) * 0.0

    ants = {i: (x[i], y[i], z[i]) for i in range(nants)}

    # Observing parameters in a UVData object
    return io.empty_uvdata(
        Nfreqs=nfreq,
        start_freq=100e6,
        channel_width=97.3e3,
        start_time=obstime.jd,
        integration_time=20.0,
        Ntimes=ntime,
        array_layout=ants,
        polarization_array=pol_array,
        telescope_location=(hera_lat, hera_lon, hera_alt),
        telescope_name="test_array",
        x_orientation="east",
        phase_type="drift",
        vis_units="Jy",
        write_files=False,
    )


@pytest.fixture(scope="function")
def uvdata_allpols():
    return get_uvdata()


def get_sky_model(uvdata, nsource):
    # One fixed source plus random other sources
    sources = [
        [125.7, -30.72, 2, 0],  # Fix a single source near zenith
    ]
    if nsource > 1:  # Add random other sources
        ra = np.random.uniform(low=0.0, high=360.0, size=nsource - 1)
        dec = -30.72 + np.random.random(nsource - 1) * 10.0
        flux = np.random.random(nsource - 1) * 4
        for i in range(nsource - 1):
            sources.append([ra[i], dec[i], flux[i], 0])
    sources = np.array(sources)

    # Source locations and frequencies
    ra_dec = np.deg2rad(sources[:, :2])
    freqs = np.unique(uvdata.freq_array)

    # Stokes for the first frequency only. Stokes for other frequencies
    # are calculated later.
    stokes = np.zeros((4, 1, ra_dec.shape[0]))
    stokes[0, 0] = sources[:, 2]
    reference_frequency = np.full(len(ra_dec), freqs[0])

    # Set up sky model
    sky_model = SkyModel(
        name=[str(i) for i in range(len(ra_dec))],
        ra=Longitude(ra_dec[:, 0], "rad"),
        dec=Latitude(ra_dec[:, 1], "rad"),
        spectral_type="spectral_index",
        spectral_index=sources[:, 3],
        stokes=stokes * units.Jy,
        reference_frequency=Quantity(reference_frequency, "Hz"),
        frame="icrs",
    )

    # Calculate stokes at all the frequencies.
    sky_model.at_frequencies(Quantity(freqs, "Hz"), inplace=True)

    return sky_model


def get_beams(beam_type, polarized):
    """Get a list of beam objects, one per antenna."""
    if beam_type == "gaussian":
        beams = [AnalyticBeam("gaussian", sigma=0.103)]

    elif beam_type == "PolyBeam":
        cfg_pol_beam = dict(
            ref_freq=1e8,
            spectral_index=-0.6975,
            beam_coeffs=[
                2.35088101e-01,
                -4.20162599e-01,
                2.99189140e-01,
                -1.54189057e-01,
                3.38651457e-02,
                3.46936067e-02,
                -4.98838130e-02,
                3.23054464e-02,
                -7.56006552e-03,
                -7.24620596e-03,
                7.99563166e-03,
                -2.78125602e-03,
                -8.19945835e-04,
                1.13791191e-03,
                -1.24301372e-04,
                -3.74808752e-04,
                1.93997376e-04,
                -1.72012040e-05,
            ],
            polarized=polarized,
        )

        beams = [PolyBeam(**cfg_pol_beam)]
    else:
        raise ValueError("beam_type '%s' not recognized" % beam_type)
    return beams


@pytest.mark.parametrize(
    "nsource,beam_type,polarized",
    [
        (1, "gaussian", False),
        (1, "PolyBeam", False),
        (1, "PolyBeam", True),
        (100, "gaussian", False),
        (100, "PolyBeam", False),
        (100, "PolyBeam", True),
    ],
)
def test_compare_matvis_with_pyuvsim(uvdata_allpols, nsource, beam_type, polarized):
    """Compare matvis and pyuvsim simulated visibilities."""
    sky_model = get_sky_model(uvdata_allpols, nsource)

    # Beam models
    beams = get_beams(beam_type=beam_type, polarized=polarized)
    beam_dict = {str(i): 0 for i in range(nants)}

    # ---------------------------------------------------------------------------
    # (1) Run matvis
    # ---------------------------------------------------------------------------
    # Trim unwanted polarizations
    uvdata_matvis = copy.deepcopy(uvdata_allpols)

    if not polarized:
        uvdata_matvis.select(polarizations=["ee"], inplace=True)

    # Construct simulator object and run
    simulator = MatVis(
        ref_time=Time("2018-08-31T04:02:30.11", format="isot", scale="utc"),
        use_gpu=False,
    )

    # TODO: if we update the PolyBeam API so that it doesn't *require* 2 feeds,
    # we can get rid of this.
    vis_cpu_beams = [copy.deepcopy(beam) for beam in beams]
    if not polarized:
        for beam in vis_cpu_beams:
            beam.efield_to_power()

    sim = VisibilitySimulation(
        data_model=ModelData(
            uvdata=uvdata_matvis, sky_model=sky_model, beams=vis_cpu_beams
        ),
        simulator=simulator,
    )

    sim.simulate()
    uvd_matvis = sim.uvdata

    # ---------------------------------------------------------------------------
    # (2) Run pyuvsim
    # ---------------------------------------------------------------------------
    uvd_uvsim = uvsim.run_uvdata_uvsim(
        uvdata_allpols,
        BeamList(beams),
        beam_dict=beam_dict,
        catalog=simsetup.SkyModelData(sky_model),
        quiet=True,
    )

    # ---------------------------------------------------------------------------
    # Compare results
    # ---------------------------------------------------------------------------
    # Set relative/absolute tolerances depending on no. of sources
    # (N.B. vis_cpu source position correction approximation degrades with time)
    if nsource < 10:
        # Very stringent for a few sources
        rtol = 1e-4
        atol = 1e-7
    else:
        # Within 0.1% or so for many sources
        rtol = 1e-3
        atol = 1e-5

    for i in range(nants):
        for j in range(nants):
            print("Baseline: ", i, j)
            np.testing.assert_allclose(
                uvd_uvsim.get_data((i, j, "xx")),
                uvd_matvis.get_data((i, j, "xx")),
                atol=atol,
                rtol=rtol,
            )
