from __future__ import division, print_function
import numpy
import batman
from transitleastsquares_ES import transitleastsquares_ES


# Test case for statistics when data contains gap during a transit

if __name__ == "__main__":
    print("Starting test: Gap in test statistic...", end="")
    numpy.random.seed(seed=0)  # reproducibility
    # Create test data
    start = 48
    days = 365.25 * 3
    samples_per_day = 12  # 48
    samples = int(days * samples_per_day)  # 48
    t = numpy.linspace(start, start + days, samples)

    # Use batman to create transits
    ma = batman.TransitParams()
    ma.t0 = start + 20
    ma.per = 365.25  # orbital period
    ma.rp = 6371 / 696342  # 6371 planet radius (in units of stellar radii)
    ma.a = 217  # semi-major axis (in units of stellar radii)
    ma.inc = 90  # orbital inclination (in degrees)
    ma.ecc = 0  # eccentricity
    ma.w = 90  # longitude of periastron (in degrees)
    ma.u = [0.5]  # limb darkening coefficients
    ma.limb_dark = "linear"  # limb darkening model
    m = batman.TransitModel(ma, t)  # initializes model
    original_flux = m.light_curve(ma)  # calculates light curve

    # Create noise and merge with flux
    ppm = 5
    stdev = 10 ** -6 * ppm
    noise = numpy.random.normal(0, stdev, int(samples))
    y = original_flux + noise
    y[1] = numpy.nan

    # print(len(y))
    y[200:500] = numpy.nan
    t[200:500] = numpy.nan
    # import matplotlib.pyplot as plt
    # plt.plot(t, y)
    # plt.show()

    model = transitleastsquares_ES(t, y)
    results = model.power(
        period_min=360,
        period_max=370,
        transit_depth_min=10 * 10 ** -6,
        oversampling_factor=2,
        duration_grid_step=1.1,
        T0_fit_margin=1.2,
    )

    numpy.testing.assert_almost_equal(
        results.period_uncertainty, 0.3153203546531813, decimal=5
    )
    numpy.testing.assert_equal(results.per_transit_count, [0, 5, 5])
    numpy.testing.assert_equal(len(results.transit_times), 3)
    numpy.testing.assert_almost_equal(results.period, 365.22218620040417, decimal=5)
    numpy.testing.assert_almost_equal(
        results.transit_times,
        [68.08637, 433.30855, 798.53074],
        decimal=5,
    )

    numpy.testing.assert_almost_equal(results.depth, 0.9998972750356973, decimal=5)
    numpy.testing.assert_almost_equal(results.duration, 0.41845319797978703, decimal=5)
    numpy.testing.assert_almost_equal(results.SDE, 4.243572802600693, decimal=3)
    numpy.testing.assert_almost_equal(
        results.odd_even_mismatch, 0.15059221218811772, decimal=3
    )
    numpy.testing.assert_almost_equal(results.rp_rs, 0.009114758081257387, decimal=3)

    # Full light curve model
    numpy.testing.assert_almost_equal(
        numpy.sum(results.model_lightcurve_time), 38275494.19583159, decimal=3
    )
    numpy.testing.assert_almost_equal(
        numpy.sum(results.model_lightcurve_model), 64233.9941755991, decimal=3
    )

    transit_times_expected = [68.086, 433.309, 798.531]
    numpy.testing.assert_almost_equal(
        results.transit_times, transit_times_expected, decimal=3
    )
    numpy.testing.assert_almost_equal(results.duration, 0.41845319797978703, decimal=3)

    numpy.testing.assert_almost_equal(
        max(results.model_folded_phase), 1.0000380285975052, decimal=3
    )
    numpy.testing.assert_almost_equal(
        min(results.model_folded_phase), 3.8028597505324e-05, decimal=3
    )
    numpy.testing.assert_almost_equal(
        numpy.mean(results.model_folded_phase), 0.5000380285975052, decimal=3
    )

    numpy.testing.assert_almost_equal(
        results.depth_mean_even, (0.999915, 6.785539e-06), decimal=3
    )
    numpy.testing.assert_almost_equal(
        results.depth_mean_odd, (0.999920, 1.209993e-05), decimal=3
    )
    numpy.testing.assert_almost_equal(
        results.depth_mean, (0.999917, 6.086923e-06), decimal=3
    )

    numpy.testing.assert_almost_equal(
        results.transit_depths, [numpy.nan, 0.99991, 0.9999], decimal=3
    )

    numpy.testing.assert_almost_equal(
        results.transit_depths_uncertainties,
        [numpy.nan, 2.92371e-06, 4.48803e-06],
        decimal=3,
    )
    numpy.testing.assert_almost_equal(
        results.odd_even_mismatch, 0.15059221218811772, decimal=3
    )
    numpy.testing.assert_almost_equal(results.transit_count, 3, decimal=3)
    numpy.testing.assert_almost_equal(results.distinct_transit_count, 2, decimal=3)
    numpy.testing.assert_almost_equal(results.empty_transit_count, 1, decimal=3)
    numpy.testing.assert_almost_equal(
        results.snr_per_transit, [0., 37.052, 36.558], decimal=3
    )
    numpy.testing.assert_almost_equal(results.snr, 52.050323372452034, decimal=3)
    numpy.testing.assert_almost_equal(
        results.snr_pink_per_transit, [0., 45.477, 44.871], decimal=3
    )
    print("passed")
