#!/usr/bin/env python3

from backscattering_analyzer.display import show_projection
from backscattering_analyzer.experiment import AcquisitionType, Experiment

from gettext import install
from rich.progress import track

from numpy import exp, loadtxt
from matplotlib.pyplot import (
    loglog,
    show,
    legend,
    close,
    title,
    xlabel,
    ylabel,
    xlim,
    ylim,
    grid,
    tick_params,
)

install(__name__)

date = "2024_08_15"

design_o5_sensitivity = loadtxt(
    "/home/demagny/data/sensitivity/O5/23932_O5DesignASD.txt"
)
plan_o5_sensitivity = loadtxt("/home/demagny/data/sensitivity/O5/23932_O5PlanBASD.txt")
high_o5_sensitivity = loadtxt(
    "/home/demagny/data/sensitivity/O5/23932_O5HighSensASD.txt"
)
low_o5_sensitivity = loadtxt("/home/demagny/data/sensitivity/O5/23932_O5LowSensASD.txt")
h1_o5_sensitivity = loadtxt("/home/demagny/data/sensitivity/O5/23932_O5HighSensASD.txt")
h1_o5_sensitivity[:, 1] = h1_o5_sensitivity[:, 1] / 10
current_good = loadtxt("/home/demagny/data/sensitivity/O4/nominal_reference.txt")
current_bad = loadtxt("/home/demagny/data/sensitivity/O4/bad_weather_reference.txt")

# fscs = [2e-15, 7e-14, 3e-14]
# SDB1 = 2e-14
fscs = [5e-16, 7e-15, 5e-15]
fsc_SDB1 = 5e-15
benches = ["SDB2", "SNEB", "SWEB"]

experiment = Experiment("SDB1", date, "values-coupling.toml")

experiment.factors = {"pre": fsc_SDB1 / 1e-6, "true": fsc_SDB1}

experiment.projection_reference = experiment.compute_projection(
    AcquisitionType.REFERENCE
)

sum = [experiment.projection_reference.x, experiment.projection_reference.y]

loglog(
    experiment.projection_reference.x,
    experiment.projection_reference.y,
    label=_("{} projection ($f_{{sc}} = {}$)".format("SDB1", fsc_SDB1)),
)

for index in track(range(len(benches)), description=_("Computing projection...")):
    bench = benches[index]
    fsc = fscs[index]

    experiment = Experiment(bench, date, "values-coupling.toml")

    experiment.factors = {"pre": fsc / 1e-6, "true": fsc}

    experiment.projection_reference = experiment.compute_projection(
        AcquisitionType.REFERENCE
    )

    sum[1] += experiment.projection_reference.y

    loglog(
        experiment.projection_reference.x,
        experiment.projection_reference.y,
        label=_("{} projection ($f_{{sc}} = {}$)".format(bench, fsc)),
    )
loglog(sum[0], sum[1], label="sum of all projections")
loglog(
    current_good[0],
    current_good[1],
    label="current sensitivity in good condition",
)
loglog(
    current_bad[0],
    current_bad[1],
    label="current sensitivity in bad condition",
)
loglog(
    high_o5_sensitivity[:, 0],
    high_o5_sensitivity[:, 1],
    label="high sensitivity projection for O5 (BNS range: 160 Mpc)",
)
loglog(
    h1_o5_sensitivity[:, 0],
    h1_o5_sensitivity[:, 1],
    label="order 10 below high O5 projection",
)
loglog(
    low_o5_sensitivity[:, 0],
    low_o5_sensitivity[:, 1],
    label="low sensitivity projection for O5 (BNS range: 106 Mpc)",
)
legend()
title(_("Projection when bad weather (august, 2024), computed using O5 TF"))
xlabel(_("frequencies (Hz)"))
ylabel(_("sensibility ($\\frac{1} {\\sqrt {Hz}}$)"))
xlim(5, 100)
ylim(10e-28, 10e-18)
tick_params(axis="both", which="both")
grid(True, which="both", axis="both")

show()
close()