# ------------------------------------------------------------------------------
# Copyright (c) Acoular Development Team.
# ------------------------------------------------------------------------------
"""
MultiSector
===========

This example demonstrates how to use the MultiSector class in Acoular to combine multiple sectors
and perform spatial integration over complex regions. It reuses the measurement setup and helper
functions from the sectors example for convenience.
"""

# %%
# ===========
# Preparation
# ===========
#
# First, we import the modules and functions we are going to use in this example.

from pathlib import Path

import acoular as ac
import matplotlib.pyplot as plt
import numpy as np
from acoular.tools import barspectrum
from acoular.tools.helpers import get_data_file

# Import Acoular objects and helper functions from the sectors example
# from example_sectors import bb, freqs, grid, sector, spl_map

time_data_file = get_data_file('example_data.h5')
calib_file = get_data_file('example_calib.xml')

ts = ac.MaskedTimeSamples(
    file=time_data_file,
    invalid_channels=[1, 7],
    start=0,
    stop=16000,
)
calib = ac.Calib(source=ts, file=calib_file, invalid_channels=[1, 7])
mics = ac.MicGeom(file=Path(ac.__file__).parent / 'xml' / 'array_56.xml', invalid_channels=[1, 7])
grid = ac.RectGrid(x_min=-0.6, x_max=0.0, y_min=-0.3, y_max=0.3, z=-0.68, increment=0.05)
env = ac.Environment(c=346.04)
st = ac.SteeringVector(grid=grid, mics=mics, env=env)
f = ac.PowerSpectra(source=calib, window='Hanning', overlap='50%', block_size=128)
bb = ac.BeamformerBase(freq_data=f, steer=st)

sector = ac.RectSector(x_min=-0.275, x_max=-0.225, y_min=-0.20, y_max=0.15)

map = bb.synthetic(8000)
spl_map = ac.L_p(map)

freqs = f.fftfreq()

# %%
# =================
# Combining Sectors
# =================
#
# Since the :class:`~acoular.grids.MultiSector` class combines multiple
# :class:`~acoular.grids.Sector`-derived objects, we need to define a
# second sector. Here, we choose the :class:`~acoular.grids.CircSector` class.

circsector = ac.CircSector(x=-0.4, y=0.0, r=0.07)

# %%
# Let us see how the two sectors look on the source map.

plt.figure(figsize=(8, 5))
im = plt.imshow(spl_map.T, origin='lower', vmin=spl_map.max() - 10, extent=grid.extent, cmap='hot_r')
plt.fill_between([sector.x_min, sector.x_max], sector.y_min, sector.y_max, alpha=0.7, label='RectSector', color='gray')
circ = plt.Circle((circsector.x, circsector.y), circsector.r, color='orange', alpha=0.4, label='CircSector')
plt.gca().add_patch(circ)
plt.scatter(*grid.pos[0:2], c='lightgray', s=10, label='Grid Points', alpha=0.2)
plt.xlabel('x / m')
plt.ylabel('y / m')
plt.title('RectSector and CircSector')
plt.colorbar(im, label='$L_p$ / dB')
plt.legend()
plt.show()

# %%
# Now we create a :class:`~acoular.grids.MultiSector` object that encompasses both sectors.

multisector = ac.MultiSector(sectors=[sector, circsector])

# %%
# Note that this object does **not** have the attributes of the :class:`~acoular.grids.SingleSector`
# class: The :attr:`~acoular.grids.SingleSector.include_border`,
# :attr:`~acoular.grids.SingleSector.abs_tol`, and
# :attr:`~acoular.grids.SingleSector.default_nearest` attributes are **not** part of the
# :class:`~acoular.grids.MultiSector` class.

# %%
# ==============================
# Integrate Over the MultiSector
# ==============================
#
# Here, as in the sector example, we integrate once over all FFT frequencies and then also look at
# the third-octova spectrum.


# Define a function to get only SPL spectrum values greater than zero
def get_spl(spectrum):
    spl = ac.L_p(spectrum)
    return np.where(spl > 0, spl, 0)


# Integrate over multisector
bf_multisector = bb.integrate(multisector)

# Use barspectrum to get third-octave bands
f_borders, bars, f_center = barspectrum(bf_multisector, freqs, 3, bar=True)


fig, ax1 = plt.subplots(figsize=(10, 6))
color1 = 'tab:blue'
color2 = 'tab:orange'

ax1.set_xlabel('Frequency / Hz')
ax1.fill_between(f_borders, get_spl(bars), color=color2, alpha=0.5, label='Third-Octave Barspectrum')
ax1.set_ylabel('$L_p$ / dB', color=color1)
ax1.tick_params(axis='y', labelcolor=color1)
ax1.set_title('MultiSector Integration: Spectrum and Third-Octave Barspectrum')
ax1.grid(True)

ax2 = ax1.twinx()
ax2.plot(freqs, get_spl(bf_multisector), color=color1, label='Integrated Spectrum (all freqs)')
ax2.set_ylabel('$L_p$ / dB (barspectrum)', color=color2)
ax2.tick_params(axis='y', labelcolor=color2)
ax2.set_ylim(ax1.get_ylim())
ax2.set_xscale('log')

fig.tight_layout()
fig.legend(loc='upper right', bbox_to_anchor=(0.93, 0.93))
plt.show()

# %%
# You can use :class:`~acoular.grids.MultiSector` with any combination of sector types, such as
# :class:`~acoular.grids.RectSector`, :class:`~acoular.grids.CircSector`, and
# :class:`~acoular.grids.PolySector`.
# This makes it easy to analyze complex regions in your sound field.