"""
===========================================
  Cochlea Creation with Adpative Threshold
===========================================

Create a simple cochlea model and test it on a sinusoidal input signal

"""

# import matplotlib
# matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from simplecochlea import Cochlea
sns.set_context('paper')

############################
# Create the cochlea
fs, fmin, fmax, freq_scale, n_channels = 44100, 200, 8000, 'erbscale', 100
comp_factor, comp_gain = 0.3, 1.5
tau, v_thresh, v_spike = np.linspace(0.001, 0.0004, n_channels), 0, 0.5
# Adaptive threshold parameters
tau_j, alpha_j = np.array([0.010, 0.200]), np.array([0.010, 0.000002])
omega = np.linspace(0.15, 0.2, n_channels)

cochlea_adaptive_thresh = Cochlea(n_channels, fs, fmin, fmax, freq_scale, comp_factor=comp_factor, comp_gain=comp_gain,
                                  lif_tau=tau, lif_v_thresh=v_thresh, lif_v_spike=v_spike, tau_j=tau_j, alpha_j=alpha_j,
                                  omega=omega)

###############################
# Print the description
print(cochlea_adaptive_thresh)

###############################
# Process a sin input signal
spikelist_sin, _ = cochlea_adaptive_thresh.process_test_signal('sin', f_sin=400, t_offset=0, t_max=0.5, do_plot=0)

###############################
# Plot the output spikelist
spikelist_sin.plot()