"""
=======================
 Phase basic functions
=======================

This example shows how to use the Phase functions

"""

# import matplotlib
# matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
from os.path import join, isdir
import seaborn as sns
from phase_utils import *
sns.set()
sns.set_context('paper')

###############################
# Parameters
fs = 256
tmax = 0.7
data_dirpath = join('pySAB', 'sample_data') if isdir('pySAB') else join('..', '..', 'pySAB', 'sample_data')

###############################
# Load the example EEG signal and visualize it
x = np.fromfile(join(data_dirpath, 'rec_042_chan_EEG_Cp1-Cp2_trial_1_2048Hz.dat'))
f = plt.figure()
ax = f.add_subplot(111)
plt.plot(np.linspace(0, tmax, len(x)), x)
plt.autoscale(axis='x', tight=True)
ax.set(title='Raw signal', xlabel='Time (s)', ylabel='Amplitude')

#####################################
# Filter the signal in the alpha band
# ``bp_filter_1d()`` allows to visualize the bode diagram of the filter
x_alpha, _ = bp_filter_1d(x, fs, ftype='elliptic', wn=2 / fs * np.array([8, 12]), order=3, do_plot=1)


############################
# Plot the analytical signal
plot_analytical_signal(x_alpha, fs)

#####################################
# Compute the robust phase estimation
compute_robust_estimation(x, fs, fmin=8, fmax=12, f_tolerance=0.1, noise_tolerance=1, n_monte_carlo=20, do_fplot=0,
                          do_plot=1)