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cg_fc_rank_mi.py
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cg_fc_rank_mi.py
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#!/Users/kchen/miniconda3/bin/python
# Author: Kai Chen
# Institute: INS, SJTU
# Plot ranked TDMI value, and calculate the gap threshold value.
if __name__ == '__main__':
import time
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams['font.size'] = 14
# plt.rcParams['axes.labelsize'] = 16
plt.rcParams['xtick.labelsize'] = 12
plt.rcParams['ytick.labelsize'] = 12
from fcpy.core import EcogTDMI
from fcpy.utils import print_log
from fcpy.plot import gen_fc_rank_figure_single
from fcpy.plot_frame import *
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
arg_default = {
'path': 'tdmi_snr_analysis/',
}
parser = ArgumentParser(
prog='tdmi_rank_cg',
description = "Plot ranked TDMI.",
formatter_class=ArgumentDefaultsHelpFormatter
)
parser.add_argument(
'path', default=arg_default['path'], nargs='?',
type = str,
help = "path of working directory."
)
args = parser.parse_args()
start = time.time()
# Load SC and FC data
# ==================================================
data = EcogTDMI('data/')
data.init_data(args.path)
sc, fc = data.get_sc_fc('cg')
# ==================================================
data_plt = {}
for band in data.filters:
data_plt[band] = {
'fc':fc[band],
'sc':sc[band],
'band':band,
}
fig = fig_frame52(data_plt, gen_fc_rank_figure_single)
ax = fig.get_axes()
[axi.set_ylabel('Ranked TDMI index') for axi in ax if axi.get_ylabel()]
[axi.set_xlabel(r'$\log_{10}$(TDMI value)') for axi in ax if axi.get_xlabel()]
fname = f'cg_mi_rank.png'
fig.savefig(args.path + fname)
print_log(f'Figure save to {args.path+fname:s}.', start)
plt.close(fig)