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unsupervised_rythmic.py
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# Est-ce que quand c’est chanté le préfrontal est plus activé?
from dataset_generator import *
import matplotlib
# matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import spectrum
FREQ_RANGES = [[0.5, 4], [4, 8], [8, 12], [11, 15], [15, 30], [30, 45]]
labels = ["Delta", "Theta", "Alpha1", "Alpha2", "Beta", "Gamma"]
SIGNALS_TO_ANALYZE = ["T8", "C4", "F4", "T7", "C3", "CZ"]
def get_spectral_intensities(data, ranges=FREQ_RANGES):
intensities = []
spectral_data = spectrum.pmtm(data, 2.5, show=False)
l = len(data)
for [min, max] in ranges:
intensities.extend(sum(spectral_data[int(min * l / FREQ):int(max * l / FREQ)])/(max-min))
return intensities
def get_all_spectral_intensities(sample, ranges=FREQ_RANGES, signals=SIGNALS_TO_ANALYZE):
intensities = []
for signal in signals:
intensities.extend(get_spectral_intensities(sample[signal], ranges))
return(intensities)
plt.figure("C1['T8']")
width = 1
# Rythmic
plt.subplot(521)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[8]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("City Lies")
plt.subplot(523)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[5]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("Victor Wooten")
plt.subplot(525)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[3]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("Gorillaz")
plt.subplot(527)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[4]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("Above n Beyond")
plt.subplot(529)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[9]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("Glaciation")
# Instru
plt.subplot(522)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[1]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("District7")
plt.subplot(524)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[2]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("Patrick Sebastien")
plt.subplot(526)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[6]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("Stravinsky")
plt.subplot(528)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[7]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("Symbolic n Avalon")
plt.subplot(520)
plt.bar(np.arange(6), get_spectral_intensities(enrC1[0]["T8"]))
plt.xticks(np.arange(6) + width/2., labels)
plt.yscale('log')
plt.ylabel("Nekfeu")
plt.show()
# plt.savefig("C1.png")
# prefrontal_sung = np.array([])
# prefrontal_instru = np.array([])
# for i in range(10):
# if features1[i]["sung"] == 1:
# print(i)
# # prefrontal_sung = np.concatenate((prefrontal_sung, enrL1[i]["T8"]), axis=0)
# else:
# print("lol", i)
# # prefrontal_instru = np.concatenate((prefrontal_instru, enrL1[i]["F4"]), axis=0)
# prefrontal_sung = abs(fft(prefrontal_sung))
# prefrontal_instru = abs(fft(prefrontal_instru))
#
# def ffty(y):
# # len(y)=T*N
# # de 0 a 40 Hz
# fmax = 40.0
# T = 1.0 / (2.0 * fmax)
# # Number of samplepoints
# N = len(y)/T
# print("N ", N)
# yf = fft(y)
# print(len(yf))
# xf = np.linspace(0.0, 1.0/(2.0*T), N/2)
# print(len(xf))
# plt.plot(xf, 2.0/N * np.abs(yf[0:N/2]))
# plt.grid()
# plt.show()