for i in range(len(fil)):
if (fil[i] < 20):
fil[i] = 0
pitches = np.asarray(fil, dtype=float)
#remove silent sections
index = np.argwhere(pitches == 0.0)
#print index
pitches_with_no_zero = np.delete(pitches, index)
'''
plt.plot(t,pitches_with_no_zero)
plt.xlabel('time')
plt.ylabel('frequency hz')
plt.show()
'''
hz_to_cents.convert_to_cents(pitches_with_no_zero, cent_vals)
#cut frequencies below 3000 cents
cents = np.asarray(cent_vals, dtype=float)
t = np.arange(0, len(cents))
plt.plot(t, cents)
plt.xlabel('time')
plt.ylabel('frequency cents')
plt.show()
'''
f,axarr=plt.subplots(2,sharex=True)
axarr[0].plot(t,pitches_with_no_zero)
axarr[0].set_ylabel('hz')
axarr[1].plot(t,cents)
axarr[1].set_ylabel('cents')
plt.show()
new_part = '.notes.csv'
new_fname = base + new_part
with open(new_fname, 'rb') as f:
reader = csv.reader(f)
for row in reader:
times.append(round(float(row[0]), 3))
durations.append(round(float(row[1]), 3))
notes.append(row[2])
#get_the_gap(4.362,,time_start,pitch_values)
for i in range(len(times)):
get_the_gap(times[i], times[i] + durations[i], time_start, diffs,
int(notes[i]))
diffs_normal = []
hz_to_cents.convert_to_cents(diffs, diffs_normal)
#diffs.append(100)
'''
for i in range(len(diffs)):
if(diffs[i]<=100):
diffs_normal.append(diffs[i])
''',
diff_np = np.asarray(diffs_normal, dtype=float)
time_np = np.arange(0, len(diff_np), 1)
plt.figure
plt.plot(time_np, diff_np, 'b')
plt.xlabel('note')
plt.ylabel('FO CENTS')
plt.title(base)