import matplotlib.pyplot as plt
import numpy as np
from scipy.io import wavfile
from tones import sin_tone, exp_decay
if __name__ == '__main__':
RATE = 48000
MAX_VOL = 15000
FREQ = 440 # * 2**(1/4)
MOD = int(RATE / (2 * FREQ))
signal = np.array([
sin_tone(FREQ, RATE, i) * MAX_VOL * exp_decay(RATE, i)
for i in range(RATE)
])
FREQ = 440 * 2**(1/3)
MOD = RATE / FREQ
# signal += np.array([
# (-1)**(i//int(MOD)) * MAX_VOL * np.exp(-i/(RATE/5))
# for i in range(RATE)
# ])
# signal = np.concatenate((signal, signal2))
plt.plot(signal)
))
RATE = 8000
MAX_VOL = 15000
TONE = sin_tone
empty_song = make_space(notes, RATE)
pointer = 0 # keeps current position in song
for note, duration in notes:
duration = int(RATE * notelen(duration))
freq = NOTES[note]
if freq != 0:
for i in range(duration):
empty_song[pointer + i] = \
MAX_VOL *\
TONE(freq, RATE, i) *\
exp_decay(RATE, i)
else:
for i in range(duration):
empty_song[pointer + i] = 0
pointer += duration
plt.plot(empty_song)
plt.show()
wavfile.write('melody.wav', RATE, np.array(empty_song, dtype=np.int16))
filter(lambda x: not x.startswith('#'), sheet_music)))
RATE = 8000
MAX_VOL = 15000
TONE = sin_tone
empty_song = make_space(notes, RATE)
pointer = 0 # keeps current position in song
for note, duration in notes:
duration = int(RATE * notelen(duration))
freq = NOTES[note]
if freq != 0:
for i in range(duration):
empty_song[pointer + i] = \
MAX_VOL *\
TONE(freq, RATE, i) *\
exp_decay(RATE, i)
else:
for i in range(duration):
empty_song[pointer + i] = 0
pointer += duration
plt.plot(empty_song)
plt.show()
wavfile.write('melody.wav', RATE, np.array(empty_song, dtype=np.int16))
import matplotlib.pyplot as plt
import numpy as np
from scipy.io import wavfile
from tones import sin_tone, exp_decay
if __name__ == '__main__':
RATE = 48000
MAX_VOL = 15000
FREQ = 440 # * 2**(1/4)
MOD = int(RATE / (2 * FREQ))
signal = np.array([
sin_tone(FREQ, RATE, i) * MAX_VOL * exp_decay(RATE, i)
for i in range(RATE)
])
FREQ = 440 * 2**(1 / 3)
MOD = RATE / FREQ
# signal += np.array([
# (-1)**(i//int(MOD)) * MAX_VOL * np.exp(-i/(RATE/5))
# for i in range(RATE)
# ])
# signal = np.concatenate((signal, signal2))
plt.plot(signal)
