1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
|
# This is a sample Python script.
import struct
# Press ⌃R to execute it or replace it with your code.
# Press Double ⇧ to search everywhere for classes, files, tool windows, actions, and settings.
from scipy.fftpack import fft
import numpy as np
import pyaudio
import matplotlib.pyplot as plt
class Test(object):
def __init__(self):
# stream constants
self.CHUNK = 2048 * 2
self.FORMAT = pyaudio.paInt32
self.CHANNELS = 1
self.RATE = 44100
self.pause = False
# stream object
self.p = pyaudio.PyAudio()
self.stream = self.p.open(
format=self.FORMAT,
channels=self.CHANNELS,
rate=self.RATE,
input=True,
output=True,
frames_per_buffer=self.CHUNK,
)
self.seenvalues = set()
# goal: returns the max frequency of waveform
def get_fundamental_frequency(self, audio_waveform):
spectrum = fft(audio_waveform)
# scale the spectrum
scaled_spectrum = np.abs(spectrum[0:self.CHUNK]) / (128 * self.CHUNK)
# clean the nullish first and last values
cleaned_scaled_spectrum = scaled_spectrum[10:-10]
# get the index of the max
np_max = max(cleaned_scaled_spectrum)
max_index = np.where(scaled_spectrum == np_max)[0][0]
# the index corresponds to the following linspace
index_to_freq = np.linspace(0, self.RATE, self.CHUNK)
return index_to_freq[max_index], scaled_spectrum
def read_audio_stream(self):
data = self.stream.read(self.CHUNK, exception_on_overflow=False)
data_int = struct.unpack(str(4 * self.CHUNK) + 'B', data)
return data_int
def open_loop(self, graphics=True):
self.init_plots()
while not self.pause:
waveform = self.read_audio_stream()
freq_max, scaled_spectrum = self.get_fundamental_frequency(waveform)
if 250 < freq_max < 550:
if freq_max not in self.seenvalues:
print(freq_max)
self.seenvalues.add(freq_max)
# update figure canvas if wanted
if graphics:
# set top graph
data_np = np.array(waveform, dtype='b')[::4] + 128
self.line.set_ydata(data_np)
# set bottom graph
self.line_fft.set_ydata(scaled_spectrum)
# update figures
self.fig.canvas.draw()
self.fig.canvas.flush_events()
def init_plots(self):
# x variables for plotting
x = np.arange(0, 2 * self.CHUNK, 2)
xf = np.linspace(0, self.RATE, self.CHUNK)
# create matplotlib figure and axes
self.fig, (ax1, ax2) = plt.subplots(2, figsize=(15, 7))
# create a line object with random data
self.line, = ax1.plot(x, np.random.rand(self.CHUNK), '-', lw=2)
# create semilogx line for spectrum
self.line_fft, = ax2.semilogx(
xf, np.random.rand(self.CHUNK), '-', lw=2)
# format waveform axes
ax1.set_title('AUDIO WAVEFORM')
ax1.set_xlabel('samples')
ax1.set_ylabel('volume')
ax1.set_ylim(0, 255)
ax1.set_xlim(0, 2 * self.CHUNK)
plt.setp(
ax1, yticks=[0, 128, 255],
xticks=[0, self.CHUNK, 2 * self.CHUNK],
)
plt.setp(ax2, yticks=[0, 1], )
# format spectrum axes
ax2.set_xlim(20, self.RATE / 2)
# show axes
thismanager = plt.get_current_fig_manager()
# thismanager.window.setGeometry(5, 120, 1910, 1070)
plt.show(block=False)
if __name__ == '__main__':
t = Test()
t.open_loop()
|
