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| -rw-r--r-- | before_train.py | 120 |
1 files changed, 0 insertions, 120 deletions
diff --git a/before_train.py b/before_train.py deleted file mode 100644 index 64e5487..0000000 --- a/before_train.py +++ /dev/null @@ -1,120 +0,0 @@ -# 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() |