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nimaijinimaiji
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develop Noise class and Hn class
1 parent 28d4061 commit af9a973

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7 files changed

+306
-71
lines changed

7 files changed

+306
-71
lines changed

‎Hn.txt

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-0.0001
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0.0000
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0.0004
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0.0013
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0.0028
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0.0047
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0.0068
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0.0085
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0.0090
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0.0078
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0.0050
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0.0008
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-0.0036
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-0.0067
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-0.0075
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-0.0053
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-0.0007
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0.0048
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0.0091
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0.0101
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0.0069
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0.0002
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-0.0077
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-0.0137
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-0.0147
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-0.0094
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0.0010
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0.0131
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0.0219
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0.0228
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0.0135
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-0.0043
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-0.0250
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-0.0402
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-0.0414
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-0.0229
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0.0158
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0.0692
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0.1265
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0.1748
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0.2024
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0.2024
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0.1748
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0.1265
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0.0692
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0.0158
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-0.0229
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-0.0414
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-0.0402
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-0.0250
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-0.0043
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0.0135
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0.0228
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0.0219
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0.0131
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0.0010
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-0.0094
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-0.0147
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-0.0137
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-0.0077
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0.0002
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0.0069
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0.0101
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0.0091
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0.0048
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-0.0007
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-0.0053
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-0.0075
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-0.0067
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-0.0036
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0.0008
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0.0050
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0.0078
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0.0090
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0.0085
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0.0068
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0.0047
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0.0028
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0.0013
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0.0004
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0.0000
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-0.0001

‎Sound.py

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This file was deleted.

‎main.py

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from sound import Noise,Hn
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#
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# s1 = Noise(path='./M1.wav', name='M1')
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# s1.draw_fft()
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#
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# s2 = Noise(path='./M2.wav', name='M2')
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# s2.draw_fft()
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# #
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s3 = Noise(path='./M3.wav', name='M3')
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shifted = s3.shift_right(0.001)
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# s3.draw()
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# s3.hear_noise()
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# print(s3.when_max())
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# Reading Hn
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hn = Hn(path='./Hn.txt')
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# hn.draw()
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# conv = s3.convolve(hn)
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# print(conv.get_duration())
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# slc = conv.get_slice(float(0.2))
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# print(slc.get_duration())
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# slc_conv = slc.convolve(conv)
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# slc_conv.draw()
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‎new_sound_draw.py

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import matplotlib.pyplot as plt
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from scipy.io import wavfile
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samplerate,date = wavfile.read('1980s-Casio-Piano-C5.wav','r')
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print(samplerate)

‎sampleSound.py

Whitespace-only changes.

‎sound.py

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import matplotlib.pyplot as plt
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import numpy as np
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from IPython.lib.display import Audio
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from scipy.io import wavfile
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from scipy.fftpack import fft, fftfreq
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import logging
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from tempfile import mkdtemp
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import os.path as path
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import sys
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logging.basicConfig(level=logging.DEBUG, filename='app.log', filemode='w',
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format='%(levelname)s - %(name)s: %(message)s')
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def printCmd(str):
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h = (32 * '-') + '\n'
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print(h + str + '\n' + h)
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class Hn:
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def __init__(self, **kwargs):
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self.data = []
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self.name = 'H[n]'
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self.path = None
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self.points = [[], []]
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if kwargs['path'] != '':
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self.path = kwargs['path']
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file = open(self.path, 'r')
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for line in file:
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self.data += [float(line)]
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elif kwargs['data']:
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self.data = kwargs['data']
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elif kwargs['path'] != '' and kwargs['data']:
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logging.debug('please insert a path or array of data')
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raise AttributeError('please insert a path or array of data')
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else:
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logging.debug('please insert a path or array of data')
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raise AttributeError('please insert a path or array of data')
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logging.info('Hn = {}'.format(str(self.data)))
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for i in range(len(self.data)):
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self.points[0] += [i]
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self.points[1] += [self.data[i]]
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def draw(self):
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plt.title(self.name)
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plt.plot(self.points[0], self.points[1])
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plt.xlabel('Rate')
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plt.ylabel('Amplitude')
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plt.show()
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def draw_phase(self):
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plt.title(self.name + 'Phase spectrum')
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plt.phase_spectrum(self.points[1])
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plt.show()
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def __str__(self):
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return self.data
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class Noise:
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def __init__(self, **kwargs):
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self.data = []
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self.sample_rate = 0
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self.fft = []
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self.frame = 0
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self.path = None
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if kwargs['path']:
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self.path = kwargs['path']
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self.parse_wav()
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elif kwargs['data'] is not None:
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self.data = kwargs['data']
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self.sample_rate = 32000
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logging.info('noise data = {}'.format(self.data))
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elif kwargs['path'] != '' and kwargs['data']:
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logging.debug('please insert a path or array of data')
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raise AttributeError('please insert a path or array of data')
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else:
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logging.debug('please insert a path or array of data')
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raise AttributeError('please insert a path or array of data')
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try:
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self.name = kwargs['name']
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except:
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self.name = 'Unknown' if self.path is None else self.path
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logging.info('{} noise created.'.format(self.name))
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def parse_wav(self):
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sample_rate, data = wavfile.read(self.path, 'r')
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self.data = data
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self.sample_rate = sample_rate
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logging.info('noise sample rate = {}'.format(self.sample_rate))
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logging.info('noise data = {}'.format(self.data))
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return self.data
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def init_fft(self):
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self.fft = fft(self.data)
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def get_fft(self):
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self.init_fft()
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return self.fft
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def get_energy(self):
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return np.sum((np.abs(self.data) ** 2) / (self.sample_rate ** -1))
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def get_duration(self):
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return len(self.data) / float(self.sample_rate)
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def get_slice(self, slc):
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length = len(self.data)
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mul = (slc / self.get_duration()) * length
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index = int(mul)
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return Noise(name='{}s of {}'.format(slc, self.name), data=self.data[0:index], path='')
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def get_max(self):
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return np.amax(self.data)
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def when_max(self):
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length = len(self.data)
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index = np.where(self.data == self.get_max())
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when = ((index[0] * self.get_duration()) / length)[0]
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logging.info('{} at {}s is max'.format(self.name, when))
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return when
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def shift_right(self, slc):
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amount = int(slc * self.sample_rate)
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filename = path.join(mkdtemp(), 'newfile.dat')
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fpath = np.memmap(filename, dtype='int16', mode='w+', shape=amount + len(self.data))
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fpath[amount::] = self.data
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logging.info('{} {} shifted right'.format(self.name, amount))
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return Noise(name='{} time shifted right {}'.format(amount, self.name),
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data=fpath, path='')
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# Todo: check this function
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def shift_left(self, slc):
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amount = int(slc * self.sample_rate)
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filename = path.join(mkdtemp(), 'newfile.dat')
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fpath = np.memmap(filename, dtype='int16', mode='w+', shape=amount + len(self.data))
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fpath[::len(self.data)] = self.data
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logging.info('{} {} shifted left'.format(self.name, amount))
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return Noise(name='{} time shifted left {}'.format(amount, self.name),
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data=fpath, path='')
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def reverse(self):
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self.data = [ele for ele in reversed(self.data)]
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def draw(self):
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plt.figure(self.name, figsize=(12, 5))
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plt.title(self.name + ' Noise')
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time = np.arange(0, self.get_duration(), 1 / self.sample_rate) # time vector
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plt.plot(time, self.data)
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plt.xlabel('Time (s)')
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plt.ylabel('Amplitude')
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plt.grid(True)
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plt.show()
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def draw_fft(self):
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self.init_fft()
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plt.figure(self.name + ' FFT')
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plt.plot(self.fft)
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plt.xlim([10, self.sample_rate / 2])
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plt.xscale('log')
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plt.grid(True)
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plt.xlabel('Frequency (Hz)')
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plt.show()
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def draw_all(self):
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plt.figure(self.name)
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plt.plot(self.data)
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plt.grid(True)
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plt.figure(self.name + ' FFT')
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plt.plot(self.fft)
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plt.xlim([10, self.sample_rate / 2])
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plt.xscale('log')
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plt.grid(True)
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plt.xlabel('Frequency (Hz)')
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plt.show()
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def draw_phase(self):
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plt.title(self.name + 'Phase spectrum')
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plt.phase_spectrum(self.data)
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plt.show()
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def convolve(self, hn):
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return Noise(name='{} * {}'.format(self.name, hn.name), data=np.convolve(self.data, hn.data), path='')
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def hear_noise(self):
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return Audio(data=self.data, rate=self.sample_rate)
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def __str__(self):
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return self.data

‎soundDraw.py

Whitespace-only changes.

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