def get_wav_info(wav_file):
    wav = wave.open(wav_file, 'r')
    frames = wav.readframes(-1)
    sound_info = pylab.frombuffer(frames, 'int16')
    frame_rate = wav.getframerate()
    wav.close()
    return sound_info, frame_rate
Exemple #2
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def loadMNISTImages(filename):
  f = open(filename, 'rb')

  # Verify Magic Number
  s = f.read(4)
  magic = int(s.encode('hex'),16)
  assert(magic == 2051)

  # Get Number of Images
  s = f.read(4)
  numImages = int(s.encode('hex'),16)
  s = f.read(4)
  numRows = int(s.encode('hex'),16)
  s = f.read(4)
  numCols = int(s.encode('hex'),16)

  # Get Data
  s = f.read()
  a = frombuffer(s, uint8)

  # Use 'F' to ensure that we read by column
  a = reshape(a, (numCols , numRows, numImages), order='F');
  images = transpose(a, (1, 0, 2))
  f.close()

  # Reshape to #pixels * #examples
  images  = reshape(a, (shape(images)[0] * shape(images)[1], numImages),
          order='F');
  images = double(images)/255
  return images
Exemple #3
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    def __init__(self, audioName):
        self.wf = wave.open(audioName, "r")
        buffer = self.wf.readframes(self.wf.getnframes())
        self.data = plt.frombuffer(buffer, dtype="int16")
        self.Y = None
        self.freqs = None
        self.bins = None

        print ("MyWav_init")
Exemple #4
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    def __init__(self, audioName):
        self.wf = wave.open(audioName, "r")
        buffer = self.wf.readframes(self.wf.getnframes())
        self.data = plt.frombuffer(buffer, dtype="int16")
        self.Y = None
        self.freqs = None
        self.bins = None

        print("MyWav_init")
Exemple #5
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 def get_raw_specgram_for_frame(self, frame, pad_seconds=DEFAULT_PADDING):
     if pad_seconds:
         pad_frames = int(self.audio_params.framerate * pad_seconds)
     (nchannels, sampwidth, framerate, nframes, comptype, compname) = self.audio_params
     raw_data = self.extract_specgram_data_for_frame(frame=frame, pad_frames=pad_frames)
     data = pylab.frombuffer(raw_data, 'Int' + str(8 * self.audio_params.sampwidth))
     min_frame = max(0, frame - pad_frames)
     max_frame = min(frame + pad_frames, nframes)
     audio_pos = frame * 1.0 / framerate
     audio_min = max(0, audio_pos - pad_seconds)
     audio_max = min(audio_pos + pad_seconds, nframes * 1.0 / framerate)
     pylab.figure(num=None, figsize=(8, 6))
     pylab.subplot(111)
     pylab.title('Spectrogram of {0}: {1:04.5f} - {2:04.5f} s'.format(self.filename, audio_min, audio_max))
     pylab.suptitle('Frames {0:09d} - {1:09d}'.format(min_frame, max_frame))
     # results = pyfigaxes.specgram(data, Fs=self.audio_params.framerate)
     return pylab.specgram(data, Fs=framerate, NFFT=1024, noverlap=512)
Exemple #6
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def loadMNISTLabels(filename):
  f = open(filename, 'rb')

  # Verify Magic Number
  s = f.read(4)
  magic = int(s.encode('hex'), 16)
  assert(magic == 2049)

  # Read Number Labels
  s = f.read(4)
  numLabels = int(s.encode('hex'), 16)

  # Get Data
  s = f.read()
  f.close()

  labels = frombuffer(s, uint8)
  assert(len(labels) == numLabels)
  return labels