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 python main_test_indices.py
Traceback (most recent call last):
  File "main_test_indices.py", line 16, in <module>
    from compute_indice import *
  File "/home/kdarras/Documents/Boulot/2020 Hangzhou/ecoSound-web/indices/Acoustic_Indices/compute_indice.py", line 23, in <module>
    from scipy import signal, fftpack
  File "/usr/lib/python3/dist-packages/scipy/__init__.py", line 62, in <module>
    from numpy import show_config as show_numpy_config
ImportError: No module named numpy

data_config['Filtering']['type'] = 'windowed_sinc'

    # Pre-processing -----------------------------------------------------------------------------------
    if 'Filtering' in data_config:
        if data_config['Filtering']['type'] == 'butterworth':
            print('- Pre-processing - High-Pass Filtering:', data_config['Filtering'])
            freq_filter = data_config['Filtering']['frequency']
            Wn = freq_filter/float(file.niquist)
            order = data_config['Filtering']['order']
            [b,a] = signal.butter(order, Wn, btype='highpass')
            # to plot the frequency response
            # w, h = signal.freqz(b, a, worN=2000)
            # plt.plot((file.sr * 0.5 / np.pi) * w, abs(h))
            # plt.show()
            file.process_filtering(signal.filtfilt(b, a, file.sig_float))
            
        elif data_config['Filtering']['type'] == 'windowed_sinc':
            print('- Pre-processing - High-Pass Filtering:', data_config['Filtering'])
            freq_filter = data_config['Filtering']['frequency']
            fc = freq_filter / float(file.sr)
            roll_off = data_config['Filtering']['roll_off']
            b = roll_off / float(file.sr)
            N = int(np.ceil((4 / b)))
            if not N % 2: N += 1  # Make sure that N is odd.
            n = np.arange(N)
            # Compute a low-pass filter.
            h = np.sinc(2 * fc * (n - (N - 1) / 2.))
            w = np.blackman(N)
            h = h * w
            h = h / np.sum(h)
            # Create a high-pass filter from the low-pass filter through spectral inversion.
            h = -h
            h[(N - 1) / 2] += 1
            file.process_filtering(np.convolve(file.sig_float, h))

Read the audio file: audio_files\S4A12065_20200808_160000.wav
	Successful read of the audio file: audio_files\S4A12065_20200808_160000.wav
	The audio file contains more than one channel. Only the channel 0 will be used.
- Pre-processing - High-Pass Filtering: {'type': 'windowed_sinc', 'order': 8, 'frequency': 300}
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-16-1a5bba1bece8> in <module>
     19         freq_filter = data_config['Filtering']['frequency']
     20         fc = freq_filter / float(file.sr)
---> 21         roll_off = data_config['Filtering']['roll_off']
     22         b = roll_off / float(file.sr)
     23         N = int(np.ceil((4 / b)))

KeyError: 'roll_off'