#for filter
    from scipy.signal import butter, buttord, lfilter, freqz
    from scipy.signal import freqs

    def lowpass_filter(integer_data, sample_framerate, sample_bitwidth,threshold):#works with cutoff from 400 and higher

        def butter_lowpass(cutOff, fs, order):

            nyq = 0.5 * fs
            normalCutoff = cutOff / nyq
            b, a = butter(order, normalCutoff, btype='low', analog = False)
            return b, a

        def butter_lowpass_filter(data, cutOff, fs, order):
            b, a = butter_lowpass(cutOff, fs, order=order)
            y = lfilter(b, a, data)
            return y

        result=butter_lowpass_filter(integer_data, threshold, sample_framerate, order=4)#what is order?
        result=truncate_if_outside(result, sample_bitwidth)
        return result

    def sweep_filter(integer_data, start_freq, end_freq, sample_framerate, sample_bitwidth, slice_width):
        num_slice= int(len(integer_data)/ float(slice_width))
        print "nombre de tranche dans cette durée :",num_slice
        new_data=[]
        diff_cutoff=end_freq-start_freq
        for i in range(num_slice):
            current_cutoff=start_freq+((i/float(num_slice))*diff_cutoff)
            print "cutoff",current_cutoff
            print "start:",i*slice_width
            offset_first_sample=(i*slice_width)-1
            offset_last_sample=((i*slice_width)+slice_width)-1

            slice_data=integer_data[offset_first_sample:offset_last_sample]
            slice_data=lowpass_filter(slice_data, sample_framerate, sample_bitwidth, current_cutoff)
            for j in range(len(slice_data)):
                new_data.append(slice_data[j])
        return new_data