ee723d05e9cf56fa26a33735ee7bc2be882e0683,pliers/extractors/base.py,ExtractorResult,resample,#ExtractorResult#Any#Any#Any#,210

Before Change

        max_duration = self.onset[-1] + self.duration[-1]

        n = int(math.ceil(bin_sr * max_duration))
        x = np.arange(n)

        // Calculate final number of samples after re-sampling
        num = int(np.round((sampling_rate / bin_sr) * n))

        resampled = {}
        for f_name in self.features:
            values = self.data[f_name]

After Change

        max_duration = self.onset[-1] + self.duration[-1]

        // Calculate final number of samples after re-sampling
        num = math.ceil(max_duration / interval)

        // Maximum duration in bin_sr upscaling space
        max_dur_bin_sr = int(num * interval * bin_sr)
        x = np.arange(max_dur_bin_sr)

        resampled = {}
        for f_name in self.features:
            values = self.data[f_name]

            ts = np.zeros(int(max_dur_bin_sr), dtype=values.dtype)
            start = 0
            for i, val in enumerate(values):
                _onset = int(start + onsets[i])
                _offset = int(_onset + durations[i])
                ts[_onset:_offset] = val

            f = interp1d(x, ts, kind=kind)
            x_new = np.arange(0, max_dur_bin_sr, step=interval * bin_sr)
            resampled[f_name] = f(x_new)

        new_onsets = np.arange(0, max_dur_bin_sr / bin_sr, interval)

Instances