ad66bf0a8faf1f230891faea92c31d8a3a0baa3f,niftynet/engine/sampler_selective.py,,candidate_indices,#Any#Any#Any#,112

Before Change

            // print("Begin fft convolve")
            counts_window = fftconvolve(seg_label, window_mean, "same")
            // print("finished fft convolve")
            valid_places = np.where(counts_window > np.max([num_min, 1]),
                                    np.ones_like(data), np.zeros_like(data))
            counts_size = fftconvolve(
                label_size * valid_places, window_mean, "same")
            mean_counts_size_temp = np.nan_to_num(
                counts_size * 1.0 / counts_window)

After Change

            counts_window = fftconvolve(seg_label, window_ones, "same")
            // print("finished fft convolve")
            valid_places = \
                (counts_window > np.max([num_min, 1])).astype(data.dtype)
            counts_size = fftconvolve(
                label_size * valid_places, window_ones, "same")
            mean_counts_size_temp = np.nan_to_num(
                counts_size * 1.0 / counts_window)

Instances