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

Before Change

            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(

After Change

        for value in unique:
            // print(np.sum(data), "sum in data", np.prod(data.shape),
            //       " elements in data")
            seg_label = (data == value).astype(data.dtype)
            // print(np.sum(seg_label), " num values in seg_label ", value)
            label_size = create_label_size_map(seg_label)
            // print(value, np.sum(seg_label), seg_label.shape,
            //       window_ones.shape, num_min)

Instances