c8b28432a637a780eed96547260722ff3dede57e,niftynet/engine/sampler_selective.py,,rand_choice_coordinates,#Any#Any#Any#Any#Any#Any#,350

Before Change

    // print(np.sum(candidates), list_indices)
    // print(len(candidates_indices), candidates_indices.shape)
    if mean_counts_size is not None:
        print("Probability weighting considered")
        proba = []
        for (c,  p) in zip(candidates.flatten(), mean_counts_size.flatten()):
            if c >= 1:
                proba.append(p)

After Change

    spatial_win_sizes = np.asarray(spatial_win_sizes, dtype=np.int32)
    max_spatial_win = np.max(spatial_win_sizes, axis=0)
    for i in range(0, N_SPATIAL):
        assert uniq_spatial_size[i] >= max_spatial_win[i], \
            "window size {} is larger than image size {}".format(
                max_spatial_win[i], uniq_spatial_size[i])

    // randomly choose n_samples from candidate locations
    candidates_indices = np.vstack(np.where(candidates == 1)).T
    list_indices_fin = np.arange(len(candidates_indices))

Instances