5af1994def9a52fe1ffd2847b2519f1e27cfbc64,niftynet/io/misc_io.py,,do_resampling,#Any#Any#Any#Any#,149

Before Change

        return data_array
    to_multiply = np.divide(pixdim_init, pixdim_fin[:len(pixdim_init)])
    if len(to_multiply) < data_array.ndim:
        ones = np.ones(data_array.ndim - len(to_multiply))
        to_multiply = np.concatenate((to_multiply, ones))
    to_multiply = to_multiply[:data_array.ndim]
    data_resampled = scipy.ndimage.zoom(data_array,
                                        zoom=to_multiply,
                                        order=interp_order)

After Change

        return data_array
    to_multiply = np.divide(pixdim_init, pixdim_fin[:len(pixdim_init)])
    data_resampled = []
    for t in range(0, data_array.shape[4]):
        data_mod = []
        for m in range(0, data_array.shape[3]):
            data_3d = data_array[..., m, t]
            data_new = scipy.ndimage.zoom(data_3d,
                                          to_multiply[0:3],
                                          order=interp_order)
            data_mod.append(data_new[..., np.newaxis])
        data_mod = np.concatenate(data_mod, axis=-1)
        data_resampled.append(data_mod[..., np.newaxis])
    data_resampled = np.concatenate(data_resampled, axis=-1)
    return data_resampled

Instances