code: def _min_at(a, index, value):
      index = np.asarray(index)
      sort_keys = [value] + list(index)
      order = np.lexsort(sort_keys)
      index = index[:, order]
      value = value[order]
      uniq = np.ones(index.shape[1], dtype=bool)
      uniq[1:] = (index[:, 1:] != index[:, :-1]).any(axis=0)
  
      index = index[:, uniq]
      value = value[uniq]
  
      a[tuple(index)] = np.minimum(a[tuple(index)], value)
  
imports: from collections import defaultdict, OrderedDict
  from functools import wraps
  from itertools import combinations, groupby
  from warnings import warn
  import numpy
  from nibabel.affines import apply_affine
  from scipy.spatial.distance import cdist
  from dipy.core.geometry import dist_to_corner
  from dipy.tracking import metrics
  from dipy.tracking.vox2track import _streamlines_in_mask
  from dipy.tracking._utils import _mapping_to_voxel, _to_voxel_coordinates
label_desc: Use image node_id 17 for calling a global function with example usage: _min_at(a, index, value) without return types