code: def minimum(input, labels=None, index=None):
      """
      Calculate the minimum of the values of an array over labeled regions.
  
      Parameters
      ----------
      input : array_like
          Array_like of values. For each region specified by `labels`, the
          minimal values of `input` over the region is computed.
      labels : array_like, optional
          An array_like of integers marking different regions over which the
          minimum value of `input` is to be computed. `labels` must have the
          same shape as `input`. If `labels` is not specified, the minimum
          over the whole array is returned.
      index : array_like, optional
          A list of region labels that are taken into account for computing the
          minima. If index is None, the minimum over all elements where `labels`
          is non-zero is returned.
  
      Returns
      -------
      minimum : float or list of floats
          List of minima of `input` over the regions determined by `labels` and
          whose index is in `index`. If `index` or `labels` are not specified, a
          float is returned: the minimal value of `input` if `labels` is None,
          and the minimal value of elements where `labels` is greater than zero
          if `index` is None.
  
      See Also
      --------
      label, maximum, median, minimum_position, extrema, sum, mean, variance,
      standard_deviation
  
      Notes
      -----
      The function returns a Python list and not a NumPy array, use
      `np.array` to convert the list to an array.
  
      Examples
      --------
      >>> from scipy import ndimage
      >>> import numpy as np
      >>> a = np.array([[1, 2, 0, 0],
      ...               [5, 3, 0, 4],
      ...               [0, 0, 0, 7],
      ...               [9, 3, 0, 0]])
      >>> labels, labels_nb = ndimage.label(a)
      >>> labels
      array([[1, 1, 0, 0],
             [1, 1, 0, 2],
             [0, 0, 0, 2],
             [3, 3, 0, 0]])
      >>> ndimage.minimum(a, labels=labels, index=np.arange(1, labels_nb + 1))
      [1.0, 4.0, 3.0]
      >>> ndimage.minimum(a)
      0.0
      >>> ndimage.minimum(a, labels=labels)
      1.0
  
      """
      return _select(input, labels, index, find_min=True)[0]
  
imports: import numpy
  import numpy
  from .None import _ni_support
  from .None import _ni_label
  from .None import _nd_image
  from .None import _morphology
label_desc: Use image node_id 13 for calling a global function with example usage: minimum(input, labels, index) and returns: _select