class_docstr: Declare an interface common to all supported algorithms.
  :class:`SampleMorris` uses this interface to call the algorithm
  defined by a ConcreteStrategy.
docstr: Computes the optimum k_choices of trajectories
  from the input_sample.
  
  Parameters
  ----------
  input_sample : numpy.ndarray
  num_samples : int
      The number of samples to generate
  num_params : int
      The number of parameters
  k_choices : int
      The number of optimal trajectories
  num_groups : int, default=None
      The number of groups
  
  Returns
  -------
  numpy.ndarray
docstr_tok: ["Computes","the","optimum","k_choices","of","trajectories","from","the","input_sample",".","Parameters","--","--","--","--","--","input_sample",":","numpy.ndarray","num_samples",":","int","The","number","of","samples","to","generate","num_params",":","int","The","number","of","parameters","k_choices",":","int","The","number","of","optimal","trajectories","num_groups",":","int",",","default=None","The","number","of","groups","Returns","--","--","--","-","numpy.ndarray"]
code: def sample(
      self,
      input_sample,
      num_samples,
      num_params,
      k_choices,
      num_groups=None,
  ):
      """Computes the optimum k_choices of trajectories
      from the input_sample.
  
      Parameters
      ----------
      input_sample : numpy.ndarray
      num_samples : int
          The number of samples to generate
      num_params : int
          The number of parameters
      k_choices : int
          The number of optimal trajectories
      num_groups : int, default=None
          The number of groups
  
      Returns
      -------
      numpy.ndarray
      """
      self.run_checks(num_samples, k_choices)
      maximum_combo = self._sample(
          input_sample, num_samples, num_params, k_choices, num_groups
      )
  
      assert isinstance(maximum_combo, list)
  
      output = self.compile_output(
          input_sample,
          num_samples,
          num_params,
          maximum_combo,
          num_groups,
      )
      return output
  
file_path: SALib/src/SALib/sample/morris/strategy.py
imports: import abc
  import numpy
  from scipy.spatial.distance import cdist
label_desc: Use image node_id 2 for calling the Strategy obj's underlying member method code with example usage: obj.sample(input_sample, num_samples, num_params, k_choices, num_groups) and returns: output