class_docstr: Dictionary-like object representing an SALib Problem specification.
  
  Attributes
  ----------
  samples : np.array, of generated samples
  results : np.array, of evaluations (i.e., model outputs)
  analysis : np.array or dict, of sensitivity indices
docstr: Create sample using given function.
  
  Parameters
  ----------
  func : function,
      Sampling method to use. The given function must accept the SALib
      problem specification as the first parameter and return a numpy
      array.
  
  *args : list,
      Additional arguments to be passed to `func`
  
  **kwargs : dict,
      Additional keyword arguments passed to `func`
  
  Returns
  -------
  self : ProblemSpec object
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code: def sample(self, func, *args, **kwargs):
      """Create sample using given function.
  
      Parameters
      ----------
      func : function,
          Sampling method to use. The given function must accept the SALib
          problem specification as the first parameter and return a numpy
          array.
  
      *args : list,
          Additional arguments to be passed to `func`
  
      **kwargs : dict,
          Additional keyword arguments passed to `func`
  
      Returns
      -------
      self : ProblemSpec object
      """
      # Clear model output and analysis results to avoid confusion
      # especially if samples are forcibly changed...
      self._analysis = None
      self._results = None
      self._samples = func(self, *args, **kwargs)
  
      return self
  
imports: import warnings
  import importlib
  from types import MethodType
  from functools import partial, wraps
  from multiprocess import Pool, cpu_count
  import numpy
  import SALib.sample
  import SALib.analyze
  from SALib.util import avail_approaches
  from SALib.util.results import ResultDict
label_desc: Use image node_id 7 for calling the ProblemSpec obj's underlying member method code with example usage: obj.sample(func) and returns: self