code: def evalPDF(self, u_values):
          '''Returns the PDF of the uncertain parameter evaluated at the values
          provided in u_values.
  
          :param iterable u_values: values of the uncertain parameter at which to
              evaluate the PDF
  
          *Example Usage* ::
  
              >>> u = UniformParameter()
              >>> X = numpy.linspace(-1, 1, 100)
              >>> Y = [u.evalPDF(x) for x in X]
  
          '''
  
          if isinstance(u_values, np.ndarray):
              return self._evalPDF(u_values)
          else:
              try:
                  iter(u_values)
                  return [self._evalPDF(u) for u in u_values]
              except:
                  return self._evalPDF(u_valuesf evalPDF(self, u_values):
          '''Returns the PDF of the uncertain parameter evaluated at the values
          provided in u_values.
  
          :param iterable u_values: values of the uncertain parameter at which to
              evaluate the PDF
  
          *Example Usage* ::
  
              >>> u = UniformParameter()
              >>> X = numpy.linspace(-1, 1, 100)
              >>> Y = [u.evalPDF(x) for x in X]
  
          '''
  
          if isinstance(u_values, np.ndarray):
              return self._evalPDF(u_values)
          else:
              try:
                  iter(u_values)
                  return [self._evalPDF(u) for u in u_values]
              except:
                  return self._evalPDF(u_values)
docs: Returns the PDF of the uncertain parameter evaluated at the values
          provided in u_values.
  
          :param iterable u_values: values of the uncertain parameter at which to
              evaluate the PDF
  
          *Example Usage* ::
  
              >>> u = UniformParameter()
              >>> X = numpy.linspace(-1, 1, 100)
              >>> Y = [u.evalPDF(x) for x in X]