code: def generate_values(self, *args, **kwargs):
          
          sample_size = kwargs.get('size', self.size)
  
          f = self.instantiate_distribution_function(self.module_name, self.distribution_name)
          distribution_function = partial(f, *self.random_function_params, size=sample_size)
  
          if self.sample_mean_value:
              sample = np.full(sample_size, self.get_mean(distribution_function))
          else:
              sample = distribution_function()
  
          return sample
docs: Generate a sample of values by sampling from a distribution. The size of the sample can be overriden with the 'size' kwarg.
  
          If `self.sample_mean_value == True` the sample will contain "size" times the mean value.
  
          :param args:
          :param kwargs:
          :return: sample as vector of given size