code: def instance_from_physical_vector(self, physical_vector):
          
          arguments = dict(
              map(lambda prior_tuple, physical_unit: (prior_tuple.prior, physical_unit), self.prior_tuples_ordered_by_id,
                  physical_vector))
  
          return self.instance_for_arguments(arguments)
docs: Creates a ModelInstance, which has an attribute and class instance corresponding to every PriorModel \
          attributed to this instance.
  
          This method takes as input a physical vector of parameter values, thus omitting the use of priors.
  
          Parameters
          ----------
          physical_vector: [float]
              A unit hypercube vector
  
          Returns
          -------
          model_instance : autofit.mapper.model.ModelInstance
              An object containing reconstructed model_mapper instances