No_Predation_Operator.py
This class is designed to allow the user to not use a predation operator during the genetic algorithm run.
No_Predation_Operator.py, Geoffrey Weal, 28/10/2018
This is one of the Predation Operators that can be used by the genetic algorithm program.
- class Organisms.GA.Predation_Operators.No_Predation_Operator.No_Predation_Operator(Predation_Information, population, print_details)
This is one of the Predation Operators that can be used by the genetic algorithm program.
This Predation Operator will not do anything. It is the option to pick if you do not want to remove offspring or clusters from the population due to being energetically or strucutrally similar.
- Parameters:
Predation_Information (dict.) – This contains all the information needed by the Predation Operator you want to use to run.
population (Organisms.GA.Population) – This is the population that this Operator will be controlling to make sure that no two clusters in the population have the same energy.
print_details (bool) – Print details of the predation operator, like verbose
- add_to_database(collection)
Add clusters similarities to the CNA database to be stored for future generations.
This does not do anything since this predation method does notthing
- Parameters:
collection (Organisms.GA.Collection.Collection) – update the fitnesses of clusters in the collection.
- assess_for_violations(offspring_pool, force_replace_pop_clusters_with_offspring)
This definition is designed to determine which offspring (and the clusters in the population) violate the predation Operator. It will not remove or change any clusters in the offspring or population, but instead will record which offspring violate the predation Operator.
Since this ‘Operator’ does nothing, this def will not do anything.
It will return two tuples with nothing in them, as required by this def.
- Parameters:
offspring_pool (Organisms.GA.Offspring_Pool.Offspring_Pool) – This is the collection of offspring to assess for violations to the Predation Operator.
force_replace_pop_clusters_with_offspring (bool.) – This will tell the genetic algorithm whether to swap clusters in the population with offspring if the predation operator indicates they are the same but the predation operator has a better fitness value than the cluster in the population.
- Returns:
A list of the names of the offspring to be removed * force_replacement (tuple of (int, int)): A list of the clusters in the population that should be replaced, and the offspring they should be replaced by.
- Return type:
offspring_to_remove (tuple of ints)
- check_initial_population(return_report=False)
This definition is responsible for making sure that the initialised population obeys the Energy Predation Operator.
Since this ‘Operator’ does nothing, this def will not do anything. It will report back that it has not removed any cluster
- Parameters:
return_report (bool.) – Will return a dict with all the information about what clusters are similar to what other clusters in the population.
- Returns:
a list of the clusters to remove from the population as they violate the Predation Operator. Format is [(index in population, name fo cluster),…] * CNA_report (dict.): a dictionary with information on the clusters being removed and the other clusters in the population which have caused the violation to the SCM Predation Operator. This information is only used to display information so they know why there are violations to the Predation Operator when they occur. For is {removed cluster: [list of clusters that this cluster is similar to in the population.]}
- Return type:
clusters_to_remove (list of ints)
- remove_from_database(cluster_names_to_remove)
Clusters to remove from the CNA database
This does not do anything since this predation method does notthing
- Parameters:
cluster_names_to_remove (list of ints) – A list of the names of all the clusters to remove from the CNA database
- reset()
Reset the CNA database with no inputs
This does not do anything since this predation method does notthing