Config Table - danielwilczak101/EasyGA GitHub Wiki

Here you can read about how we store the configuration data of the genetic algorithm data.

Acessing stored config variables for past runs

import EasyGA

# Create the genetic algorithm
ga = EasyGA.GA()

# Evolve the genetic algorithm
ga.evolve()

# Print out all prior runs.
ga.database.past_runs()

Data stored:

All the data stored in the config table is basically all the variables that you can change using EasyGA.

  config_id  attribute_name                attribute_value
-----------  ----------------------------  --------------------------------------------
          0  adapt_population_flag         True
          0  adapt_probability_rate        0.05
          0  adapt_rate                    0.05
          0  chromosome_impl               None
          0  chromosome_length             10
          0  chromosome_mutation_rate      0.15
          0  current_fitness               0
          0  current_generation            0
          0  database                      <database.sql_database.SQL_Databa...
          0  database_name                 database.db
          0  fitness_goal                  None
          0  gene_mutation_rate            0.05
          0  generation_goal               100
          0  graph                         <database.matplotlib_graph.Matplotlib_...
          0  max_chromosome_mutation_rate  0.3
          0  max_gene_mutation_rate        0.15
          0  max_selection_probability     0.75
          0  min_chromosome_mutation_rate  0.075
          0  min_gene_mutation_rate        0.01
          0  min_selection_probability     0.25
          0  parent_ratio                  0.1
          0  percent_converged             0.5
          0  population_size               10
          0  run                           0
          0  selection_probability         0.5
          0  sql_create_data_structure     CREATE TABLE IF NOT EXISTS data (
                                                       id INTEGER PRIMARY KEY,
                                                       config_id INTEGER DEFAULT NULL,
                                                       generation INTEGER NOT NULL,
                                                       fitness REAL,
                                                       chromosome TEXT
                                                       );
          0  target_fitness_type           max
          0  tolerance_goal                None
          0  tournament_size_ratio         0.1