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Completed Feature List
clarencecastillo edited this page Dec 30, 2013
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- Organization of biological entities from chromosome, genome (consisting of one or more chromosomes), organism (consisting of one genome), population (consisting of one or more organisms). Reference: Foundational paper; Lim et al., 2010.
- Random mutation operators - point, insertion, deletion, inversion, duplication, and translocation. Reference: Foundational paper; Lim et al., 2010.
- Regional (known mutation) mutation operators - point, insertion, deletion, inversion, duplication, and translocation. Reference: Foundational paper; Lim et al., 2010.
- Separation of background mutation rate and additional (on top of background mutation rate) mutation rate. Reference: Foundational paper; Lim et al., 2010.
- 32-character random name generated for each organism. Reference: version 1.0.0.
- Organism status - alive, vitality, parents, age, gender, lifespan, fitness, blood, identity, deme, location, and death reasons. Reference: Foundational paper; Lim et al., 2010; and version 1.0.0.
- Population freeze and revival. Reference: Foundational paper; Lim et al., 2010.
- Crossover operator between 2 chromosomes. Reference: Foundational paper; Lim et al., 2010.
- 3-dimensional cubic/rectangular world of one or more ecological cells. Reference: Foundational paper; Ling, 2012.
- Rajaraga interpreter to decode/express genome. Reference: Foundational paper; Ling, 2012.
- Bury and excavate the 3-dimensional world. Reference: Foundational paper; Ling, 2012.
- Organism status - new identity generated for each organism and descendants. Reference: Example 01.
- Organism status - location of descendant recorded. Reference: Example 01.
- Organism status - deme of descendant recorded. Reference: Example 01.
- List of 29 parameters for a simulation - simulation_name, population_names, population_locations, deployment_code, chromosome_bases, background_mutation, additional_mutation, mutation_type, chromosome_size, genome_size, max_tape_length, clean_cell, interpret_chromosome, max_codon, population_size, eco_cell_capacity, world_x, world_y, world_z, goal, maximum_generations, fossilized_ratio, fossilized_frequency, print_frequency, ragaraja_version, ragaraja_instructions, eco_buried_frequency, database_file, and database_logging_frequency. Reference: Example 01.
- List of 15 functions for a simulation - organism_movement, organism_location, ecoregulate, update_ecology, update_local, report, fitness, mutation_scheme, prepopulation_control, mating, postpopulation_control, generation_events, population_report, database_report, and deployment_scheme. Reference: Example 01.
- Simulation parameters - simulation_name to store name of simulation. Reference: Example 01.
- Simulation parameters - population_names to store one or more population names. Reference: Example 01.
- Simulation parameters - population_locations to define the centroid location of population(s). Reference: Example 01.
- Simulation parameters - deployment_code to define how population(s) are deployed into the world. Reference: Example 01.
- Simulation parameters - chromosome_bases to define allowable characters for use as chromosomal bases. Reference: Example 01.
- Simulation parameters - background_mutation to define background mutation rate. Reference: Example 01.
- Simulation parameters - mutation_type to define default type of mutation. Reference: Example 01.
- Simulation parameters - chromosome_size to define initial size of a chromosome. Reference: Example 01.
- Simulation parameters - genome_size to define the initial number of chromosome(s) for each organism. Reference: Example 01.
- Simulation parameters - max_tape_length to define the number of cells to act as cytoplasm. Reference: Example 01.
- Simulation parameters - clean_cell to define whether a new cytoplasm is needed for each expression. Reference: Example 01.
- Simulation parameters - interpret_chromosome to define whether the genome is expressed (interpreted by Rajaraga). Reference: Example 01.
- Simulation parameters - max_codon to define the maximum number of codons to express. Reference: Example 01.
- Simulation parameters - population_size to define the initial number of organisms for each population. Reference: Example 01.
- Simulation parameters - eco_cell_capacity to define the initial capacity of each ecological cell. Reference: Example 01.
- Simulation parameters - world_x, world_y, world_z to define the size of world in x, y, and z coordinates. Reference: Example 01.
- Simulation parameters - maximum_generations to define the maximum number of generations to simulate. Reference: Example 01.
- Simulation parameters - fossilized_ratio to define the proportion of populations for each fossilization. Reference: Example 01.
- Simulation parameters - fossilized_frequency to define the interval of fossilization. Reference: Example 01.
- Simulation parameters - ragaraja_version to define the version of Ragaraja instructions to use. Reference: Example 01.
- Simulation parameters - ragaraja_instructions to define a specific list of Ragaraja instructions to use. Reference: Example 01.
- Simulation parameters - eco_buried_frequency to define the interval of ecological burial. Reference: Example 01.
- Simulation parameters - database_file to define the file name of logging database. Reference: Example 01.
- Simulation parameters - database_logging_frequency to define the interval of database logging. Reference: Example 01.
- Simulation functions - mutation_scheme to specify the mutation scheme for each organism. Reference: Example 01.
- Simulation functions - population_report to generate simulation text report. Reference: Example 01.
- Simulation functions - database_report to log organisms and ecological system into the logging database at specified intervals. Reference: Example 01.
- Logging all population details into database. Reference: Example 01.
- Logging entire ecological details into database. Reference: Example 01.
- Sequential simulation - organism by organism mutation and mating within a cell, cell by cell processing until all ecological cells are processed. Reference: Example 01.
- Deployment scheme - deployment code 1 to deploy all organisms into one eco cell specified in simulation parameter population_locations. Reference: Example 01.
- Deployment scheme - deployment code 3 to deploy all organisms evenly into the different eco cells specified in simulation parameter population_locations. Reference: Example 02.
- Simulation functions - mating function to define mating behavior of organisms in each generation. Reference: Example 03.
- Simulation functions - organism_movement to trigger organism movement from current ecological cell to an adjacent ecological cell. Reference: Example 04.
- Simulation functions - organism_location to trigger organism movement from current ecological cell to a distant ecological cell. Reference: Example 05.
- Simulation revival parameters - sim_folder to define location of simulation files to be revived. Reference: [Example 06] (https://github.com/mauriceling/dose/blob/master/examples/06_revive_simulation_01.py).
- Simulation revival parameters - eco_file to specify which *.eco file to be excavated for re-simulation. Reference: [Example 06] (https://github.com/mauriceling/dose/blob/master/examples/06_revive_simulation_01.py).
- Simulation revival parameters - pop_files to specify which *.gap files to be revived for re-simulation, wherein each *.gap file specified would be considered as one population. Reference: [Example 06] (https://github.com/mauriceling/dose/blob/master/examples/06_revive_simulation_01.py).
- Simulation revival parameters - extend_gen to define the number of generations in continued simulation. Reference: [Example 06] (https://github.com/mauriceling/dose/blob/master/examples/06_revive_simulation_01.py).
- Database extraction functions - connect_database to prepare the specified database in simulation parameter database_file for data extraction Reference: [Example 07] (https://github.com/mauriceling/dose/blob/master/examples/07_logging_database_extraction.py).
- Database extraction functions - db_list_simulations to list simulations inside a database by extracting starting times of the simulations Reference: [Example 07] (https://github.com/mauriceling/dose/blob/master/examples/07_logging_database_extraction.py).
- Database extraction functions - db_list_generations to list all logged generations within a simulation specified by its own starting time Reference: [Example 07] (https://github.com/mauriceling/dose/blob/master/examples/07_logging_database_extraction.py).
- Database extraction functions - db_list_population_name to list all logged population's name within a simulation specified by its own starting time Reference: [Example 07] (https://github.com/mauriceling/dose/blob/master/examples/07_logging_database_extraction.py).
- Database extraction functions - db_list_datafields to list all logged types of data within a simulation specified by its own starting time Reference: [Example 07] (https://github.com/mauriceling/dose/blob/master/examples/07_logging_database_extraction.py).
- Database extraction functions - db_get_ecosystem to get a specific field of the ecosystem or the entire ecosystem for one or more generations within a simulation specified by its own starting time Reference: [Example 07] (https://github.com/mauriceling/dose/blob/master/examples/07_logging_database_extraction.py).
- Database extraction functions - db_get_organisms_status to get a specific field of the organism's status dictionary or the entire dictionary for one or more generations within a simulation specified by its own starting time Reference: [Example 07] (https://github.com/mauriceling/dose/blob/master/examples/07_logging_database_extraction.py).
- Database extraction functions - db_get_organisms_chromosome_sequences to get chromosomal sequences of entire genome of organisms for one or more generations within a simulation specified by its own starting time Reference: [Example 07] (https://github.com/mauriceling/dose/blob/master/examples/07_logging_database_extraction.py).
- Simulation revival parameters - database_source to specify the file name of which database file to revive a simulation from. Reference: [Example 08] (https://github.com/mauriceling/dose/blob/master/examples/08_revive_simulation_03.py).
- Simulation revival parameters - simulation_time to identify which simulation within the specified database file is to be revived. Reference: [Example 08] (https://github.com/mauriceling/dose/blob/master/examples/08_revive_simulation_03.py).
- Simulation revival parameters - rev_start to specify at which generation(s) are the populations to be revived in the simulation. Reference: [Example 08] (https://github.com/mauriceling/dose/blob/master/examples/08_revive_simulation_03.py).
- Simulation parameters - additional_mutation to influence mutation per base above background mutation. Reference: [Example 11] (https://github.com/mauriceling/dose/blob/master/examples/11_no_migration_natural_selection.py).
- Simulation parameters - goal to be reached by the population through the fitness scheme. Reference: [Example 11] (https://github.com/mauriceling/dose/blob/master/examples/11_no_migration_natural_selection.py).
- Simulation functions - fitness to calculate the fitness of an organism. Reference: [Example 11] (https://github.com/mauriceling/dose/blob/master/examples/11_no_migration_natural_selection.py).
- Simulation functions - prepopulation_control to trigger population control events before mating event in each generation. Reference: [Example 11] (https://github.com/mauriceling/dose/blob/master/examples/11_no_migration_natural_selection.py).
- Simulation functions - postpopulation_control to trigger population control events after mating event in each generation. Reference: [Example 11] (https://github.com/mauriceling/dose/blob/master/examples/11_no_migration_natural_selection.py).
Copyright (c) 2010-2018, Maurice HT Ling on behalf of all authors.