Package schrodinger :: Package application :: Package matsci :: Package genetic_optimization :: Module genetic_optimization :: Class CheckInput

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Class CheckInput

object --+
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        CheckInput

Manage checking user input.

Instance Methods

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checkMaeFile(self, input_file, logger=None)
Check that a file exists and is *mae.

checkOperatorWeights(self, operators, logger=None)
Check the operator weights.

checkRates(self, crossover_rate, mutation_rate, logger=None)
Check the specified rates of crossover and mutation.

checkInitialPopulation(self, initial_population, crossover_names, mutator_names, crossover_rate, mutation_rate, logger=None)
Check the initial population.

checkPopulationParam(self, population, num_structures_given, logger=None)
Check the population parameter.

list

checkFragmentLibs(self, fragment_libs, logger=None)
Check the specified fragment libraries.

checkProperties(self, properties, logger=None)
Check the list of properties.

checkGenerations(self, generations, logger=None)
Check the specified number of generations.

checkSelection(self, selection, logger=None)
Check the specified selection protocol.

checkTournamentSize(self, tournament_size, population, logger=None)
Check the specified tournament size.

list and int

checkTerminationParams(self, terminators, num_unproductive, logger=None)
Check the termination parameters.

checkScaling(self, scaling, properties, logger=None)
Check the scaling.

checkElitism(self, elitism, population, logger=None)
Check the elitism.

float

checkRandomSeed(self, random_seed, logger=None)
Check the specified random seed.

checkNumRetStructures(self, num_ret_structures, population, logger=None)
Check the number of structures to return.

checkTpp(self, tpp_ga, eval_kwargs, logger=None)
Check the threads per processor.

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __init__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

Properties

[hide private]

Inherited from object: __class__

Method Details

[hide private]

checkMaeFile(self, input_file, logger=None)

Check that a file exists and is *mae.

Parameters:

input_file (str) - the name of the input file
logger (logging.Logger) - output logger

checkOperatorWeights(self, operators, logger=None)

Check the operator weights.

Parameters:

operators (list) - contains tuples of the operator functions and their weights
logger (logging.Logger) - output logger

checkRates(self, crossover_rate, mutation_rate, logger=None)

Check the specified rates of crossover and mutation.

Parameters:

crossover_rate (float) - the rate of crossover as a percentage
mutation_rate (float) - the rate of mutation as a percentage
logger (logging.Logger) - output logger

checkInitialPopulation(self, initial_population, crossover_names, mutator_names, crossover_rate, mutation_rate, logger=None)

Check the initial population.

Parameters:

initial_population (list) - the initial population of schrodinger.structure.Structure
crossover_names (list) - contains the function names of the crossover operators to be used
mutator_names (list) - contains the function names of the mutation operators to be used
crossover_rate (float) - the rate of crossover
mutation_rate (float) - the rate of mutation
logger (logging.Logger) - output logger

checkPopulationParam(self, population, num_structures_given, logger=None)

Check the population parameter.

Parameters:

population (int) - the size of the population to use in the genetic optimization
num_structures_given (int) - the number of structures provided to the genetic optimization
logger (logging.Logger) - output logger

checkFragmentLibs(self, fragment_libs, logger=None)

Check the specified fragment libraries.

Parameters:

fragment_libs (list) - strings specifying fragment libraries to be used
logger (logging.Logger) - output logger

Returns: list

valid user provided fragment files

checkProperties(self, properties, logger=None)

Check the list of properties.

Parameters:

properties (list) - contains Property instances
logger (logging.Logger) - output logger

checkGenerations(self, generations, logger=None)

Check the specified number of generations.

Parameters:

generations (int) - the number of generations
logger (logging.Logger) - output logger

checkSelection(self, selection, logger=None)

Check the specified selection protocol.

Parameters:

selection (str) - the selection protocol to use.
logger (logging.Logger) - output logger

checkTournamentSize(self, tournament_size, population, logger=None)

Check the specified tournament size.

Parameters:

tournament_size (int) - the size of tournament to use in tournament based selection
population (int) - the size of population to use
logger (logging.Logger) - output logger

checkTerminationParams(self, terminators, num_unproductive, logger=None)

Check the termination parameters.

Parameters:

terminators (list) - the list of terminators to use
num_unproductive (int) - used when the unproductive termination option is active, it is the generation number on which to exit if the score hasn't improved
logger (logging.Logger) - output logger

Returns: list and int

valid terminators and valid num_unproductive

checkScaling(self, scaling, properties, logger=None)

Check the scaling.

Parameters:

scaling (str) - the scaling protocol to use in the genetic optimization
properties (list) - the properties to be optimized
logger (logging.Logger) - output logger

checkElitism(self, elitism, population, logger=None)

Check the elitism.

Parameters:

elitism (int) - the number of elite individuals to use
population (int) - the size of population to use
logger (logging.Logger) - output logger

checkRandomSeed(self, random_seed, logger=None)

Check the specified random seed.

Parameters:

random_seed (float) - the seed for the random number generator
logger (logging.Logger) - output logger

Returns: float

random_seed, updated seed

checkNumRetStructures(self, num_ret_structures, population, logger=None)

Check the number of structures to return.

Parameters:

num_ret_structures (int) - the number of structures to return
population (int) - the size of population to use
logger (logging.Logger) - output logger

checkTpp(self, tpp_ga, eval_kwargs, logger=None)

Check the threads per processor.

Parameters:

tpp_ga (int) - the threads per processor for the genetic optimization
eval_kwargs (dict) - the kwargs for the evaluation function
logger (logging.Logger) - output logger