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Package Bio :: Package NeuralNetwork :: Package Gene :: Module Schema :: Class GeneticAlgorithmFinder
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Class GeneticAlgorithmFinder

Find schemas using a genetic algorithm approach.

This approach to finding schema uses Genetic Algorithms to evolve a set of schema and find the best schema for a specific set of records.

The 'default' finder searches for ambiguous DNA elements. This can be overridden easily by creating a GeneticAlgorithmFinder with a different alphabet.
Method Summary
  __init__(self, alphabet)
Initialize a finder to get schemas using Genetic Algorithms.
  find_schemas(self, fitness, num_schemas)
Find the given number of unique schemas using a genetic algorithm

Method Details

__init__(self, alphabet=SchemaDNAAlphabet())
(Constructor)

Initialize a finder to get schemas using Genetic Algorithms.

Arguments:

o alphabet -- The alphabet which specifies the contents of the schemas we'll be generating. This alphabet must contain the attribute 'alphabet_matches', which is a dictionary specifying the potential ambiguities of each letter in the alphabet. These ambiguities will be used in building up the schema.

find_schemas(self, fitness, num_schemas)

Find the given number of unique schemas using a genetic algorithm

Arguments:

o fitness - A callable object (ie. function) which will evaluate the fitness of a motif.

o num_schemas - The number of unique schemas with good fitness that we want to generate.

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