G2DList – the 2D list chromosome

This is the 2D List representation, this list can carry real numbers or integers or any kind of object, by default, we have genetic operators for integer and real lists, which can be found on the respective modules. This chromosome class extends the GenomeBase.GenomeBase.

Default Parameters

Initializator

Initializators.G2DListInitializatorInteger()

The Integer Initializator for G2DList

Mutator

Mutators.G2DListMutatorSwap()

The Swap Mutator for G2DList

Crossover

Crossovers.G2DListCrossoverUniform()

The Uniform Crossover for G2DList

Class

class G2DList.G2DList(height, width, cloning=False)

G2DList Class - The 2D List chromosome representation

Inheritance diagram for G2DList.G2DList:

Examples

The instantiation

>>> genome = G2DList.G2DList(10, 10)

Compare

>>> genome2 = genome1.clone()
>>> genome2 == genome1
True

Iteration

>>> for row in genome:
>>>   print row
[1, 3, 4, 1]
[7, 5, 3, 4]
[9, 0, 1, 2]

Size, slice, get/set, append

>>> len(genome)
3
>>> genome
(...)
[1, 3, 4, 1]
[7, 5, 3, 4]
[9, 0, 1, 2]
>>> genome[1][2]
3
>>> genome[1] = [666, 666, 666, 666]
>>> genome
(...)
[1, 3, 4, 1]
[666, 666, 666, 666]
[9, 0, 1, 2]
>>> genome[1][1] = 2
(...)

Parameters:

• height – the number of rows
• width – the number of columns

clearList()

Remove all genes from Genome

clone()

Return a new instace copy of the genome

Return type:the G2DList clone instance

copy(g)

Copy genome to ‘g’

Example:

>>> genome_origin.copy(genome_destination)

Parameter:g – the destination G2DList instance

crossover

This is the reproduction function slot, the crossover. You can change the default crossover method using:

genome.crossover.set(Crossovers.G2DListCrossoverSingleHPoint)

evaluate(**args)

Called to evaluate genome

Parameter:args – this parameters will be passes to the evaluator

evaluator

This is the evaluation function slot, you can add a function with the set method:

genome.evaluator.set(eval_func)

getFitnessScore()

Get the Fitness Score of the genome

Return type:genome fitness score

getHeight()

Return the height (lines) of the List

getItem(x, y)

Return the specified gene of List

Example:

>>> genome.getItem(3, 1)
666
>>> genome[3][1]

Parameters:

• x – the x index, the column
• y – the y index, the row

Return type:

the item at x,y position

getParam(key, nvl=None)

Gets an internal parameter

Example:

>>> genome.getParam("rangemax")
100

Note

All the individuals of the population shares this parameters and uses the same instance of this dict.

Parameters:

• key – the key of param
• nvl – if the key doesn’t exist, the nvl will be returned

getRawScore()

Get the Raw Score of the genome

Return type:genome raw score

getSize()

Returns a tuple (height, widht)

Example:

>>> genome.getSize()
(3, 2)

getWidth()

Return the width (lines) of the List

initializator

This is the initialization function of the genome, you can change the default initializator using the function slot:

genome.initializator.set(Initializators.G2DListInitializatorAllele)

In this example, the initializator Initializators.G2DListInitializatorAllele() will be used to create the initial population.

initialize(**args)

Called to initialize genome

Parameter:args – this parameters will be passed to the initializator

mutate(**args)

Called to mutate the genome

Parameter:args – this parameters will be passed to the mutator Return type:the number of mutations returned by mutation operator

mutator

This is the mutator function slot, you can change the default mutator using the slot set function:

genome.mutator.set(Mutators.G2DListMutatorIntegerGaussian)

resetStats()

Clear score and fitness of genome

resumeString()

Returns a resumed string representation of the Genome

New in version 0.6: The resumeString method.

setItem(x, y, value)

Set the specified gene of List

Example:

>>> genome.setItem(3, 1, 666)
>>> genome[3][1] = 666

Parameters:

• x – the x index, the column
• y – the y index, the row
• value – the value

setParams(**args)

Set the internal params

Example:

>>> genome.setParams(rangemin=0, rangemax=100, gauss_mu=0, gauss_sigma=1)

Note

All the individuals of the population shares this parameters and uses the same instance of this dict.

Parameter:args – this params will saved in every chromosome for genetic op. use