def generate_genes_from_array_with_mut(self, array, rate):
"""
Transform DNA sequence into a list of genes,
plus a mutation.
Args:
array: DNA sequence.
rate: mutation rate.
"""
new_array = zip(*[iter(array)]*6)
self.genes = []
for chunk in new_array:
g = gene()
if random.uniform(0, 1) > rate:
g.pos_1 = chunk[0]
g.pos_2 = chunk[1]
g.pos_3 = chunk[2]
g.color['r'] = chunk[3]
g.color['g'] = chunk[4]
g.color['b'] = chunk[5]
self.genes.append(g)
def generate_genes_from_array_with_mut(self, array, rate):
"""
Transform DNA sequence into a list of genes,
plus a mutation.
Args:
array: DNA sequence.
rate: mutation rate.
"""
new_array = zip(*[iter(array)] * 6)
self.genes = []
for chunk in new_array:
g = gene()
if random.uniform(0, 1) > rate:
g.pos_1 = chunk[0]
g.pos_2 = chunk[1]
g.pos_3 = chunk[2]
g.color['r'] = chunk[3]
g.color['g'] = chunk[4]
g.color['b'] = chunk[5]
self.genes.append(g)
def __init__(self, parent_1=None, parent_2=None):
"""
Inits an individual.
If it has parents, generate its genes via crossover operation.
If not, generate its genes randomly.
Args:
parent_1: a parent.
parent_2: another parent.
"""
self.genes = []
op = genetic()
if parent_1 and parent_2:
array = op.crossover3(parent_1, parent_2, TRI_NUM)
self.generate_genes_from_array_with_mut(array, MUT_RATE)
else:
for i in xrange(TRI_NUM):
self.genes.append(gene())
# set actual image
self.im = self.get_current_img()
# calculate fitness
self.fitness = self.get_fitness(TARGET)
def __init__(self, parent_1=None, parent_2=None):
"""
Inits an individual.
If it has parents, generate its genes via crossover operation.
If not, generate its genes randomly.
Args:
parent_1: a parent.
parent_2: another parent.
"""
self.genes = []
op = genetic()
if parent_1 and parent_2:
array = op.crossover3(parent_1, parent_2, TRI_NUM)
self.generate_genes_from_array_with_mut(array, MUT_RATE)
else:
for i in xrange(TRI_NUM):
self.genes.append(gene())
# set actual image
self.im = self.get_current_img()
# calculate fitness
self.fitness = self.get_fitness(TARGET)
def getBeam():
"Genome prototype"
beam = []
#Date Scan Chunk Stat PEnergy PowOpt Pow Mat TarDiam TarLen TarDist Cur1 Cur2 TunRad TunLen PosFoc BinN BinMin BinMax Fitness
beam.append( genetic.gene("PEnergy", [ 1, 100, 1.0 ] ) )#0 GeV
beam.append( genetic.gene("Pow", [ 0.2, 5, 0.2 ] ) )#1 MW
beam.append( genetic.gene("Mat", ("myGraphite","myBeryllium","Water","quartz","Tungsten")) )
beam.append( genetic.gene("TarDiam", [ 1, 10, 0.5 ] ) )#5 mm
beam.append( genetic.gene("TarLen", [ 20, 200, 1.0 ] ) )#4 cm
beam.append( genetic.gene("TarDist", [ 13963, 14063, 1.0 ] ) )#6 cm
beam.append( genetic.gene("Cur1", [ 100e3, 350e3, 10.e3 ] ) )#7 A
beam.append( genetic.gene("Cur2", [ 100e3, 350e3, 10.e3 ] ) )#8 A
beam.append( genetic.gene("TunRad", [ 50, 500, 10.0 ] ) )#3 cm
beam.append( genetic.gene("TunLen", [ 10, 500, 10.0 ] ) )#2 m
beam.append( genetic.gene("PosFoc", [ 1, 9, 1 ] ) )#9 y
return beam
