code/code/rencode2.py at master · rmlopes/code · GitHub

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import logging

from functools import partial

from bitstring import BitStream

import math

import arn

import rencode

from rencode import evaluatecircuit, regressionfun, nnlikefun, mergefun,P,cleanpairs

from arnmiguel import *

from evodevo import Problem, Agent

from utils import *

from utils.bitstrutils import *

from utils.mathlogic import *

log = logging.getLogger(__name__)

def printrencode2(phenotype, **kwargs):

return rencode.printdotcircuit(

phenotype.circuits[phenotype.output_idx],**kwargs)

def printmultiplecircuit(phenotype, labels=None, arnet = None):

circuit = phenotype.getcircuit(phenotype.output_idx)

if not arnet:

arnet = phenotype.arnet

s = 'digraph best {\nordering = out;\n'

for c in circuit:

shape='oval'

if c[0] in arnet.effectorproms:

shape='hexagon'

elif c[0] in arnet.receptorproms:

shape='rectangle'

s += '%i [label="%s",shape="%s"];\n' % (c[0], c[1], shape)

#else labels[c[1]])

for inp in c[2]:

aux = "dir=back"

if inp < 0:

aux += ",style=dotted"

s += '%i -> %i [%s];\n' % (c[0],abs(inp),aux)

s += '}'

return s

### Agent model to use with this CoDe module

class ARNGPAgent(Agent):

genotype = None

phenotype = None

fitness = None

def __init__(self, config, problem, gcode = None, parent = None):

Agent.__init__(self, parent)

generator = bindparams(config, self.generate)

if gcode == None:

numprods = 0

numtfs = 0

while not numprods or not numtfs:

arnet = ARNetwork(generator(),config, problem=problem)

numprods = arnet.numeff

numtfs = arnet.numtf

else:

arnet = ARNetwork(gcode,config, problem=problem)

self.genotype = arnet

self.phenotype = Phenotype(arnet,problem)

self.problem = problem

self.fitness = 1e9

def __str__(self):

return "### Agent ###\n%s\n%s: %f" % (self.arn,self.phenotype,

self.fitness)

def pickled(self):

return (self.genotype.code.to01(),self.phenotype.output_idx)

def print_(self):

return printmultiplecircuit(self.phenotype)

class DMAgent(ARNGPAgent):

def __init__(self, config, problem, gcode = None, parent = None):

self.generate = arn.generatechromo

ARNGPAgent.__init__(self, config, problem, gcode, parent)

class RndAgent(ARNGPAgent):

def __init__(self, config, problem, gcode = None, parent = None):

self.generate = partial(arn.generatechromo_rnd,

genomesize = 32 * pow(2,config.getint('default','initdm')))

ARNGPAgent.__init__(self, config, problem, gcode, parent)

class Phenotype:

def __init__(self, arnet, problem):

self.funskel = regressionfun

self.problem = problem

self.products = arnet.effectorproms

self.circuits = []

self.graph = arnet.ebindings - arnet.ibindings

cleanpairs(self.graph)

self.arnet = arnet

self.output_idx = 0

if problem.nout == 1:

for i in range(len(self.products)):

self.output_idx = i

queue = self.getinputs(arnet.numtf+arnet.numrec+i)

fset = problem.funs

if not queue:

fset = problem.terms

circuit = [(arnet.effectors[i][0],

self.problem.nodemap_(arnet.effectors[i][4],fset),

[q[0] for q in queue])]

self.circuits.append(self.buildcircuit(queue, circuit))

else:

queue=[]

circuit=[]

#outputs = self.selectoutputs(problem.nout, problem)

#for o in outputs:

#slice-out the index of the output

# circuit.append(o[:3])

# queue.extend(self.getinputs(arnet.numtf+arnet.numrec+o[3]))

for i in range(arnet.numeff):

inps = self.getinputs(arnet.numtf+arnet.numrec+i)

fset = problem.funs

if not inps:

fset = problem.terms

circuit.append((arnet.effectors[i][0],

self.problem.nodemap_(arnet.effectors[i][4],

fset),

[inp[0] for inp in inps]))

queue.extend(inps)

queue.sort(key=lambda x: x[1], reverse=True)

self.circuits.append(self.buildcircuit(queue,circuit))

#self.circuitstr = map(lambda x: compile(x,'<string>','eval'),

# evaluatecircuit(self.circuits[0], mergefun, dict(),

# *problem.terms, nout=problem.nout))

#self.replaceinp = re.compile('inputs')

def __len__(self, index = 0):

return len(self.circuits[index])

def __call__(self, *inputs, **kwargs):

# #print self.circuitstr

#vardict = dict(globals())

# globals()['inputs']=inputs

#print vardict

#return map(lambda x: eval(x,globals(),{'inputs':inputs}), self.circuitstr)

#print r

#return r

return evaluatecircuit(self.getcircuit(self.output_idx),

self.funskel,dict(), *inputs, nout=self.problem.nout)

def __eq__(self, other):

if len(self.circuits) != len(other.circuits):

return False

for i in range(len(self.circuits)):

if self.circuits[i] != other.circuits[i]:

return False

return True

def selectoutputs(self,n, problem):

'''Selects the output nodes by number of input edges.'''

temp = list()

for i in range(self.arnet.numeff):

inps = self.getinputs(self.arnet.numtf+self.arnet.numrec+i)

fset = problem.funs

if not inps:

fset = problem.terms

temp.append((self.arnet.effectors[i][0],

self.problem.nodemap_(self.arnet.effectors[i][4],

fset),

[inp[0] for inp in inps],

i))

#temp.sort(key=lambda x: len(x[2]), reverse=True)

return temp[:n]

def getcircuit(self, index=0):

return self.circuits[index]

def buildcircuit(self, queue, circuit=[], force_inputs=False):

if not queue:

#if len(circuit) > 1 or force_inputs:

circuit.extend(self.getinputnodes())

return circuit

blacklist = [c[0] for c in circuit]

while True:

if not queue:

circuit.extend(self.getinputnodes())

return circuit

pnext = queue.pop(0)

if pnext[0] not in blacklist+self.arnet.receptorproms:

break;

blacklist.append(pnext[0])

index = self.arnet.promlist.index(pnext[0])

signature = self.arnet.proteins[index][4]

fun = self.problem.nodemap_(signature,self.problem.funs)

inputs = self.getinputs(index)

inputs = filter(lambda x: x[0] not in blacklist, inputs)

ar = self.problem.arity[fun]

if ar > 0:

inputs = inputs[:ar]

if not inputs:

fun = str(random.choice([0,1]))

#fun = self.problem.nodemap_(signature,self.problem.terms)

circuit.append((pnext[0],fun,[i[0] for i in inputs]))

queue.extend(inputs)

queue.sort(key=lambda x: x[1], reverse=True)

return self.buildcircuit(queue,circuit)

def getinputs(self, index):

inputs=[]

for e,i in zip(self.graph[:,index],

range(self.graph.shape[0])):

if e > 0:

inputs.append(((self.arnet.promlist + self.arnet.receptorproms)[i],e))

inputs.sort(key=lambda x: x[1], reverse = True)

return inputs

def getinputnodes(self):

return map(lambda x: (x[0],

self.problem.terms[x[0]],

[]),

self.arnet.receptors)

def printgraph(self):

s = 'digraph best {\nordering = out;\n'

shape = 'hexagon'

arnet = self.arnet

labelidx = 0

for outprom in arnet.effectorproms:

s += '%i [label="%s",shape="hexagon"];\n' % (outprom, labelidx)

for e,i in zip(self.graph[:,arnet.numtf+arnet.numrec+labelidx],

range(self.graph.shape[0])):

if e > 0:

s += '%i -> %i [dir=back,weight=%i];\n' % \

(outprom, (arnet.promlist + arnet.receptorproms)[i],e)

labelidx += 1

for tf,idx in zip(arnet.promlist,range(arnet.numtf)):

s += '%i [label="%s"];\n' % (tf, labelidx)

for e,i in zip(self.graph[:,idx],

range(self.graph.shape[0])):

if e > 0:

s += '%i -> %i [dir=back,weight=%i];\n' % \

(tf, (arnet.promlist + arnet.receptorproms)[i],e)

labelidx += 1

for rec in arnet.receptorproms:

s += '%i [label="%s",shape="rectangle"];\n' % (rec, labelidx)

labelidx += 1

s += '}'

return s

###########################################################################

### Test ###

###########################################################################

if __name__ == '__main__':

import ConfigParser

import random

from bitstring import BitStream

from bitstringutils import dm_event

from arn import ARNetwork

from evodevo import Problem

log.setLevel(logging.DEBUG)

cfg = ConfigParser.ConfigParser()

cfg.readfp(open('test-rencode.cfg'))

arncfg = ConfigParser.ConfigParser()

arncfg.readfp(open('arnsim-rencode2.cfg'))

proteins=[]

nump = 0

while nump < 3:

genome = BitStream(float=random.random(), length=32)

for i in range(5):

genome = dm_event(genome,

.02)

arnet = ARNetwork(genome, arncfg)

nump = len(arnet.promlist)

for p in arnet.proteins: print p

prob = Problem(defaultnodemap,regressionfun, None)

circuit = buildcircuit(arnet, prob,False)

_printcircuit(circuit)

print printdotcircuit(circuit, prob.labels)

code/code/rencode2.py at master · rmlopes/code · GitHub

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