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Generates a random :py:class:`~AChemKit.reactionnet.ReactionNetwork` from molecules that are strings of atoms and can join together or break apart. Based on the paper Autocatalytic sets of proteins. 1986. Journal of Theoretical Biology 119:1-24 by Kauffman, Stuart A. but without the explicit catalytic activity. Arguments: natoms Number of atoms to use. Can be a single value or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. .. note:: :py:class:`AChemKit.reactionnet.ReactionNetwork` tracks molecules by their reactions, so if a molecule is not part of any reaction it will not appear at all e.g. in :py:attr:`~AChemKit.reactionnet.ReactionNetwork.seen`. maxlength Maximum number of atoms in a molecule. If this is None, then they are unbounded; this might cause problems with a computational explosion. Can be a single value or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. pform Probability that a pair of molecules will join together per orientation. Must be between 0 and 1. Can be a single value or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. pbreak Probability that any pair of atoms will break. Must be between 0 and 1.Can be a single value or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. directed If false, molecules have no intrinsic direction so AlphBeta is equivlanet to BetaAlpha. rates Rate of each reaction in the reaction network. Can be a single value, or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. cls Alternative class to use for constructing the return rather than :py:class:`AChemKit.reactionnet.ReactionNetwork`. rng Random number generator to use. If not specifed, one will be generated at random.

def Linear(natoms, maxlength, pform, pbreak, directed = True, rates = 1.0, cls = ReactionNetwork, rng = None): """ Generates a random :py:class:`~AChemKit.reactionnet.ReactionNetwork` from molecules that are strings of atoms and can join together or break apart. Based on the paper Autocatalytic sets of proteins. 1986. Journal of Theoretical Biology 119:1-24 by Kauffman, Stuart A. but without the explicit catalytic activity. Arguments: natoms Number of atoms to use. Can be a single value or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. .. note:: :py:class:`AChemKit.reactionnet.ReactionNetwork` tracks molecules by their reactions, so if a molecule is not part of any reaction it will not appear at all e.g. in :py:attr:`~AChemKit.reactionnet.ReactionNetwork.seen`. maxlength Maximum number of atoms in a molecule. If this is None, then they are unbounded; this might cause problems with a computational explosion. Can be a single value or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. pform Probability that a pair of molecules will join together per orientation. Must be between 0 and 1. Can be a single value or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. pbreak Probability that any pair of atoms will break. Must be between 0 and 1.Can be a single value or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. directed If false, molecules have no intrinsic direction so AlphBeta is equivlanet to BetaAlpha. rates Rate of each reaction in the reaction network. Can be a single value, or a tuple/list which will be uniformly sampled from (duplicates can be used to give a non-uniform distribution), or a dict of value:weight which will be sampled from. cls Alternative class to use for constructing the return rather than :py:class:`AChemKit.reactionnet.ReactionNetwork`. rng Random number generator to use. If not specifed, one will be generated at random. """ if rng is None: rng = random.Random(random.random()) natoms = get_sample(natoms, rng) maxlength = get_sample(maxlength, rng) pform = get_sample(pform, rng) pbreak = get_sample(pbreak, rng) assert pform >= 0.0 assert pform <= 1.0 assert pbreak >= 0.0 assert pbreak <= 1.0 #these are lists not sets because sets have machine-dependant ordering, which prevents reproducibility for the same random seed. molecules = [] new = [] #create some inital atoms #of the form Abc where first letter is capitalized alpha = "abcdefghijklmnopqrstuvwxyz" assert natoms > 0 for i in xrange(natoms): name = alpha[i%len(alpha)] while i >= len(alpha): i /= len(alpha) name = alpha[(i%len(alpha))-1] + name name = name.strip().capitalize() new.append(name) outrates = {} assert maxlength > 0 def mol_to_atoms(mol, cache = {}): if mol not in cache: cache[mol] = tuple(filter(lambda x: len(x) > 0, re.split(r"([A-Z][a-z]*)", mol))) return cache[mol] def mol_len(mol): #return len(mol) return len(mol_to_atoms(mol)) def mol_reverse(mol): rmol = "" for atom in mol_to_atoms(mol): rmol = atom + rmol return rmol def mol_order(mol): rmol = mol_reverse(mol) if mol < rmol: return mol else: return rmol def atoms_to_mol(atoms): mol = "" for atom in atoms: mol = mol + atom return mol while len(new) > 0: oldnew = new new = [] #decomposition for z in oldnew: for i in xrange(1, mol_len(z)): if rng.random() < pbreak: a = atoms_to_mol(mol_to_atoms(z)[:i]) b = atoms_to_mol(mol_to_atoms(z)[i:]) if not directed: a = mol_order(a) b = mol_order(b) reaction = (OrderedFrozenBag((z,)), OrderedFrozenBag(sorted((a,b)))) if reaction not in outrates: outrates[reaction] = get_sample(rates, rng) if a not in molecules and a not in new: new.append(a) if b not in molecules and b not in new: new.append(b) for a, b in itertools.chain(itertools.product(oldnew, molecules), combinations_with_replacement(oldnew, 2)): if maxlength is None or mol_len(a) + mol_len(b) <= maxlength: combinations = ((a,b), (b,a)) if not directed: combinations += ((mol_reverse(a), b), (a, mol_reverse(b))) for x,y in combinations: if rng.random() < pform: z = x + y if not directed: z = mol_order(z) #because we may have revereed them, we have to order them again if not directed: reactants = OrderedFrozenBag(sorted((mol_order(x), mol_order(y)))) else: reactants = OrderedFrozenBag(sorted((x, y))) products = OrderedFrozenBag((z,)) reaction = (reactants, products) if reaction not in outrates: outrates[reaction] = get_sample(rates, rng) if z not in molecules and z not in new: new.append(z) for z in oldnew: molecules.append(z) return cls(outrates)

**AChemKit**(Download)

import AChemKit from AChemKit.randomnet import Linear if __name__=="__main__":

#import cProfile #cProfile.run(""" net = Linear(args.natoms, args.length, args.pform, args.pbreak, args.directed, rates, rng=rng) #""".strip())

src/a/c/AChemKit-0.3.0/AChemKit/randomnet_test.py

**AChemKit**(Download)

import unittest from AChemKit.randomnet import Uniform, Linear import random

def test_natoms_int(self): net = Linear(2, 3, 0.2, 0.2) net = Linear(2, 3, 0.2, 0.2, rng = self.rng) def test_natoms_tuple(self): net = Linear((2,3), 3, 0.2, 0.2) net = Linear((2,3), 3, 0.2, 0.2, rng = self.rng)