本文整理汇总了Python中random.Random.seed方法的典型用法代码示例。如果您正苦于以下问题:Python Random.seed方法的具体用法?Python Random.seed怎么用?Python Random.seed使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类random.Random
的用法示例。
在下文中一共展示了Random.seed方法的15个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _graph_example
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def _graph_example(n=4):
from string import ascii_uppercase as labels
from random import Random
n = min(n, 26)
class Node(object):
def __init__(self, letter):
self.letter = str(letter)
self.neigh = list()
def __str__(self):
return self.letter
__repr__ = __str__
# create a reproductible random graph
nodes = [Node(x) for x in labels[:n]]
ran = Random()
ran.seed(6164554331563)
neighmax = 3
for n in nodes:
n.neigh[:] = sorted((x for x in ran.sample(nodes, neighmax)
if x is not n), key=lambda n: n.letter)
#for n in nodes:
# print(n, ":", list(n.neigh))
for path in walk(nodes[0], (lambda n: n.neigh), event(~0), tree=False):
print(list(path), "{0:<7}".format(event_repr(path.event)))
示例2: main
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def main(prng=None, display=False):
if prng is None:
prng = Random()
prng.seed(time())
import logging
logger = logging.getLogger('inspyred.ec')
logger.setLevel(logging.DEBUG)
file_handler = logging.FileHandler('inspyred.log', mode='w')
file_handler.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
file_handler.setFormatter(formatter)
logger.addHandler(file_handler)
ea = inspyred.ec.DEA(prng)
if display:
ea.observer = inspyred.ec.observers.stats_observer
ea.terminator = inspyred.ec.terminators.evaluation_termination
final_pop = ea.evolve(generator=generate_rastrigin,
evaluator=inspyred.ec.evaluators.parallel_evaluation_pp,
pp_evaluator=evaluate_rastrigin,
pp_dependencies=(my_squaring_function,),
pp_modules=("math",),
pop_size=8,
bounder=inspyred.ec.Bounder(-5.12, 5.12),
maximize=False,
max_evaluations=256,
num_inputs=3)
if display:
best = max(final_pop)
print('Best Solution: \n{0}'.format(str(best)))
return ea
示例3: main
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def main(prng=None, display=False):
if prng is None:
prng = Random()
prng.seed(time())
items = [(80, 1),
(0, 0),
(80, 10)]
problem = inspyred.benchmarks.Knapsack(100, items, duplicates=False)
ea = inspyred.ec.EvolutionaryComputation(prng)
ea.selector = inspyred.ec.selectors.tournament_selection
ea.variator = [inspyred.ec.variators.uniform_crossover,
inspyred.ec.variators.gaussian_mutation]
ea.replacer = inspyred.ec.replacers.steady_state_replacement
ea.terminator = inspyred.ec.terminators.evaluation_termination
final_pop = ea.evolve(generator=problem.generator,
evaluator=problem.evaluator,
bounder=problem.bounder,
maximize=problem.maximize,
pop_size=100,
max_evaluations=2500,
tournament_size=5,
num_selected=2)
if display:
best = max(ea.population)
print('Best Solution: {0}: {1}'.format(str(best.candidate),
best.fitness))
return ea
示例4: brachistochrone
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def brachistochrone():
initial = [(float(i) / num_intervals) for i in range(num_intervals)]
initial.append(1.0)
initial.reverse()
rand = Random()
rand.seed(int(time()))
real = initial[:]
k = find_optimal(initial[:], 1000, rand)
print duration(k)
tenk = find_optimal(k[:], 10000, rand)
print duration(tenk)
#hundk = find_optimal(tenk[:], 100000, rand)
#print duration(hundk)
initial.reverse()
plt.plot(initial, k, '-', lw=2)
plt.plot(initial, tenk, '-', lw=2)
#plt.plot(initial, hundk, '-', lw=2)
plt.plot(initial, initial, '-', lw=2)
real = actual(2.0)
initial.reverse()
plt.plot(initial, real[1], '-', lw=2)
print duration(real[1])
print duration(initial)
plt.title('Brachistochrone')
plt.grid(True)
plt.show()
示例5: main
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def main(prng=None, display=False):
if prng is None:
prng = Random()
prng.seed(time())
problem = inspyred.benchmarks.Kursawe(3)
ea = inspyred.ec.emo.NSGA2(prng)
ea.variator = [inspyred.ec.variators.blend_crossover,
inspyred.ec.variators.gaussian_mutation]
ea.terminator = inspyred.ec.terminators.generation_termination
final_pop = ea.evolve(generator=problem.generator,
evaluator=problem.evaluator,
pop_size=100,
maximize=problem.maximize,
bounder=problem.bounder,
max_generations=80)
if display:
final_arc = ea.archive
print('Best Solutions: \n')
for f in final_arc:
print(f)
import pylab
x = []
y = []
for f in final_arc:
x.append(f.fitness[0])
y.append(f.fitness[1])
pylab.scatter(x, y, color='b')
pylab.savefig('{0} Example ({1}).pdf'.format(ea.__class__.__name__,
problem.__class__.__name__),
format='pdf')
pylab.show()
return ea
示例6: optimize
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def optimize(self,do_plot=True,seed=int(time()), summary_dir=None):
rand = Random()
rand.seed(seed)
if summary_dir is None:
cwd=os.getcwd()
summary_dir=os.path.dirname(cwd)+'/data/'
if not os.path.exists(summary_dir):
os.mkdir(summary_dir)
stat_file_name=summary_dir+'/ga_statistics.csv'
ind_file_name=summary_dir+'/ga_individuals.csv'
stat_file = open(stat_file_name, 'w')
ind_file = open(ind_file_name, 'w')
print("Created files: %s and %s"%(stat_file_name, ind_file_name))
if self.verbose:
logger = logging.getLogger('inspyred.ec')
logger.setLevel(logging.DEBUG)
ch = logging.StreamHandler()
# ch.setLevel(logging.DEBUG)
formatter = logging.Formatter('>>> EC: - %(levelname)s - %(message)s')
ch.setFormatter(formatter)
logger.addHandler(ch)
algorithm = ec.EvolutionaryComputation(rand)
algorithm.observer = observers.file_observer
algorithm.terminator = terminators.evaluation_termination
algorithm.selector = selectors.tournament_selection
algorithm.replacer = replacers.steady_state_replacement
algorithm.variator = [variators.blend_crossover, variators.gaussian_mutation]
final_pop = algorithm.evolve(generator=self.uniform_random_chromosome,
evaluator=self.evaluator.evaluate,
pop_size=self.population_size,
maximize=self.maximize,
bounder=ec.Bounder(lower_bound=self.min_constraints,
upper_bound=self.max_constraints),
num_selected=self.num_selected,
tourn_size=self.tourn_size,
num_elites=self.num_elites,
num_offspring=self.num_offspring,
max_evaluations=self.max_evaluations,
mutation_rate=self.mutation_rate,
statistics_file=stat_file,
seeds=self.seeds,
individuals_file=ind_file)
stat_file.close()
ind_file.close()
self.print_report(final_pop,do_plot,stat_file_name)
#return the parameter set for the best individual
return final_pop[0].candidate, final_pop[0].fitness
示例7: main
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def main():
g = trees.Graph("benchmark/n010d100C100c001Q100q001s-3i1.txt")
rand = Random()
rand.seed(int(time()))
my_ec = inspyred.ec.EvolutionaryComputation(rand)
my_ec.selector = inspyred.ec.selectors.tournament_selection
my_ec.variator = [inspyred.ec.variators.crossover(crossover_tree), mutate_tree]
my_ec.replacer = inspyred.ec.replacers.steady_state_replacement
my_ec.terminator = [inspyred.ec.terminators.evaluation_termination, inspyred.ec.terminators.average_fitness_termination]
my_ec.observer = observer_tree
final_pop = my_ec.evolve(
generator=generate_tree,
evaluator=evaluate_tree,
pop_size=100,
maximize=False,
max_evaluations=5000,
num_selected=50,
mutation_rate=0.25,
c = g.c,
q = g.q,
v2e = g.v2e,
best = 100000000000000
)
print final_pop
示例8: generateNetwork
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def generateNetwork(self,nodes,rw_prob,seed):
"""
A method for generating a Watts-Strogatz network model from specified
parameters.
Although a variation of this method is given in igraph,
it does not use parameters, rather a list of dimensions, which is not
desirable for this application.
"""
rand = Random()
rand.seed(seed)
#generate a 4-regular network first
graph = FourRegularGenerator().generateNetwork(nodes,seed)
# iterate over all edges in the graph and select those to
# be removed
# a list for storing edges to be removed
remove = []
for i in range(0,nodes):
rfloat = rand.random()
if rfloat < rw_prob:
remove.append(graph.es[i])
# after specifying nodes to be removed, add more edges, and remove the
# previous edges
for i in range(0,len(remove)):
graph.add_edges((remove[i].source,rand.randint(0,nodes-1)))
graph.delete_edges(remove[i])
return graph
示例9: main
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def main():
global rand
logger = logging.getLogger('inspyred.ec')
logger.setLevel(logging.DEBUG)
file_handler = logging.FileHandler('inspyred.log', mode='w')
file_handler.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
file_handler.setFormatter(formatter)
logger.addHandler(file_handler)
rand = Random()
rand.seed(int(time()))
params=dict()
params['name']='simple'
params['debug']=True
subsequent_runs(params)
params=dict()
params['name']='mutation_cooling'
params['mutation_cooling']=0.99
params['mutation_rate']=1.0
params['debug']=True
subsequent_runs(params)
params=dict()
params['name']='tournament_cooling'
params['tournament_cooling']=0.99
params['tournament_percentage']=1.0
params['debug']=True
subsequent_runs(params)
示例10: CreateTable
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def CreateTable():
try:
global generator
conn = MySQLdb.connect(host='localhost',user='root',passwd='asher',port=3306)
cur = conn.cursor()
#cmd_dropdb = 'drop database if exists bank2'
#cur.execute(cmd_dropdb)
cmd_createdb = 'create database if not exists bank2'
cmd_createtable = 'create table account(id int not null auto_increment PRIMARY KEY, kahao varchar(20), name varchar(20), sfid varchar(40),tel varchar(20), passwd varchar(40),quota varchar(20))'
cur.execute(cmd_createdb)
conn.select_db('bank2')
cur.execute('%s' % cmd_createtable)
cur.execute('alter table account AUTO_INCREMENT=1000;')
values = []
for i in range(len(NameList)):
generator = Random()
generator.seed() # Seed from current time
# print("darkcoding credit card generator\n")
#kahao = credit_card_number(generator, mastercardPrefixList, 16, 1)
kahao = credit_card_number(generator, ccbPrefixList, 16, 1)
# print kahao
sfid = makeNew()
tel = TelNumber()
password_md5 = hashlib.md5(sfid).hexdigest()
values.append((kahao[0],NameList[i],sfid,tel,password_md5,50000))
cur.executemany('insert into account (kahao,name,sfid,tel,passwd,quota) values(%s,%s,%s,%s,%s,%s)',values)
# cur.execute('update account set tel="13611095014" where id=3')
conn.commit()
cur.close()
conn.close()
except MySQLdb.Error,e:
print "Mysql Error %d: %s" % (e.args[0], e.args[1])
示例11: setUp
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def setUp(self):
self.field = self._create_field()
seed = "28391kaasd9129akdbb1o293"
rnd = Random()
rnd.seed(seed)
self.field.content_gen = ContentGen(rnd)
示例12: random_insert
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def random_insert(circuit, choices, seed=None):
"""Insert a circuit into another quantum circuit.
random_insert randomly selects a circuit from
choices and randomly chooses a location to insert
into circuit.
Parameters
==========
circuit : Gate tuple or Mul
A tuple or Mul of Gates representing a quantum circuit
choices : list
Set of circuit choices
seed : int
Seed value for the random number generator
"""
if len(choices) < 1:
return circuit
if isinstance(circuit, Mul):
circuit = circuit.args
# Create the random integer generator with the seed
int_gen = Random()
int_gen.seed(seed)
insert_loc = int_gen.randint(0, len(circuit))
insert_circuit_loc = int_gen.randint(0, len(choices)-1)
insert_circuit = choices[insert_circuit_loc]
left = circuit[0:insert_loc]
right = circuit[insert_loc:len(circuit)]
return left + insert_circuit + right
示例13: main
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def main(numproc=20, prng=None, display=True):
global numberofprocessors
numberofprocessors = numproc
if prng is None:
prng = Random()
prng.seed(time.time())
ea = inspyred.ec.ES(prng)
ea.terminator = [inspyred.ec.terminators.evaluation_termination,
inspyred.ec.terminators.diversity_termination,
inspyred.ec.terminators.generation_termination]
ea.observer = [inspyred.ec.observers.stats_observer,
inspyred.ec.observers.best_observer,
inspyred.ec.observers.file_observer]
final_pop = ea.evolve(generator = generate_randomFDA5Params,
evaluator = inspyred.ec.evaluators.parallel_evaluation_mp,
mp_evaluator = evaluate_FDA5,
mp_nprocs = numberofprocessors,
pop_size = 100,
bounder = bound_FDA,
maximize = True,
max_evaluations = 10000,
max_generations = 10,
num_inputs=5)
if display:
best = max(final_pop)
print('Best Solution: \n{0}'.format(str(best)))
"""
示例14: Dice
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
class Dice():
def __init__(self, die = 1, sides = 6, **kw):
self.rand = Random()
self.rand.seed(datetime.now())
self.die = die # Standard is 1
self.sides = sides # Standard is 6
if kw.has_key('random') and kw['random']:
self.randomDice()
self.randomSides()
def __repr__(self):
return "<Dice Die: %s - Sides: %s>" % (self.die, self.sides)
def randomSides(self):
self.sides = int(self.rand.random() * 100) + 1
print "Die now has %s sides" % self.sides
def randomDice(self):
self.die = int(self.rand.random() * 100) + 1
if self.die != 1:
print "There are now %s dice to be thrown" % self.die
else:
print "There is only %s die to be thrown" % self.die
def roll(self):
return int(self.rand.random() * self.sides) + 1
示例15: main
# 需要导入模块: from random import Random [as 别名]
# 或者: from random.Random import seed [as 别名]
def main(prng=None, display=False):
if prng is None:
prng = Random()
prng.seed(time())
points = [(110.0, 225.0), (161.0, 280.0), (325.0, 554.0), (490.0, 285.0),
(157.0, 443.0), (283.0, 379.0), (397.0, 566.0), (306.0, 360.0),
(343.0, 110.0), (552.0, 199.0)]
weights = [[0 for _ in range(len(points))] for _ in range(len(points))]
for i, p in enumerate(points):
for j, q in enumerate(points):
weights[i][j] = math.sqrt((p[0] - q[0])**2 + (p[1] - q[1])**2)
problem = inspyred.benchmarks.TSP(weights)
ac = inspyred.swarm.ACS(prng, problem.components)
ac.terminator = inspyred.ec.terminators.generation_termination
final_pop = ac.evolve(generator=problem.constructor,
evaluator=problem.evaluator,
bounder=problem.bounder,
maximize=problem.maximize,
pop_size=10,
max_generations=50)
if display:
best = max(ac.archive)
print('Best Solution:')
for b in best.candidate:
print(points[b.element[0]])
print(points[best.candidate[-1].element[1]])
print('Distance: {0}'.format(1/best.fitness))
return ac