运行例子报错

[pytlab]

运行例子报错

[hoboly]

105a5ff

pip in install 也有問題, 人手條改 C:\ProgramData\Anaconda3\Lib\site-packages\gaft\mpiutil.py 後就無事

[PytLab]

可以通过pip install 安装 0.5.7版本，bug已修复

[PytLab]

你好，由于最近更新了GAFT的部分接口，mpi的部分在最新版本中不会自动实例化，而是用户自行实例化。例子是我忘记更新了，你可以将你的脚本中的

from gaft.mpiutil import mpi

改写成

from gaft.mpiutil import MPIUtil

mpi = MPIUtil()

[PytLab]

例子我会在今天进行更新，谢谢提醒

[lilyef2000]

运行例子还是报错：

C:\Users\Administrator\Envs\py3MachineLearning\Scripts\python.exe D:/personal/Mathematical_modeling/genetic_algorithm.py
Traceback (most recent call last):
File "D:/personal/Mathematical_modeling/genetic_algorithm.py", line 48, in
engine.run(ng=100)
File "C:\Users\Administrator\Envs\py3MachineLearning\lib\site-packages\gaft\engine.py", line 45, in profiled_func
result = func(*args, **kwargs)
File "C:\Users\Administrator\Envs\py3MachineLearning\lib\site-packages\gaft\engine.py", line 160, in run
a.setup(ng=ng, engine=self)
File "C:\Users\Administrator\Envs\py3MachineLearning\lib\site-packages\gaft\mpiutil.py", line 147, in _call_in_master_proc
if mpi.is_master:
NameError: name 'mpi' is not defined
麻烦您帮忙看下这是什么问题呢？

engine.py：

import cProfile
import pstats
import os

from .components import IndividualBase, Population
from .plugin_interfaces.operators import Selection, Crossover, Mutation
from .plugin_interfaces.analysis import OnTheFlyAnalysis
from .mpiutil import MPIUtil

mpi = MPIUtil()

mpiutile.py

def master_only(func):
''' Decorator to limit a function to be called only in master process in MPI env.
'''
@wraps(func)
def _call_in_master_proc(*args, **kwargs):
if mpi.is_master:
return func(*args, **kwargs)

return _call_in_master_proc

代码：
#!/usr/bin/env python

-- coding: utf-8 --

'''
Find the global maximum for binary function: f(x) = ysim(2pix) + xcos(2piy)
'''

from math import sin, cos, pi

from gaft import GAEngine
from gaft.components import BinaryIndividual
from gaft.components import Population
from gaft.operators import TournamentSelection
from gaft.operators import UniformCrossover
from gaft.operators import FlipBitBigMutation

Built-in best fitness analysis.

from gaft.analysis.fitness_store import FitnessStore
from gaft.analysis.console_output import ConsoleOutput

Define population.

indv_template = BinaryIndividual(ranges=[(-2, 2), (-2, 2)], eps=0.001)
population = Population(indv_template=indv_template, size=50).init()

Create genetic operators.

#selection = RouletteWheelSelection()
selection = TournamentSelection()
crossover = UniformCrossover(pc=0.8, pe=0.5)
mutation = FlipBitBigMutation(pm=0.1, pbm=0.55, alpha=0.6)

Create genetic algorithm engine.

Here we pass all built-in analysis to engine constructor.

engine = GAEngine(population=population, selection=selection,
crossover=crossover, mutation=mutation,
analysis=[ConsoleOutput, FitnessStore])

Define fitness function.

@engine.fitness_register
def fitness(indv):
x, y = indv.solution
return ysin(2pix) + xcos(2piy)

if 'main' == name:
engine.run(ng=100)

[PytLab]

Did you install GAFT using pip install? I forgot to push the newest version to PyPI, you can currently install GAFT from source. I'll upload it to PyPI today.

Thanks for your issue.