deap

Using multiprocessing in DEAP for genetic programming

浪尽此生 提交于 2020-08-09 10:19:07
问题 I'm using DEAP library to implement genetic programming and I have used eaMuCommaLambda algorithm for this purpose. In order to run the program in parallel, I followed the instructions in the DEAP document and added the two following lines of code in the if __name__ == "__main__" section. import multiprocessing pool = multiprocessing.Pool() toolbox.register("map", pool.map) pop, log = algorithms.eaMuCommaLambda(pop, toolbox, MU, LAMBDA, cxpb, mutpb, gen, halloffame=hof, stats=mstats, verbose

Using multiprocessing in DEAP for genetic programming

醉酒当歌 提交于 2020-08-09 10:18:50
问题 I'm using DEAP library to implement genetic programming and I have used eaMuCommaLambda algorithm for this purpose. In order to run the program in parallel, I followed the instructions in the DEAP document and added the two following lines of code in the if __name__ == "__main__" section. import multiprocessing pool = multiprocessing.Pool() toolbox.register("map", pool.map) pop, log = algorithms.eaMuCommaLambda(pop, toolbox, MU, LAMBDA, cxpb, mutpb, gen, halloffame=hof, stats=mstats, verbose

jmeter5.0生成html报告 快速入门

不打扰是莪最后的温柔 提交于 2020-08-05 18:18:33
JMeter性能测试5.0时代之-多维度的图形化HTML报告 快速入门 1.确认基本配置 在jmeter.properties或者user.properties确认如下配置项: jmeter.save.saveservice.bytes = true jmeter.save.saveservice.label = true jmeter.save.saveservice.latency = true jmeter.save.saveservice.response_code = true jmeter.save.saveservice.response_message = true jmeter.save.saveservice.successful = true jmeter.save.saveservice.thread_counts = true jmeter.save.saveservice.thread_name = true jmeter.save.saveservice.time = true # the timestamp format must include the time and should include the date. # For example the default, which is milliseconds since the epoch:

Unable to speed up Python DEAP with Multiprocessing

别等时光非礼了梦想. 提交于 2020-06-16 16:59:11
问题 I am using the below sample code for OneMax problem (maximizing the number of ones of a bitstring) using DEAP package and multiprocessing. I am unable to speed up the process using multiprocessing. I want to use this for a more complex problem before finding out what is the issue here. Thank you. import array import multiprocessing from multiprocessing import Pool import random import time import numpy as np from deap import algorithms from deap import base from deap import creator from deap

Python DEAP library, using random words as individuals

守給你的承諾、 提交于 2020-01-06 05:28:15
问题 I'm trying to get a better handle on DEAP. I want to make a genetic algorithm that has words as individuals as a population and it maximizes this by checking how far in distance(read: spelling) these words are from a given "maximal word". This is what I have done so far following examples in the documentation import random from randomwordgenerator import randomwordgenerator from deap import base from deap import creator from deap import tools creator.create("FitnessMax", base.Fitness, weights

RuntimeError of python occers on windows to multiprocessing

余生颓废 提交于 2020-01-03 05:00:27
问题 I am trying Threading and Multiprocessing for python on a windows machine.But python give the following message. RuntimeError: Attempt to start a new process before the current process has finished its bootstrapping phase. This probably means that you are on Windows and you have forgotten to use the proper idiom in the main module: if __name__ == '__main__': freeze_support() ... The "freeze_support()" line can be omitted if the program is not going to be frozen to produce a Windows executable

How can I create a list with random numbers in different ranges for deap package in python

删除回忆录丶 提交于 2019-12-24 03:25:11
问题 I am using DEAP package in Python to write a program for optimization with evolutionary algorithm specifically with Genetic. I need to create chromosomes by using list type in python. This chromosome should have five float genes (alleles) in different ranges. My main problem is to create such a chromosome. However, it would be better if I could use tools.initRepeat function of deap package for this. For the cases in which all the genes are in the same range we could use the following code:

Programming DEAP with Scoop

守給你的承諾、 提交于 2019-12-24 01:14:48
问题 I'm using the DEAP library in python for a multi-objective optimization problem. I'd like to use multiple processors for this task; however, I'm running into some trouble. To give some context, I'm using networkx in conjunction with DEAP I also define the fitness function, crossover, and mutation functions (which I won't show here due to certain reasons). It says here that all I need to do is to install Scoop and add the lines from scoop import futures toolbox.register("map", futures.map)

Install Deap for Python (Spyder)

跟風遠走 提交于 2019-12-13 09:47:09
问题 How should I install deap package for python from spyder? I have tried: pip install deal import deap deap.download() 回答1: Assuming deap is not installed, type: pip install deap If you get the response Collecting deap Installing collected packages: deap Successfully installed deap-1.0.2 Then you have just installed deap and you are ready to import it into your projects. If you get the response, Requirement already satisfied (use --upgrade to upgrade): deap in ./Path/To/site-packages , deap is

Deap python package: create individuals with different ranges and mix of integers and floats

假如想象 提交于 2019-12-12 08:13:39
问题 I am trying to use DEAP to maximise a function. I understand how to do it with the basic example: toolbox.register("attr_bool", random.randint, 0, 1) toolbox.register("individual", tools.initRepeat, creator.Individual, toolbox.attr_bool, 100) which creates 100 random values or either 0 or 1. You then go on and create a population and mutate ... How do you build a population when you have for example two parameters: parameter 1 integer with range [0,1] parameter 2 float with range [0,2] Then