From 0f7ec42d022451d8bcb2133de8f1de236784b020 Mon Sep 17 00:00:00 2001 From: Daniel Isaac Date: Thu, 9 May 2019 09:57:13 +0530 Subject: [PATCH] final changes --- examples/tutorial.md | 2 +- pygenetic/GAEngine.py | 2 +- setup.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/tutorial.md b/examples/tutorial.md index 59a4507..dc5cca8 100644 --- a/examples/tutorial.md +++ b/examples/tutorial.md @@ -70,7 +70,7 @@ Other parameters of `GAEngine` include * `adaptive_mutation`: which is a Boolean which decides if adaptive mutation is to be used(default: True) * `population_control`: which is a Boolean which decides whether or not the GAEngine should ensure that the population size remains the same in every evolution iteration. This ensures that any error/issue in user's custom selection or evolution code doesn't cause population size to change. (default: False) * `hall_of_fame_injection`: which is a boolean used to carry out the injection of the best chromosome encountered so far in every 20 generations. (default: True) -* `efficient_iteration_halt`: which is a boolean used to carry out efficient_iteration_halt optimization. It stops evolving if same best fitness value is encountered for 20 consecutive generations (default: True) +* `efficient_iteration_halt`: which is a boolean used to carry out efficient_iteration_halt optimization. It stops evolving if same best fitness value is encountered for 20 consecutive generations (default: False) * `use_pyspark`: which is a boolean used to decide if sequential execution is to be carried out or parallel execution on Apache Spark is to be carried out (default: False) ### 1.3 Crossovers, Mutations and Selection Functions diff --git a/pygenetic/GAEngine.py b/pygenetic/GAEngine.py index 4c6f9d8..bc3a967 100644 --- a/pygenetic/GAEngine.py +++ b/pygenetic/GAEngine.py @@ -153,7 +153,7 @@ class GAEngine: """ - def __init__(self,factory,population_size=100,cross_prob=0.7,mut_prob=0.1,fitness_type='max',adaptive_mutation=True, population_control=False,hall_of_fame_injection=True,efficient_iteration_halt=True,use_pyspark=False): + def __init__(self,factory,population_size=100,cross_prob=0.7,mut_prob=0.1,fitness_type='max',adaptive_mutation=True, population_control=False,hall_of_fame_injection=True,efficient_iteration_halt=False,use_pyspark=False): self.fitness_func = None self.factory = factory self.cross_prob = cross_prob diff --git a/setup.py b/setup.py index ffec29e..88c6847 100644 --- a/setup.py +++ b/setup.py @@ -5,7 +5,7 @@ setuptools.setup( name="pygenetic", - version="1.0.1", + version="1.0.2", author="Bharatraj S Telkar, Daniel Isaac, Shreyas V Patil", author_email="telkarraj@gmail.com, danielbcbs2@gmail.com, pshreyasv100@gmail.com", description="An Efficient Python Genetic Algorithm API",