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# Derek Tishler

# Deap Hypervolume comparison for varying population size and number of objectives, 
# testing for use with high dimensional NSGA III with many objectives (over 8).)

# Discussion here, also required fitness_values.txt with 212x14 array of fitness values per ind in pop:
# https://groups.google.com/g/deap-users/c/XLfLa3at6pw

import numpy as np

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# Based on https://raw.githubusercontent.com/DEAP/deap/master/examples/ga/onemax_mp.py
# Using onemax(ignore the problem sorta) to show how to work with only normalized individuals
# Can Uses numpy individuals but no multiproc: https://deap.readthedocs.io/en/master/examples/ga_onemax_numpy.html

# Derek M Tishler, Dec 2020

import multiprocessing
import random
import sys

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import array
import random

import numpy

from deap import algorithms
from deap import base
from deap import creator
from deap import tools

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import sklearn.decomposition
import sklearn.ensemble
import sklearn.linear_model
import sklearn.preprocessing
import sklearn.svm
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split

from baikal import Input, Model, make_step
from baikal.plot import plot_model

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# Derek M. Tishler
# nx plot example deap individual
# For post: https://groups.google.com/g/deap-users/c/nZFZpm5OPZA

import matplotlib.pyplot as plt
import networkx as nx
from networkx.drawing.nx_agraph import graphviz_layout

## May need is resuming session
#from deap import creator