Python Config Examples

Example #1

File: GA_Helper.py Project: rfcoles1/Genetic_Algorithms

import numpy as np

from GA_Config import Config
from GA_Network import Network

config = Config()

#copies all the weights to a another network object
def copy_net(old_net):
    new_net = Network(config)
    new_net.w_in = np.copy(old_net.w_in)
    for i in range(config.num_layers):
        new_net.w_hidden[i] = np.copy(old_net.w_hidden[i])
    new_net.w_out = np.copy(old_net.w_out)
    return new_net

#weights are mutated by adding random noise
def mutation(policy):
    noise = np.random.randn(policy.total_num)
    noise *= config.sigma

    policy.w_in += noise[:policy.num_in].reshape(policy.w_in.shape)
    curr = policy.num_in
    for i in range(config.num_layers):
        policy.w_hidden[i] += noise[curr:curr+policy.num_weights[i]].reshape(policy.w_hidden[i].shape)
        curr += policy.num_weights[i]
    policy.w_out += noise[policy.total_num - policy.num_out:].reshape(policy.w_out.shape)

Example #2

from scipy import stats
import GPy
import matplotlib.pyplot as plt
import matplotlib.patches as mpatch

import gym
import os
import sys
sys.path.insert(0, '../../..')
import GP_Games

sys.path.insert(0, '../../../Genetic_Algorithms')
from GA_Config import Config
from GA_Network import Network

config = Config()
config.num_layers = 2
config.num_hidden = 128
config.env_name = 'GP_Water-v0'
config.a_size = 4

network = Network(config)

generations = 100
steps = 100
iters = 1
actions = np.zeros([steps, generations, iters])

TargetTemp = 100
TargetMass = [0, 0.5, 0.5]
StartTemp = 21

Example #3

File: video_GA_1.py Project: rfcoles1/RL_Games_MultiAgent

import numpy as np
import gym
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors

import os
import sys
sys.path.insert(0, '../../../')
import MultiAgent_Games

sys.path.insert(0, '../../../MultiAgent_GA')
from GA_Config import Config
from GA_Network import Network

config = Config()
config.num_layers = 2
config.num_hidden = 128
config.env_name = 'Bees-v1'
config.a_size = 5

network = Network(config)
weights = np.load('./models/Bees-v1_11/10500.npz')
network.w_in = weights['w_in']
network.w_hidden = weights['w_h']
network.w_out = weights['w_out']

env = gym.make(config.env_name).unwrapped
env.engine.num_bees = 1
env.engine.num_flowers = 1
s = env.reset()

Example #4

File: demo.py Project: rfcoles1/RL_Games_GP

import numpy as np
import gym
import matplotlib.pyplot as plt

import time
from Tkinter import *
import os
import sys
sys.path.insert(0, '../../..')
import GP_Games

sys.path.insert(0, '../../../Genetic_Algorithms')
from GA_Config import Config
from GA_Network import Network

config = Config()
config.num_layers = 2
config.num_hidden = 128

network = Network(config)
weights = np.load('../../../Genetic_Algorithms/models/GP_Water-v0/126.npz')
network.w_in = weights['w_in']
network.w_hidden = weights['w_h']
network.w_out = weights['w_out']

env = gym.make('GP_Water-v0')
s = env.reset()
print(env.unwrapped.TargetTemp, env.unwrapped.TargetMass)


def plt_model(ind, s, r):