def draw(self):
for i in self.points:
plot(i)
if (self.divided):
self.boundary.drawDivision()
self.northEast.draw()
self.northWest.draw()
self.southEast.draw()
self.southWest.draw()
def ppo_test():
env = gym.make('Pendulum-v0')
ppo = PPO(3, 1, 2)
ppo.ep_max = 500
for ep in range(ppo.ep_max):
s = env.reset()
buffer_s, buffer_a, buffer_r = [], [], []
ep_r = 0
for t in range(300): # in one episode
env.render()
a = ppo.get_action(s)
s_, r, done, _ = env.step(a)
s_ = np.squeeze(s_)
buffer_s.append(s)
buffer_a.append(a)
buffer_r.append((r + 2) / 2) # normalize reward, find to be useful
s = s_
ep_r += r
if (t + 1) % ppo.batch_size == 0 or t == 300 - 1:
v_s_ = ppo.get_value(s_)
discounted_r = []
for r in buffer_r[::-1]:
v_s_ = r + 0.9 * v_s_
discounted_r.append(v_s_)
discounted_r.reverse()
bs, ba, br = np.vstack(buffer_s), np.vstack(
buffer_a), np.vstack(
discounted_r) #np.array(discounted_r)[:,np.newaxis]
buffer_s, buffer_a, buffer_r = [], [], []
ppo.train(bs, ba, br, ep)
ep_r_all.append(ep_r)
print(ep, ' ', ep_r)
plot(ppo.a_loss)
plot(ppo.c_loss)
plot(ep_r_all)
def drawMove(move, port):
fileName = getfile(move)
plot(fileName, port)
X.append(data["X1"])
X.append(data["X2"])
# Now array X has two rows, first row contains all the numbers for X1 and the
# second row contains all the numbers for X2 but I want an output in which
# the number of rows is equal to the number of data and each row contains
# one X1 and X2 so I got the transpose of array X
Xt = np.transpose(X)
return np.array(Xt), data["Label"].values
X, y = read_data('dataset.csv')
plot(X, y)
# I want to split the data to training and test data but before doing it I shuffle the data to get a different
# training and test data every time I run the code so the result I get may differ each time.
X_train, X_test, y_train, y_test = train_test_split(X,
y,
test_size=0.2,
shuffle=True)
# # Make a perceptron and train it
# p = perceptron.Perceptron()
# p.fit(X_train, y_train)
#
# border(X, p)
#
# # Now I want to test the trained perceptron
print("training...")
seller_train_data = []
buyer_train_data = []
for i in tqdm(range(NEG_TRAIN_DATA)):
world = SCML2020World(
**SCML2020World.generate(
agent_types=[MyLearnNegotiationAgent, DecentralizingAgent,],
n_steps=40,
n_processes=2,
),
construct_graphs=True
)
SCML2020World.cancelled_contracts = cancelled_contracts
world.run()
plot(world)
seller_data, buyer_data = get_train_data(world)
seller_train_data += seller_data
buyer_train_data += buyer_data
seller_train_features, seller_train_tags = split_features_tags(seller_train_data)
seller_train_features = [
torch.from_numpy(feature).float() for feature in seller_train_features
]
seller_train_tags = [torch.from_numpy(tag).float() for tag in seller_train_tags]
all_seller_data = list(zip(seller_train_features, seller_train_tags))
shuffle(all_seller_data)
train_seller_data = all_seller_data[: -int(len(all_seller_data) * NEG_VALIDATION_SPLIT)]
test_seller_data = all_seller_data[-int(len(all_seller_data) * NEG_VALIDATION_SPLIT) :]
from draw import plot
import argparse
parser = argparse.ArgumentParser(
description='This is a basic gcode sender. http://crcibernetica.com')
parser.add_argument('-p', '--port', help='Input USB port', required=True)
parser.add_argument('-f', '--file', help='Gcode file name', required=True)
args = parser.parse_args()
port = args.port
#plot("1.g",port)
#plot("2.g",port)
#plot("3.g",port)
#plot("4.g",port)
#plot("5.g",port)
#plot("6.g",port)
#plot("7.g",port)
#plot("8.g",port)
plot(args.file, args.port)
def clicked(x, y):
qt.insertDraw([x, y])
if qt.contains([x, y]): plot([x, y])
print("You clicked : ", x, ", ", y)
from quadTree import quadTree
from draw import Rect, win, head, plot
import random
import turtle
def clicked(x, y):
qt.insertDraw([x, y])
if qt.contains([x, y]): plot([x, y])
print("You clicked : ", x, ", ", y)
boundary = Rect([0, 0], 250, 250)
boundary.draw()
qt = quadTree(boundary, 4)
for _ in [0] * 600:
rand_x = random.uniform(-250, 251)
rand_y = random.uniform(-250, 251)
qt.insertDraw([rand_x, rand_y])
plot([rand_x, rand_y])
win.onclick(clicked)
qt.draw()
win.mainloop()
import sys
import draw
if len(sys.argv) > 4:
def f(x):
return eval(sys.argv[1])
draw.plot(f, float(sys.argv[2]), float(sys.argv[3]), float(sys.argv[4]))
else:
print('Bad arguments')
