def game_loop(self):
"""The main game loop. This is where your hivemind code goes."""
# Setting up rate limiter.
rate_limit = rate_limiter.RateLimiter(120)
# Setting up data.
field_info = FieldInfoPacket()
self.game_interface.update_field_info_packet(field_info)
packet = GameTickPacket()
self.game_interface.update_live_data_packet(packet)
data.setup(self, packet, field_info, self.running_indices)
self.ball.predict = BallPrediction()
# https://github.com/RLBot/RLBotPythonExample/wiki/Ball-Path-Prediction
# MAIN LOOP:
while True:
# Updating the game packet from the game.
self.game_interface.update_live_data_packet(packet)
# Processing packet.
data.process(self, packet)
# Ball prediction.
self.game_interface.update_ball_prediction(self.ball.predict)
# Planning.
brain.plan(self)
# Rendering.
self.render_debug(self.game_interface.renderer)
# For each drone under the hivemind's control, do something.
for drone in self.drones:
# The controls are reset each frame.
drone.ctrl = PlayerInput(
) # Basically the same as SimpleControllerState().
# Role execution.
if drone.role is not None:
drone.role.execute(self, drone)
self.render_role(self.game_interface.renderer, drone)
# Send the controls to the bots.
self.game_interface.update_player_input(
drone.ctrl, drone.index)
# Rate limit sleep.
rate_limit.acquire()
def game_loop(self):
"""The main game loop. This is where your hivemind code goes."""
# Setting up rate limiter.
rate_limit = rate_limiter.RateLimiter(120)
# Setting up data.
field_info = FieldInfoPacket()
self.game_interface.update_field_info_packet(field_info)
packet = GameTickPacket()
self.game_interface.update_live_data_packet(packet)
data.setup(self, packet, field_info, self.running_indices)
self.ball.predict = BallPrediction()
# MAIN LOOP:
while True:
# Updating the game packet from the game.
self.game_interface.update_live_data_packet(packet)
# Processing packet.
data.process(self, packet)
# Ball prediction.
self.game_interface.update_ball_prediction(self.ball.predict)
brain.think(self)
for drone in self.drones:
drone.ctrl = PlayerInput()
if drone.role is not None:
drone.role.execute(self, drone)
self.game_interface.update_player_input(
drone.ctrl, drone.index)
self.draw_debug()
# Rate limit sleep.
rate_limit.acquire()
def get_output(self, packet: GameTickPacket) -> SimpleControllerState:
# Runs setup.
if self.need_setup:
field_info = self.get_field_info()
data.setup(self, packet, field_info)
self.need_setup = False
# Preprocessing.
data.process(self, packet)
self.ctrl = SimpleControllerState()
# Handle states.
self.checkState()
# Execute state.
if not self.state.expired:
self.state.execute(self)
# Render.
self.render(self.renderer)
return self.ctrl
#
return sequence_groups
#### Load data
# sequence_groups[i] contains data for class i
# 4-dimensional data structure: (class, sequence_num, timestep, channel_num)
#
# PROVIDED DATASETS:
# digits_session_1_dataset
# digits_session_2_dataset
# digits_session_3_dataset
# digits_session_4_dataset
sequence_groups = transform_data(data.join([
data.process(1, ['data/data/utkarsh1.txt'], sample_rate=1000),
data.process(1, ['data/data/utkarsh2.txt'], sample_rate=1000),
data.process(1, ['data/data/utkarsh3.txt'], sample_rate=1000),
]))
# Split sequence_groups into training and validation data
training_sequence_groups, validation_sequence_groups = data.split(sequence_groups, 1./6)
# Manually selecting different training and validation datasets
#training_sequence_groups = transform_data(data.digits_session_1_dataset())
#validation_sequence_groups = transform_data(data.digits_session_4_dataset())
# Pads or truncates each sequence to length
length = 2400 # 300,600
training_sequence_groups = data.transform.pad_truncate(training_sequence_groups, length)
validation_sequence_groups = data.transform.pad_truncate(validation_sequence_groups, length)
return sequence_groups
#### Load data
# sequence_groups[i] contains data for class i
# 4-dimensional data structure: (class, sequence_num, timestep, channel_num)
#
# PROVIDED DATASETS:
# digits_session_1_dataset
# digits_session_2_dataset
# digits_session_3_dataset
# digits_session_4_dataset
sequence_groups = transform_data(
data.join([
data.process(1, ['data/data/181_silence1_50.txt'], sample_rate=1000),
# data.process(1, ['data/data/182_silence2_50.txt'], sample_rate=1000),
data.process(1, ['data/data/183_silence3_50.txt'], sample_rate=1000),
# data.process(1, ['data/data/95_subvocal_silence_300_trials.txt'])[:,:50],
# data.process(1, ['data/data/107_subvocal_silence_300_trials.txt'])[:,:50],
## data.process(1, ['data/data/119_subvocal_silence_300_trials.txt']),
]),
sample_rate=1000)
print np.shape(sequence_groups[0][0])
sequence_groups = data.transform.downsample(sequence_groups, 4)
print np.shape(sequence_groups[0][0])
#plt.figure()
import numpy as np
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
import data
#sequence_groups = data.silence_and_not_silence_dataset()
sequence_groups1 = data.digits_session_2_dataset()
sequence_groups2 = data.join([
data.process(1, ['data/test_data/testing_0_s2.txt']),
data.process(1, ['data/test_data/testing_1_s2.txt']),
data.process(1, ['data/test_data/testing_2_s2.txt']),
data.process(1, ['data/test_data/testing_3_s2.txt']),
data.process(1, ['data/test_data/testing_4_s2.txt']),
data.process(1, ['data/test_data/testing_5_s2.txt']),
data.process(1, ['data/test_data/testing_6_s2.txt']),
data.process(1, ['data/test_data/testing_7_s2.txt']),
data.process(1, ['data/test_data/testing_8_s2.txt']),
data.process(1, ['data/test_data/testing_9_s2.txt']),
])
print np.shape(sequence_groups1)
print np.shape(sequence_groups2)
length = 300
sequence_groups1 = data.transform.default_transform(sequence_groups1)
sequence_groups2 = data.transform.default_transform(sequence_groups2)
def run():
fetched = data.fetch()
return data.process(fetched)