def setup_experiment():
"""
Intialize the environment for the experiment
Returns:
the window
"""
bufhelp.connect()
plt.rcParams['toolbar'] = 'None'
fig = plt.figure()
fig.patch.set_facecolor('black')
ax = fig.add_subplot(1, 1, 1)
ax.set_xlim((-1, 1))
ax.set_ylim((-1, 1))
ax.set_axis_off()
ax.set_facecolor('black')
text = ax.text(0,
0,
'STARTING',
color='white',
fontsize=120,
ha='center',
va='center')
drawnow()
return text
def signalproxy(fSample=100, nChans=10, blocksize=2):
from time import sleep, time
import numpy
ftc = bufhelp.connect(header=False)
print "Putting header."
ftc.putHeader(nChans, fSample, 10)
print "Starting singal proxy"
delta = 1.0 / (fSample / blocksize)
sample = numpy.random.rand(blocksize, nChans)
n = 0;
while True:
sendtime = time()
ftc.putData(sample)
n = n + 1
if n % 100 == 0:
print str(n) + " data packages sent."
sample = numpy.random.rand(blocksize, nChans)
wait = delta - (time() - sendtime)
if wait > 0:
sleep(wait)
def echoClient(timeout=5000):
## init connection to the buffer
ftc,hdr=bufhelp.connect();
# Now do the echo client
nEvents=hdr.nEvents;
endExpt=None;
while endExpt is None:
bufhelp.sendEvent('echo',1)
# wait for ackknowledgement from Server
ack_received = False
while ack_received is False:
(curSamp,curEvents)=ftc.wait(-1,nEvents,timeout) # Block until there are new events to process
if curEvents>nEvents :
evts=ftc.getEvents([nEvents,curEvents-1])
nEvents=curEvents # update record of which events we've seen
for evt in evts:
if evt.type == "exit": endExpt=1
if evt.type == "ack": ack_received = True
print(evt)
else:
print("Waiting for acknowledgement...")
ftc.disconnect() # disconnect from buffer when done
def echoClient(timeout=5000):
## init connection to the buffer
ftc, hdr = bufhelp.connect()
# Now do the echo client
nEvents = hdr.nEvents
endExpt = None
while endExpt is None:
bufhelp.sendEvent('echo', 1)
# wait for ackknowledgement from Server
ack_received = False
while ack_received is False:
(curSamp, curEvents) = ftc.wait(
-1, nEvents,
timeout) # Block until there are new events to process
if curEvents > nEvents:
evts = ftc.getEvents([nEvents, curEvents - 1])
nEvents = curEvents # update record of which events we've seen
for evt in evts:
if evt.type == "exit": endExpt = 1
if evt.type == "ack": ack_received = True
print(evt)
else:
print("Waiting for acknowledgement...")
ftc.disconnect() # disconnect from buffer when done
def __init__(self):
self.si = SOSInterface()
self.controller = EnvController()
self.num_of_options = self.si.prepare_main_screen()
ftc, hdr = bufhelp.connect()
if (DEBUG):
self.all_predictions = []
self.all_targets = []
def __init__(self):
self.si = StimulusInterface()
self.controller = EnvController()
info = self.si.prepare_main_screen()
self.num_of_options, self.num_of_groups = info[:2]
self.row_indices, self.column_indices = info[2:]
ftc, hdr = bufhelp.connect()
if (DEBUG):
self.all_predictions = []
self.all_targets = []
def send_prior_loop(events, timeout=2):
## init connection to the buffer
ftc, hdr = bufhelp.connect()
ev_list = []
# Now do the echo client
nEvents = hdr.nEvents
endExpt = None
bufhelp.sendEvent('prior.start', '1')
priors = calc_priors(ev_list)
bufhelp.sendEvent('priors', priors.to_csv())
priors.to_csv('priors.csv')
# bufhelp.sendEvent('p300preds', priors.to_csv())
i = 0
while endExpt is None:
(curSamp, curEvents) = ftc.wait(
-1, nEvents,
timeout) # Block until there are new events to process
if curEvents > nEvents:
evts = ftc.getEvents([nEvents, curEvents - 1])
nEvents = curEvents # update record of which events we've seen
for evt in evts:
if evt.type == "exit": endExpt = 1
if evt.type == "p300preds":
# read classifier predictions
preds = pd.read_csv(StringIO(evt.value),
header=None).set_index(0)[1]
preds = preds.drop('pause')
preds.to_csv('p300pred_wouter' + str(i) + '.csv')
i += 1
print(priors)
print('preds', preds)
p = preds * priors
print(p)
p /= sum(p)
print(p)
best = p.sort_values().index[-1]
best_event, best_value = best.split('.')
if best_event == 'sos':
bufhelp.sendEvent('sos', 'start')
# send actual event to virtual environment
bufhelp.sendEvent(best_event, best_value)
# send event to MatLab code
bufhelp.sendEvent('finalprediction',
best_event + '.' + best_value)
ev_list.append(best)
priors = calc_priors(ev_list)
priors.to_csv('priors.csv')
# print(evt)
ftc.disconnect() # disconnect from buffer when done
def echoClient(timeout=5000):
## init connection to the buffer
ftc,hdr=bufhelp.connect();
# send event to buffer
bufhelp.sendEvent('echo',1)
# wait for ackknowledgement from Server
ftc.disconnect() # disconnect from buffer when done
def echoClient(timeout=5000):
## init connection to the buffer
ftc, hdr = bufhelp.connect()
# send event to buffer
bufhelp.sendEvent('echo', 1)
# wait for ackknowledgement from Server
ftc.disconnect() # disconnect from buffer when done
def echoClient(timeout=5000):
## init connection to the buffer
ftc,hdr=bufhelp.connect();
# send event to buffer
while True:
events = bufhelp.buffer_newevents(state=True)
for event in events:
if event.type == 'quit':
ftc.disconnect()
return
elif event.type != 'echo':
bufhelp.sendEvent('echo', event.value)
stimPos=np.stack((np.cos(theta),np.sin(theta))) #[2 x nSymbs]
for hi,pos in enumerate(stimPos):
rect=patches.Rectangle((pos[0]-stimRadius/2,pos[1]-stimRadius/2),stimRadius/2,stimRadius/2,facecolor=bgColor)
hhi=ax.add_patch(rect)
hdls.insert(hi,hhi)
# add symbol for the center of the screen
spos = np.array((0,0)).reshape((-1,1))
stimPos=np.hstack((stimPos,spos)) #[2 x nSymbs+1]
rect = patches.Rectangle((0-stimRadius/4,0-stimRadius/4),stimRadius/2,stimRadius/2,facecolor=bgColor)
hhi =ax.add_patch(rect)
hdls.insert(nSymbs,hhi)
[ _.set(visible=False) for _ in hdls] # make all invisible
## init connection to the buffer
ftc,hdr=bufhelp.connect();
#wait for key-press to continue
[_.set(facecolor=bgColor) for _ in hdls]
txthdl.set(text='Press key to start')
drawnow()
waitforkey(fig)
bufhelp.sendEvent('stimulus.training','start')
state=None
## STARTING stimulus loop
for si,tgt in enumerate(tgtSeq):
# YOUR CODE HERE #
#catch the prediction
# Loading the preproc and bufhelp libraries, preproc provides the processing functions for the signal data # bufhelp will provide the connection to the buffer, where al programs can pass events Path_Preproc = "/../python/signalproc" # This variable contains the path to the folder where the libraries files are sys.path.append(os.getcwd() + Path_Preproc) # This allows to load the libraries this way import preproc # Loading import bufhelp Path_FieldTrip = "../dataAcq/buffer/python" # Variable which contains the path to the Fieldtrip library sys.path.append(os.getcwd() + Path_FieldTrip) import FieldTrip ftc,hdr=bufhelp.connect() #This functions connects the program to the buffer, and the passing of messages ##### Variables ##### verbose = True # For True values, the terminal will detail what it's happening inside the program im_length = 3000 # Length of time that the signal will be collected # This time should be the same as the time used to collect the data to train the classifier, #otherwise, the sizes of the classifier training and the processed signal wont match classifier_right_name = 'classifier_right' # Name of the file with the classifier for the right hand, must be of pk type classifier_left_name = 'classifier_left' # Name of the file with the classifier for the left hand, must be of pk type
#!/usr/bin/env python3
import sys,os
sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)),"../../dataAcq/buffer/python"))
sys.path.append("../signalProc")
import preproc
import bufhelp
#import linear
import pickle
bufhelp.connect()
trlen_ms = 600
run = True
print ("Waiting for startPhase.cmd event.")
while run:
e = bufhelp.waitforevent("startPhase.cmd",1000, True)
print("Got startPhase event: %s"%e)
if e is not None:
if e.value == "calibration":
print("Calibration phase")
data, events, stopevents = bufhelp.gatherdata("stimulus.tgtFlash",trlen_ms,("stimulus.training","end"), milliseconds=True)
pickle.dump({"events":events,"data":data}, open("subject_data", "w"))
elif e.value == "train":
print("Training classifier")
data = preproc.detrend(data)
data, badch = preproc.badchannelremoval(data)
data = preproc.spatialfilter(data)
data = preproc.spectralfilter(data, (0, .1, 10, 12), bufhelp.fSample)
# Sends a command to BrainRacer.
def send_command(command):
global br_socket
print("Send cmd " + str(command))
cmd = (br_player * 10) + command
data = struct.pack('B', cmd)
br_socket.sendto(data, (br_hostname, br_port))
#Connect to BrainRacers
br_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
#Connect to Buffer
(ftc, hdr) = bufhelp.connect(buffer_hostname, buffer_port)
print("Connected to " + buffer_hostname + ":" + str(buffer_port))
print(hdr)
def max2(numbers):
i1 = i2 = None
m1 = m2 = float('-inf')
for i, v in enumerate(numbers):
if v > m2:
if v >= m1:
m1, m2 = v, m1
i1, i2 = i, i1
else:
m2 = v
i2 = i
# Sends a command to BrainRacer.
def send_command(command):
global br_socket
print("Send cmd " + str(command))
cmd = (br_player * 10) + command
data = struct.pack("B", cmd)
br_socket.sendto(data, (br_hostname, br_port))
# Connect to BrainRacers
br_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
# Connect to Buffer
(ftc, hdr) = bufhelp.connect(buffer_hostname, buffer_port)
print("Connected to " + buffer_hostname + ":" + str(buffer_port))
print(hdr)
def max2(numbers):
i1 = i2 = None
m1 = m2 = float("-inf")
for i, v in enumerate(numbers):
if v > m2:
if v >= m1:
m1, m2 = v, m1
i1, i2 = i, i1
else:
m2 = v
i2 = i
if braincontrol:
sys.path.append(
os.path.join(os.path.dirname(os.path.abspath(__file__)), bufferpath))
import FieldTrip
import bufhelp
sys.path.append(
os.path.join(os.path.dirname(os.path.abspath(__file__)), sigProcPath))
## CONFIGURABLE VARIABLES
# Connection options of fieldtrip, hostname and port of the computer running the fieldtrip buffer.
hostname = 'localhost'
port = 1972
## init connection to the buffer
timeout = 5000
(ftc, hdr) = bufhelp.connect(hostname, port)
# Wait until the buffer connects correctly and returns a valid header
hdr = None
while hdr is None:
print(('Trying to connect to buffer on %s:%i ...' % (hostname, port)))
try:
ftc.connect(hostname, port)
print('\nConnected - trying to read header...')
hdr = ftc.getHeader()
except IOError:
pass
if hdr is None:
print('Invalid Header... waiting')
sleep(1)
def draw_enemies(enemies, screen):
"""Draw the enemies and the red line behind them"""
for enemy in enemies:
pygame.draw.line(screen, [155, 10, 10], [0, enemy.rect.center[1]], [screen_rect[0], enemy.rect.center[1]], 3)
enemies.draw(screen)
# Set up the game
screen = pygame.display.set_mode(RESOLUTION, DOUBLEBUF | NOFRAME)
screen_rect = screen.get_rect()
screen_rect = np.array([screen_rect.w, screen_rect.h])
clock = pygame.time.Clock()
keys = defaultdict(bool)
if not SIMULATION: bufhelp.connect()
score = n_shots = n_deaths = n_hits = 0
rect = screen.get_rect()
ship = ShipSprite()
ship_group = pygame.sprite.RenderPlain(ship)
controller = ProbablisticConroller(alpha=0.5*PREDICTION_TIME) if SIMULATION else PlayerController()
enemy_group = pygame.sprite.RenderPlain()
bullet_group = pygame.sprite.RenderPlain()
last_enemy_spawned = -ENEMY_SPAWN_TIME
ship_start_pos = 0
last_pred_time = 0
left = True
pygame.init()
font = pygame.font.Font(pygame.font.get_default_font(), 16)
lasttime = last_bullet_spawned = game_start_time = time.time()
#!/usr/bin/env python3
import sys, os
sys.path.append(
os.path.join(os.path.dirname(os.path.abspath(__file__)),
"../../dataAcq/buffer/python"))
sys.path.append("../signalProc")
import preproc
import bufhelp
#import linear
import pickle
bufhelp.connect()
trlen_ms = 600
run = True
print("Waiting for startPhase.cmd event.")
while run:
e = bufhelp.waitforevent("startPhase.cmd", 1000, True)
print("Got startPhase event: %s" % e)
if e is not None:
if e.value == "calibration":
print("Calibration phase")
data, events, stopevents = bufhelp.gatherdata(
"stimulus.tgtFlash",
trlen_ms, ("stimulus.training", "end"),
milliseconds=True)
pickle.dump({
"events": events,
"data": data
