def handle_message(self, mxmsg):
LOGGER.info("P300EtrDecision\n")
if mxmsg.type == types.ETR_ANALYSIS_RESULTS:
res = variables_pb2.Sample()
res.ParseFromString(mxmsg.message)
LOGGER.debug("GOT ETR ANALYSIS RESULTS: " + str(res.channels))
#self.conn.send_message(message = str(dec), type = types.DECISION_MESSAGE, flush=True)
elif mxmsg.type == types.P300_ANALYSIS_RESULTS:
res = variables_pb2.Sample()
res.ParseFromString(mxmsg.message)
LOGGER.debug("GOT P300 ANALYSIS RESULTS: " + str(res.channels))
#self.conn.send_message(message = str(dec), type = types.DECISION_MESSAGE, flush=True)
# Probabilty from etr
pdf_etr = np.random.random(8)
# Probability from p300
pdf_p300 = np.random.random(8)
# Hybryd probability
pdf = pdf_p300 * pdf_etr
# Assume pdf is T distribution
loc = pdf.mean()
scale = pdf.std()
cdf = st.t.cdf(pdf, len(pdf), loc=loc, scale=scale)
# If only one value is over threshold
if np.sum(cdf > self.tresholdValue) == 1:
dec = int(np.arange(len(cdf))[cdf > self.tresholdValue])
SEND_DECISION(dec)
self.no_response
def _send_results(self):
r = variables_pb2.Sample()
r.timestamp = time.time()
for i in range(8):
r.channels.append(random.random())
self.conn.send_message(message = r.SerializeToString(),
type = types.ETR_CALIBRATION_RESULTS, flush=True)
def handle_message(self, mxmsg):
if mxmsg.type == types.ETR_CALIBRATION_RESULTS:
res = variables_pb2.Sample()
res.ParseFromString(mxmsg.message)
data = res.channels
self.logger.debug("GOT ETR CALIBRATION RESULTS: " + str(data))
self.handle_calibration_mesage(data)
elif mxmsg.type == types.ETR_SIGNAL_MESSAGE:
l_msg = variables_pb2.Sample2D()
l_msg.ParseFromString(mxmsg.message)
self.logger.debug("GOT MESSAGE: " + str(l_msg))
dec, ugm = self.handle_etr_message(l_msg)
if dec >= 0:
self.logger.debug("Sending dec message...")
self.conn.send_message(message=str(dec),
type=types.DECISION_MESSAGE,
flush=True)
elif ugm is not None:
self.logger.debug("Sending ugm message...")
ugm_helper.send_config(self.conn, ugm, 1)
else:
self.logger.info("Got notihing from manager...")
self.no_response()
def handle_message(self, mxmsg):
#~ self.logger.info("EtrAnalysis\n")
if mxmsg.type == types.ETR_CALIBRATION_RESULTS:
#### What to do when receive ETR_MATRIX information
res = variables_pb2.Sample()
res.ParseFromString(mxmsg.message)
self.logger.debug("GOT ETR CALIBRATION RESULTS: "+str(res.channels))
#process blinks only when hold_time passed
if self._last_dec_time > 0:
t = time.time() - self._last_dec_time
if t > self.hold_after_dec:
self._last_dec_time = 0
else:
self.no_response()
return
# What to do after everything is done...
if mxmsg.type == types.DECISION_MESSAGE:
self._last_dec_time = time.time()
if mxmsg.type == types.ETR_SIGNAL_MESSAGE:
#### What to do when receive ETR_SIGNAL information
msg = variables_pb2.Sample2D()
msg.ParseFromString(mxmsg.message)
self.logger.debug("GOT MESSAGE: "+str(msg))
# Save positions
x, y = msg.x, msg.y
self._update_buffor(np.array([[x],[y]]))
# Turn position into heatmap
m = self._calc_metric(x,y)
self._update_heatmap(m)
ugm = self.ugm_mgr.get_ugm_updates(self.feeds, msg)
ugm_helper.send_config(self.conn, ugm, 1)
self.nCount += 1
if self.nCount % self.nRefresh == 0:
# Calc heatmap as probabilty density
pdf = self._calc_pdf()
# Send results to decision modul
self._send_results()
#~ elif mxmsg.type == types.BLINK_MESSAGE:
#### What to do when receive BLINK_NO information
#~ blink = variables_pb2.Blink()
#~ blink.ParseFromString(mxmsg.message)
#~ self.logger.debug("GOT BLINK: "+str(blink.index)+" / "+str(blink.timestamp))
self.no_response()
def _send_results(self):
"""
Sends results do decision making module.
"""
r = variables_pb2.Sample()
t.timestamp = time.time()
for i in range(8):
r.channels.append(random.random())
self.conn.send_message(message=r.SerializeToString(),
type=types.ETR_ANALYSIS_RESULTS,
flush=True)
def _send_results(self):
r = variables_pb2.Sample()
r.timestamp = time.time()
for val in self.invH.flatten().tolist():
r.channels.append(val)
self.logger.info("sending matrix: " +
str(self.invS.flatten().tolist()))
print "types.ETR_CALIBRATION_RESULTS: ", types.ETR_CALIBRATION_RESULTS
self.conn.send_message(message=r.SerializeToString(),
type=types.ETR_CALIBRATION_RESULTS,
flush=False)
def _send_results(self):
"""
Sends results do decision making module.
"""
pdf = self._getPdf()
# Flip pdf matrix
pdf = pdf.reshape((self.rows,self.cols))[:,::-1].flatten()
r = variables_pb2.Sample()
r.timestamp = time.time()
for i in range(self.areaCount):
r.channels.append(pdf[i])
self.conn.send_message(message = r.SerializeToString(), type = types.ETR_ANALYSIS_RESULTS, flush=True)
def send_decision(self, pdf):
"""Send dec message to the system (probably to LOGIC peer).
dec is of integer type."""
self.logger.info("Sending dec message: " + str(pdf))
#self.buffer.clear() dont do it in p300 - just ignore some blinks sometimes ...
r = variables_pb2.Sample()
r.timestamp = time.time()
for i in range(len(pdf)):
r.channels.append(pdf[i])
self.conn.send_message(message=r.SerializeToString(),
type=types.P300_ANALYSIS_RESULTS,
flush=True)
def send_results(self, results):
"""Send dec message to the system (probably to LOGIC peer).
dec is of integer type."""
LOGGER.info("Sending dec message: " + str(dec))
self._last_dec_time = time.time()
#self.buffer.clear() dont do it in p300 - just ignore some blinks sometimes ...
#self.buffer.clear_blinks()
#ugm_helper.send_stop_blinking(self.conn)
r = variables_pb2.Sample()
t.timestamp = time.time()
for i in range(8):
r.channels.append(results[i])
self.conn.send_message(message=r.SerializeToString(),
type=types.P300_ANALYSIS_RESULTS,
flush=True)
def handle_message(self, mxmsg):
LOGGER.info("EtrAnalysis\n")
if mxmsg.type == types.ETR_CALIBRATION_RESULTS:
#### What to do when receive ETR_MATRIX information
res = variables_pb2.Sample()
res.ParseFromString(mxmsg.message)
LOGGER.debug("GOT ETR CALIBRATION RESULTS: " + str(res.channels))
elif mxmsg.type == types.ETR_SIGNAL_MESSAGE:
#### What to do when receive ETR_SIGNAL information
l_msg = variables_pb2.Sample2D()
l_msg.ParseFromString(mxmsg.message)
LOGGER.debug("GOT MESSAGE: " + str(l_msg))
# Change shape of data
x, y = l_msg.x, l_msg.y
xy = np.array([[x], [y]])
self._update_buffor(xy)
# Caunt metric
m = self.metric(xy)
self._update_heatmap(m)
# Calc heatmap as probabilty density
pdf = self._calc_pdf()
##self.conn.send_message(message = str(dec), type = types.DECISION_MESSAGE, flush=True)
l_msg.ParseFromString(mxmsg.message)
LOGGER.debug("GOT MESSAGE: " + str(l_msg))
#zrob cos z sygnalem
elif mxmsg.type == types.BLINK_MESSAGE:
#### What to do when receive BLINK_NO information
blink = variables_pb2.Blink()
blink.ParseFromString(mxmsg.message)
LOGGER.debug("GOT BLINK: " + str(blink.index) + " / " +
str(blink.timestamp))
self.no_response()
def handle_message(self, mxmsg):
self.logger.debug("P300EtrDecision\n")
if mxmsg.type == types.ETR_ANALYSIS_RESULTS:
res = variables_pb2.Sample()
res.ParseFromString(mxmsg.message)
self.logger.debug("GOT ETR ANALYSIS RESULTS: " + str(res.channels))
self.pdf_etr = np.array(res.channels)
self.logger.debug("pdf_etr: " + str(self.pdf_etr))
#self.conn.send_message(message = str(dec), type = types.DECISION_MESSAGE, flush=True)
elif mxmsg.type == types.P300_ANALYSIS_RESULTS:
res = variables_pb2.Sample()
res.ParseFromString(mxmsg.message)
self.logger.debug("GOT P300 ANALYSIS RESULTS: " +
str(res.channels))
self.pdf_p300 = np.array(res.channels)
# Probabilty from etr
pdf_etr = self.pdf_etr
# Probability from p300
pdf_p300 = self.pdf_p300
# Hybryd probability
pdf = self.alpha * pdf_etr + (1. - self.alpha) * pdf_p300
pdf *= 0.01
# Debugging leftouts...
self.logger.debug("pdf_etr: " + str(pdf_etr))
self.logger.debug("pdf_p300: " + str(pdf_p300))
self.logger.debug("pdf: " + str(pdf))
dec = -1
# If both interfaces return significant value
if (pdf > self.thresholdPercent).sum() == 1:
dec = int(np.arange(self.cols * self.rows)[pdf == pdf.max()])
self.logger.info("Dec: " + str(dec))
# If only P300 declares significant and all ETR values are highly insignificant
elif ((pdf_p300 > self.p300Tr).sum()
== 1) and (pdf_etr < self.etrTr).all():
dec = int(
np.arange(self.cols *
self.rows)[pdf_p300 == pdf_p300.max()])
self.logger.info("Dec (only p300): " + str(dec))
# If only ETR declares significant and all P300 values are highly insignificant
elif (pdf_p300 < self.p300Tr).all() and (
(pdf_etr > self.etrTr).sum() == 1):
dec = int(
np.arange(self.cols * self.rows)[pdf_etr == pdf_etr.max()])
self.logger.info("Dec (only etr): " + str(dec))
# If decision is to be made
if dec != -1:
self.conn.send_message(message=str(dec),
type=types.DECISION_MESSAGE,
flush=True)
self.no_response()