def setUp(self):
self.chain = SignalProcessor()
self.qualUtil = QualityUtil()
config = ConfigProvider().getProcessingConfig()
self.upperBound = config.get("upperBound")
self.lowerBound = config.get("lowerBound")
self.minQuality = config.get("minQual")
self.maxNaNValues = config.get("maxNaNValues")
class ProcessedSignalPlotter(RawSignalPlotter):
def __init__(self, person, eegData, signals, filePath, save=True, plot=True, logScale=False):
RawSignalPlotter.__init__(self, person, eegData, signals, filePath, save, plot, logScale, name="processed")
self.chain = SignalProcessor()
def _getData(self, signal):
raw = self.eegData.getColumn(signal)
qual = self.eegData.getQuality(signal)
raw, _ = self.chain.process(raw, qual)
return raw
class DeltaSignalPlotter(RawSignalPlotter):
def __init__(self, person, eegData, signals, filePath, save=True, plot=True, logScale=False):
RawSignalPlotter.__init__(self, person, eegData, signals, filePath, save, plot, logScale, name="delta")
self.chain = SignalProcessor()
self.eegUtil = EEGUtil()
def _getData(self, signal):
raw = self.eegData.getColumn(signal)
qual = self.eegData.getQuality(signal)
samplingRate = self.eegData.getSamplingRate()
proc, _ = self.chain.process(raw, qual)
proc = QualityUtil().replaceNans(proc)
return self.eegUtil.getDeltaWaves(proc, samplingRate)
def __init__(self, inputQueue, outputQueue):
config = ConfigProvider()
self.eegFields = config.getEmotivConfig()["eegFields"]
self.gyroFields = config.getEmotivConfig()["gyroFields"]
self.samplingRate = config.getEmotivConfig()["samplingRate"]
self.processingConfig = config.getProcessingConfig()
self.preProcessor = SignalPreProcessor()
self.signalProcessor = SignalProcessor()
self.fftProcessor = FFTProcessor()
self.inputQueue = inputQueue
self.outputQueue = outputQueue
self.runProcess = True
self.totalInvalid = 0
self.totalCount = 0
class DataProcessor(object):
def __init__(self, inputQueue, outputQueue):
config = ConfigProvider()
self.eegFields = config.getEmotivConfig()["eegFields"]
self.gyroFields = config.getEmotivConfig()["gyroFields"]
self.samplingRate = config.getEmotivConfig()["samplingRate"]
self.processingConfig = config.getProcessingConfig()
self.preProcessor = SignalPreProcessor()
self.signalProcessor = SignalProcessor()
self.fftProcessor = FFTProcessor()
self.inputQueue = inputQueue
self.outputQueue = outputQueue
self.runProcess = True
self.totalInvalid = 0
self.totalCount = 0
def close(self):
self.runProcess = False
def processData(self):
while self.runProcess:
try:
data = self.inputQueue.get(timeout=1)
procData, procInvalid = self.process(data)
if not procInvalid:
self.outputQueue.put(procData)
except Empty:
pass
def process(self, data):
#TODO make me fast and nice
eegRaw, gyroRaw = self.splitData(data)
eegProc, eegInvalid = self.processEEGData(eegRaw)
gyroProc, gyroIvalid = self.processGyroData(gyroRaw)
eegProc.update(gyroProc)
return eegProc, (eegInvalid or gyroIvalid)
def splitData(self, data):
'''split eeg and gyro data
:param data: all values as dict
:return:
eegData: eeg values as dict
gyroData: gyro values as dict
'''
#TODO handle data except eeg and gyro?
eegData = {x: data[x] for x in data if x in self.eegFields}
gyroData = {x: data[x] for x in data if x in self.gyroFields}
return eegData, gyroData
def processEEGData(self, eegData):
invalidCount = 0
for _, signal in eegData.iteritems():
raw = array(signal["value"])
quality = array(signal["quality"])
proc = self.preProcessor.process(raw)
proc, _ = self.signalProcessor.process(proc, quality)
chan, fInvalid = self.fftProcessor.process(proc)
signal["theta"] = chan["theta"]
invalidCount += sum([fInvalid])
if invalidCount > 0:
self.totalInvalid += 1
self.totalCount += 1
return eegData, (invalidCount > 0)
def processGyroData(self, gyroData):
return gyroData, False
class TestSimpleChain(unittest.TestCase):
def setUp(self):
self.chain = SignalProcessor()
self.qualUtil = QualityUtil()
config = ConfigProvider().getProcessingConfig()
self.upperBound = config.get("upperBound")
self.lowerBound = config.get("lowerBound")
self.minQuality = config.get("minQual")
self.maxNaNValues = config.get("maxNaNValues")
def _checkValidData(self, data, invalid):
self.assertEqual(invalid, self.maxNaNValues < count_nonzero(isnan(data)))
def test_process_sunshine(self):
data = [-2.0, -1.0, 0, 1.0, 2.0]
qual = [15, 15, 15, 15, 15]
proc, invalidData = self.chain.process(data, qual)
self._checkValidData(proc, invalidData)
assert_allclose(proc, [-1.0, -0.5, 0, 0.5, 1])
def test_process_badQuality(self):
data = [-2.0, -1.0, 0, 1.0, 2.0]
qual = [15, 0, self.minQuality-1, self.minQuality, self.minQuality+1]
proc, invalidData = self.chain.process(data, qual)
self._checkValidData(proc, invalidData)
assert_allclose(proc, [-1.0, NaN, NaN, 0.5, 1])
def test_process_replaceSequences(self):
data = [1.0, 1.0, 1.0, 1.0, 1.0, 2.0, 4.0]
qual = [15, 15,15, 15, 15, 15, 15]
proc, invalidData = self.chain.process(data, qual)
self._checkValidData(proc, invalidData)
assert_allclose(proc, [NaN, NaN, NaN, NaN, NaN, 0.5, 1.0])
def test_process_replaceOutliners(self):
data = [-5000, self.lowerBound-1, self.lowerBound, self.lowerBound+1, self.upperBound-1, self.upperBound, self.upperBound+1, 5000]
qual = [15, 15, 15, 15, 15, 15, 15, 15]
proc, invalidData = self.chain.process(data, qual)
self._checkValidData(proc, invalidData)
self.assertEquals(count_nonzero(isnan(proc)), 4)
def test_process_allTogether(self):
data = [3.0, 1.0, 1.0, 1.0, 1.0, 1.0, self.lowerBound-1, self.upperBound+1, -8, -4.0, 2.0, 4.0]
cp = copy(data[:])
qual = [self.minQuality-1, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15]
proc, invalidData = self.chain.process(data, qual)
self._checkValidData(proc, invalidData)
#make sure we work on copies only
assert_allclose(cp, data)
assert_allclose(proc, [NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, -1.0, -0.5, 0.25, 0.5])
def test_checkValid(self):
maxNaNValues = self.maxNaNValues
for length in range(0, maxNaNValues+1):
data = self._getNaNList(length)
qual = [15]*length
_, invalidData = self.chain.process(data, qual)
self.assertFalse(invalidData, "length %d" % length)
for length in range(maxNaNValues+1, maxNaNValues+5):
data = self._getNaNList(length)
qual = [15]*length
_, invalidData = self.chain.process(data, qual)
self.assertTrue(invalidData, "length %d" % length)
def _getNaNList(self, length):
return array([NaN]*length)
def __init__(self, person, eegData, signals, filePath, save=True, plot=True, logScale=False):
RawSignalPlotter.__init__(self, person, eegData, signals, filePath, save, plot, logScale, name="processed")
self.chain = SignalProcessor()
