class SignalProcessor(object):
def __init__(self, verbose=False):
config = ConfigProvider().getProcessingConfig()
self.maxNaNValues = config.get("maxNaNValues")
self.lowerBound = config.get("lowerBound")
self.upperBound = config.get("upperBound")
self.normalize = config.get("normalize")
self.mean = config.get("mean")
self.samplingRate = ConfigProvider().getEmotivConfig().get(
"samplingRate")
self.windowSeconds = ConfigProvider().getCollectorConfig().get(
"windowSeconds")
self.qualUtil = QualityUtil()
self.sigUtil = SignalUtil()
self.verbose = verbose
def process(self, raw, quality):
# remove outliners
proc = self.qualUtil.replaceOutliners(raw, NaN)
# too much outliners?
if self.qualUtil.isInvalidData(proc, len(raw) / self.windowSeconds):
return None, True
# center signal (mean = 0)
#proc = self.sigUtil.center(proc, self.mean)
# normalize date between -1 and 1
#proc = self.sigUtil.normalize(proc)
# replace Nans with zero (for fft)
proc = self.qualUtil.replaceNans(proc)
return proc, False
def __init__(self, verbose=False):
config = ConfigProvider().getProcessingConfig()
self.maxNaNValues = config.get("maxNaNValues")
self.lowerBound = config.get("lowerBound")
self.upperBound = config.get("upperBound")
self.normalize = config.get("normalize")
self.samplingRate = ConfigProvider().getEmotivConfig().get("samplingRate")
self.qualUtil = QualityUtil()
self.sigUtil = SignalUtil()
self.verbose = verbose
def __init__(self, verbose=False):
self.samplingRate = ConfigProvider().getEmotivConfig().get(
"samplingRate")
self.qualUtil = QualityUtil()
self.fftUtil = FFTUtil()
self.eegUtil = EEGUtil()
self.verbose = verbose
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 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 SignalProcessor(object):
def __init__(self, verbose=False):
config = ConfigProvider().getProcessingConfig()
self.maxNaNValues = config.get("maxNaNValues")
self.lowerBound = config.get("lowerBound")
self.upperBound = config.get("upperBound")
self.normalize = config.get("normalize")
self.samplingRate = ConfigProvider().getEmotivConfig().get("samplingRate")
self.qualUtil = QualityUtil()
self.sigUtil = SignalUtil()
self.verbose = verbose
def process(self, raw, quality):
proc = self.qualUtil.replaceOutliners(raw, 0)
proc = self.sigUtil.normalize(proc, self.normalize)
invalid = self.qualUtil.isInvalidData(proc)
return proc, invalid
def __init__(self):
self.mneUtil = MNEUtil()
config = ConfigProvider().getProcessingConfig()
self.lowerFreq = config.get("lowerFreq")
self.upperFreq = config.get("upperFreq")
self.windowSeconds = ConfigProvider().getCollectorConfig().get(
"windowSeconds")
self.resampleFreq = config.get("resamplingRate")
self.eegFields = ConfigProvider().getEmotivConfig().get("eegFields")
self.si = SignalUtil()
self.qu = QualityUtil()
self.eog = EOGExtractor()
class FFTProcessor(object):
def __init__(self, verbose=False):
self.samplingRate = ConfigProvider().getEmotivConfig().get("samplingRate")
self.qualUtil = QualityUtil()
self.fftUtil = FFTUtil()
self.eegUtil = EEGUtil()
self.verbose = verbose
def process(self, proc):
fft = self.fftUtil.fft(proc)
chan = self.eegUtil.getChannels(fft)
invalid = self.qualUtil.isInvalidData(fft)
return chan, invalid
def __init__(self, queue, filePath, signals=None, save=True, plot=True, logScale=False, name=""):
self.queue = queue
self.filePath = filePath
self._initStatsDict()
self.config = ConfigProvider()
self.eegData = FileUtil().getDto(filePath)
self._initSignals(signals)
self.su = SignalUtil()
self.qu = QualityUtil()
self.eu = EEGUtil()
self.fft = FFTUtil()
self._initFields()
self.save = save
self.plot = plot
self.name = name
self._initPlotter(logScale)
self.ssPrint = SignalStatisticPrinter(filePath)
self.preProcessor = SignalPreProcessor()
self.processor = SignalProcessor()
windowSeconds = self.config.getCollectorConfig().get("windowSeconds")
self.windowSize = EEGDataCollector.calcWindowSize(windowSeconds, self.eegData.samplingRate)