class SignalStatisticUtil(object):
'''
class to show some statistical values for a channel
'''
def __init__(self, person, filePath, signals=None, save=True, plot=True, logScale=False):
self.person = person
self.filePath = filePath
self._initStatsDict()
self._readData()
self._initSignals(signals)
self.su = SignalUtil()
self.qu = QualityUtil()
self.eu = EEGUtil()
self._initFields()
self.save = save
self._initPlotter(person, plot, logScale)
self.ssPrint = SignalStatisticPrinter(person)
self.preProcessor = SignalPreProcessor()
self.processor = SignalProcessor()
self.windowSize = ConfigProvider().getCollectorConfig().get("windowSize")
def _initStatsDict(self):
self.stats = OrderedDict()
self.stats[GENERAL_KEY] = OrderedDict()
self.stats[SIGNALS_KEY] = OrderedDict()
def _readData(self):
self.reader = EEGTableFileUtil()
self.eegData = self.reader.readFile(self.filePath)
def _initSignals(self, signals):
if not signals:
signals = ConfigProvider().getEmotivConfig().get("eegFields")
self.signals = signals
def _initFields(self):
self.statFields = STAT_FIELDS
self.statFields["max"][METHOD] = self.su.maximum
self.statFields["min"][METHOD] = self.su.minimum
self.statFields["mean"][METHOD] = self.su.mean
self.statFields["std"][METHOD] = self.su.std
self.statFields["var"][METHOD] = self.su.var
self.statFields["zeros"][METHOD] = self.qu.countZeros
self.statFields["seq"][METHOD] = self.qu.countSequences
self.statFields["out"][METHOD] = self.qu.countOutliners
self.statFields["nrgy"][METHOD] = self.su.energy
self.statFields["zcr"][METHOD] = self.su.zcr
def _initPlotter(self, person, plot, logScale):
self.plotter = []
for clazz in PLOTTER:
plotter = clazz(person, self.eegData, self.signals, self.filePath, self.save, plot, logScale)
thread = multiprocessing.Process(target=plotter.doPlot)
self.plotter.append(thread)
def main(self):
self.doPlot()
self.collect_stats()
self.printStats()
def doPlot(self):
for thread in self.plotter:
thread.start()
def collect_stats(self):
self.collectGeneralStats()
for signal in self.signals:
self.stats[SIGNALS_KEY][signal] = {}
self.collectRawStats(signal)
def collectGeneralStats(self):
self._addGeneralStatValue("file path", self.filePath)
self._addGeneralStatValue("sampleRate", ("%f.2" % self.eegData.getSamplingRate()))
self._addGeneralStatValue("dataLength", ("%d" % self.eegData.len))
self._addGeneralStatValue("bound", ("%d - %d" % (self.qu.lowerBound, self.qu.upperBound)))
self._addGeneralTimeStat("start time", "getStartTime", TIME_FORMAT_STRING)
self._addGeneralTimeStat("end time", "getEndTime", TIME_FORMAT_STRING)
self._addGeneralTimeStat("duration", "getDuration", DURATION_FORMAT_STRING)
def _addGeneralTimeStat(self, name, method, formatString):
time = getattr(self.eegData, method)()
value = self._buildFormattedTime(time, formatString)
self._addGeneralStatValue(name, value)
def _buildFormattedTime(self, time, formatString):
value = datetime.fromtimestamp(time).strftime(formatString)
return value
def _addGeneralStatValue(self, name, value):
self.stats[GENERAL_KEY][name] = value
def collectRawStats(self, signal):
data = self.eegData.getColumn(signal)
self._collectSignalStat(signal, RAW_KEY, data)
def _collectSignalStat(self, signal, category, data):
self.stats[SIGNALS_KEY][signal][category] = OrderedDict()
for field, attributes in self.statFields.iteritems():
fieldValues = []
for window in self.getWindows(data):
fieldValues.append(self._getSignalStat(signal, category, field, attributes["method"], window, 0))
merged = self._mergeValues(fieldValues, field)
self._addSignalStatValue(signal, category, field, merged)
def getWindows(self, raw):
windows = []
for start in range(0, len(raw), self.windowSize / 2):
end = start + self.windowSize
if end <= len(raw):
windows.append(raw[start:end])
return windows
def _getSignalStat(self, signal, category, name, method, raw, decPlace=2):
return method(raw)
def _addSignalStatValue(self, signal, category, name, value):
self.stats[SIGNALS_KEY][signal][category][name] = value
def _mergeValues(self, values, field):
typ = self.statFields[field][TYPE]
if typ == MAX_TYPE:
return nanmax(values)
if typ == MIN_TYPE:
return nanmin(values)
if typ == AGGREGATION_TYPE:
return nansum(values)
if typ == MEAN_TYPE:
return nanmean(values)
if typ == DIFF_TYPE:
return nanmean(values)
def setStats(self, stats):
self.stats = stats
def printStats(self):
content = self.ssPrint.getSignalStatsString(self.stats)
print content
if self.save:
filePath = getNewFileName(self.filePath, "txt", "_stats")
self.ssPrint.saveStats(filePath, content)
class TestEEGTableFileUtil(unittest.TestCase):
def setUp(self):
self.reader = EEGTableFileUtil()
def test_readData(self):
file_path = PATH + "example_32.csv"
if os.path.isfile(file_path):
self.reader.readData(file_path)
else:
print "'%s' not found" % file_path
def test_readHeader(self):
file_path = PATH + "example_32.csv"
if os.path.isfile(file_path):
self.reader.readHeader(file_path)
else:
print "'%s' not found" % file_path
def test_readFile(self):
file_path = PATH + "example_32.csv"
if os.path.isfile(file_path):
self.reader.readFile(file_path)
else:
print "'%s' not found" % file_path
def test_writeFile(self):
filePath = PATH + "test.csv"
header= ["A", "B", "C"]
data = np.array([[1.123456789, 2, 3], [-4.123456789, 5, 6], [7.123456789, 8, 99.123]])
self.reader.writeFile(filePath, data, header)
if os.path.isfile(filePath):
read = self.reader.readFile(filePath)
for i in range(len(data)):
for j in range(len(data[i])):
self.assertAlmostEqual(data[i, j], read.data[i, j], delta= 0.001)
removeFile(filePath)
def test_writeStructredFile(self):
filePath = PATH + "test_structured.csv"
data = {
"A": {
"value": [1, 2, 3],
"quality": [-1, -1, -1]
},
"B": {
"value": [4, 5, 6],
"quality": [-2, -2, -2]
},
"C": {
"value": [7, 8, 9],
"quality": [-3, -3, -3]
}
}
self.reader.writeStructredFile(filePath, data)
if os.path.isfile(filePath):
read = self.reader.readFile(filePath)
for key, values in data.iteritems():
self.assertTrue(sameEntries(values["value"], read.getColumn(key)))
removeFile(filePath)
def test_readFile_NaNValues(self):
eegData = self.reader.readFile(PATH + "example_32_empty.csv")
emptyCol = eegData.getColumn("Y")
self.assertTrue(np.isnan(emptyCol).any())
nonEmptyCol = eegData.getColumn("F3")
self.assertFalse(np.isnan(nonEmptyCol).any())
def test_readFile_SeparatorFallback(self):
eegData = self.reader.readFile(PATH + "example_32_empty.csv")
semicolonData = eegData.getColumn("F3")
eegData = self.reader.readFile(PATH + "example_32_comma.csv")
commaData = eegData.getColumn("F3")
self.assertTrue((semicolonData == commaData).all())
