nupic_anomaly_output.py 文件源码

def initializeLines(self, timestamp):
        print "initializing %s" % self.name
        anomalyRange = (0.0, 1.0)
        self.dates = deque([timestamp] * WINDOW, maxlen=WINDOW)
        self.convertedDates = deque(
            [date2num(date) for date in self.dates], maxlen=WINDOW
        )
        self.value = deque([0.0] * WINDOW, maxlen=WINDOW)
        self.rawValue = deque([0.0] * WINDOW, maxlen=WINDOW)
        self.predicted = deque([0.0] * WINDOW, maxlen=WINDOW)
        self.anomalyScore = deque([0.0] * WINDOW, maxlen=WINDOW)
        self.anomalyLikelihood = deque([0.0] * WINDOW, maxlen=WINDOW)

        actualPlot, = self._mainGraph.plot(self.dates, self.value)
        self.actualLine = actualPlot
        rawPlot, = self._mainGraph.plot(self.dates, self.rawValue)
        self.rawLine = rawPlot
        predictedPlot, = self._mainGraph.plot(self.dates, self.predicted)
        self.predictedLine = predictedPlot
        self._mainGraph.legend(tuple(['actual', 'raw', 'predicted']), loc=3)

        anomalyScorePlot, = self._anomalyGraph.plot(
            self.dates, self.anomalyScore, 'm'
        )
        anomalyScorePlot.axes.set_ylim(anomalyRange)

        self.anomalyScoreLine = anomalyScorePlot
        anomalyLikelihoodPlot, = self._anomalyGraph.plot(
            self.dates, self.anomalyScore, 'r'
        )
        anomalyLikelihoodPlot.axes.set_ylim(anomalyRange)
        self.anomalyLikelihoodLine = anomalyLikelihoodPlot
        self._anomalyGraph.legend(
            tuple(['anomaly score', 'anomaly likelihood']), loc=3
        )

        dateFormatter = DateFormatter('%H:%M:%S.%f')
        self._mainGraph.xaxis.set_major_formatter(dateFormatter)
        self._anomalyGraph.xaxis.set_major_formatter(dateFormatter)

        self._mainGraph.relim()
        self._mainGraph.autoscale_view(True, True, True)

        self.linesInitialized = True