예제 #1
0
    def plotStatistics(self, output_file):

        p = stats.statRemoveNum(np.array(self.param), self.missingValue)
        a = p - np.mean(p)
        pmin = p.min()
        pmax = p.max()
        amin = a.min()
        amax = a.max()
        abins = np.linspace(amin, amax, 50)
        bins = np.linspace(pmin, pmax, 50)
        hist = np.empty((len(bins) - 1, self.maxCell))
        ahist = np.empty((len(abins) - 1, self.maxCell))
        x = np.arange(11)
        alpha = np.empty((11, self.maxCell))
        aalpha = np.empty((11, self.maxCell))

        for i in xrange(self.maxCell + 1):
            p = self.extractParameter(i, 0)
            a = p - np.mean(p)
            hist[:, i - 1], b = np.histogram(p, bins, normed=True)
            ahist[:, i - 1], b = np.histogram(a, abins, normed=True)
            alpha[:, i - 1] = acf(p, 10)
            aalpha[:, i - 1] = acf(a, 10)

        mhist = np.mean(hist, axis=1)
        uhist = percentile(hist, per=95, axis=1)
        lhist = percentile(hist, per=5, axis=1)

        mahist = np.mean(ahist, axis=1)
        uahist = percentile(ahist, per=95, axis=1)
        lahist = percentile(ahist, per=5, axis=1)

        malpha = np.mean(alpha, axis=1)
        ualpha = percentile(alpha, per=95, axis=1)
        lalpha = percentile(alpha, per=5, axis=1)

        maalpha = np.mean(aalpha, axis=1)
        uaalpha = percentile(aalpha, per=95, axis=1)
        laalpha = percentile(aalpha, per=5, axis=1)

        fig = RangeCurve()
        fig.add(bins[:-1], mhist, uhist, lhist, "Values", "Probability", "")
        fig.add(abins[:-1], mahist, uahist, lahist, "Anomalies", "Probability",
                "")
        fig.add(x, malpha, ualpha, lalpha, "Lag", "Autocorrelation",
                "ACF of values")
        fig.add(x, maalpha, uaalpha, laalpha, "Lag", "Autocorrelation",
                "ACF of anomalies")
        fig.plot()

        saveFigure(fig, output_file + '.png')
예제 #2
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    def plotStatistics(self, output_file):

        p = stats.statRemoveNum(np.array(self.param), self.missingValue)
        a = p - np.mean(p)
        pmin = p.min()
        pmax = p.max()
        amin = a.min()
        amax = a.max()
        abins = np.linspace(amin, amax, 50)
        bins = np.linspace(pmin, pmax, 50)
        hist = np.empty((len(bins) - 1, self.maxCell))
        ahist = np.empty((len(abins) - 1, self.maxCell))
        x = np.arange(11)
        alpha = np.empty((11, self.maxCell))
        aalpha = np.empty((11, self.maxCell))

        for i in xrange(self.maxCell + 1):
            p = self.extractParameter(i, 0)
            a = p - np.mean(p)
            hist[:, i - 1], b = np.histogram(p, bins, normed=True)
            ahist[:, i - 1], b = np.histogram(a, abins, normed=True)
            alpha[:, i - 1] = acf(p, 10)
            aalpha[:, i - 1] = acf(a, 10)

        mhist = np.mean(hist, axis=1)
        uhist = percentile(hist, per=95, axis=1)
        lhist = percentile(hist, per=5, axis=1)

        mahist = np.mean(ahist, axis=1)
        uahist = percentile(ahist, per=95, axis=1)
        lahist = percentile(ahist, per=5, axis=1)

        malpha = np.mean(alpha, axis=1)
        ualpha = percentile(alpha, per=95, axis=1)
        lalpha = percentile(alpha, per=5, axis=1)

        maalpha = np.mean(aalpha, axis=1)
        uaalpha = percentile(aalpha, per=95, axis=1)
        laalpha = percentile(aalpha, per=5, axis=1)
        
        fig = RangeCurve()
        fig.add(bins[:-1], mhist, uhist, lhist, "Values", "Probability", "")
        fig.add(abins[:-1], mahist, uahist, lahist, "Anomalies", "Probability", "")
        fig.add(x, malpha, ualpha, lalpha, "Lag", "Autocorrelation", "ACF of values")
        fig.add(x, maalpha, uaalpha, laalpha, "Lag", "Autocorrelation", "ACF of anomalies")
        fig.plot()

        saveFigure(fig, output_file + '.png')
예제 #3
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    def plot(self):

        figure = RangeCompareCurve()
        figure.set_size_inches(8,3)
        xlab = "Gate number"
        ylab = "Landfall probability"
        
        x = np.arange(len(self.gates) - 1)

        figure.add(x, self.historicLandfall, self.synMeanLandfall,
                   self.synUpperLF, self.synLowerLF,
                   xlab, ylab, "Landfall")

        ylab = "Offshore probability"
        figure.add(x, self.historicOffshore, self.synMeanOffshore,
                   self.synUpperOF, self.synLowerOF,
                   xlab, ylab, "Offshore")

        figure.plot()
        outputFile = pjoin(self.plotPath, 'landfall_rates.png')
        saveFigure(figure, outputFile)
예제 #4
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    def plot(self):
        """
        Plot the results and save to file.

        """

        figure = RangeCompareCurve()
        figure.set_size_inches(8, 3)
        xlab = "Gate number"
        ylab = "Landfall probability"

        x = np.arange(len(self.gates) - 1)

        figure.add(x, self.historicLandfall, self.synMeanLandfall,
                   self.synUpperLF, self.synLowerLF, xlab, ylab, "Landfall")

        ylab = "Offshore probability"
        figure.add(x, self.historicOffshore, self.synMeanOffshore,
                   self.synUpperOF, self.synLowerOF, xlab, ylab, "Offshore")

        figure.plot()
        outputFile = pjoin(self.plotPath, 'landfall_rates.png')
        saveFigure(figure, outputFile)