Esempio n. 1
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    def plot(self, overplot=False, clearwindow=True):
        default_color = self.histo_prefs['linecolor']
        count = 0
        for xlo, xhi, y, color in izip(self.xlo, self.xhi, self.y, self.colors):
            if count != 0:
                overplot=True
                self.histo_prefs['linecolor']=color
            Histogram.plot(self, xlo, xhi, y, title=self.title,
                           xlabel=self.xlabel, ylabel=self.ylabel,
                           overplot=overplot, clearwindow=clearwindow)
            count += 1

        self.histo_prefs['linecolor'] = default_color
Esempio n. 2
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    def plot(self, overplot=False, clearwindow=True):
        xlo = self.xlo
        xhi = self.xhi
        y = self.y

        if self.mask is not None:
            xlo = self.xlo[self.mask]
            xhi = self.xhi[self.mask]
            y = self.y[self.mask]

        Histogram.plot(self, xlo, xhi, y, title=self.title,
                       xlabel=self.xlabel, ylabel=self.ylabel,
                       overplot=overplot, clearwindow=clearwindow)
Esempio n. 3
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    def plot(self, overplot=False, clearwindow=True, **kwargs):
        default_color = self.histo_prefs['linecolor']
        count = 0
        for xlo, xhi, y, color in \
                zip(self.xlo, self.xhi, self.y, self.colors):
            if count != 0:
                overplot = True
                self.histo_prefs['linecolor'] = color

            # Note: the user settings are sent to each plot
            Histogram.plot(self,
                           xlo,
                           xhi,
                           y,
                           title=self.title,
                           xlabel=self.xlabel,
                           ylabel=self.ylabel,
                           overplot=overplot,
                           clearwindow=clearwindow,
                           **kwargs)
            count += 1

        self.histo_prefs['linecolor'] = default_color
Esempio n. 4
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edges = np.asarray([-10, -5, 5, 12, 17, 20, 30, 56, 60])
y = np.asarray([28, 62, 17, 4, 2, 4, 125, 55])

from sherpa.data import Data1DInt
d = Data1DInt('example histogram', edges[:-1], edges[1:], y)

from sherpa.plot import DataPlot
dplot = DataPlot()
dplot.prepare(d)
dplot.plot()

savefig('dataplot_histogram.png')

from sherpa.plot import Histogram
hplot = Histogram()
hplot.overplot(d.xlo, d.xhi, d.y)

savefig('dataplot_histogram_overplot.png')

from sherpa.models.basic import Const1D, Gauss1D
mdl = Const1D('base') - Gauss1D('line')
mdl.pars[0].val = 10
mdl.pars[1].val = 25
mdl.pars[2].val = 22
mdl.pars[3].val = 10
report("mdl")

from sherpa.plot import ModelPlot
mplot = ModelPlot()
mplot.prepare(d, mdl)