def _updateRanges(self):
tree = self.data.tree()
n = tree.Draw(self.x.GetName(), '', 'goff')
mi = ModalInterval(n, tree.GetV1())
if self.doAutoXRange:
## Determine the range as a modal interval
if self.xRangeMode == 'SigmaLevel':
mi.setSigmaLevel(self.xRangeSigmaLevel)
elif self.xRangeMode == 'Fraction':
mi.setFraction(self.xRangeFraction)
elif self.xRangeMode == 'NumberOfEntries':
mi.setNumberOfEntriesToCover(self.xRangeNumberOfEntries)
else:
message = "Illegal xRangeMode = '%s'" % self.xRangeMode
raise RuntimeError, message
xmargin = 0.1 * mi.length()
self.xRange = (mi.lowerBound() - xmargin,
mi.upperBound() + xmargin)
else:
## If possible, shrink the range to cover the data plus a margin
mi.setFraction(1.)
xlo = mi.lowerBound()
xhi = mi.upperBound()
xmargin = 0.1 * mi.length()
self.xRange = (max(xlo - xmargin, self.xRange[0]),
min(xhi + xmargin, self.xRange[1]))
if self.doAutoXRangeZoom:
mi.setSigmaLevel(self.xRangeSigmaLevelZoom)
self.xRangeZoom = tuple(mi.bounds())
if self.doAutoFitRange:
## Determine the range as a modal interval
if self.fitRangeMode == 'SigmaLevel':
mi.setSigmaLevel(self.fitRangeSigmaLevel)
elif self.fitRangeMode == 'Fraction':
mi.setFraction(self.fitRangeFraction)
elif self.fitRangeMode == 'NumberOfEntries':
mi.setNumberOfEntriesToCover(self.fitRangeNumberOfEntries)
print "setting fit range number of entries:", mi.bounds()
else:
message = "Illegal fitRangeMode = '%s'" % self.fitRangeMode
raise RuntimeError, message
self.fitRange = tuple(mi.bounds())
print "++++ fit range changed to:", self.fitRange
def _updateRanges(self):
tree = self.data.tree()
n = tree.Draw(self.x.GetName(), '', 'goff')
mi = ModalInterval(n, tree.GetV1())
if self.doAutoXRange:
## Determine the range as a modal interval
if self.xRangeMode == 'SigmaLevel':
mi.setSigmaLevel(self.xRangeSigmaLevel)
elif self.xRangeMode == 'Fraction':
mi.setFraction(self.xRangeFraction)
elif self.xRangeMode == 'NumberOfEntries':
mi.setNumberOfEntriesToCover(self.xRangeNumberOfEntries)
else:
message = "Illegal xRangeMode = '%s'" % self.xRangeMode
raise RuntimeError, message
xmargin = 0.1 * mi.length()
self.xRange = (mi.lowerBound() - xmargin,
mi.upperBound() + xmargin)
else:
## If possible, shrink the range to cover the data plus a margin
mi.setFraction(1.)
xlo = mi.lowerBound()
xhi = mi.upperBound()
xmargin = 0.1 * mi.length()
self.xRange = (max(xlo - xmargin, self.xRange[0]),
min(xhi + xmargin, self.xRange[1]))
if self.doAutoXRangeZoom:
mi.setSigmaLevel(self.xRangeSigmaLevelZoom)
self.xRangeZoom = tuple(mi.bounds())
if self.doAutoFitRange:
## Determine the range as a modal interval
if self.fitRangeMode == 'SigmaLevel':
mi.setSigmaLevel(self.fitRangeSigmaLevel)
elif self.fitRangeMode == 'Fraction':
mi.setFraction(self.fitRangeFraction)
elif self.fitRangeMode == 'NumberOfEntries':
mi.setNumberOfEntriesToCover(self.fitRangeNumberOfEntries)
print "setting fit range number of entries:", mi.bounds()
else:
message = "Illegal fitRangeMode = '%s'" % self.fitRangeMode
raise RuntimeError, message
self.fitRange = tuple(mi.bounds())
print "++++ fit range changed to:", self.fitRange
self.pullRange = getattr(self, self.pullRangeMode)
self.residRange = getattr(self, self.residRangeMode)
import ROOT
from JPsi.MuMu.common.modalinterval import ModalInterval
from JPsi.MuMu.vector import vector
## Configuration
nSigmaCoverage = 1.
mean = 0.
sigma = 1.
n = 100000
## Get some toy data
print ("Sampling Gaussian PDF with mean=%g and sigma=%g "
"%d times..." % (mean, sigma, n))
data = vector('double')()
data.reserve(n)
for i in range(n):
data.push_back(ROOT.gRandom.Gaus(0,1))
## Create the ModalInterval object
mi = ModalInterval(data)
## Pring the full range of toy data
mi.setFraction(1.)
print "\nShortest interval covering all data:"
print "[%f, %f]" % tuple(mi.bounds())
## Print the range corresponding to n effective sigma
print "\nRange corresponding to +/-%g effective sigma:" % nSigmaCoverage
mi.setSigmaLevel(nSigmaCoverage)
print "[%f, %f]" % tuple(mi.bounds())
