GenDecay: GenDecay::beta::Spectra Class Reference

def GenDecay::beta::Spectra::__init__	(	self,
		z,
		a
	)

Create Spectra for given ground state isotope of given Z and A.

Definition at line 8 of file beta.py.

00010                           :
00011         '''
00012         Create Spectra for given ground state isotope of given Z and A.
00013         '''
00014         import random
00015         self.random = random.Random()
00016 
00017         from g4data import G4RadData
00018         rd = G4RadData()
00019         rd = G4RadData()
00020         self.nuc = rd.nuclideData(z,a)
00021         state = self.nuc.excitedState()
00022 
00023         betas = []
00024         for dk in state.decays:
00025             if dk.type[0:4] == 'Beta':
00026                 betas.append(dk)
00027                 continue
00028             continue
00029 
00030         if not betas:
00031             print 'Warning: no beta decays for: %s'%nuc
00032             return
00033 
00034         self.betas = betas
        return

def GenDecay::beta::Spectra::modeledSpectra	(	self,
		nbins = `100`
	)

Definition at line 35 of file beta.py.

00037                                       :
00038         total_fraction = sum([dk.fraction for dk in self.betas])
00039         maximum = max([dk.radiation.endpoint for dk in self.betas])
00040 
00041         ret = []
00042         from numpy import array
00043         total = array([0.0 for x in range(nbins)])
00044         bins = [(x+0.5)*maximum/nbins for x in range(nbins)]
00045         for dk in self.betas:
00046             ratio = dk.fraction/total_fraction
00047             Sm = []
00048             Sm = map(dk.radiation.dnde,bins)
00049             scaled = [ratio*x for x in Sm]
00050             total += scaled
00051             ret.append(scaled)
00052             continue
        return (ret,bins,total)

def GenDecay::beta::Spectra::sampledSpectra	(	self,
		ndecays = `1000`,
		nbins = `100`
	)

Return a list of tuples (decay.BetaDecay,numpy.histogram).
Each histogram has the given number of bins and gives the
sampled energy spectrum.  The total number of entries of all
histograms is as given.  The branching fractions of the decay
are used to divide up the total number of decays when sampling
each branch.  Histograms are normalized so their sum is 1 and
keeping the branching ratios intact

Definition at line 53 of file beta.py.

00055                                                    :
00056         '''Return a list of tuples (decay.BetaDecay,numpy.histogram).
00057         Each histogram has the given number of bins and gives the
00058         sampled energy spectrum.  The total number of entries of all
00059         histograms is as given.  The branching fractions of the decay
00060         are used to divide up the total number of decays when sampling
00061         each branch.  Histograms are normalized so their sum is 1 and
00062         keeping the branching ratios intact'''
00063         from numpy import histogram, array
00064 
00065         total_fraction = float(sum([dk.fraction for dk in self.betas]))
00066         maximum = max([dk.radiation.endpoint for dk in self.betas])
00067         ret = []
00068         
00069         binwidth = maximum/nbins
00070 
00071         for dk in self.betas:
00072             ratio = dk.fraction/total_fraction
00073             energies = []
00074             dk_number = ndecays*ratio
00075             for count in range(0,int(dk_number)):
00076                 energies.append(dk.radiation.sampleEnergy())
00077             h = histogram(energies,nbins,(0,maximum))
00078             norm = ratio/(binwidth*sum(h[0]))
00079             scaled = array([ bin*norm for bin in h[0] ])
00080             ret.append((dk,(scaled,h[1])))
00081             continue
00082         return ret
00083

In This Package:

GenDecay::beta::Spectra Class Reference

Public Member Functions

Detailed Description

Member Function Documentation


Public Member Functions
def	__init__
def	modeledSpectra
def	sampledSpectra