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For quick example suppose that we have this class defined in user module:
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# user analysis class
class myana(object):
def __init__(self, name, lower, upper, bins=100)
self.name = name
self.lower = float(lower)
self.upper = float(upper)
self.bins = int(bins)
...
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and this job configuration file:
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[pyana] modules = mypackage.myana mypackage.myana:wide [mypackage.myana] lower = 0 upper = 100 name = default [mypackage.myana:wide] lower = 0 upper = 1000 bins = 1000 name = wide |
With this the analysis job will instantiate two analysis objects with different parameters, equivalent to this pseudo-code:
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# import class myana
from mypackage.myana import myana
# create instances
instances = [ myana(lower = "0", upper = "100", name = "default"),
myana(lower = "0", upper = "1000", bins = "1000", name = "wide") ]
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Here is an almost identical example from Initialization section above which illustrates the inheritance and overriding of the user options:
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[pyana] modules = mypackage.myana mypackage.myana:wide [mypackage.myana] lower = 0 upper = 100 name = default [mypackage.myana:wide] ; 'lower' option will be reused from [mypackage.myana] section bins = 1000 ; this overrides default module value ; two options below will override [mypackage.myana] values upper = 1000 name = wide |
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Here is a brief example of booking and filling of few histograms in user module:
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# user analysis class
class myana(object):
def beginjob(self, event, env):
# get histogram manager
hmgr = env.hmgr()
# book histograms, store references
self.hist1 = hmgr.h1d('energy', 'Energy Distribution', 100, 0., 1.)
self.hist2 = hmgr.h2d('energy vs something', 'Histo2 title', 100, 0., 1., 100, -20., 20.)
def event(self, event, env):
# fill histograms
energy = ...
something = ...
self.hist1.Fill(energy)
self.hist2.Fill(energy, something)
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Here is very brief example of using SciPy for integration of experimental data:
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from scipy import integrate
class myana(object):
def event(self, event, env):
# Get Acqiris waveform object
ddesc = evt.getAcqValue( "AmoITof", channel, env )
wf = ddesc.waveform()
ts = ddesc.timestamps()
# integrate it using Simpson's rule
integral = integrate.simps (wf, ts)
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