Poisson¶
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class
sherpa.models.basic.
Poisson
(name='poisson')[source] [edit on github]¶ Bases:
sherpa.models.model.RegriddableModel1D
One-dimensional Poisson function.
A model expressing the ratio of two Poisson distributions of mean mu, one for which the random variable is x, and the other for which the random variable is equal to mu itself.
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mean
¶ The mean of the first distribution.
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ampl
¶ The amplitude of the model.
Notes
The functional form of the model for points is:
f(x) = ampl * mean! exp((x - mean) * log(mean)) / x!
The grid version is evaluated by numerically intgerating the function over each bin using a non-adaptive Gauss-Kronrod scheme suited for smooth functions [1], falling over to a simple trapezoid scheme if this fails.
References
[1] https://www.gnu.org/software/gsl/manual/html_node/QNG-non_002dadaptive-Gauss_002dKronrod-integration.html Attributes Summary
thawedparhardmaxes
thawedparhardmins
thawedparmaxes
thawedparmins
thawedpars
Methods Summary
apply
(outer, *otherargs, **otherkwargs)calc
(pars, xlo, *args, **kwargs)get_center
()guess
(dep, *args, **kwargs)Set an initial guess for the parameter values. regrid
(*arrays)reset
()set_center
(*args, **kwargs)startup
()Called before a model may be evaluated multiple times. teardown
()Called after a model may be evaluated multiple times. Attributes Documentation
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thawedparhardmaxes
¶
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thawedparhardmins
¶
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thawedparmaxes
¶
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thawedparmins
¶
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thawedpars
¶
Methods Documentation
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apply
(outer, *otherargs, **otherkwargs) [edit on github]¶
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calc
(pars, xlo, *args, **kwargs) [edit on github]¶
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get_center
() [edit on github]¶
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guess
(dep, *args, **kwargs)[source] [edit on github]¶ Set an initial guess for the parameter values.
Attempt to set the parameter values, and ranges, for the model to match the data values. This is intended as a rough guess, so it is expected that the model is only evaluated a small number of times, if at all.
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regrid
(*arrays) [edit on github]¶
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reset
() [edit on github]¶
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set_center
(*args, **kwargs) [edit on github]¶
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startup
() [edit on github]¶ Called before a model may be evaluated multiple times.
See also
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teardown
() [edit on github]¶ Called after a model may be evaluated multiple times.
See also
setup()
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