StepHi1D

class sherpa.models.basic.StepHi1D(name='stephi1d')[source] [edit on github]

Bases: sherpa.models.model.RegriddableModel1D

One-dimensional step function.

The model is flat above xcut, where it is set to the ampl parameter, and zero below this.

xcut

The position of the step.

ampl

The amplitude of the step.

Notes

The functional form of the model for points is:

f(x) = ampl if x >= xcut
     = 0       otherwise

and for an integrated grid it is:

f(xlo,xhi) = ampl * (xhi - xlo)  if xlo >= xcut
           = ampl * (xhi - xcut) if xlo < xcut and xhi >= xcut
           = 0                   if xhi < xcut

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, **kwargs) The class RegriddableModel1D allows the user to evaluate in the requested space then interpolate onto the data space.
reset()
set_center(*args, **kwargs)
startup(cache) Called before a model may be evaluated multiple times.
teardown() Called after a model may be evaluated multiple times.

Attributes Documentation

thawedparhardmaxes
thawedparhardmins
thawedparmaxes
thawedparmins
thawedpars

Methods Documentation

apply(outer, *otherargs, **otherkwargs) [edit on github]
calc(pars, xlo, *args, **kwargs) [edit on github]
get_center() [edit on github]
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.

regrid(*arrays, **kwargs) [edit on github]

The class RegriddableModel1D allows the user to evaluate in the requested space then interpolate onto the data space. An optional argument ‘interp’ enables the user to change the interpolation method.

Examples

>>> import numpy as np
>>> from sherpa.models.basic import Box1D
>>> mybox = Box1D()
>>> request_space = np.arange(1, 10, 0.1)
>>> regrid_model = mybox.regrid(request_space, interp=linear_interp)
reset() [edit on github]
set_center(*args, **kwargs) [edit on github]
startup(cache) [edit on github]

Called before a model may be evaluated multiple times.

See also

teardown()

teardown() [edit on github]

Called after a model may be evaluated multiple times.

See also

setup()