Delta1D

class sherpa.models.basic.Delta1D(name='delta1d')[source] [edit on github]

Bases: sherpa.models.model.RegriddableModel1D

One-dimensional delta function.

The delta function model is only non-zero at a single point (or bin for integrated grids).

pos

The position of the signal.

ampl

The amplitude.

Notes

The functional form of the model for points is:

f(x) = ampl if x == pos
     = 0       otherwise

and for an integrated grid it is:

f(lo,hi) = ampl         if lo <= pos <= hi
         = 0            otherwise

This behavior is different to how the amplitude is handled in other models, such as Const1D.

Attributes Summary

ndim

thawedparhardmaxes

thawedparhardmins

thawedparmaxes

thawedparmins

thawedpars

Methods Summary

apply(outer, *otherargs, **otherkwargs)

calc(pars, xlo, *args, **kwargs)

Evaluate the model on a grid.

get_center()

guess(dep, *args, **kwargs)

Set an initial guess for the parameter values.

regrid(*args, **kwargs)

The class RegriddableModel1D allows the user to evaluate in the requested space then interpolate onto the data space.

reset()

set_center(pos, *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

ndim = 1
thawedparhardmaxes
thawedparhardmins
thawedparmaxes
thawedparmins
thawedpars

Methods Documentation

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

Evaluate the model on a grid.

Parameters
  • p (sequence of numbers) – The parameter values to use. The order matches the pars field.

  • *args – The model grid. The values can be scalar or arrays, and the number depends on the dimensionality of the model and whether it is being evaluated over an integrated grid or at a point (or points).

get_center()[source] [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(*args, **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(pos, *args, **kwargs)[source] [edit on github]
startup(cache=False) [edit on github]

Called before a model may be evaluated multiple times.

Parameters

cache (bool, optional) – Should a cache be used when evaluating the models.

See also

teardown()

teardown() [edit on github]

Called after a model may be evaluated multiple times.

See also

setup()