SphereSLDModel

sans.models.SphereSLDModel

Provide functionality for a C extension model

WARNING:THIS FILE WAS GENERATED BY WRAPPERGENERATOR.PY DO NOT MODIFY THIS FILE, MODIFY ..c_extensionsspheresld.h AND RE-RUN THE GENERATOR SCRIPT

class sans.models.SphereSLDModel.SphereSLDModel

Bases: CSphereSLDModel, sans.models.BaseComponent.BaseComponent

Class that evaluates a SphereSLDModel model. This file was auto-generated from ..c_extensionsspheresld.h. Refer to that file and the structure it contains for details of the model. List of default parameters:

n_shells = 1.0 scale = 1.0 thick_inter0 = 50.0 [A] func_inter0 = 0.0 sld_core0 = 2.07e-06 [1/A^(2)] sld_solv = 1e-06 [1/A^(2)] background = 0.0 sld_flat1 = 4e-06 [1/A^(2)] sld_flat2 = 3.5e-06 [1/A^(2)] sld_flat3 = 4e-06 [1/A^(2)] sld_flat4 = 3.5e-06 [1/A^(2)] sld_flat5 = 4e-06 [1/A^(2)] sld_flat6 = 3.5e-06 [1/A^(2)] sld_flat7 = 4e-06 [1/A^(2)] sld_flat8 = 3.5e-06 [1/A^(2)] sld_flat9 = 4e-06 [1/A^(2)] sld_flat10 = 3.5e-06 [1/A^(2)] thick_inter1 = 50.0 [A] thick_inter2 = 50.0 [A] thick_inter3 = 50.0 [A] thick_inter4 = 50.0 [A] thick_inter5 = 50.0 [A] thick_inter6 = 50.0 [A] thick_inter7 = 50.0 [A] thick_inter8 = 50.0 [A] thick_inter9 = 50.0 [A] thick_inter10 = 50.0 [A] thick_flat1 = 100.0 [A] thick_flat2 = 100.0 [A] thick_flat3 = 100.0 [A] thick_flat4 = 100.0 [A] thick_flat5 = 100.0 [A] thick_flat6 = 100.0 [A] thick_flat7 = 100.0 [A] thick_flat8 = 100.0 [A] thick_flat9 = 100.0 [A] thick_flat10 = 100.0 [A] func_inter1 = 0.0 func_inter2 = 0.0 func_inter3 = 0.0 func_inter4 = 0.0 func_inter5 = 0.0 func_inter6 = 0.0 func_inter7 = 0.0 func_inter8 = 0.0 func_inter9 = 0.0 func_inter10 = 0.0 nu_inter1 = 2.5 nu_inter2 = 2.5 nu_inter3 = 2.5 nu_inter4 = 2.5 nu_inter5 = 2.5 nu_inter6 = 2.5 nu_inter7 = 2.5 nu_inter8 = 2.5 nu_inter9 = 2.5 nu_inter10 = 2.5 npts_inter = 35.0 nu_inter0 = 2.5 rad_core0 = 50.0 [A]

__add__()

__class__

alias of type

__delattr__

x.__delattr__(‘name’) <==> del x.name

__dict__ = <dictproxy object at 0x02071830>

__div__()

__getattribute__

x.__getattribute__(‘name’) <==> x.name

__hash__

x.__hash__() <==> hash(x)

__init__()

Initialization

__module__ = 'sans.models.SphereSLDModel'

__mul__()

static __new__(S, ...) → a new object with type S, a subtype of T

__reduce__()

helper for pickle

__reduce_ex__()

Overwrite the __reduce_ex__ of PyTypeObject *type call in the init of c model.

__repr__

x.__repr__() <==> repr(x)

__setattr__

x.__setattr__(‘name’, value) <==> x.name = value

__setstate__()

restore the state of a model from pickle

__str__

x.__str__() <==> str(x)

__sub__()

__weakref__

list of weak references to the object (if defined)

_clone()

Internal utility function to copy the internal data members to a fresh copy.

calculate_ER()

Calculate the effective radius for P(q)*S(q)

Returns:the value of the effective radius

clone()

Return a identical copy of self

dispersion

Dispersion parameters

evalDistribution()

Evaluate the model in cartesian coordinates

Parameters:x – input q[], or [qx[], qy[]] Returns:scattering function P(q[])

getDispParamList()

Return a list of all available parameters for the model

getParam()

Set the value of a model parameter

Parameters:name – name of the parameter

getParamList()

Return a list of all available parameters for the model

getParamListWithToken()

getParamWithToken()

is_fittable()

Check if a given parameter is fittable or not

Parameters:par_name – the parameter name to check

log

Log

params

Parameters

reset()

Reset pair correlation

run()

Evaluate the model

Parameters:x – input q, or [q,phi] Returns:scattering function P(q)

runXY()

Evaluate the model in cartesian coordinates

Parameters:x – input q, or [qx, qy] Returns:scattering function P(q)

setParam()

Set the value of a model parameter

Parameters:

• name – name of the parameter
• value – value of the parameter

setParamWithToken()

set_dispersion()

Set the dispersion object for a model parameter

Parameters:

• parameter – name of the parameter [string]
• dispersion – dispersion object of type DispersionModel

sans.models.SphereSLDModel.create_SphereSLDModel()