ReflectivityModel

sans.models.ReflectivityModel

class sans.models.ReflectivityModel.ReflectivityModel

Bases: sans.models.BaseComponent.BaseComponent

This multi-model is based on Parratt formalism and provides the capability of changing the number of layers between 0 and 10.

__add__()

__div__()

__init__()

__module__ = 'sans.models.ReflectivityModel'

__mul__()

__str__()

Returns:string representatio

__sub__()

_clone()

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

_get_func()

Get the function asked to buil sld profile : param index: index of sub_layer : param n_sub: total number of sub_layer : param func_idx: an integer to identify a function

: return out: the output from the function, float

_get_func_list()

Get the list of functions in each layer (shell)

_setParamHelper()

Helper function to setParam

_set_details()

Concatenate details of the original model to create this model details

_set_dispersion()

model dispersions

_set_fixed_params()

Fill the self.fixed list with the model fixed list

_set_params()

Concatenate the parameters of the model to create this model parameters

_set_xtra_model_param()

Set params of original model that are hidden from this model

calculate_ER()

clone()

Returns a new object identical to the current object

evalDistribution()

Evaluate the model in cartesian coordinates

: param x: input q[], or [qx[], qy[]] : return: 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()

getProfile()

Get SLD profile

: return: (z, beta) where z is a list of depth of the transition points

beta is a list of the corresponding SLD values

is_fittable()

Check if a given parameter is fittable or not

Parameters:par_name – the parameter name to check

run()

Evaluate the model

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

runXY()

Evaluate the model

: param x: input q-value (float or [float, float] as [qx, qy]) : return: scattering function value

setParam()

Set the value of a model parameter

: param name: name of the parameter : param value: value of the parameter

setParamWithToken()

set_dispersion()

Set the dispersion object for a model parameter

: param parameter: name of the parameter [string] :dispersion: dispersion object of type DispersionModel