sas.perspectives.fitting.plugin_models package

Submodules

sas.perspectives.fitting.plugin_models.polynomial5 module

Test plug-in model These are links of available functions:

http://docs.python.org/library/math.html http://www.scipy.org/Numpy_Functions_by_Category

class sas.perspectives.fitting.plugin_models.polynomial5.Model

Bases: sas.models.pluginmodel.Model1DPlugin

##YOU CAN BE MODIFY ANYTHING BETWEEN ##DESCRIPTION OF MODEL PLUG-IN GOES HERE

##EXAMPLE: Class that evaluates a polynomial model.

function(x=0.0)

Evaluate the model :param x: input x :return: function value

get_fname()

Get the model name same as the file name

name = ''

sas.perspectives.fitting.plugin_models.sph_bessel_jn module

Test plug-in model These are links of available functions:

http://docs.python.org/library/math.html http://www.scipy.org/Numpy_Functions_by_Category

class sas.perspectives.fitting.plugin_models.sph_bessel_jn.Model

Bases: sas.models.pluginmodel.Model1DPlugin

##YOU CAN BE MODIFY ANYTHING BETWEEN ##DESCRIPTION OF MODEL PLUG-IN GOES HERE

##EXAMPLE: Class that evaluates a polynomial model.

function(x=0.0)

Evaluate the model

Parameters:x – input x Returns:function value

get_fname()

Get the model name same as the file name

name = ''

sas.perspectives.fitting.plugin_models.sum_Ap1_1_Ap2 module

class sas.perspectives.fitting.plugin_models.sum_Ap1_1_Ap2.Model

Bases: sas.models.pluginmodel.Model1DPlugin

Use for A*p1(Q)+(1-A)*p2(Q); Note: P(Q) refers to ‘form factor’ model.

evalDistribution(x=[])

Evaluate the model in cartesian coordinates

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

fill_description(p_model1, p_model2)

Fill the description for P(Q)+P(Q)

function(x=0.0)

getParam(name)

Set the value of a model parameter

Parameters:name – name of the parameter

getProfile()

Get SLD profile of p_model if exists

: return: (r, beta) where r is a list of radius of the transition points

beta is a list of the corresponding SLD values

: Note: This works only for func_shell# = 2 (exp function)

and is not supporting for p2

get_fname()

Get the model name same as the file name

name = ''

run(x=0.0)

Evaluate the model

Parameters:x – input q-value (float or [float, float] as [r, theta]) Returns:(scattering function value)

runXY(x=0.0)

Evaluate the model

Parameters:x – input q-value (float or [float, float] as [qx, qy]) Returns:scattering function value

setParam(name, value)

Set the value of a model parameter

Parameters:

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

set_dispersion(parameter, dispersion)

Set the dispersion object for a model parameter

Parameters:parameter – name of the parameter [string] Dispersion:dispersion object of type DispersionModel

sas.perspectives.fitting.plugin_models.sum_p1_p2 module

class sas.perspectives.fitting.plugin_models.sum_p1_p2.Model

Bases: sas.models.pluginmodel.Model1DPlugin

Use for p1(Q)+p2(Q); Note: P(Q) refers to ‘form factor’ model.

evalDistribution(x=[])

Evaluate the model in cartesian coordinates

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

fill_description(p_model1, p_model2)

Fill the description for P(Q)+P(Q)

function(x=0.0)

getParam(name)

Set the value of a model parameter

Parameters:name – name of the parameter

getProfile()

Get SLD profile of p_model if exists

: return: (r, beta) where r is a list of radius of the transition points

beta is a list of the corresponding SLD values

: Note: This works only for func_shell# = 2 (exp function)

and is not supporting for p2

get_fname()

Get the model name same as the file name

name = ''

run(x=0.0)

Evaluate the model

Parameters:x – input q-value (float or [float, float] as [r, theta]) Returns:(scattering function value)

runXY(x=0.0)

Evaluate the model

Parameters:x – input q-value (float or [float, float] as [qx, qy]) Returns:scattering function value

setParam(name, value)

Set the value of a model parameter

Parameters:

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

set_dispersion(parameter, dispersion)

Set the dispersion object for a model parameter

Parameters:parameter – name of the parameter [string] Dispersion:dispersion object of type DispersionModel

sas.perspectives.fitting.plugin_models.testmodel module

Test plug-in model These are links of available functions:

http://docs.python.org/library/math.html http://www.scipy.org/Numpy_Functions_by_Category

class sas.perspectives.fitting.plugin_models.testmodel.Model

Bases: sas.models.pluginmodel.Model1DPlugin

##YOU CAN BE MODIFY ANYTHING BETWEEN ##DESCRIPTION OF MODEL PLUG-IN GOES HERE

##EXAMPLE:Class that evaluates a cos(x) model.

function(x=0.0)

Evaluate the model

Parameters:x – input x Returns:function value

get_fname()

Get the model name same as the file name

name = ''

sas.perspectives.fitting.plugin_models.testmodel_2 module

Test plug-in model These are links of available functions:

http://docs.python.org/library/math.html http://www.scipy.org/Numpy_Functions_by_Category

class sas.perspectives.fitting.plugin_models.testmodel_2.Model

Bases: sas.models.pluginmodel.Model1DPlugin

##YOU CAN BE MODIFY ANYTHING BETWEEN ##DESCRIPTION OF MODEL PLUG-IN GOES HERE

##EXAMPLE: Class that evaluates a polynomial model.

function(x=0.0)

Evaluate the model

Parameters:x – input x Returns:function value

get_fname()

Get the model name same as the file name

name = ''

Module contents