ParkFitting module contains SansParameter,Model,Data FitArrange, ParkFit,Parameter classes.All listed classes work together to perform a simple fit with park optimizer.
Bases: sans.fit.AbstractFitEngine.FitEngine
ParkFit performs the Fit.This class can be used as follow: #Do the fit Park create an engine: engine = ParkFit() Use data must be of type plottable Use a sans model
Add data with a dictionnary of FitArrangeList where Uid is a key and data is saved in FitArrange object. engine.set_data(data,Uid)
Set model parameter “M1”= model.name add {model.parameter.name:value}.
Note : | Set_param() if used must always preceded set_model() for the fit to be performed. |
---|
engine.set_param( model,”M1”, {‘A’:2,’B’:4})
Add model with a dictionnary of FitArrangeList{} where Uid is a key and model is save in FitArrange object. engine.set_model(model,Uid)
engine.fit return chisqr,[model.parameter 1,2,..],[[err1....][..err2...]] chisqr1, out1, cov1=engine.fit({model.parameter.name:value},qmin,qmax)
Note : | {model.parameter.name:value} is ignored in fit function since the user should make sure to call set_param himself. |
---|
Performs fit with park.fit module.It can perform fit with one model and a set of data, more than two fit of one model and sets of data or fit with more than two model associated with their set of data and constraints
Parameters: |
|
---|---|
Note : | all parameter are ignored most of the time.Are just there to keep ScipyFit and ParkFit interface the same. |
Returns: | result.fitness Value of the goodness of fit metric |
Returns: | result.pvec list of parameter with the best value found during fitting |
Returns: | result.cov Covariance matrix |
Parameters: |
|
---|---|
Returns: | a model at this uid or None if no FitArrange element was created with this Uid |
return the self.selected value of the fit problem of Uid
Parameters: |
|
---|
select a couple of model and data at the Uid position in dictionary and set in self.selected value to value
Parameters: |
|
---|
Receives plottable, creates a list of data to fit,set data in a FitArrange object and adds that object in a dictionary with key Uid.
Parameters: |
|
---|
set a model on a given uid in the fit engine.
Parameters: |
|
---|---|
Note : | pars must contains only name of existing model’s parameters |