CombiModel

CombiModel = class CombiModel(BracketModel)

CombiModel(model, nrepeat=1, copy=None, oper='add', addCombi=None, mulCombi=None, **kwargs) CombiModel combines a number of copies of the same model. Fixed relations can be set between similar parameters. The relations can be either multiplicative or additive. When these relations are set, they must be set for all models. f( x:p ) = ∑ g( x:p ) where g( x:p ) is a model ( e.g. GaussModel ) For consistency reasons it is not possible to change the attributes of a CombiModel. It is better to make a new one with the required settings. Attributes ---------- nrepeat : int number of Models in this CombiModel nmp : int number of parameters in each Model expandpar : array of float expanded parameters. to be used in the repeated models npcmax : int number of parameters in expandpar (= nmp * nrepeat) expandindex : array of int converts parameter index into expandpar index addindex : array of int indices of additively connected parameters addvalue : array of float list of values to be added to the parameters in addindex mulindex : array of int indices of multiplicatively connected parameters mulvalue : array of float list of values to be multiplied to the parameters in mulindex select : array of int indices of expandpar to get parameters Attributes from BracketModel -------------------------- model, deep Attributes from Model -------------------------- npchain, parameters, stdevs, xUnit, yUnit Attributes from FixedModel -------------------------- npmax, fixed, parlist, mlist Attributes from BaseModel -------------------------- npbase, ndim, priors, posIndex, nonZero, tiny, deltaP, parNames Examples -------- >>> gauss = GaussModel( ) >>> combi = CombiModel( gauss, 3, addCombi={1:[0,0.1,0.3]}, mulCombi={2,[0]*3} ) >>> print combi Combi of 3 times GaussModel >>> print( combi.npchain, combi.nrepeat, combi.nmp, combi.nexpand ) 5 3 3 9 >>> print( combi.select ) [0 1 2 3 6] >>> print( combi.expandindex ) [0 1 2 3 1 2 4 1 2] >>> print( combi.modelindex ) [0 0 0 1 2] >>> print( combi.addindex ) [1 4 7] >>> print( combi.mulindex ) [2 5 8] Category mathematics/Fitting Notes ----- 1. When all parameters are left free, precise initial parameters are needed to converge to the global optimum. 2. The model seems to be especially unstable when the basic models are overlapping. Fixing the widths relative to each other, helps. 3. Using a PolynomialModel ( or similar ones ) as basic model, is not going to work.

Method resolution order:: CombiModel; BracketModel; Model.Brackets; Model; FixedModel; BaseModel; builtins.object

Constructor:

CombiModel( model, nrepeat=1, copy=None, oper='add', addCombi=None,
mulCombi=None, **kwargs): CombiModel combines several copies of the same model int one. Parameters ---------- model : Model model to be repeated nrepeat : int number of repetitions oper : "add" or "mul" the repeated models are combined using this operation addCombi : None or dict make additive connections between parameters None : no additive connection dict : { int : array } key : int index pointing to the key-th parameter in the model value : array of nrepeat floats values added to each of the key-th parameters mulCombi : None or dict make multiplicative connections between parameters None : no multiplicative connection dict : { int : array } key : int index pointing to the key-th parameter in the model value : array of nrepeat floats values multiplied to each of the key-th parameters

Methods defined here:

baseDerivative( xdata, params ): Returns the derivative (df/dx) calculated at the xdatas. Parameters ---------- xdata : array_like values at which to calculate the partials params : array_like values for the parameters.

baseName(): Returns a string representation of the model.

baseParameterName( k ): Return the name of the indicated parameter. Parameters --------- k : int parameter number.

baseParameterUnit( k ): Return the unit of the indicated parameter. Parameters --------- k : int parameter number.

basePartial( xdata, params, parlist=None ): Returns the partial derivatives calculated at the xdatas. Parameters ---------- xdata : array_like values at which to calculate the partials params : array_like values for the parameters. parlist : array_like Not in use

baseResult( xdata, params ): Returns the result calculated at the xdatas. Parameters ---------- xdata : array_like values at which to calculate the result params : array_like values for the parameters.

combine( addCombi=None, mulCombi=None ): (re)sets the value of attributes "addindex", "addvalue", "mulindex", "mulvalue", "select" and "expandindex". Parameters ---------- addCombi : None or dict make additive connections between parameters None : no additive connection dict : { int : array } key : int index pointing to the key-th parameter in the model value : array of nrepeat floats values added to each of the key-th parameters mulCombi : None or dict make multiplicative connections between parameters None : no multiplicative connection dict : { int : array } key : int index pointing to the key-th parameter in the model value : array of nrepeat floats values multiplied to each of the key-th parameters

copy(): Copy method.

expandParameters( param )

makeExpandIndex( expandindex, amindex ): Make an expanded index enumerating the parameters for the full model

setCombi( combi )

Methods inherited from Model.Brackets:

Methods inherited from Model:

Overloaded operators and aliases

Other methods

Methods inherited from FixedModel:

Methods inherited from BaseModel: