PadeModel

PadeModel = class PadeModel(NonLinearModel)

PadeModel(num, den, copy=None, fixed=None, **kwargs) General Pade model of arbitrary degrees in numerator and denominator. f( x:p ) = ∑ p_n * x^n / ( ∑ p_{num+1+k} * x^k ) where the sum in the numerator is over n running from 0 to num ( inclusive ) and the sum in the denominator is over k running from 0 to den ( inclusive ) At least one parameter needs to be fixed, otherwise the model is degenerate in its parameters. By default the first parameter of the denominator (p_{num+1}) is fixed to 1.0. All parameters are initialized at 0. It is a non-linear model. Beware of the poles where the denominator equals zero. Author: Do Kester Examples -------- >>> pade = PadeModel( 3, 1 ) # 3rd degree polynomial >>> print pade.getNumberOfParameters( ) # 5 5 Attributes ---------- num : int order of the polynomial in the numerator den : int order of the polynomial in the denominator 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 Alternate --------- PadeModel( 2, 3 ) is equivalent to PolynomialModel( 2 ) / PolynomialModel( 3, fixed={0:1.0} )

Method resolution order:: PadeModel; NonLinearModel; Model; FixedModel; BaseModel; builtins.object

Constructor:

PadeModel( num, den, copy=None, fixed=None, **kwargs ): Pade of a certain degree in numerator and denominator. The number of parameters is ( num + den + 1 ) Parameters ---------- num : int the degree of the polynomial in the numerator. den : int the degree of the polynomial in the denominator. copy : PadeModel model to be copied fixed : dictionary of {int:float|Model} int index of parameter to fix permanently. float|Model values for the fixed parameters. Default {num+1 : 1.0} Attribute fixed can only be set in the constructor. See: FixedModel

Methods defined here:

baseDerivative( xdata, params ): Returns the partials at the xdata values. Parameters ---------- xdata : array_like values at which to calculate the partials params : array_like parameters for the model.

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

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

basePartial( xdata, params, parlist=None ): Returns the partials at the xdata values. Parameters ---------- xdata : array_like values at which to calculate the partials params : array_like parameters for the model. parlist : array_like list of indices active parameters (or None for all)

baseResult( xdata, params ): Returns the result of the model function. Parameters ---------- xdata : array_like values at which to calculate the partials params : array_like parameters for the model.

copy(): Copy method.

Methods inherited from NonLinearModel:

Methods inherited from Model:

Overloaded operators and aliases

Other methods

Methods inherited from FixedModel:

Methods inherited from BaseModel: