| class PolynomialDynamicModel( PolynomialModel,Dynamic ) | Source |
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General polynomial model of an adaptable degree.
f( x:p ) = ∑ pk * xk
where the sum is over k running from 0 to degree ( inclusive ).
It is a linear model.
Author Do Kester
Examples
poly = PolynomialDynamicModel( ) # polynomial with unknown degree
poly.grow( ) # starts at degree = 0, npar = 1
poly.grow( ) # each grow( ) adds 1
poly.grow( )
poly.grow( )
print poly.npchain
5
poly.shrink( ) # shrink( ) deletes 1 degree
print poly.npbase
4
Attributes
- minDegree : int
minimum degree of the polynomial - maxDegree : int or None
maximum degree of the polynomial
Attributes from Dynamic
ncomp (=degree+1), deltaNpar, minComp (=minDegree+1), maxComp (=maxDegree+1), growPrior
Attributes from PolynomialModel
degree
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
Category mathematics/Fitting
| PolynomialDynamicModel( degree, minDegree=0, maxDegree=None, fixed=None, growPrior=None, copy=None, **kwargs ) |
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Polynomial of a adaptable degree.
The model starts as a PolynomialModel of degree = 0. Growth of the model is governed by a exponential prior ( scale=1 ).
Parameters
- degree : int
degree to start with; it should be minDegree <= degree <= maxDegree - minDegree : int
minimum degree of polynomial (def=0) - maxDegree : None or int
maximum degree of polynomial (def=None) - growPrior : None or Prior
governing the birth and death.
ExponentialPrior (scale=2) if maxDegree is None else UniformPrior - copy : PolynomialDynamicModel
model to copy
Raises
AttributeError when fixed parameters are requested ValueError when degree is outside [min..max] range
| copy( ) |
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| isDynamic( ) |
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| changeNComp( dn ) |
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| baseName( ) |
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Return a string representation of the model.
| Methods inherited from PolynomialModel, |
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- basePartial( xdata, params, parlist=None )
- baseDerivative( xdata, params )
- baseParameterName( k )
- baseParameterUnit( k )
| Methods inherited from LinearModel |
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| Methods inherited from Model |
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- chainLength( )
- isNullModel( )
- isolateModel( k )
- addModel( model )
- subtractModel( model )
- multiplyModel( model )
- divideModel( model )
- pipeModel( model )
- appendModel( model, operation )
- correctParameters( params )
- result( xdata, param=None )
- operate( res, pars, next )
- derivative( xdata, param, useNum=False )
- partial( xdata, param, useNum=False )
- selectPipe( ndim, ninter, ndout )
- pipe_0( dGd, dHdG )
- pipe_1( dGd, dHdG )
- pipe_2( dGd, dHdG )
- pipe_3( dGd, dHdG )
- pipe_4( dGdx, dHdG )
- pipe_5( dGdx, dHdG )
- pipe_6( dGdx, dHdG )
- pipe_7( dGdx, dHdG )
- pipe_8( dGdx, dHdG )
- pipe_9( dGdx, dHdG )
- shortName( )
- getNumberOfParameters( )
- numDerivative( xdata, param )
- numPartial( xdata, param )
- hasPriors( isBound=True )
- getPrior( kpar )
- setPrior( kpar, prior=None, **kwargs )
- getParameterName( kpar )
- getParameterUnit( kpar )
- getIntegralUnit( )
- setLimits( lowLimits=None, highLimits=None )
- getLimits( )
- hasLimits( fitindex=None )
- unit2Domain( uvalue, kpar=None )
- domain2Unit( dvalue, kpar=None )
- partialDomain2Unit( dvalue )
- nextPrior( )
- isMixed( )
- getLinearIndex( )
- testPartial( xdata, params, silent=True )
- strictNumericPartial( xdata, params, parlist=None )
- assignDF1( partial, i, dpi )
- assignDF2( partial, i, dpi )
- strictNumericDerivative( xdata, param )
| Methods inherited from FixedModel |
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| Methods inherited from BaseModel |
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- checkParameter( param )
- checkPositive( param )
- checkZeroParameter( param )
- isModifiable( )
- basePrior( kpar )
| Methods inherited from Dynamic |
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- setGrowPrior( growPrior=None, min=1, max=None, name="Comp" )
- setDynamicAttribute( name, value )
- grow( offset=0, rng=None, **kwargs )
- shrink( offset=0, rng=None, **kwargs )
- alterParameterNames( dnp )
- alterParameterSize( dnp, offset, location=None, value=0 )
- alterParameters( param, location, dnp, offset, value=None )
- alterFitindex( findex, location, dnp, offset )
- shuffle( param, offset, np, rng )