PolynomialDynamicModel = class PolynomialDynamicModel(PolynomialModel, Dynamic) |
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PolynomialDynamicModel(degree, minDegree=0, maxDegree=None, fixed=None, growPrior=None,
copy=None, **kwargs)
General polynomial model of an adaptable degree.
f( x:p ) = ∑ p_k * x^k
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 |
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- Method resolution order:
- PolynomialDynamicModel
- PolynomialModel
- LinearModel
- Model
- FixedModel
- BaseModel
- Dynamic
- builtins.object
Constructor:
- PolynomialDynamicModel( degree, minDegree=0, maxDegree=None, fixed=None, growPrior=None,
copy=None, **kwargs)
- 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
Methods defined here:
- baseName()
- Return a string representation of the model.
- changeNComp( dn )
- copy()
- Copy method.
- isDynamic()
- Return whether the model can change the number of parameters dynamically.
Methods inherited from PolynomialModel:
Methods inherited from LinearModel:
Methods inherited from Model:
Overloaded operators and aliases
Other methods
- addModel( model )
- appendModel( model, operation )
- assignDF1( partial, i, dpi )
- assignDF2( partial, i, dpi )
- chainLength()
- correctParameters( params )
- derivative( xdata, param, useNum=False )
- divideModel( model )
- domain2Unit( dvalue, kpar=None )
- getIntegralUnit()
- getLimits()
- getLinearIndex()
- getNumberOfParameters()
- getParameterName( k )
- getParameterUnit( k )
- getPrior( k )
- hasLimits( fitindex=None )
- hasPriors( isBound=True )
- isMixed()
- isNullModel()
- isolateModel( k )
- multiplyModel( model )
- nextPrior()
- numDerivative( xdata, param )
- numPartial( xdata, param )
- operate( res, pars, next )
- partial( xdata, param, useNum=False )
- partialDomain2Unit( dvalue )
- pipeModel( model )
- 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)
- result( xdata, param=None )
- selectPipe( ndim, ninter, ndout )
- setLimits( lowLimits=None, highLimits=None )
- setPrior( k, prior=None, **kwargs )
- shortName()
- strictNumericDerivative( xdata, param )
- strictNumericPartial( xdata, params, parlist=None )
- subtractModel( model )
- testPartial( xdata, params, silent=True )
- unit2Domain( uvalue, kpar=None )
Methods inherited from FixedModel:
Methods inherited from BaseModel:
Methods inherited from Dynamic:
- alterFitindex( findex, location, dnp, offset )
- alterParameterNames( dnp )
- alterParameterSize( dnp, offset, location=None, value=0)
- alterParameters( param, location, dnp, offset, value=None )
- grow( offset=0, rng=None, **kwargs )
- setDynamicAttribute( name, value )
- setGrowPrior( growPrior=None, min=1, max=None, name='Comp')
- shrink( offset=0, rng=None, **kwargs )
- shuffle( param, offset, np, rng )
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