| class KernelModel( NonLinearModel ) | Source |
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Kernel Model, a Model build around an Kernel.
The KernelModel is defined as
f( x:p ) = p0 * K( ( x - p1 ) / p2 )
where K( u ) is a selectable kernel function on the rescaled input u
u = ( x - p1 ) / p2.
p0 is the amplitude
p1 is the center
p2 is the range.
The parameters are initialized at amp,0,1. the amplitude is such that the function integrates to 1.0. They are listed in the table.
Several kernel functions predefined.
Beware: The "bound" models are unaware of anything outside their range.
Author: Do Kester
Examples
model = KernelModel( )
model.kernel = Triweight()
Attributes
- kernel : Kernel
the kernel of this model
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
| KernelModel( copy=None, kernel=Biweight(), **kwargs ) |
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Kernel Model.
Parameters
- copy : KernelModel
model to be copied - kernel : Kernel
kernel class (default = Biweight) - fixed : None or dictionary of {int:float|Model}
int index of parameter to fix permanently.
float|Model values for the fixed parameters.
Attribute fixed can only be set in the constructor.
See: FixedModel
| copy( ) |
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| baseResult( xdata, params ) |
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Parameters
- xdata : array_like
values at which to calculate the result - params : array_like
values for the parameters.
| basePartial( xdata, params, parlist=None ) |
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Parameters
- xdata : array_like
values at which to calculate the result - params : array_like
values for the parameters. - parlist : array_like
list of indices active parameters (or None for all)
| baseDerivative( xdata, params ) |
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Parameters
- xdata : array_like
values at which to calculate the result - params : array_like
values for the parameters.
| baseName( ) |
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Returns a string representation of the model.
| isBound( ) |
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| baseParameterUnit( k ) |
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- k : int
the kth parameter.
| Methods inherited from NonLinearModel |
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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 )
- 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 )
- isDynamic( )
- 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( )
- 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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