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class AstropyModel( Model )	Source

Wrapper for Astropy Models, so they can be used in BayesicFitting.

Examples

from astropy.modelling.models import Gaussian1D
gm = Gaussian1D( mean=0, stddev=1, amplitude=1 )

gauss = AstropyModel( gm )
print( gauss )
AstropyModel( Gauss1D )
print( gauss.getNumberOfParameters( ) )
3
print( gauss( numpy.linspace( -5, 5, 11 ) ) )
[  3.72665317e-06   3.35462628e-04   1.11089965e-02   1.35335283e-01
   6.06530660e-01   1.00000000e+00   6.06530660e-01   1.35335283e-01
   1.11089965e-02   3.35462628e-04   3.72665317e-06]

Attributes

• astromodel : astropy.modeling.FittableModel
       The astropy model to be wrapped

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

AstropyModel( astromodel, copy=None, **kwargs )

Gaussian model.

Number of parameters is 3.

Parameters

• fitmodel : FittableModel
       FittableModel from astropy.modeling
• copy : GaussModel
       to be copied
• 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( )

Copy method.

baseResult( xdata, params )

Returns the result of the model function.

Parameters

• xdata : array_like
       values at which to calculate the result
• params : array_like
       values for the parameters.

basePartial( xdata, params, parlist=None )

Returns the partials at the input value.

Parameters

• xdata : array_like
       values at which to calculate the partials
• params : array_like
       values for the parameters.
• parlist : array_like
       list of indices active parameters (or None for all)

baseDerivative( xdata, params )

Return the derivative df/dx at each xdata (=x).

Parameters

• xdata : array_like
       values at which to calculate the result
• params : array_like
       values for the parameters.

baseName( )

Returns a string representation of the model.

Methods inherited from Model

• 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 )
• 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( )
• 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

• select( params )
• selectNames( names )
• expand( xdata, param )

Methods inherited from BaseModel

• checkParameter( param )
• checkPositive( param )
• checkZeroParameter( param )
• isModifiable( )
• basePrior( kpar )
• baseParameterName( kpar )
• baseParameterUnit( kpar )