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ExpModel = class ExpModel(NonLinearModel) |
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ExpModel(decay=False, copy=None, **kwargs)
Exponential Model.
f( x:p ) = p_0 * exp( p_1 * x )
where p_0 = amplitude
p_1 = slope
As always x = input.
The parameters are initialized at {1.0, -1.0}. It is a non-linear model.
Beware of a positive 2nd parameter; when positive the model is going off
to Infinity very quickly.
When decay is True the model changes into a decay model:
f( x:p ) = p_0 * exp( - p_1 * x )
The parameters are initialized at {1.0, 1.0}.
Attributes
----------
sign : [-1,1]
Whether decay is True or False.
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
Examples
--------
>>> em = ExpModel( )
>>> print( em.getNumberOfParameters( ) )
2
Author Do Kester
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- Method resolution order:
- ExpModel
- NonLinearModel
- Model
- FixedModel
- BaseModel
- builtins.object
Constructor:
- ExpModel( decay=False, copy=None, **kwargs )
- Exponential model.
<br>
Number of parameters is 2.
Parameters
----------
decay : boolean
changes sign of parameter[1]
copy : ExpModel
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
Methods defined here:
- baseDerivative( xdata, params )
- Returns the derivative df/dx at the input value.
Parameters
----------
xdata : array_like
value at which to calculate the result
params : array_like
values for the parameters
- baseName()
- Returns a string representation of the model.
- baseParameterUnit( k )
- Return the unit of the indicated parameter.
Parameters: k parameter number.
- basePartial( xdata, params, parlist=None )
- Returns the partials at the input value.
Parameters
----------
xdata : array_like
value 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)
- baseResult( xdata, params )
- Returns the result of the model function.
Parameters
----------
xdata : array_like
value at which to calculate the result
params : array_like
values for the parameters
- copy()
- Copy method.
Methods inherited from NonLinearModel:
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 )
- isDynamic()
- isNullModel()
- isolateModel( k )
- multiplyModel( model )
- nextPrior()
- numDerivative( xdata, param )
- numPartial( xdata, param )
- operate( res, pars, next )
- 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:
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