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FixedModel = class FixedModel(BaseModel) |
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FixedModel(nparams=0, ndim=1, copy=None, fixed=None, names=None, **kwargs)
A FixedModel is a BaseModel where some parameters are permanently fixed.
A parameter can be fixed either with a constant float value or more
dynamically, with another Model. The parameters of this latter model
also appear as parameters of the FixedModel.
The methods result (f(x:p)) and partial (df/dp) are calculated
in here.
Unfortunately the methods derivative (df/dx) is model dependent.
It is reset to numDerivative.
Examples
--------
>>> m1 = PolynomialModel( 1 )
>>> m1 += SineModel()
>>> print( m1.npchain ) # number of params: 2 + 3
5
>>> fixed = { 0: 1.0, 1: m1 }
>>> em = EtalonModel( fixed=fixed )
>>> print( em.npbase, em.npmax, em.npchain ) # ( 4 - 2 ) + 5
7 9 7
>>> print( em )
Attributes
----------
npmax : int
maximum number of parameters of the simple (not-fixed) model
fixed : dictionary of {int:float|Model}
int index of parameter to fix permanently. Default None.
float value for the fixed parameter.
Model model to replace the parameter
Attribute fixed can only be set in the constructor.
parlist : array_like or None
list of active (not-fixed) indices. None is all.
mlist : list of Model
list of parameter indices which are replaced by a Model in fixed.
Attributes from BaseModel
--------------------------
npbase, ndim, priors, posIndex, nonZero,
tiny, deltaP, parNames
Author Do Kester
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- Method resolution order:
- FixedModel
- BaseModel
- builtins.object
Constructor:
- FixedModel( nparams=0, ndim=1, copy=None, fixed=None, names=None, **kwargs )
- FixedModel Constructor.
Parameters
----------
nparams : int
Number of parameters in the model (default: 0)
ndim : int
Number of dimensions of the input (default: 1)
copy : BaseModel
to be copied
fixed : dictionary of {int:float|Model}
int index of parameter to fix permanently. Default None.
float value for the fixed parameter.
Model model to replace the parameter
Attribute fixed can only be set in the constructor.
names : list of string
names for the parameters
kwargs for BaseModel :
posIndex, nonZero
Methods defined here:
- basePartial( xdata, param, parlist=None )
- Replacement for models that dont define a partial.
Parameters
----------
xdata : array_like
values at which to calculate the result
param : array_like
values for the parameters.
parlist : array_like
list of indices active parameters (or None for all)
- copy()
- Return a copy.
- derivative( xdata, param )
- Returns the derivative of the model to xdata.
It is a numeric derivative as the analytic derivative is not present
in the model.
If `fixed` contains a Model, the derivative cannot be constructed
from the constituent models. Use `numDerivative` instead.
Parameters
----------
xdata : array_like
values at which to calculate the derivative
param : array_like
values for the parameters. (default: self.parameters)
- expand( xdata, param )
- Returns a complete list of parameters, where the fixed parameters
have been replaced by either a constant value or by the results of
the fixed function.
- numDerivative( xdata, param )
- Returns the numeric derivative of the model to input
Parameters
----------
xdata : array_like
values at which to calculate the derivative
param : array_like
values for the parameters. (default: self.parameters)
Raises
------
ValueError when the number of xdata dimensions > 1.
- numPartial( xdata, params, parlist=None )
- Returns numerical partial derivatives of the model to params.
Parameters
----------
xdata : array_like
values at which to calculate the result
params : array_like
values for the parameters; default is self.parameters
parlist : array_like
list of indices active parameters (or None for all)
- partial( xdata, param )
- Returns the partial derivatives calculated at the inputs.
Parameters
----------
xdata : array_like
values at which to calculate the result
params : array_like
values for the parameters.
- result( xdata, param )
- Returns the result calculated at the xdatas.
Parameters
----------
xdata : array_like
values at which to calculate the result
params : array_like
values for the parameters.
- select( params )
- Select the relevant parameters and store them.
Parameters
----------
params : array of float
parameters of the head model
- selectNames( names )
- Select the relevant parameter names and store them.
Parameters
----------
names : list of string
parameter names of the head model
Methods inherited from BaseModel:
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