PowerModel = class PowerModel(LinearModel) |
|
PowerModel(exponent=0, copy=None, **kwargs)
General power model of arbitrary degree.
f( x:p ) = p * x^a
a is an float ( positive or negative ).
To get the overall units of f(x:p) right, please note that the x-term
needs to be divided by a factor 1.0 in the same units as the x.
Otherwise possibly fractional dimensions are created.
The factor is omitted as it does not contribute in the calculations.
Examples
--------
>>> pwr = PowerModel( -1 )
>>> print pwr.getNumberOfParameters( ) # 1
1
Attributes
----------
exponent : float
exponent (a) of the power function.
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 |
|
- Method resolution order:
- PowerModel
- LinearModel
- Model
- FixedModel
- BaseModel
- builtins.object
Constructor:
- PowerModel( exponent=0, copy=None, **kwargs )
- Power of a certain degree.
The number of parameters is 1
Parameters
----------
exponent : int
power to which the xdata is to be raised.
copy : PowerModel
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 )
- 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.
- baseParameterUnit( k )
- Return the name of a parameter.
Not strictly OK. See Class documentation.
Parameters
----------
k : int
the kth parameter.
- basePartial( xdata, params, parlist=None )
- Returns the partials at the xdata value.
<br>
The partials are x ( xdata ) to degree-th power.
Parameters
----------
xdata : array_like
values at which to calculate the result
params : array_like
values for the parameters. (not used for linear models)
parlist : array_like
list of indices active parameters (or None for all)
- copy()
- Copy method.
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 )
- isDynamic()
- 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:
|
|