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LogisticModel = class LogisticModel(NonLinearModel) |
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LogisticModel(copy=None, **kwargs)
Logistic Model.
f( x:p ) = p_0 / ( 1 + exp( ( x - p_1 ) / p_2 ) )
where
p_0 : amplitude
p_1 : center
p_2 : slope
The parameters are initialized at {1.0, 0.0, 1.0}.
Examples
--------
>>> lm = LogisticModel( )
>>> print( lm )
Logistic: f( x:p ) = p_0 / ( 1 + exp( ( p_1 - x ) / p_2 ) )
>>> print( lm.npars )
3
>>> print( lm( numpy.arange( 11 ) - 5 ) )
[ 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 from Model
---------------------
npchain, parameters, stdevs, xUnit, yUnit
Attributes from FixedModel
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npmax, fixed, parlist, mlist
Attributes from BaseModel
--------------------------
npbase, ndim, priors, posIndex, nonZero,
tiny, deltaP, parNames
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- Method resolution order:
- LogisticModel
- NonLinearModel
- Model
- FixedModel
- BaseModel
- builtins.object
Constructor:
- LogisticModel( copy=None, **kwargs )
- Logistic response model.
Number of parameters is 3.
Parameters
----------
copy : LogisticModel
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 unit of the indicated parameter.
Parameters
---------
k : int
parameter number.
- 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)
- 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.
- 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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