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BaseModel = class BaseModel(builtins.object) |
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BaseModel(nparams=0, ndim=1, copy=None, posIndex=[], nonZero=[], **kwargs)
BaseModel implements the common parts of simple Models.
A simple model is a function in x with parameters p : f(x:p).
The variable x is an array of points in a space of one or more
dimensions; p can have any length, including 0 i.e. the model
has no parameters.
The result of the function for certain x and p is given by
model.result( x, p )
The partial derivatives of f to p (df/dp) is given by
model.partial( x, p )
Some fitters make use of the partials
The derivative of f to x (df/dx) is given by
model.derivative( x, p )
BaseModel checks parameters for positivity and nonzero-ness, if such
is indicated in the model itself.
BaseModel also implements the numerical calculation of the (partial)
derivatives to be used when they are not given in the model definition
itself.
Attributes
----------
npbase : int
number of params in the base model
ndim : int
number of dimensions (parallel streams) of input. (default : 1)
priors : list of Prior
pertaining to each of the parameters of the model.
If the list is shorter than the number of parameters, the last one is repeated.
posIndex : list of int
list of indices indication positive-definite parameters.
nonZero : list of int
list of parameters that need a warning when they are equal to zero.
Warnings will only be issued once. Values are replaced by self.tiny
tiny : float
very small value, replacing zero valued when found on NonZero.
(default : 1e-20)
deltaP : array_like
(list of) width(s) for numerical partial calculation. (default : 0.00001)
parNames : list of str
list of parameter names. (default : "parameter_k")
Author : Do Kester
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Constructor:
- BaseModel( nparams=0, ndim=1, copy=None, posIndex=[], nonZero=[], **kwargs )
- BaseModel Constructor.
<br>
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
posIndex : list of int
indices of parameters that need to be > 0
nonZero : list of int
indices of parameters that cannot be zero.
they are replaced by self.tiny
kwargs
for internal use.
Methods defined here:
- baseParameterName( k )
- Return the name of the indicated parameter.
Parameters
---------
k : int
parameter number.
- baseParameterUnit( k )
- Return the name of the indicated parameter.
Parameters
---------
k : int
parameter number.
- basePrior( k )
- Return the prior of the indicated parameter.
Parameters
----------
k : int
parameter number.
- checkParameter( param )
- Return parameters corrected for positivity and Non-zero.
Parameters
----------
param : array_like
values for the parameters.
- checkPositive( param )
- Check parameters for positivity. Silently correct.
Parameters
----------
params : array_like
values for the parameters
- checkZeroParameter( param )
- Check parameters for Non-zero. Correct after one warning.
Parameters
----------
params : array_like
values for the parameters
- 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.
Parameters
----------
xdata : array_like
values at which to calculate the derivative
param : array_like
values for the parameters. (default: model.parameters)
- getParameterName( k )
- Return the name of the indicated parameter.
Parameters
---------
k : int
parameter number.
- getParameterUnit( k )
- Return the unit of the indicated parameter.
Parameters
---------
k : int
parameter number.
- getPrior( k )
- Return the prior of the indicated parameter.
Parameters
---------
k : int
parameter number.
- hasLimits( fitindex=None )
- Return True if the model has limits set.
- hasPriors( isBound=True )
- Return True when the model has priors for all its parameters.
Parameters
----------
isBound : bool
Also check if the prior is bound.
- isDynamic()
- Whether the model implements Dynamic
- isModifiable()
- Whether the model implements Modifiable
- partial( xdata, param, parlist=None )
- Returns the partial derivatives calculated at the inputs.
Parameters
----------
xdata : array_like
values at which to calculate the result
param : array_like
values for the parameters.
parlist : None or array_like
indices of active parameters
- result( xdata, param )
- Returns the result calculated at the xdatas.
Parameters
----------
xdata : array_like
values at which to calculate the result
param : array_like
values for the parameters.
- setPrior( k, prior=None, **kwargs )
- set the prior and/or limits for the indicated parameter.
The prior (by default UniformPrior) is appended when k is equal to np, the
length of the existing list of priors. It replaces the prior when k < np
and it generates an error when k > np
Parameters
---------
k : int
parameter number.
prior : Prior
prior for the parameter
kwargs : dict
attributes to be passed to the prior
- shortName()
- Return a short version the string representation: upto first non-letter.
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