leastsq5.py

Functions
	leastsq5.LeastSqModelData.buildModel (self)
	adding the variables and constraints to the model
	leastsq5.LeastSqModelData.evaluateNonlinearTerm (self, x, rowno, ignerr, thread)
	callback method for evaluating the nonlinear terms in a given row
	leastsq5.LeastSqModelData.evaluateNonlinearJacobian (self, x, rowno, jacnum, ignerr, thread)
	callback method for evaluating the jacobian for the nonlinear terms in a given row
	leastsq5.LeastSqModelData.evaluateDirectionalSD (self, x, dx, rowno, jacnum, thread)
	computes the directional second derivative for a single constraint

Detailed Description

This model is similar to leastsq, but this time we define 2nd order information in the form of a 2DDir routine.

We solve the following nonlinear least squares model:

\[ \min \sum_i res_{i}^2 \!! \sum_j ( a_{ij}x_j + b_{ij}x_j^2 ) + res_i = obs_i \]

where \(a\), \(b\), and \(obs\) are known data, and \(res\) and \(x\) are the variables of the model.

For more information about the individual callbacks, please have a look at the source code.

Function Documentation

buildModel()

leastsq5.LeastSqModelData.buildModel

(

self

)

adding the variables and constraints to the model

Definition at line 68 of file leastsq5.py.

evaluateNonlinearTerm()

leastsq5.LeastSqModelData.evaluateNonlinearTerm	(		self,
			x,
			rowno,
			ignerr,
			thread )

callback method for evaluating the nonlinear terms in a given row

Parameters

x	the solution vector that needs to be evaluated.
rowno	the number for the row in which the nonlinear term exists.
ignerr	a boolean to indicate whether the current point is safe or unsafe.
thread	the index of the thread from which this method is being called from.

Returns

the value of the nonlinear terms.

Notes: an error in the evaluation is reported by calling errorInEvaluation()

Definition at line 118 of file leastsq5.py.

evaluateNonlinearJacobian()

leastsq5.LeastSqModelData.evaluateNonlinearJacobian	(		self,
			x,
			rowno,
			jacnum,
			ignerr,
			thread )

callback method for evaluating the jacobian for the nonlinear terms in a given row

Parameters

x	the solution vector that needs to be evaluated.
rowno	the number for the row in which the nonlinear term exists.
jacnum	vector with a list of column numbers for the nonlinear nonzero Jacobian elements in the row.
ignerr	a boolean to indicate whether the current point is safe or unsafe.
thread	the index of the thread from which this method is being called from.

Returns

a vector the length of jacnum that contains the jacobian values for the referenced elements.

Notes: an error in the evaluation is reported by calling errorInEvaluation()

Definition at line 142 of file leastsq5.py.

evaluateDirectionalSD()

leastsq5.LeastSqModelData.evaluateDirectionalSD	(		self,
			x,
			dx,
			rowno,
			jacnum,
			thread )

computes the directional second derivative for a single constraint

Parameters

x	the solution vector that needs to be evaluated.
dx	vector with the direction in which the directional second derivatives should be computed.
rowno	the number for the row in which the nonlinear term exists.
jacnum	vector with a list of column numbers for the nonlinear nonzero Jacobian elements in the row.
thread	the index of the thread from which this method is being called from.

returns a vector for the directional second derivative. The length of the vector is the number of variables.

Notes: an error in the evaluation is reported by calling errorInEvaluation()

Definition at line 161 of file leastsq5.py.