leastsq.py

Functions
	leastsq.LeastSqModelData.buildModel (self)
	adding the variables and constraints to the model
	leastsq.LeastSqModelData.evaluateNonlinearTerm (self, x, rowno, ignerr, thread)
	callback method for evaluating the nonlinear terms in a given row
	leastsq.LeastSqModelData.evaluateNonlinearJacobian (self, x, rowno, jacnum, ignerr, thread)
	callback method for evaluating the jacobian for the nonlinear terms in a given row

Detailed Description

Solves a nonlinear least squares model.

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()

leastsq.LeastSqModelData.buildModel

(

self

)

adding the variables and constraints to the model

Definition at line 68 of file leastsq.py.

evaluateNonlinearTerm()

leastsq.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 115 of file leastsq.py.

evaluateNonlinearJacobian()

leastsq.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 139 of file leastsq.py.