RelativeNormUnbalanceTest

RelativeNormUnbalanceTest(tol: float, max_iter: int, print_flag: int = 0, norm_type: int = 2)

Bases: Test

Relative norm unbalance convergence test.

RelativeNormUnbalanceTest compares the current norm of the residual vector against the initial residual norm scaled by a tolerance. Convergence is achieved when current residual norm <= tol * initial residual norm.

Tcl form

test RelativeNormUnbalance <tol> <maxIter> <printFlag> <normType>

Example

from femora.core.model import Model

model = Model()
test = model.analysis.test.relativenormunbalance(
    tol=1e-6,
    max_iter=100,
    print_flag=1,
    norm_type=2,
)

Create a RelativeNormUnbalance convergence test.

Parameters:

Name	Type	Description	Default
`tol`	`float`	Tolerance criteria for convergence.	required
`max_iter`	`int`	Maximum number of iterations to perform before returning failure.	required
`print_flag`	`int`	Print control flag. 0 prints nothing, 1 prints norm info each iteration, 2 prints norms and iterations at success, 4 prints norms, displacement, and residual vectors, 5 prints warnings only.	`0`
`norm_type`	`int`	Mathematical norm type to use. 0 for Max-norm, 1 for 1-norm, 2 for 2-norm (default).	`2`