o3seespy.test¶

class o3seespy.command.test.EnergyIncr(osi, tol, max_iter, p_flag=0, n_type=2)[source]¶

Bases: TestBase

The EnergyIncr Test Class

Create a EnergyIncr test, which uses the dot product of the solution vector and norm of the right hand side of the matrix equation to determine if convergence has been reached.

Initial method for EnergyIncr

Parameters

osi (o3seespy.OpenSeesInstance) –
tol (float) – Tolerance criteria used to check for convergence.
max_iter (int) – Max number of iterations to check
p_flag (int, optional) – Print flag : * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\delta u$ and $r(u)$ vectors. * 5 if it fails to converge at end of numiter it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.EnergyIncr(osi, tol=1.0, max_iter=1, p_flag=0, n_type=2)

op_type = 'EnergyIncr'¶

class o3seespy.command.test.FixedNumIter(osi, max_iter, p_flag=0, n_type=2)[source]¶

Bases: TestBase

The FixedNumIter Test Class

Create a FixedNumIter test, that performs a fixed number of iterations without testing for convergence.

Initial method for FixedNumIter

Parameters

osi (o3seespy.OpenSeesInstance) –
max_iter (int) – Max number of iterations to check
p_flag (int, optional) – Print flag : * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\delta u$ and $r(u)$ vectors. * 5 if it fails to converge at end of numiter it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.FixedNumIter(osi, max_iter=1, p_flag=0, n_type=2)

op_type = 'FixedNumIter'¶

class o3seespy.command.test.NormDispAndUnbalance(osi, tol_incr, tol_r, max_iter, p_flag=0, n_type=2, max_incr=None)[source]¶

Bases: TestBase

The NormDispAndUnbalance Test Class

Create a NormDispAndUnbalance test, which check if both

Initial method for NormDispAndUnbalance

Parameters

osi (o3seespy.OpenSeesInstance) –
tol_incr (float) – Tolerance for right hand residual
tol_r (float) –
max_iter (int) – Max number of iterations to check
p_flag (int, optional) – Print flag : * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\delta u$ and $r(u)$ vectors. * 5 if it fails to converge at end of numiter it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).
max_incr (int, optional) – Maximum times of error increasing.

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.NormDispAndUnbalance(osi, tol_incr=1.0, tol_r=1, max_iter=1, p_flag=0, n_type=2)

op_type = 'NormDispAndUnbalance'¶

class o3seespy.command.test.NormDispIncr(osi, tol, max_iter, p_flag=0, n_type=2)[source]¶

Bases: TestBase

The NormDispIncr Test Class

Create a NormUnbalance test, which uses the norm of the left hand side solution vector of the matrix equation to determine if convergence has been reached.

Initial method for NormDispIncr

Parameters

osi (o3seespy.OpenSeesInstance) –
tol (float) – Tolerance criteria used to check for convergence.
max_iter (int) – Max number of iterations to check
p_flag (int, optional) – Print flag : * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\delta u$ and $r(u)$ vectors. * 5 if it fails to converge at end of numiter it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.NormDispIncr(osi, tol=1.0, max_iter=1, p_flag=0, n_type=2)

op_type = 'NormDispIncr'¶

class o3seespy.command.test.NormDispOrUnbalance(osi, tol_incr, tol_r, max_iter, p_flag=0, n_type=2, maxincr=-1)[source]¶

Bases: TestBase

The NormDispOrUnbalance Test Class

Create a NormDispOrUnbalance test, which check if both

Initial method for NormDispOrUnbalance

Parameters

osi (o3seespy.OpenSeesInstance) –
tol_incr (float) – Tolerance for right hand residual
tol_r (None) –
max_iter (int) – Max number of iterations to check
p_flag (int, optional) – Print flag : * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\delta u$ and $r(u)$ vectors. * 5 if it fails to converge at end of numiter it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).
maxincr (int, optional) – Maximum times of error increasing.

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.NormDispOrUnbalance(osi, tol_incr=1.0, tol_r=1, max_iter=1, p_flag=0, n_type=2, maxincr=-1)

op_type = 'NormDispOrUnbalance'¶

class o3seespy.command.test.NormUnbalance(osi, tol, max_iter, p_flag=0, n_type=2, max_incr: Optional[float] = None)[source]¶

Bases: TestBase

The NormUnbalance Test Class

Create a NormUnbalance test, which uses the norm of the right hand side of the matrix equation to determine if convergence has been reached.

Initial method for NormUnbalance

Parameters

osi (o3seespy.OpenSeesInstance) –
tol (float) – Tolerance criteria used to check for convergence.
max_iter (int) – Max number of iterations to check
p_flag (int, optional) – Print flag : * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\delta u$ and $r(u)$ vectors. * 5 if it fails to converge at end of numiter it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).
max_incr (int (default=True), optional) – Maximum times of error increasing.

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.NormUnbalance(osi, tol=1.0, max_iter=1, p_flag=0, n_type=2, max_incr=None)

op_type = 'NormUnbalance'¶

class o3seespy.command.test.RelativeEnergyIncr(osi, tol, max_iter, p_flag=0, n_type=2)[source]¶

Bases: TestBase

The RelativeEnergyIncr Test Class

Create a RelativeEnergyIncr test, which uses the relative dot product of the solution vector and norm of the right hand side of the matrix equation to determine if convergence has been reached.

Initial method for RelativeEnergyIncr

Parameters

osi (o3seespy.OpenSeesInstance) –
tol (float) – Tolerance criteria used to check for convergence.
max_iter (int) – Max number of iterations to check
p_flag (int, optional) – Print flag : * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\delta u$ and $r(u)$ vectors. * 5 if it fails to converge at end of numiter it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.RelativeEnergyIncr(osi, tol=1.0, max_iter=1, p_flag=0, n_type=2)

op_type = 'RelativeEnergyIncr'¶

class o3seespy.command.test.RelativeNormDispIncr(osi, tol, max_iter, p_flag=0, n_type=2)[source]¶

Bases: TestBase

The RelativeNormDispIncr Test Class

Create a RelativeNormDispIncr test, which uses the relative of the solution vector of the matrix equation to determine if convergence has been reached.

Initial method for RelativeNormDispIncr

Parameters

osi (o3seespy.OpenSeesInstance) –
tol (float) – Tolerance criteria used to check for convergence.
max_iter (int) –
Max number of iterations to check p_flag: int

Print flag (optional): * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\\delta u$ and $R(u)$ vectors. * 5 if it fails to converge at end of numiter

it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.RelativeNormDispIncr(osi, tol=1.0, max_iter=1, p_flag=0, n_type=2)

op_type = 'RelativeNormDispIncr'¶

class o3seespy.command.test.RelativeNormUnbalance(osi, tol, max_iter, p_flag=0, n_type=2)[source]¶

Bases: TestBase

The RelativeNormUnbalance Test Class

Create a RelativeNormUnbalance test, which uses the relative norm of the right hand side of the matrix equation to determine if convergence has been reached.

Initial method for RelativeNormUnbalance

Parameters

osi (o3seespy.OpenSeesInstance) –
tol (float) – Tolerance criteria used to check for convergence.
max_iter (int) – Max number of iterations to check
p_flag (int, optional) – Print flag : * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\delta u$ and $r(u)$ vectors. * 5 if it fails to converge at end of numiter it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.RelativeNormUnbalance(osi, tol=1.0, max_iter=1, p_flag=0, n_type=2)

op_type = 'RelativeNormUnbalance'¶

class o3seespy.command.test.RelativeTotalNormDispIncr(osi, tol, max_iter, p_flag=0, n_type=2)[source]¶

Bases: TestBase

The RelativeTotalNormDispIncr Test Class

Create a RelativeTotalNormDispIncr test, which uses the ratio of the current norm to the total norm (the sum of all the norms since last convergence) of the solution vector.

Initial method for RelativeTotalNormDispIncr

Parameters

osi (o3seespy.OpenSeesInstance) –
tol (float) – Tolerance criteria used to check for convergence.
max_iter (int) – Max number of iterations to check
p_flag (int, optional) – Print flag : * 0 print nothing. * 1 print information on norms each time test() is invoked. * 2 print information on norms and number of iterations at end of successful test. * 4 at each step it will print the norms and also the $\delta u$ and $r(u)$ vectors. * 5 if it fails to converge at end of numiter it will print an error message but return a successfull test.
n_type (int, optional) – Type of norm, (0 = max-norm, 1 = 1-norm, 2 = 2-norm).

Examples

>>> import o3seespy as o3
>>> osi = o3.OpenSeesInstance(ndm=2)
>>> o3.test.RelativeTotalNormDispIncr(osi, tol=1.0, max_iter=1, p_flag=0, n_type=2)

op_type = 'RelativeTotalNormDispIncr'¶

class o3seespy.command.test.TestBase[source]¶

Bases: OpenSeesObject

op_base_type = 'test'¶

reapply(osi)[source]¶

to_process(osi)[source]¶

o3seespy.test¶

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