sellar.py

Test objects for the sellar two discipline problem.

From Sellar’s analytic problem.

Sellar, R. S., Batill, S. M., and Renaud, J. E., “Response Surface Based, Concurrent Subspace Optimization for Multidisciplinary System Design,” Proceedings References 79 of the 34th AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, January 1996.

class openmdao.test_suite.components.sellar.SellarDerivatives(**kwargs)

Bases: Group

Group containing the Sellar MDA. This version uses the disciplines with derivatives.

Attributes:

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

model_options

Get the model options from self._problem_meta.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
add_subsystem(name, subsys[, promotes, ...])	Add a subsystem.
approx_totals([method, step, form, step_calc])	Approximate derivatives for a Group using the specified approximation method.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
compute_sys_graph([comps_only, add_edge_info])	Compute a dependency graph for subsystems in this group.
configure()	Configure this group to assign children settings.
connect(src_name, tgt_name[, src_indices, ...])	Connect source src_name to target tgt_name in this namespace.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_indep_vars(local[, include_discrete])	Return a dict of independant variables contained in this group or any of its subgroups.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
guess_nonlinear(inputs, outputs, residuals)	Provide initial guess for states.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this Group contains only explicit systems and has no cycles.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
promotes(subsys_name[, any, inputs, ...])	Promote a variable in the model tree.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln, driver])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_initial_values()	Set all input and output variables to their declared initial values.
set_input_defaults(name[, val, units, src_shape])	Specify metadata to be assumed when multiple inputs are promoted to the same name.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_order(new_order)	Specify a new execution order for subsystems in this group.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Build this group.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

display_conn_graph
display_dataflow_graph

initialize()

Perform any one-time initialization run at instantiation.

setup()

Build this group.

This method should be overidden by your Group’s method. The reason for using this method to add subsystem is to save memory and setup time when using your Group while running under MPI. This avoids the creation of systems that will not be used in the current process.

You may call ‘add_subsystem’ to add systems to this group. You may also issue connections, and set the linear and nonlinear solvers for this group level. You cannot safely change anything on children systems; use the ‘configure’ method instead.

Available attributes:

name pathname comm options

class openmdao.test_suite.components.sellar.SellarDerivativesConnected(**kwargs)

Bases: Group

Group containing the Sellar MDA. This version uses the disciplines with derivatives.

Attributes:

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

model_options

Get the model options from self._problem_meta.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
add_subsystem(name, subsys[, promotes, ...])	Add a subsystem.
approx_totals([method, step, form, step_calc])	Approximate derivatives for a Group using the specified approximation method.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
compute_sys_graph([comps_only, add_edge_info])	Compute a dependency graph for subsystems in this group.
configure()	Configure this group to assign children settings.
connect(src_name, tgt_name[, src_indices, ...])	Connect source src_name to target tgt_name in this namespace.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_indep_vars(local[, include_discrete])	Return a dict of independant variables contained in this group or any of its subgroups.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
guess_nonlinear(inputs, outputs, residuals)	Provide initial guess for states.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this Group contains only explicit systems and has no cycles.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
promotes(subsys_name[, any, inputs, ...])	Promote a variable in the model tree.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln, driver])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_initial_values()	Set all input and output variables to their declared initial values.
set_input_defaults(name[, val, units, src_shape])	Specify metadata to be assumed when multiple inputs are promoted to the same name.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_order(new_order)	Specify a new execution order for subsystems in this group.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Build this group.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

display_conn_graph
display_dataflow_graph

setup()

Build this group.

This method should be overidden by your Group’s method. The reason for using this method to add subsystem is to save memory and setup time when using your Group while running under MPI. This avoids the creation of systems that will not be used in the current process.

You may call ‘add_subsystem’ to add systems to this group. You may also issue connections, and set the linear and nonlinear solvers for this group level. You cannot safely change anything on children systems; use the ‘configure’ method instead.

Available attributes:

name pathname comm options

class openmdao.test_suite.components.sellar.SellarDerivativesGrouped(**kwargs)

Bases: Group

Group containing the Sellar MDA. This version uses the disciplines with derivatives.

Attributes:

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

model_options

Get the model options from self._problem_meta.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
add_subsystem(name, subsys[, promotes, ...])	Add a subsystem.
approx_totals([method, step, form, step_calc])	Approximate derivatives for a Group using the specified approximation method.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
compute_sys_graph([comps_only, add_edge_info])	Compute a dependency graph for subsystems in this group.
configure()	Configure this group to assign children settings.
connect(src_name, tgt_name[, src_indices, ...])	Connect source src_name to target tgt_name in this namespace.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_indep_vars(local[, include_discrete])	Return a dict of independant variables contained in this group or any of its subgroups.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
guess_nonlinear(inputs, outputs, residuals)	Provide initial guess for states.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this Group contains only explicit systems and has no cycles.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
promotes(subsys_name[, any, inputs, ...])	Promote a variable in the model tree.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln, driver])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_initial_values()	Set all input and output variables to their declared initial values.
set_input_defaults(name[, val, units, src_shape])	Specify metadata to be assumed when multiple inputs are promoted to the same name.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_order(new_order)	Specify a new execution order for subsystems in this group.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Build this group.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

display_conn_graph
display_dataflow_graph

initialize()

Perform any one-time initialization run at instantiation.

setup()

Build this group.

This method should be overidden by your Group’s method. The reason for using this method to add subsystem is to save memory and setup time when using your Group while running under MPI. This avoids the creation of systems that will not be used in the current process.

You may call ‘add_subsystem’ to add systems to this group. You may also issue connections, and set the linear and nonlinear solvers for this group level. You cannot safely change anything on children systems; use the ‘configure’ method instead.

Available attributes:

name pathname comm options

class openmdao.test_suite.components.sellar.SellarDis1(units=None, scaling=None)

Bases: ExplicitComponent

Component containing Discipline 1 – no derivatives version.

Attributes:

checking

Return True if check_partials or check_totals is executing.

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_discrete_input(name, val[, desc, tags, ...])	Add a discrete input variable to the component.
add_discrete_output(name, val[, desc, tags, ...])	Add an output variable to the component.
add_input(name[, val, shape, units, desc, ...])	Add an input variable to the component.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_output(name[, val, shape, units, ...])	Add an output variable to the component.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
check_partials([out_stream, compact_print, ...])	Check partial derivatives comprehensively for this component.
check_sparsity([method, max_nz, out_stream])	Check the sparsity of the computed jacobian against the declared sparsity.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute(inputs, outputs)	Evaluates the equation y1 = z1**2 + z2 + x1 - 0.2*y2
compute_fd_jac(jac[, method])	Force the use of finite difference to compute a jacobian.
compute_fd_sparsity([method, num_full_jacs, ...])	Use finite difference to compute a sparsity matrix.
compute_jacvec_product(inputs, d_inputs, ...)	Compute jac-vector product.
compute_partials(inputs, partials[, ...])	Compute sub-jacobian parts.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
declare_partials(of, wrt[, dependent, rows, ...])	Declare information about this component's subjacobians.
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_declare_partials_calls([sparsity])	Return a string containing declare_partials() calls based on the subjac sparsity.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this is an explicit component.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
override_method(name, method)	Dynamically add a method to this component instance.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_check_partial_options(wrt[, method, ...])	Set options that will be used for checking partial derivatives.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Declare inputs and outputs.
setup_partials()	Declare partials.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

__init__(units=None, scaling=None)

Store some bound methods so we can detect runtime overrides.

compute(inputs, outputs)

Evaluates the equation y1 = z1**2 + z2 + x1 - 0.2*y2

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.

class openmdao.test_suite.components.sellar.SellarDis1CS(units=None, scaling=None)

Bases: SellarDis1

Component containing Discipline 1 – complex step version.

Attributes:

checking

Return True if check_partials or check_totals is executing.

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_discrete_input(name, val[, desc, tags, ...])	Add a discrete input variable to the component.
add_discrete_output(name, val[, desc, tags, ...])	Add an output variable to the component.
add_input(name[, val, shape, units, desc, ...])	Add an input variable to the component.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_output(name[, val, shape, units, ...])	Add an output variable to the component.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
check_partials([out_stream, compact_print, ...])	Check partial derivatives comprehensively for this component.
check_sparsity([method, max_nz, out_stream])	Check the sparsity of the computed jacobian against the declared sparsity.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute(inputs, outputs)	Evaluates the equation y1 = z1**2 + z2 + x1 - 0.2*y2
compute_fd_jac(jac[, method])	Force the use of finite difference to compute a jacobian.
compute_fd_sparsity([method, num_full_jacs, ...])	Use finite difference to compute a sparsity matrix.
compute_jacvec_product(inputs, d_inputs, ...)	Compute jac-vector product.
compute_partials(inputs, partials[, ...])	Compute sub-jacobian parts.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
declare_partials(of, wrt[, dependent, rows, ...])	Declare information about this component's subjacobians.
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_declare_partials_calls([sparsity])	Return a string containing declare_partials() calls based on the subjac sparsity.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this is an explicit component.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
override_method(name, method)	Dynamically add a method to this component instance.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_check_partial_options(wrt[, method, ...])	Set options that will be used for checking partial derivatives.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Declare inputs and outputs.
setup_partials()	Declare partials.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.

class openmdao.test_suite.components.sellar.SellarDis1withDerivatives(units=None, scaling=None)

Bases: SellarDis1

Component containing Discipline 1 – derivatives version.

Attributes:

checking

Return True if check_partials or check_totals is executing.

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_discrete_input(name, val[, desc, tags, ...])	Add a discrete input variable to the component.
add_discrete_output(name, val[, desc, tags, ...])	Add an output variable to the component.
add_input(name[, val, shape, units, desc, ...])	Add an input variable to the component.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_output(name[, val, shape, units, ...])	Add an output variable to the component.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
check_partials([out_stream, compact_print, ...])	Check partial derivatives comprehensively for this component.
check_sparsity([method, max_nz, out_stream])	Check the sparsity of the computed jacobian against the declared sparsity.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute(inputs, outputs)	Evaluates the equation y1 = z1**2 + z2 + x1 - 0.2*y2
compute_fd_jac(jac[, method])	Force the use of finite difference to compute a jacobian.
compute_fd_sparsity([method, num_full_jacs, ...])	Use finite difference to compute a sparsity matrix.
compute_jacvec_product(inputs, d_inputs, ...)	Compute jac-vector product.
compute_partials(inputs, partials)	Jacobian for Sellar discipline 1.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
declare_partials(of, wrt[, dependent, rows, ...])	Declare information about this component's subjacobians.
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_declare_partials_calls([sparsity])	Return a string containing declare_partials() calls based on the subjac sparsity.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this is an explicit component.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
override_method(name, method)	Dynamically add a method to this component instance.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_check_partial_options(wrt[, method, ...])	Set options that will be used for checking partial derivatives.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Declare inputs and outputs.
setup_partials()	Declare partials.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

compute_partials(inputs, partials)

Jacobian for Sellar discipline 1.

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.

class openmdao.test_suite.components.sellar.SellarDis2(units=None, scaling=None)

Bases: ExplicitComponent

Component containing Discipline 2 – no derivatives version.

Attributes:

checking

Return True if check_partials or check_totals is executing.

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_discrete_input(name, val[, desc, tags, ...])	Add a discrete input variable to the component.
add_discrete_output(name, val[, desc, tags, ...])	Add an output variable to the component.
add_input(name[, val, shape, units, desc, ...])	Add an input variable to the component.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_output(name[, val, shape, units, ...])	Add an output variable to the component.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
check_partials([out_stream, compact_print, ...])	Check partial derivatives comprehensively for this component.
check_sparsity([method, max_nz, out_stream])	Check the sparsity of the computed jacobian against the declared sparsity.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute(inputs, outputs)	Evaluates the equation y2 = y1**(.5) + z1 + z2
compute_fd_jac(jac[, method])	Force the use of finite difference to compute a jacobian.
compute_fd_sparsity([method, num_full_jacs, ...])	Use finite difference to compute a sparsity matrix.
compute_jacvec_product(inputs, d_inputs, ...)	Compute jac-vector product.
compute_partials(inputs, partials[, ...])	Compute sub-jacobian parts.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
declare_partials(of, wrt[, dependent, rows, ...])	Declare information about this component's subjacobians.
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_declare_partials_calls([sparsity])	Return a string containing declare_partials() calls based on the subjac sparsity.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this is an explicit component.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
override_method(name, method)	Dynamically add a method to this component instance.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_check_partial_options(wrt[, method, ...])	Set options that will be used for checking partial derivatives.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Declare inputs and outputs.
setup_partials()	Declare partials.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

__init__(units=None, scaling=None)

Store some bound methods so we can detect runtime overrides.

compute(inputs, outputs)

Evaluates the equation y2 = y1**(.5) + z1 + z2

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.

class openmdao.test_suite.components.sellar.SellarDis2CS(units=None, scaling=None)

Bases: SellarDis2

Component containing Discipline 2 – complex step version.

Attributes:

checking

Return True if check_partials or check_totals is executing.

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_discrete_input(name, val[, desc, tags, ...])	Add a discrete input variable to the component.
add_discrete_output(name, val[, desc, tags, ...])	Add an output variable to the component.
add_input(name[, val, shape, units, desc, ...])	Add an input variable to the component.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_output(name[, val, shape, units, ...])	Add an output variable to the component.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
check_partials([out_stream, compact_print, ...])	Check partial derivatives comprehensively for this component.
check_sparsity([method, max_nz, out_stream])	Check the sparsity of the computed jacobian against the declared sparsity.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute(inputs, outputs)	Evaluates the equation y2 = y1**(.5) + z1 + z2
compute_fd_jac(jac[, method])	Force the use of finite difference to compute a jacobian.
compute_fd_sparsity([method, num_full_jacs, ...])	Use finite difference to compute a sparsity matrix.
compute_jacvec_product(inputs, d_inputs, ...)	Compute jac-vector product.
compute_partials(inputs, partials[, ...])	Compute sub-jacobian parts.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
declare_partials(of, wrt[, dependent, rows, ...])	Declare information about this component's subjacobians.
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_declare_partials_calls([sparsity])	Return a string containing declare_partials() calls based on the subjac sparsity.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this is an explicit component.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
override_method(name, method)	Dynamically add a method to this component instance.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_check_partial_options(wrt[, method, ...])	Set options that will be used for checking partial derivatives.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Declare inputs and outputs.
setup_partials()	Declare partials.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.

class openmdao.test_suite.components.sellar.SellarDis2withDerivatives(units=None, scaling=None)

Bases: SellarDis2

Component containing Discipline 2 – derivatives version.

Attributes:

checking

Return True if check_partials or check_totals is executing.

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_discrete_input(name, val[, desc, tags, ...])	Add a discrete input variable to the component.
add_discrete_output(name, val[, desc, tags, ...])	Add an output variable to the component.
add_input(name[, val, shape, units, desc, ...])	Add an input variable to the component.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_output(name[, val, shape, units, ...])	Add an output variable to the component.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
check_partials([out_stream, compact_print, ...])	Check partial derivatives comprehensively for this component.
check_sparsity([method, max_nz, out_stream])	Check the sparsity of the computed jacobian against the declared sparsity.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute(inputs, outputs)	Evaluates the equation y2 = y1**(.5) + z1 + z2
compute_fd_jac(jac[, method])	Force the use of finite difference to compute a jacobian.
compute_fd_sparsity([method, num_full_jacs, ...])	Use finite difference to compute a sparsity matrix.
compute_jacvec_product(inputs, d_inputs, ...)	Compute jac-vector product.
compute_partials(inputs, J)	Jacobian for Sellar discipline 2.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
declare_partials(of, wrt[, dependent, rows, ...])	Declare information about this component's subjacobians.
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_declare_partials_calls([sparsity])	Return a string containing declare_partials() calls based on the subjac sparsity.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this is an explicit component.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
override_method(name, method)	Dynamically add a method to this component instance.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_check_partial_options(wrt[, method, ...])	Set options that will be used for checking partial derivatives.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Declare inputs and outputs.
setup_partials()	Declare partials.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

compute_partials(inputs, J)

Jacobian for Sellar discipline 2.

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.

class openmdao.test_suite.components.sellar.SellarImplicitDis1(units=None, scaling=None)

Bases: ImplicitComponent

Component containing Discipline 1 – no derivatives version.

Attributes:

checking

Return True if check_partials or check_totals is executing.

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_discrete_input(name, val[, desc, tags, ...])	Add a discrete input variable to the component.
add_discrete_output(name, val[, desc, tags, ...])	Add an output variable to the component.
add_input(name[, val, shape, units, desc, ...])	Add an input variable to the component.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_output(name[, val])	Add an output variable to the component.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_residual(name[, shape, units, desc, ref])	Add a residual variable to the component.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
apply_linear(inputs, outputs, d_inputs, ...)	Compute jac-vector product.
apply_nonlinear(inputs, outputs, resids)	Evaluates the equation y1 = z1**2 + z2 + x1 - 0.2*y2
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
check_partials([out_stream, compact_print, ...])	Check partial derivatives comprehensively for this component.
check_sparsity([method, max_nz, out_stream])	Check the sparsity of the computed jacobian against the declared sparsity.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute_fd_jac(jac[, method])	Force the use of finite difference to compute a jacobian.
compute_fd_sparsity([method, num_full_jacs, ...])	Use finite difference to compute a sparsity matrix.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
declare_partials(of, wrt[, dependent, rows, ...])	Declare information about this component's subjacobians.
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_declare_partials_calls([sparsity])	Return a string containing declare_partials() calls based on the subjac sparsity.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
guess_nonlinear(inputs, outputs, residuals)	Provide initial guess for states.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this is an explicit component.
linearize(inputs, outputs, J)	Jacobian for Sellar discipline 1.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
override_method(name, method)	Dynamically add a method to this component instance.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_check_partial_options(wrt[, method, ...])	Set options that will be used for checking partial derivatives.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Declare inputs and outputs.
setup_partials()	Declare partials.
setup_residuals()	User hook for adding named residuals to this component.
solve_linear(d_outputs, d_residuals, mode)	Apply inverse jac product.
solve_nonlinear(inputs, outputs)	Compute outputs given inputs.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

__init__(units=None, scaling=None)

Store some bound methods so we can detect runtime overrides.

apply_nonlinear(inputs, outputs, resids)

Evaluates the equation y1 = z1**2 + z2 + x1 - 0.2*y2

linearize(inputs, outputs, J)

Jacobian for Sellar discipline 1.

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.

class openmdao.test_suite.components.sellar.SellarImplicitDis2(units=None, scaling=None)

Bases: ImplicitComponent

Component containing Discipline 2 – implicit version.

Attributes:

checking

Return True if check_partials or check_totals is executing.

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_discrete_input(name, val[, desc, tags, ...])	Add a discrete input variable to the component.
add_discrete_output(name, val[, desc, tags, ...])	Add an output variable to the component.
add_input(name[, val, shape, units, desc, ...])	Add an input variable to the component.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_output(name[, val])	Add an output variable to the component.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_residual(name[, shape, units, desc, ref])	Add a residual variable to the component.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
apply_linear(inputs, outputs, d_inputs, ...)	Compute jac-vector product.
apply_nonlinear(inputs, outputs, resids)	Evaluates the equation y2 = y1**(.5) + z1 + z2
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
check_partials([out_stream, compact_print, ...])	Check partial derivatives comprehensively for this component.
check_sparsity([method, max_nz, out_stream])	Check the sparsity of the computed jacobian against the declared sparsity.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute_fd_jac(jac[, method])	Force the use of finite difference to compute a jacobian.
compute_fd_sparsity([method, num_full_jacs, ...])	Use finite difference to compute a sparsity matrix.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
declare_partials(of, wrt[, dependent, rows, ...])	Declare information about this component's subjacobians.
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_declare_partials_calls([sparsity])	Return a string containing declare_partials() calls based on the subjac sparsity.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
guess_nonlinear(inputs, outputs, residuals)	Provide initial guess for states.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this is an explicit component.
linearize(inputs, outputs, J)	Jacobian for Sellar discipline 2.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
override_method(name, method)	Dynamically add a method to this component instance.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_check_partial_options(wrt[, method, ...])	Set options that will be used for checking partial derivatives.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Declare inputs and outputs.
setup_partials()	Declare partials.
setup_residuals()	User hook for adding named residuals to this component.
solve_linear(d_outputs, d_residuals, mode)	Apply inverse jac product.
solve_nonlinear(inputs, outputs)	Compute outputs given inputs.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

__init__(units=None, scaling=None)

Store some bound methods so we can detect runtime overrides.

apply_nonlinear(inputs, outputs, resids)

Evaluates the equation y2 = y1**(.5) + z1 + z2

linearize(inputs, outputs, J)

Jacobian for Sellar discipline 2.

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.

class openmdao.test_suite.components.sellar.SellarNoDerivatives(**kwargs)

Bases: Group

Group containing the Sellar MDA. This version uses the disciplines without derivatives.

Attributes:

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

model_options

Get the model options from self._problem_meta.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
add_subsystem(name, subsys[, promotes, ...])	Add a subsystem.
approx_totals([method, step, form, step_calc])	Approximate derivatives for a Group using the specified approximation method.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
compute_sys_graph([comps_only, add_edge_info])	Compute a dependency graph for subsystems in this group.
configure()	Configure this group to assign children settings.
connect(src_name, tgt_name[, src_indices, ...])	Connect source src_name to target tgt_name in this namespace.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_indep_vars(local[, include_discrete])	Return a dict of independant variables contained in this group or any of its subgroups.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
guess_nonlinear(inputs, outputs, residuals)	Provide initial guess for states.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this Group contains only explicit systems and has no cycles.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
promotes(subsys_name[, any, inputs, ...])	Promote a variable in the model tree.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln, driver])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_initial_values()	Set all input and output variables to their declared initial values.
set_input_defaults(name[, val, units, src_shape])	Specify metadata to be assumed when multiple inputs are promoted to the same name.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_order(new_order)	Specify a new execution order for subsystems in this group.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Build this group.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

display_conn_graph
display_dataflow_graph

configure()

Configure this group to assign children settings.

This method may optionally be overidden by your Group’s method.

You may only use this method to change settings on your children subsystems. This includes setting solvers in cases where you want to override the defaults.

You can assume that the full hierarchy below your level has been instantiated and has already called its own configure methods.

Available attributes:

name pathname comm options system hieararchy with attribute access

initialize()

Perform any one-time initialization run at instantiation.

setup()

Build this group.

This method should be overidden by your Group’s method. The reason for using this method to add subsystem is to save memory and setup time when using your Group while running under MPI. This avoids the creation of systems that will not be used in the current process.

You may call ‘add_subsystem’ to add systems to this group. You may also issue connections, and set the linear and nonlinear solvers for this group level. You cannot safely change anything on children systems; use the ‘configure’ method instead.

Available attributes:

name pathname comm options

class openmdao.test_suite.components.sellar.SellarProblem(model_class=<class 'openmdao.test_suite.components.sellar.SellarDerivatives'>, **kwargs)

Bases: Problem

The Sellar problem with configurable model class.

Attributes:

driver

Get the Driver for this Problem.

msginfo

Return info to prepend to messages.

Methods

add_recorder(recorder)	Add a recorder to the problem.
check_config([logger, checks, out_file])	Perform optional error checks on a Problem.
check_partials([out_stream, includes, ...])	Check partial derivatives comprehensively for all components in your model.
check_totals([of, wrt, out_stream, ...])	Check total derivatives for the model vs.
cleanup()	Clean up resources prior to exit.
compute_jacvec_product(of, wrt, mode, seed)	Given a seed and 'of' and 'wrt' variables, compute the total jacobian vector product.
compute_totals([of, wrt, return_format, ...])	Compute derivatives of desired quantities with respect to desired inputs.
final_setup()	Perform final setup phase on problem in preparation for run.
find_feasible([case_prefix, ...])	Attempt to find design variable values which minimize the constraint violation.
get_coloring_dir(mode[, mkdir])	Get the path to the directory for the coloring files.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this problem are to be placed.
get_reports_dir([force])	Get the path to the directory where the report files should go.
get_total_coloring([coloring_info, of, wrt, ...])	Get the total coloring.
get_val(name[, units, indices, get_remote, ...])	Get an output/input variable.
is_local(name)	Return True if the named variable or system is local to the current process.
list_driver_vars([show_promoted_name, ...])	Print all design variables and responses (objectives and constraints).
list_indep_vars([include_design_vars, ...])	Retrieve the independent variables in the Problem.
list_pre_post([outfile])	Display the pre and post optimization components.
list_problem_vars([show_promoted_name, ...])	Print all design variables and responses (objectives and constraints).
load_case(case)	Pull all input and output variables from a case into the model.
record(case_name)	Record the variables at the Problem level.
run_driver([case_prefix, reset_iter_counts])	Run the driver on the model.
run_model([case_prefix, reset_iter_counts])	Run the model by calling the root system's solve_nonlinear.
set_complex_step_mode(active)	Turn on or off complex stepping mode.
set_setup_status(status, **setup_kwargs)	Set the setup status of the problem, running any setup steps that haven't been run yet.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name[, val, units, indices])	Set an output/input variable.
setup([check, logger, mode, ...])	Set up the model hierarchy.

__init__(model_class=<class 'openmdao.test_suite.components.sellar.SellarDerivatives'>, **kwargs)

Initialize attributes.

class openmdao.test_suite.components.sellar.SellarProblemWithArrays(model_class=<class 'openmdao.test_suite.components.sellar.SellarDerivatives'>, **kwargs)

Bases: Problem

The Sellar problem with ndarray variable options

Attributes:

driver

Get the Driver for this Problem.

msginfo

Return info to prepend to messages.

Methods

add_recorder(recorder)	Add a recorder to the problem.
check_config([logger, checks, out_file])	Perform optional error checks on a Problem.
check_partials([out_stream, includes, ...])	Check partial derivatives comprehensively for all components in your model.
check_totals([of, wrt, out_stream, ...])	Check total derivatives for the model vs.
cleanup()	Clean up resources prior to exit.
compute_jacvec_product(of, wrt, mode, seed)	Given a seed and 'of' and 'wrt' variables, compute the total jacobian vector product.
compute_totals([of, wrt, return_format, ...])	Compute derivatives of desired quantities with respect to desired inputs.
final_setup()	Perform final setup phase on problem in preparation for run.
find_feasible([case_prefix, ...])	Attempt to find design variable values which minimize the constraint violation.
get_coloring_dir(mode[, mkdir])	Get the path to the directory for the coloring files.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this problem are to be placed.
get_reports_dir([force])	Get the path to the directory where the report files should go.
get_total_coloring([coloring_info, of, wrt, ...])	Get the total coloring.
get_val(name[, units, indices, get_remote, ...])	Get an output/input variable.
is_local(name)	Return True if the named variable or system is local to the current process.
list_driver_vars([show_promoted_name, ...])	Print all design variables and responses (objectives and constraints).
list_indep_vars([include_design_vars, ...])	Retrieve the independent variables in the Problem.
list_pre_post([outfile])	Display the pre and post optimization components.
list_problem_vars([show_promoted_name, ...])	Print all design variables and responses (objectives and constraints).
load_case(case)	Pull all input and output variables from a case into the model.
record(case_name)	Record the variables at the Problem level.
run_driver([case_prefix, reset_iter_counts])	Run the driver on the model.
run_model([case_prefix, reset_iter_counts])	Run the model by calling the root system's solve_nonlinear.
set_complex_step_mode(active)	Turn on or off complex stepping mode.
set_setup_status(status, **setup_kwargs)	Set the setup status of the problem, running any setup steps that haven't been run yet.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name[, val, units, indices])	Set an output/input variable.
setup([check, logger, mode, ...])	Set up the model hierarchy.

__init__(model_class=<class 'openmdao.test_suite.components.sellar.SellarDerivatives'>, **kwargs)

Initialize attributes.

class openmdao.test_suite.components.sellar.SellarStateConnection(**kwargs)

Bases: Group

Group containing the Sellar MDA. This version uses the disciplines with derivatives.

Attributes:

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

model_options

Get the model options from self._problem_meta.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
add_subsystem(name, subsys[, promotes, ...])	Add a subsystem.
approx_totals([method, step, form, step_calc])	Approximate derivatives for a Group using the specified approximation method.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
compute_sys_graph([comps_only, add_edge_info])	Compute a dependency graph for subsystems in this group.
configure()	Configure this group to assign children settings.
connect(src_name, tgt_name[, src_indices, ...])	Connect source src_name to target tgt_name in this namespace.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_indep_vars(local[, include_discrete])	Return a dict of independant variables contained in this group or any of its subgroups.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
guess_nonlinear(inputs, outputs, residuals)	Provide initial guess for states.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this Group contains only explicit systems and has no cycles.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
promotes(subsys_name[, any, inputs, ...])	Promote a variable in the model tree.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln, driver])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_initial_values()	Set all input and output variables to their declared initial values.
set_input_defaults(name[, val, units, src_shape])	Specify metadata to be assumed when multiple inputs are promoted to the same name.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_order(new_order)	Specify a new execution order for subsystems in this group.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Build this group.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

display_conn_graph
display_dataflow_graph

configure()

Configure this group to assign children settings.

This method may optionally be overidden by your Group’s method.

You may only use this method to change settings on your children subsystems. This includes setting solvers in cases where you want to override the defaults.

You can assume that the full hierarchy below your level has been instantiated and has already called its own configure methods.

Available attributes:

name pathname comm options system hieararchy with attribute access

initialize()

Perform any one-time initialization run at instantiation.

setup()

Build this group.

This method should be overidden by your Group’s method. The reason for using this method to add subsystem is to save memory and setup time when using your Group while running under MPI. This avoids the creation of systems that will not be used in the current process.

You may call ‘add_subsystem’ to add systems to this group. You may also issue connections, and set the linear and nonlinear solvers for this group level. You cannot safely change anything on children systems; use the ‘configure’ method instead.

Available attributes:

name pathname comm options

class openmdao.test_suite.components.sellar.StateConnection(**kwargs)

Bases: ImplicitComponent

Define connection with an explicit equation.

Attributes:

checking

Return True if check_partials or check_totals is executing.

comm

Return the MPI communicator object for the system.

linear_solver

Get the linear solver for this system.

msginfo

Our instance pathname, if available, or our class name.

nonlinear_solver

Get the nonlinear solver for this system.

under_approx

Return True if under complex step or finite difference.

Methods

abs_meta_iter(iotype[, local, cont, discrete])	Iterate over absolute variable names and their metadata for this System.
add_constraint(name[, lower, upper, equals, ...])	Add a constraint variable to this system.
add_design_var(name[, lower, upper, ref, ...])	Add a design variable to this system.
add_discrete_input(name, val[, desc, tags, ...])	Add a discrete input variable to the component.
add_discrete_output(name, val[, desc, tags, ...])	Add an output variable to the component.
add_input(name[, val, shape, units, desc, ...])	Add an input variable to the component.
add_objective(name[, ref, ref0, index, ...])	Add a response variable to this system.
add_output(name[, val])	Add an output variable to the component.
add_recorder(recorder[, recurse])	Add a recorder to the system.
add_residual(name[, shape, units, desc, ref])	Add a residual variable to the component.
add_response(name, type_[, lower, upper, ...])	Add a response variable to this system.
apply_linear(inputs, outputs, d_inputs, ...)	Compute jac-vector product.
apply_nonlinear(inputs, outputs, residuals)	Don't solve; just calculate the residual.
best_partial_deriv_direction()	Return the best direction for partial deriv calculations based on input and output sizes.
check_config(logger)	Perform optional error checks.
check_partials([out_stream, compact_print, ...])	Check partial derivatives comprehensively for this component.
check_sparsity([method, max_nz, out_stream])	Check the sparsity of the computed jacobian against the declared sparsity.
cleanup()	Clean up resources prior to exit.
comm_info_iter()	Yield comm size for this system and all subsystems.
compute(inputs, outputs)	This is a dummy comp that doesn't modify its state.
compute_fd_jac(jac[, method])	Force the use of finite difference to compute a jacobian.
compute_fd_sparsity([method, num_full_jacs, ...])	Use finite difference to compute a sparsity matrix.
compute_sparsity([direction, num_iters, ...])	Compute the sparsity of the partial jacobian.
convert2units(name, val, units)	Convert the given value to the specified units.
convert_from_units(name, val, units)	Convert the given value from the specified units to those of the named variable.
convert_units(name, val, units_from, units_to)	Wrap the utility convert_units and give a good error message.
declare_coloring([wrt, method, form, step, ...])	Set options for deriv coloring of a set of wrt vars matching the given pattern(s).
declare_partials(of, wrt[, dependent, rows, ...])	Declare information about this component's subjacobians.
dist_size_iter(io, top_comm)	Yield names and distributed ranges of all local and remote variables in this system.
get_coloring_fname(mode)	Return the full pathname to a coloring file.
get_conn_graph()	Return the model connection graph.
get_constraints([recurse, get_sizes, ...])	Get the Constraint settings from this system.
get_declare_partials_calls([sparsity])	Return a string containing declare_partials() calls based on the subjac sparsity.
get_design_vars([recurse, get_sizes, ...])	Get the DesignVariable settings from this system.
get_io_metadata([iotypes, metadata_keys, ...])	Retrieve metadata for a filtered list of variables.
get_linear_vectors()	Return the linear inputs, outputs, and residuals vectors.
get_nonlinear_vectors()	Return the inputs, outputs, and residuals vectors.
get_objectives([recurse, get_sizes, ...])	Get the Objective settings from this system.
get_outputs_dir(*subdirs[, mkdir])	Get the path under which all output files of this system are to be placed.
get_promotions([inprom, outprom])	Return all promotions for the given promoted variable(s).
get_reports_dir()	Get the path to the directory where the report files should go.
get_responses([recurse, get_sizes, use_prom_ivc])	Get the response variable settings from this system.
get_self_statics()	Override this in derived classes if compute_primal references static values.
get_source(name)	Return the source variable connected to the given named variable.
get_val(name[, units, indices, get_remote, ...])	Get an output/input/residual variable.
get_var_dup_info(name, io)	Return information about how the given variable is duplicated across MPI processes.
get_var_sizes(name, io)	Return the sizes of the given variable on all procs.
guess_nonlinear(inputs, outputs, residuals)	Provide initial guess for states.
has_vectors()	Check if the system vectors have been initialized.
initialize()	Perform any one-time initialization run at instantiation.
is_explicit([is_comp])	Return True if this is an explicit component.
linearize(inputs, outputs, J)	Analytical derivatives.
list_inputs([val, prom_name, units, shape, ...])	Write a list of input names and other optional information to a specified stream.
list_options([include_default, ...])	Write a list of output names and other optional information to a specified stream.
list_outputs([explicit, implicit, val, ...])	Write a list of output names and other optional information to a specified stream.
list_vars([val, prom_name, residuals, ...])	Write a list of inputs and outputs sorted by component in execution order.
load_case(case)	Pull all input and output variables from a Case into this System.
load_model_options()	Load the relevant model options from Problem._metadata['model_options'].
override_method(name, method)	Dynamically add a method to this component instance.
record_iteration()	Record an iteration of the current System.
run_apply_linear(mode[, scope_out, scope_in])	Compute jac-vec product.
run_apply_nonlinear()	Compute residuals.
run_linearize([sub_do_ln])	Compute jacobian / factorization.
run_solve_linear(mode)	Apply inverse jac product.
run_solve_nonlinear()	Compute outputs.
run_validation()	Run validate method on all systems below this system.
set_check_partial_options(wrt[, method, ...])	Set options that will be used for checking partial derivatives.
set_constraint_options(name[, ref, ref0, ...])	Set options for constraints in the model.
set_design_var_options(name[, lower, upper, ...])	Set options for design vars in the model.
set_objective_options(name[, ref, ref0, ...])	Set options for objectives in the model.
set_output_solver_options(name[, lower, ...])	Set solver output options.
set_solver_print([level, depth, type_, ...])	Control printing for solvers and subsolvers in the model.
set_val(name, val[, units, indices])	Set an input or output variable.
setup()	Declare inputs and outputs.
setup_partials()	Declare partials.
setup_residuals()	User hook for adding named residuals to this component.
solve_linear(d_outputs, d_residuals, mode)	Apply inverse jac product.
solve_nonlinear(inputs, outputs)	Compute outputs given inputs.
sparsity_matches_fd([direction, outstream])	Compare the sparsity computed by this system vs.
subjac_sparsity_iter(sparsity[, wrt_matches])	Iterate over sparsity for each subjac in the jacobian.
system_iter([include_self, recurse, typ, ...])	Yield a generator of local subsystems of this system.
total_local_size(io)	Return the total local size of the given variable.
use_fixed_coloring([coloring, recurse])	Use a precomputed coloring for this System.
uses_approx()	Return True if the system uses approximations to compute derivatives.
validate(inputs, outputs[, discrete_inputs, ...])	Check any final input / output values after a run.

apply_nonlinear(inputs, outputs, residuals)

Don’t solve; just calculate the residual.

compute(inputs, outputs)

This is a dummy comp that doesn’t modify its state.

linearize(inputs, outputs, J)

Analytical derivatives.

setup()

Declare inputs and outputs.

Available attributes:

name pathname comm options

setup_partials()

Declare partials.

This is meant to be overridden by component classes. All partials should be declared here since this is called after all size/shape information is known for all variables.