Documentation

Referenced Tower Modules

class wisdem.towerse.tower.PreDiscretization(**kwargs)[source]

Process some of the tower YAML inputs.

Parameters:
  • hub_height (float, [m]) – Scalar of the rotor apex height computed along the z axis.

  • tower_height (float, [m]) – Scalar of the tower height computed along the z axis.

  • foundation_height (float, [m]) – starting height of tower

Returns:

  • height_constraint (float, [m]) – mismatch between tower height and desired hub_height

  • transition_piece_height (float, [m]) – Point mass height of transition piece above water line

  • joint1 (numpy array[3], [m]) – Global dimensional coordinates (x-y-z) for bottom node of member

  • joint2 (numpy array[3], [m]) – Global dimensional coordinates (x-y-z) for top node of member

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)

Compute outputs given inputs.

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. the sparsity computed using fd.

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.

class wisdem.towerse.tower.TurbineMass(**kwargs)[source]

Compute the turbine mass, center of mass, and mass moment of inertia.

Parameters:
  • hub_height (float, [m]) – Hub-height

  • rna_mass (float, [kg]) – Total tower mass

  • rna_I (numpy array[6], [kg*m**2]) – Mass moment of inertia of RNA about tower top [xx yy zz xy xz yz]

  • rna_cg (numpy array[3], [m]) – xyz-location of RNA cg relative to tower top

  • tower_mass (float, [kg]) – Total tower mass

  • tower_center_of_mass (float, [m]) – z-position of center of mass of tower

  • tower_I_base (numpy array[6], [kg*m**2]) – Mass moment of inertia of tower about base [xx yy zz xy xz yz]

Returns:

  • turbine_mass (float, [kg]) – Total mass of tower+rna

  • turbine_center_of_mass (numpy array[3], [m]) – xyz-position of tower+rna center of mass

  • turbine_I_base (numpy array[6], [kg*m**2]) – mass moment of inertia of tower about base [xx yy zz xy xz yz]

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)

Compute outputs given inputs.

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. the sparsity computed using fd.

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.

class wisdem.towerse.tower.TowerFrame(**kwargs)[source]

Run Frame3DD on the tower

Parameters:
  • z_full (numpy array[npts], [m]) – location along cylinder. start at bottom and go to top

  • outer_diameter_full (numpy array[npts], [m]) – effective cylinder diameter for section

  • t_full (numpy array[npts-1], [m]) – effective shell thickness for section

  • E_full (numpy array[npts-1], [N/m**2]) – modulus of elasticity

  • G_full (numpy array[npts-1], [N/m**2]) – shear modulus

  • rho_full (numpy array[npts-1], [kg/m**3]) – material density

  • rna_mass (float, [kg]) – Total tower mass

  • rna_I (numpy array[6], [kg*m**2]) – Mass moment of inertia of RNA about tower top [xx yy zz xy xz yz]

  • rna_cg (numpy array[3], [m]) – xyz-location of RNA cg relative to tower top

  • rna_F (numpy array[3], [N]) – rna force at tower top from drivetrain analysis

  • rna_M (numpy array[3], [N*m]) – rna moment at tower top from drivetrain analysis

  • Px (numpy array[n_full], [N/m]) – force per unit length in x-direction

  • Py (numpy array[n_full], [N/m]) – force per unit length in y-direction

  • Pz (numpy array[n_full], [N/m]) – force per unit length in z-direction

Returns:

  • f1 (float, [Hz]) – First natural frequency

  • f2 (float, [Hz]) – Second natural frequency

  • structural_frequencies (numpy array[NFREQ], [Hz]) – First and second natural frequency

  • fore_aft_freqs (numpy array[NFREQ2]) – Frequencies associated with mode shapes in the tower fore-aft direction

  • side_side_freqs (numpy array[NFREQ2]) – Frequencies associated with mode shapes in the tower side-side direction

  • torsion_freqs (numpy array[NFREQ2]) – Frequencies associated with mode shapes in the tower torsion direction

  • fore_aft_modes (numpy array[NFREQ2, 5]) – 6-degree polynomial coefficients of mode shapes in the tower fore-aft direction (without constant term)

  • side_side_modes (numpy array[NFREQ2, 5]) – 6-degree polynomial coefficients of mode shapes in the tower side-side direction (without constant term)

  • torsion_modes (numpy array[NFREQ2, 5]) – 6-degree polynomial coefficients of mode shapes in the tower torsion direction (without constant term)

  • tower_deflection (numpy array[n_full], [m]) – Deflection of tower nodes in yaw-aligned +x direction

  • top_deflection (float, [m]) – Deflection of tower top in yaw-aligned +x direction

  • tower_Fz (numpy array[n_full-1], [N]) – Axial foce in vertical z-direction in cylinder structure.

  • tower_Vx (numpy array[n_full-1], [N]) – Shear force in x-direction in cylinder structure.

  • tower_Vy (numpy array[n_full-1], [N]) – Shear force in y-direction in cylinder structure.

  • tower_Mxx (numpy array[n_full-1], [N*m]) – Moment about x-axis in cylinder structure.

  • tower_Myy (numpy array[n_full-1], [N*m]) – Moment about y-axis in cylinder structure.

  • tower_Mzz (numpy array[n_full-1], [N*m]) – Moment about z-axis in cylinder structure.

  • base_F (numpy array[3], [N]) – Total force on cylinder

  • base_M (numpy array[3], [N*m]) – Total moment on cylinder measured at base

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)

Compute outputs given inputs.

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. the sparsity computed using fd.

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.

class wisdem.towerse.tower.TowerSE(**kwargs)[source]

This is the main TowerSE group that performs analysis of the tower.

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. the sparsity computed using fd.

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