system.py

Define the base System class.

class openmdao.core.system.System(num_par_fd=1, **kwargs)

Bases: object

Base class for all systems in OpenMDAO.

Never instantiated; subclassed by <Group> or <Component>.

In attribute names:

abs: absolute, unpromoted variable name, seen from root (unique). rel: relative, unpromoted variable name, seen from current system (unique). prom: relative, promoted variable name, seen from current system (non-unique for inputs).

Parameters:

num_par_fdint

If FD is active, number of concurrent FD solves.

**kwargsdict of keyword arguments

Keyword arguments that will be mapped into the System options.

Attributes:

namestr

Name of the system, must be different from siblings.

pathnamestr

Global name of the system, including the path.

_commMPI.Comm or <FakeComm>

MPI communicator object.

optionsOptionsDictionary

options dictionary

recording_optionsOptionsDictionary

Recording options dictionary

_problem_metadict

Problem level metadata.

under_complex_stepbool

When True, this system is undergoing complex step.

under_finite_differencebool

When True, this system is undergoing finite differencing.

iter_countint

Counts the number of times this system has called _solve_nonlinear. This also corresponds to the number of times that the system’s outputs are recorded if a recorder is present.

iter_count_applyint

Counts the number of times the system has called _apply_nonlinear. For ExplicitComponent, calls to apply_nonlinear also call compute, so number of executions can be found by adding this and iter_count together. Recorders do not record calls to apply_nonlinear.

iter_count_without_approxint

Counts the number of times the system has iterated but excludes any that occur during approximation of derivatives.

citestr

Listing of relevant citations that should be referenced when publishing work that uses this class.

_full_commMPI.Comm or None

MPI communicator object used when System’s comm is split for parallel FD.

_solver_print_cachelist

Allows solver iprints to be set to requested values after setup calls.

_subsystems_allprocsdict

Dict mapping subsystem name to SysInfo(system, index) for children of this system.

_subsystems_myproc[<System>, …]

List of local subsystems that exist on this proc.

_var_promotes{ ‘any’: [], ‘input’: [], ‘output’: [] }

Dictionary of lists of variable names/wildcards specifying promotion (used to calculate promoted names)

_var_prom2indsdict

Maps promoted name to src_indices in scope of system.

_var_allprocs_prom2abs_list{‘input’: dict, ‘output’: dict}

Dictionary mapping promoted names (continuous and discrete) to list of all absolute names. For outputs, the list will have length one since promoted output names are unique.

_var_abs2prom{‘input’: dict, ‘output’: dict}

Dictionary mapping absolute names to promoted names, on current proc. Contains continuous and discrete variables.

_var_allprocs_abs2prom{‘input’: dict, ‘output’: dict}

Dictionary mapping absolute names to promoted names, on all procs. Contains continuous and discrete variables.

_var_allprocs_abs2metadict

Dictionary mapping absolute names to metadata dictionaries for allprocs continuous variables.

_var_abs2metadict

Dictionary mapping absolute names to metadata dictionaries for myproc continuous variables.

_var_discretedict

Dictionary of discrete var metadata and values local to this process.

_var_allprocs_discretedict

Dictionary of discrete var metadata and values for all processes.

_discrete_inputsdict-like or None

Storage for discrete input values.

_discrete_outputsdict-like or None

Storage for discrete output values.

_var_allprocs_abs2idxdict

Dictionary mapping absolute names to their indices among this system’s allprocs variables. Therefore, the indices range from 0 to the total number of this system’s variables.

_var_sizes{‘input’: ndarray, ‘output’: ndarray}

Array of local sizes of this system’s allprocs variables. The array has size nproc x num_var where nproc is the number of processors owned by this system and num_var is the number of allprocs variables.

_owned_sizesndarray

Array of local sizes for ‘owned’ or distributed vars only.

_var_offsets{<vecname>: {‘input’: dict of ndarray, ‘output’: dict of ndarray}, …} or None

Dict of distributed offsets, keyed by var name. Offsets are stored in an array of size nproc x num_var where nproc is the number of processors in this System’s communicator and num_var is the number of allprocs variables in the given system. This is only defined in a Group that owns one or more interprocess connections or a top level Group that is used to compute total derivatives across multiple processes.

_vars_to_gatherdict

Contains names of non-distributed variables that are remote on at least one proc in the comm

_conn_global_abs_in2out{‘abs_in’: ‘abs_out’}

Dictionary containing all explicit & implicit connections (continuous and discrete) owned by this system or any descendant system. The data is the same across all processors.

_vectors{‘input’: dict, ‘output’: dict, ‘residual’: dict}

Dictionaries of vectors keyed by vec_name.

_inputs<Vector>

The nonlinear inputs vector.

_outputs<Vector>

The nonlinear outputs vector.

_residuals<Vector>

The nonlinear residuals vector.

_dinputs<Vector>

The linear inputs vector.

_doutputs<Vector>

The linear outputs vector.

_dresiduals<Vector>

The linear residuals vector.

_nonlinear_solver<NonlinearSolver>

Nonlinear solver to be used for solve_nonlinear.

_linear_solver<LinearSolver>

Linear solver to be used for solve_linear; not the Newton system.

_approx_schemesdict

A mapping of approximation types to the associated ApproximationScheme.

_jacobian<Jacobian>

<Jacobian> object to be used in apply_linear.

_owns_approx_jacbool

If True, this system approximated its Jacobian

_owns_approx_jac_metadict

Stores approximation metadata (e.g., step_size) from calls to approx_totals

_owns_approx_oflist or None

Overrides aproximation outputs. This is set when calculating system derivatives, and serves as a way to communicate the driver’s output quantities to the approximation objects so that we only take derivatives of variables that the driver needs.

_owns_approx_wrtlist or None

Overrides aproximation inputs. This is set when calculating system derivatives, and serves as a way to communicate the driver’s input quantities to the approximation objects so that we only take derivatives with respect to variables that the driver needs.

_subjacs_infodict of dict

Sub-jacobian metadata for each (output, input) pair added using declare_partials. Members of each pair may be glob patterns.

_approx_subjac_keyslist

List of subjacobian keys used for approximated derivatives.

_design_varsdict of dict

dict of all driver design vars added to the system.

_responsesdict of dict

dict of all driver responses added to the system.

_rec_mgr<RecordingManager>

object that manages all recorders added to this system.

_static_subsystems_allprocsdict

Dict of SysInfo(subsys, index) that stores all subsystems added outside of setup.

_static_design_varsdict of dict

Driver design variables added outside of setup.

_static_responsesdict of dict

Driver responses added outside of setup.

matrix_freebool

This is set to True if the component overrides the appropriate function with a user-defined matrix vector product with the Jacobian or any of its subsystems do. Note that the framework will not set the matrix_free flag correctly for Component instances having a matrix vector product function that is added dynamically (not declared as part of the class) and in that case the matrix_free flag must be set manually to True.

_modestr

Return the current system mode.

_scope_cachedict

Cache for variables in the scope of various mat-vec products.

_has_guessbool

True if this system has or contains a system with a guess_nonlinear method defined.

_has_output_scalingbool

True if this system has output scaling.

_has_output_adderbool

True if this system has scaling that includes an adder term.

_has_resid_scalingbool

True if this system has resid scaling.

_has_input_scalingbool

True if this system has input scaling.

_has_input_adderbool

True if this system has scaling that includes an adder term.

_has_boundsbool

True if this system has upper or lower bounds on outputs.

_has_distrib_varsbool

If True, this System contains at least one distributed variable. Used to determine if a parallel group or distributed component is below a DirectSolver so that we can raise an exception.

_owning_rankdict

Dict mapping var name to the lowest rank where that variable is local.

_filtered_vars_to_recordDict

Dict of list of var names to record

_vector_classclass

Class to use for data vectors. After setup will contain the value of either _problem_meta[‘distributed_vector_class’] or _problem_meta[‘local_vector_class’].

_assembled_jacAssembledJacobian or None

If not None, this is the AssembledJacobian owned by this system’s linear_solver.

_num_par_fdint

If FD is active, and the value is > 1, turns on parallel FD and specifies the number of concurrent FD solves.

_par_fd_idint

ID used to determine which columns in the jacobian will be computed when using parallel FD.

_has_approxbool

If True, this system or its descendent has declared approximated partial or semi-total derivatives.

_coloring_infotuple

Metadata that defines how to perform coloring of this System’s approx jacobian. Not used if this System does no partial or semi-total coloring.

_first_call_to_linearizebool

If True, this is the first call to _linearize.

_is_localbool

If True, this system is local to this mpi process.

_tot_jac__TotalJacInfo or None

If a total jacobian is being computed and this is the top level System, this will be a reference to the _TotalJacInfo object.

_saved_errorslist

Temporary storage for any saved errors that occur before this System is assigned a parent Problem.

_output_solver_optionsdict or None

Solver output options if set_output_solver_options has been called.

_promotion_treedict

Mapping of system path to promotion info indicating all subsystems where variables were promoted.

_during_sparsitybool

If True, we’re doing a sparsity computation and uncolored approxs need to be restricted to only colored columns.

compute_primalfunction or None

Function that computes the primal for the given system.

_jac_func_function or None

Function that computes the jacobian using AD (jax). Not used if jax is not active.

__init__(num_par_fd=1, **kwargs)

Initialize all attributes.

abs_meta_iter(iotype, local=True, cont=True, discrete=False)

Iterate over absolute variable names and their metadata for this System.

By setting appropriate values for ‘cont’ and ‘discrete’, yielded variable names can be continuous only, discrete only, or both.

Parameters:

iotypestr

Either ‘input’ or ‘output’.

localbool

If True, include only names of local variables. Default is True.

contbool

If True, include names of continuous variables. Default is True.

discretebool

If True, include names of discrete variables. Default is False.

Yields:

str, dict

abs_name_iter(iotype, local=True, cont=True, discrete=False)

Iterate over absolute variable names for this System.

By setting appropriate values for ‘cont’ and ‘discrete’, yielded variable names can be continuous only, discrete only, or both.

Parameters:

iotypestr

Either ‘input’ or ‘output’.

localbool

If True, include only names of local variables. Default is True.

contbool

If True, include names of continuous variables. Default is True.

discretebool

If True, include names of discrete variables. Default is False.

Yields:

str

add_constraint(name, lower=None, upper=None, equals=None, ref=None, ref0=None, adder=None, scaler=None, units=None, indices=None, linear=False, parallel_deriv_color=None, cache_linear_solution=False, flat_indices=False, alias=None)

Add a constraint variable to this system.

Parameters:

namestr

Name of the response variable in the system.

lowerfloat or ndarray, optional

Lower boundary for the variable.

upperfloat or ndarray, optional

Upper boundary for the variable.

equalsfloat or ndarray, optional

Equality constraint value for the variable.

reffloat or ndarray, optional

Value of response variable that scales to 1.0 in the driver.

ref0float or ndarray, optional

Value of response variable that scales to 0.0 in the driver.

adderfloat or ndarray, optional

Value to add to the model value to get the scaled value for the driver. adder is first in precedence. adder and scaler are an alterantive to using ref and ref0.

scalerfloat or ndarray, optional

Value to multiply the model value to get the scaled value for the driver. scaler is second in precedence. adder and scaler are an alternative to using ref and ref0.

unitsstr, optional

Units to convert to before applying scaling.

indicessequence of int, optional

If variable is an array, these indicate which entries are of interest for this particular response. These may be positive or negative integers.

linearbool

Set to True if constraint is linear. Default is False.

parallel_deriv_colorstr

If specified, this design var will be grouped for parallel derivative calculations with other variables sharing the same parallel_deriv_color.

cache_linear_solutionbool

If True, store the linear solution vectors for this variable so they can be used to start the next linear solution with an initial guess equal to the solution from the previous linear solve.

flat_indicesbool

If True, interpret specified indices as being indices into a flat source array.

aliasstr

Alias for this response. Necessary when adding multiple constraints on different indices or slices of a single variable.

Notes

The response can be scaled using ref and ref0. The argument ref0 represents the physical value when the scaled value is 0. The argument ref represents the physical value when the scaled value is 1. The arguments (lower, upper, equals) can not be strings or variable names.

add_design_var(name, lower=None, upper=None, ref=None, ref0=None, indices=None, adder=None, scaler=None, units=None, parallel_deriv_color=None, cache_linear_solution=False, flat_indices=False)

Add a design variable to this system.

Parameters:

namestr

Promoted name of the design variable in the system.

lowerfloat or ndarray, optional

Lower boundary for the input.

upperupper or ndarray, optional

Upper boundary for the input.

reffloat or ndarray, optional

Value of design var that scales to 1.0 in the driver.

ref0float or ndarray, optional

Value of design var that scales to 0.0 in the driver.

indicesiter of int, optional

If an input is an array, these indicate which entries are of interest for this particular design variable. These may be positive or negative integers.

adderfloat or ndarray, optional

Value to add to the model value to get the scaled value for the driver. adder is first in precedence. adder and scaler are an alterantive to using ref and ref0.

scalerfloat or ndarray, optional

Value to multiply the model value to get the scaled value for the driver. scaler is second in precedence. adder and scaler are an alterantive to using ref and ref0.

unitsstr, optional

Units to convert to before applying scaling.

parallel_deriv_colorstr

If specified, this design var will be grouped for parallel derivative calculations with other variables sharing the same parallel_deriv_color.

cache_linear_solutionbool

If True, store the linear solution vectors for this variable so they can be used to start the next linear solution with an initial guess equal to the solution from the previous linear solve.

flat_indicesbool

If True, interpret specified indices as being indices into a flat source array.

Notes

The response can be scaled using ref and ref0. The argument ref0 represents the physical value when the scaled value is 0. The argument ref represents the physical value when the scaled value is 1.

add_objective(name, ref=None, ref0=None, index=None, units=None, adder=None, scaler=None, parallel_deriv_color=None, cache_linear_solution=False, flat_indices=False, alias=None)

Add a response variable to this system.

Parameters:

namestr

Name of the response variable in the system.

reffloat or ndarray, optional

Value of response variable that scales to 1.0 in the driver.

ref0float or ndarray, optional

Value of response variable that scales to 0.0 in the driver.

indexint, optional

If variable is an array, this indicates which entry is of interest for this particular response. This may be a positive or negative integer.

unitsstr, optional

Units to convert to before applying scaling.

adderfloat or ndarray, optional

Value to add to the model value to get the scaled value for the driver. adder is first in precedence. adder and scaler are an alterantive to using ref and ref0.

scalerfloat or ndarray, optional

Value to multiply the model value to get the scaled value for the driver. scaler is second in precedence. adder and scaler are an alterantive to using ref and ref0.

parallel_deriv_colorstr

If specified, this design var will be grouped for parallel derivative calculations with other variables sharing the same parallel_deriv_color.

cache_linear_solutionbool

If True, store the linear solution vectors for this variable so they can be used to start the next linear solution with an initial guess equal to the solution from the previous linear solve.

flat_indicesbool

If True, interpret specified indices as being indices into a flat source array.

aliasstr

Alias for this response. Necessary when adding multiple objectives on different indices or slices of a single variable.

Notes

The objective can be scaled using scaler and adder, where

\[x_{scaled} = scaler(x + adder)\]

or through the use of ref/ref0, which map to scaler and adder through the equations:

\[ \begin{align}\begin{aligned}0 = scaler(ref_0 + adder)\\1 = scaler(ref + adder)\end{aligned}\end{align} \]

which results in:

\[ \begin{align}\begin{aligned}adder = -ref_0\\scaler = \frac{1}{ref + adder}\end{aligned}\end{align} \]

add_recorder(recorder, recurse=False)

Add a recorder to the system.

Parameters:

recorder<CaseRecorder>

A recorder instance.

recursebool

Flag indicating if the recorder should be added to all the subsystems.

add_response(name, type_, lower=None, upper=None, equals=None, ref=None, ref0=None, indices=None, index=None, units=None, adder=None, scaler=None, linear=False, parallel_deriv_color=None, cache_linear_solution=False, flat_indices=None, alias=None)

Add a response variable to this system.

The response can be scaled using ref and ref0. The argument ref0 represents the physical value when the scaled value is 0. The argument ref represents the physical value when the scaled value is 1.

Parameters:

namestr

Promoted name of the response variable in the system.

type_str

The type of response. Supported values are ‘con’ and ‘obj’.

lowerfloat or ndarray, optional

Lower boundary for the variable.

upperupper or ndarray, optional

Upper boundary for the variable.

equalsequals or ndarray, optional

Equality constraint value for the variable.

reffloat or ndarray, optional

Value of response variable that scales to 1.0 in the driver.

ref0upper or ndarray, optional

Value of response variable that scales to 0.0 in the driver.

indicessequence of int, optional

If variable is an array, these indicate which entries are of interest for this particular response.

indexint, optional

If variable is an array, this indicates which entry is of interest for this particular response.

unitsstr, optional

Units to convert to before applying scaling.

adderfloat or ndarray, optional

Value to add to the model value to get the scaled value for the driver. adder is first in precedence. adder and scaler are an alterantive to using ref and ref0.

scalerfloat or ndarray, optional

Value to multiply the model value to get the scaled value for the driver. scaler is second in precedence. adder and scaler are an alterantive to using ref and ref0.

linearbool

Set to True if constraint is linear. Default is False.

parallel_deriv_colorstr

If specified, this design var will be grouped for parallel derivative calculations with other variables sharing the same parallel_deriv_color.

cache_linear_solutionbool

If True, store the linear solution vectors for this variable so they can be used to start the next linear solution with an initial guess equal to the solution from the previous linear solve.

flat_indicesbool

If True, interpret specified indices as being indices into a flat source array.

aliasstr or None

Alias for this response. Necessary when adding multiple responses on different indices of the same variable.

best_partial_deriv_direction()

Return the best direction for partial deriv calculations based on input and output sizes.

Returns:

str

The best direction for derivative calculations, ‘fwd’ or ‘rev’.

check_config(logger)

Perform optional error checks.

Parameters:

loggerobject

The object that manages logging output.

cleanup()

Clean up resources prior to exit.

property comm

Return the MPI communicator object for the system.

Returns:

MPI.Comm

MPI communicator object.

comm_info_iter()

Yield comm size for this system and all subsystems.

Yields:

tuple

A tuple of the form (abs_name, comm_size).

compute_sparsity()

Compute the sparsity of the partial jacobian.

Returns:

coo_matrix

The sparsity matrix.

dict

Metadata about the sparsity computation.

convert2units(name, val, units)

Convert the given value to the specified units.

Parameters:

namestr

Name of the variable.

valfloat or ndarray of float

The value of the variable.

unitsstr

The units to convert to.

Returns:

float or ndarray of float

The value converted to the specified units.

convert_from_units(name, val, units)

Convert the given value from the specified units to those of the named variable.

Parameters:

namestr

Name of the variable.

valfloat or ndarray of float

The value of the variable.

unitsstr

The units to convert to.

Returns:

float or ndarray of float

The value converted to the specified units.

convert_units(name, val, units_from, units_to)

Wrap the utility convert_units and give a good error message.

Parameters:

namestr

Name of the variable.

valfloat or ndarray of float

The value of the variable.

units_fromstr

The units to convert from.

units_tostr

The units to convert to.

Returns:

float or ndarray of float

The value converted to the specified units.

declare_coloring(wrt=('*',), method='fd', form=None, step=None, per_instance=True, num_full_jacs=3, tol=1e-25, orders=None, perturb_size=1e-09, min_improve_pct=5.0, show_summary=True, show_sparsity=False)

Set options for deriv coloring of a set of wrt vars matching the given pattern(s).

Parameters:

wrtstr or list of str

The name or names of the variables that derivatives are taken with respect to. This can contain input names, output names, or glob patterns.

methodstr

Method used to compute derivative: “fd” for finite difference, “cs” for complex step.

formstr

Finite difference form, can be “forward”, “central”, or “backward”. Leave undeclared to keep unchanged from previous or default value.

stepfloat

Step size for finite difference. Leave undeclared to keep unchanged from previous or default value.

per_instancebool

If True, a separate coloring will be generated for each instance of a given class. Otherwise, only one coloring for a given class will be generated and all instances of that class will use it.

num_full_jacsint

Number of times to repeat partial jacobian computation when computing sparsity.

tolfloat

Tolerance used to determine if an array entry is nonzero during sparsity determination.

ordersint

Number of orders above and below the tolerance to check during the tolerance sweep.

perturb_sizefloat

Size of input/output perturbation during generation of sparsity.

min_improve_pctfloat

If coloring does not improve (decrease) the number of solves more than the given percentage, coloring will not be used.

show_summarybool

If True, display summary information after generating coloring.

show_sparsitybool

If True, plot sparsity with coloring info after generating coloring.

dist_size_iter(io, top_comm)

Yield names and distributed ranges of all local and remote variables in this system.

Parameters:

iostr

Either ‘input’ or ‘output’.

top_commMPI.Comm or None

The top-level MPI communicator.

Yields:

tuple

A tuple of the form ((abs_name, rank), start, end).

get_coloring_fname(mode)

Return the full pathname to a coloring file.

Parameters:

modestr

The type of coloring file desired. Must be either ‘input’ or ‘output’.

Returns:

pathlib.Path

Full pathname of the coloring file.

get_constraints(recurse=True, get_sizes=True, use_prom_ivc=True)

Get the Constraint settings from this system.

Retrieve the constraint settings for the current system as a dict, keyed by variable name.

Parameters:

recursebool, optional

If True, recurse through the subsystems and return the path of all constraints relative to the this system.

get_sizesbool, optional

If True, compute the size of each constraint.

use_prom_ivcbool

Translate ivc names to their promoted input names.

Returns:

dict

The constraints defined in the current system.

get_design_vars(recurse=True, get_sizes=True, use_prom_ivc=True)

Get the DesignVariable settings from this system.

Retrieve all design variable settings from the system and, if recurse is True, all of its subsystems.

Parameters:

recursebool

If True, recurse through the subsystems of a group and return the path of all design vars relative to the this system.

get_sizesbool, optional

If True, compute the size of each design variable.

use_prom_ivcbool

Use promoted names for inputs, else convert to absolute source names.

Returns:

dict

The design variables defined in the current system and, if recurse=True, its subsystems.

get_io_metadata(iotypes=('input', 'output'), metadata_keys=None, includes=None, excludes=None, is_indep_var=None, is_design_var=None, tags=None, get_remote=False, rank=None, return_rel_names=True)

Retrieve metadata for a filtered list of variables.

Parameters:

iotypesstr or iter of str

Will contain either ‘input’, ‘output’, or both. Defaults to both.

metadata_keysiter of str or None

Names of metadata entries to be retrieved or None, meaning retrieve all available ‘allprocs’ metadata. If ‘val’ or ‘src_indices’ are required, their keys must be provided explicitly since they are not found in the ‘allprocs’ metadata and must be retrieved from local metadata located in each process.

includesstr, iter of str or None

Collection of glob patterns for pathnames of variables to include. Default is None, which includes all variables.

excludesstr, iter of str or None

Collection of glob patterns for pathnames of variables to exclude. Default is None.

is_indep_varbool or None

If None (the default), do no additional filtering of the inputs. If True, list only inputs connected to an output tagged openmdao:indep_var. If False, list only inputs _not_ connected to outputs tagged openmdao:indep_var.

is_design_varbool or None

If None (the default), do no additional filtering of the inputs. If True, list only inputs connected to outputs that are driver design variables. If False, list only inputs _not_ connected to outputs that are driver design variables.

tagsstr or iter of strs

User defined tags that can be used to filter what gets listed. Only inputs with the given tags will be listed. Default is None, which means there will be no filtering based on tags.

get_remotebool

If True, retrieve variables from other MPI processes as well.

rankint or None

If None, and get_remote is True, retrieve values from all MPI process to all other MPI processes. Otherwise, if get_remote is True, retrieve values from all MPI processes only to the specified rank.

return_rel_namesbool

If True, the names returned will be relative to the scope of this System. Otherwise they will be absolute names.

Returns:

dict

A dict of metadata keyed on name, where name is either absolute or relative based on the value of the return_rel_names arg, and metadata is a dict containing entries based on the value of the metadata_keys arg. Every metadata dict will always contain two entries, ‘prom_name’ and ‘discrete’, to indicate a given variable’s promoted name and whether or not it is discrete.

get_linear_vectors()

Return the linear inputs, outputs, and residuals vectors.

Returns:

(inputs, outputs, residuals): tuple of <Vector> instances

Yields the linear inputs, outputs, and residuals vectors.

get_nonlinear_vectors()

Return the inputs, outputs, and residuals vectors.

Returns:

(inputs, outputs, residuals)

Yields the inputs, outputs, and residuals nonlinear vectors.

get_objectives(recurse=True, get_sizes=True, use_prom_ivc=True)

Get the Objective settings from this system.

Retrieve all objectives settings from the system as a dict, keyed by variable name.

Parameters:

recursebool, optional

If True, recurse through the subsystems and return the path of all objective relative to the this system.

get_sizesbool, optional

If True, compute the size of each objective.

use_prom_ivcbool

Translate ivc names to their promoted input names.

Returns:

dict

The objectives defined in the current system.

get_outputs_dir(*subdirs, mkdir=True)

Get the path under which all output files of this system are to be placed.

Parameters:

*subdirsstr

Subdirectories nested under the relevant problem output directory. To create {prob_output_dir}/a/b one would pass system.get_outputs_dir(‘a’, ‘b’).

mkdirbool

If True, attempt to create this directory if it does not exist.

Returns:

pathlib.Path

The path of the outputs directory for the problem.

get_promotions(inprom=None, outprom=None)

Return all promotions for the given promoted variable(s).

In other words, how and where did promotions occur to convert absolute variable names into the given promoted name(s) at the current System level.

Parameters:

inpromstr or None

The promoted input variable name.

outpromstr or None

The promoted output variable name.

Returns:

dict

Dictionary keyed on system pathname containing input and/or output promotion lists for each System where promotions occurred to produce the given promoted variable(s).

get_reports_dir()

Get the path to the directory where the report files should go.

If it doesn’t exist, it will be created.

Returns:

str

The path to the directory where reports should be written.

get_responses(recurse=True, get_sizes=True, use_prom_ivc=False)

Get the response variable settings from this system.

Retrieve all response variable settings from the system as a dict, keyed by either absolute variable name, promoted name, or alias name, depending on the value of use_prom_ivc and whether the original key was a promoted output, promoted input, or an alias.

Parameters:

recursebool, optional

If True, recurse through the subsystems and return the path of all responses relative to the this system.

get_sizesbool, optional

If True, compute the size of each response.

use_prom_ivcbool

Translate ivc names to their promoted input names.

Returns:

dict

The responses defined in the current system and, if recurse=True, its subsystems.

get_self_statics()

Override this in derived classes if compute_primal references static values.

Do NOT include self._discrete_inputs in the returned tuple. Include things like self.options[‘opt_name’], etc., that are used in compute_primal but are assumed to be constant during derivative computation.

Return value MUST be a tuple. Don’t forget the trailing comma if tuple has only one item. Return value MUST be hashable.

The order of these values doesn’t matter. They are only checked (by computing their hash) to see if they have changed since the last time compute_primal was jitted, and if so, compute_primal will be re-jitted.

Returns:

tuple

Tuple containing all static values required by compute_primal.

get_source(name)

Return the source variable connected to the given named variable.

The name can be a promoted name or an absolute name. If the given variable is an input, the absolute name of the connected source will be returned. If the given variable itself is a source, its own absolute name will be returned.

Parameters:

namestr

Absolute or promoted name of the variable.

Returns:

str

The absolute name of the source variable.

get_val(name, units=None, indices=None, get_remote=False, rank=None, vec_name='nonlinear', kind=None, flat=False, from_src=True)

Get an output/input/residual variable.

Function is used if you want to specify display units.

Parameters:

namestr

Promoted or relative variable name in the root system’s namespace.

unitsstr, optional

Units to convert to before return.

indicesint or list of ints or tuple of ints or int ndarray or Iterable or None, optional

Indices or slice to return.

get_remotebool or None

If True, retrieve the value even if it is on a remote process. Note that if the variable is remote on ANY process, this function must be called on EVERY process in the Problem’s MPI communicator. If False, only retrieve the value if it is on the current process, or only the part of the value that’s on the current process for a distributed variable. If None and the variable is remote or distributed, a RuntimeError will be raised.

rankint or None

If not None, only gather the value to this rank.

vec_namestr

Name of the vector to use. Defaults to ‘nonlinear’.

kindstr or None

Kind of variable (‘input’, ‘output’, or ‘residual’). If None, returned value will be either an input or output.

flatbool

If True, return the flattened version of the value.

from_srcbool

If True, retrieve value of an input variable from its connected source.

Returns:

object

The value of the requested output/input variable.

get_var_dup_info(name, io)

Return information about how the given variable is duplicated across MPI processes.

Parameters:

namestr

Name of the variable.

iostr

Either ‘input’ or ‘output’.

Returns:

tuple

A tuple of the form (is_duplicated, num_zeros, is_distributed).

get_var_sizes(name, io)

Return the sizes of the given variable on all procs.

Parameters:

namestr

Name of the variable.

iostr

Either ‘input’ or ‘output’.

Returns:

ndarray

Array of sizes of the variable on all procs.

initialize()

Perform any one-time initialization run at instantiation.

is_explicit()

Return True if this is an explicit component.

Returns:

bool

True if this is an explicit component.

property linear_solver

Get the linear solver for this system.

list_inputs(val=True, prom_name=True, units=False, shape=False, global_shape=False, desc=False, hierarchical=True, print_arrays=False, tags=None, print_tags=False, includes=None, excludes=None, is_indep_var=None, is_design_var=None, all_procs=False, out_stream=DEFAULT_OUT_STREAM, print_min=False, print_max=False, return_format='list')

Write a list of input names and other optional information to a specified stream.

Parameters:

valbool, optional

When True, display/return input values. Default is True.

prom_namebool, optional

When True, display/return the promoted name of the variable. Default is True.

unitsbool, optional

When True, display/return units. Default is False.

shapebool, optional

When True, display/return the shape of the value. Default is False.

global_shapebool, optional

When True, display/return the global shape of the value. Default is False.

descbool, optional

When True, display/return description. Default is False.

hierarchicalbool, optional

When True, human readable output shows variables in hierarchical format.

print_arraysbool, optional

When False, in the columnar display, just display norm of any ndarrays with size > 1. The norm is surrounded by vertical bars to indicate that it is a norm. When True, also display full values of the ndarray below the row. Format is affected by the values set with numpy.set_printoptions Default is False.

tagsstr or list of strs

User defined tags that can be used to filter what gets listed. Only inputs with the given tags will be listed. Default is None, which means there will be no filtering based on tags.

print_tagsbool

When true, display tags in the columnar display.

includesNone, str, or iter of str

Collection of glob patterns for pathnames of variables to include. Default is None, which includes all input variables.

excludesNone, str, or iter of str

Collection of glob patterns for pathnames of variables to exclude. Default is None.

is_indep_varbool or None

If None (the default), do no additional filtering of the inputs. If True, list only inputs connected to an output tagged openmdao:indep_var. If False, list only inputs _not_ connected to outputs tagged openmdao:indep_var.

is_design_varbool or None

If None (the default), do no additional filtering of the inputs. If True, list only inputs connected to outputs that are driver design variables. If False, list only inputs _not_ connected to outputs that are driver design variables.

all_procsbool, optional

When True, display output on all ranks. Default is False, which will display output only from rank 0.

out_streamfile-like object

Where to send human readable output. Default is sys.stdout. Set to None to suppress.

print_minbool

When true, if the input value is an array, print its smallest value.

print_maxbool

When true, if the input value is an array, print its largest value.

return_formatstr

Indicates the desired format of the return value. Can have value of ‘list’ or ‘dict’. If ‘list’, the return value is a list of (name, metadata) tuples. if ‘dict’, the return value is a dictionary mapping {name: metadata}.

Returns:

list of (name, metadata) or dict of {name: metadata}

List or dict of input names and other optional information about those inputs.

list_outputs(explicit=True, implicit=True, val=True, prom_name=True, residuals=False, residuals_tol=None, units=False, shape=False, global_shape=False, bounds=False, scaling=False, desc=False, hierarchical=True, print_arrays=False, tags=None, print_tags=False, includes=None, excludes=None, is_indep_var=None, is_design_var=None, all_procs=False, list_autoivcs=False, out_stream=DEFAULT_OUT_STREAM, print_min=False, print_max=False, return_format='list')

Write a list of output names and other optional information to a specified stream.

Parameters:

explicitbool, optional

Include outputs from explicit components. Default is True.

implicitbool, optional

Include outputs from implicit components. Default is True.

valbool, optional

When True, display output values. Default is True.

prom_namebool, optional

When True, display the promoted name of the variable. Default is True.

residualsbool, optional

When True, display residual values. Default is False.

residuals_tolfloat, optional

If set, limits the output of list_outputs to only variables where the norm of the resids array is greater than the given ‘residuals_tol’. Default is None.

unitsbool, optional

When True, display units. Default is False.

shapebool, optional

When True, display/return the shape of the value. Default is False.

global_shapebool, optional

When True, display/return the global shape of the value. Default is False.

boundsbool, optional

When True, display/return bounds (lower and upper). Default is False.

scalingbool, optional

When True, display/return scaling (ref, ref0, and res_ref). Default is False.

descbool, optional

When True, display/return description. Default is False.

hierarchicalbool, optional

When True, human readable output shows variables in hierarchical format.

print_arraysbool, optional

When False, in the columnar display, just display norm of any ndarrays with size > 1. The norm is surrounded by vertical bars to indicate that it is a norm. When True, also display full values of the ndarray below the row. Format is affected by the values set with numpy.set_printoptions Default is False.

tagsstr or list of strs

User defined tags that can be used to filter what gets listed. Only outputs with the given tags will be listed. Default is None, which means there will be no filtering based on tags.

print_tagsbool

When true, display tags in the columnar display.

includesNone, str, or iter of str

Collection of glob patterns for pathnames of variables to include. Default is None, which includes all output variables.

excludesNone, str, or iter of str

Collection of glob patterns for pathnames of variables to exclude. Default is None.

is_indep_varbool or None

If None (the default), do no additional filtering of the inputs. If True, list only outputs tagged openmdao:indep_var. If False, list only outputs that are _not_ tagged openmdao:indep_var.

is_design_varbool or None

If None (the default), do no additional filtering of the inputs. If True, list only inputs connected to outputs that are driver design variables. If False, list only inputs _not_ connected to outputs that are driver design variables.

all_procsbool, optional

When True, display output on all processors. Default is False.

list_autoivcsbool

If True, include auto_ivc outputs in the listing. Defaults to False.

out_streamfile-like

Where to send human readable output. Default is sys.stdout. Set to None to suppress.

print_minbool

When true, if the output value is an array, print its smallest value.

print_maxbool

When true, if the output value is an array, print its largest value.

return_formatstr

Indicates the desired format of the return value. Can have value of ‘list’ or ‘dict’. If ‘list’, the return value is a list of (name, metadata) tuples. if ‘dict’, the return value is a dictionary mapping {name: metadata}.

Returns:

list of (name, metadata) or dict of {name: metadata}

List or dict of output names and other optional information about those outputs.

list_vars(val=True, prom_name=True, residuals=False, residuals_tol=None, units=False, shape=False, global_shape=False, bounds=False, scaling=False, desc=False, print_arrays=False, tags=None, print_tags=False, includes=None, excludes=None, is_indep_var=None, is_design_var=None, all_procs=False, list_autoivcs=False, out_stream=DEFAULT_OUT_STREAM, print_min=False, print_max=False, return_format='list')

Write a list of inputs and outputs sorted by component in execution order.

Parameters:

valbool, optional

When True, display output values. Default is True.

prom_namebool, optional

When True, display the promoted name of the variable. Default is True.

residualsbool, optional

When True, display residual values. Default is False.

residuals_tolfloat, optional

If set, limits the output of list_outputs to only variables where the norm of the resids array is greater than the given ‘residuals_tol’. Default is None.

unitsbool, optional

When True, display units. Default is False.

shapebool, optional

When True, display/return the shape of the value. Default is False.

global_shapebool, optional

When True, display/return the global shape of the value. Default is False.

boundsbool, optional

When True, display/return bounds (lower and upper). Default is False.

scalingbool, optional

When True, display/return scaling (ref, ref0, and res_ref). Default is False.

descbool, optional

When True, display/return description. Default is False.

print_arraysbool, optional

When False, in the columnar display, just display norm of any ndarrays with size > 1. The norm is surrounded by vertical bars to indicate that it is a norm. When True, also display full values of the ndarray below the row. Format is affected by the values set with numpy.set_printoptions Default is False.

tagsstr or list of strs

User defined tags that can be used to filter what gets listed. Only outputs with the given tags will be listed. Default is None, which means there will be no filtering based on tags.

print_tagsbool

When true, display tags in the columnar display.

includesNone, str, or iter of str

Collection of glob patterns for pathnames of variables to include. Default is None, which includes all output variables.

excludesNone, str, or iter of str

Collection of glob patterns for pathnames of variables to exclude. Default is None.

is_indep_varbool or None

If None (the default), do no additional filtering of the inputs. If True, list only outputs tagged openmdao:indep_var. If False, list only outputs that are _not_ tagged openmdao:indep_var.

is_design_varbool or None

If None (the default), do no additional filtering of the inputs. If True, list only inputs connected to outputs that are driver design variables. If False, list only inputs _not_ connected to outputs that are driver design variables.

all_procsbool, optional

When True, display output on all processors. Default is False.

list_autoivcsbool

If True, include auto_ivc outputs in the listing. Defaults to False.

out_streamfile-like

Where to send human readable output. Default is sys.stdout. Set to None to suppress.

print_minbool

When true, if the output value is an array, print its smallest value.

print_maxbool

When true, if the output value is an array, print its largest value.

return_formatstr

Indicates the desired format of the return value. Can have value of ‘list’ or ‘dict’. If ‘list’, the return value is a list of (name, metadata) tuples. if ‘dict’, the return value is a dictionary mapping {name: metadata}.

Returns:

list of (name, metadata) or dict of {name: metadata}

List or dict of output names and other optional information about those outputs.

load_case(case)

Pull all input and output variables from a Case into this System.

Override this method if the System requires special handling when loading a case.

Parameters:

caseCase or dict

A Case from a CaseReader, or a dictionary with key ‘inputs’ mapped to the output of problem.model.list_inputs and key ‘outputs’ mapped to the output of prob.model.list_outputs. Both list_inputs and list_outputs should be called with prom_name=True and return_format=’dict’.

load_model_options()

Load the relevant model options from Problem._metadata[‘model_options’].

This method examines each path filter and corresponding options in self._problem_meta[‘model_options’]. If this System’s pathname matches the given path filter, it will assume the value for each given option which it possesses.

local_range_iter(io)

Yield names and local ranges of all local variables in this system.

Parameters:

iostr

Either ‘input’ or ‘output’.

Yields:

tuple

A tuple of the form (abs_name, start, end).

property msginfo

Our instance pathname, if available, or our class name. For use in error messages.

Returns:

str

Either our instance pathname or class name.

property nonlinear_solver

Get the nonlinear solver for this system.

record_iteration()

Record an iteration of the current System.

run_apply_linear(mode, scope_out=None, scope_in=None)

Compute jac-vec product.

This calls _apply_linear, but with the model assumed to be in an unscaled state.

Parameters:

modestr

‘fwd’ or ‘rev’.

scope_outset or None

Set of absolute output names in the scope of this mat-vec product. If None, all are in the scope.

scope_inset or None

Set of absolute input names in the scope of this mat-vec product. If None, all are in the scope.

run_apply_nonlinear()

Compute residuals.

This calls _apply_nonlinear, but with the model assumed to be in an unscaled state.

run_linearize(sub_do_ln=True)

Compute jacobian / factorization.

This calls _linearize, but with the model assumed to be in an unscaled state.

Parameters:

sub_do_lnbool

Flag indicating if the children should call linearize on their linear solvers.

run_solve_linear(mode)

Apply inverse jac product.

This calls _solve_linear, but with the model assumed to be in an unscaled state.

Parameters:

modestr

‘fwd’ or ‘rev’.

run_solve_nonlinear()

Compute outputs.

This calls _solve_nonlinear, but with the model assumed to be in an unscaled state.

set_constraint_options(name, ref=UNDEFINED, ref0=UNDEFINED, equals=UNDEFINED, lower=UNDEFINED, upper=UNDEFINED, adder=UNDEFINED, scaler=UNDEFINED, alias=UNDEFINED)

Set options for constraints in the model.

Can be used to set options that were set using add_constraint.

Parameters:

namestr

Name of the response variable in the system, or alias if given.

reffloat or ndarray, optional

Value of response variable that scales to 1.0 in the driver.

ref0float or ndarray, optional

Value of response variable that scales to 0.0 in the driver.

equalsfloat or ndarray, optional

Equality constraint value for the variable.

lowerfloat or ndarray, optional

Lower boundary for the variable.

upperfloat or ndarray, optional

Upper boundary for the variable.

adderfloat or ndarray, optional

Value to add to the model value to get the scaled value for the driver. adder is first in precedence. adder and scaler are an alterantive to using ref and ref0.

scalerfloat or ndarray, optional

Value to multiply the model value to get the scaled value for the driver. scaler is second in precedence. adder and scaler are an alterantive to using ref and ref0.

aliasstr, optional

Alias for this response. Necessary when adding multiple constraints on different indices or slices of a single variable.

set_design_var_options(name, lower=UNDEFINED, upper=UNDEFINED, scaler=UNDEFINED, adder=UNDEFINED, ref=UNDEFINED, ref0=UNDEFINED)

Set options for design vars in the model.

Can be used to set the options outside of setting them when calling add_design_var

Parameters:

namestr

Name of the variable in this system’s namespace.

lowerfloat or ndarray, optional

Lower boundary for the input.

upperupper or ndarray, optional

Upper boundary for the input.

scalerfloat or ndarray, optional

Value to multiply the model value to get the scaled value for the driver. scaler is second in precedence. adder and scaler are an alterantive to using ref and ref0.

adderfloat or ndarray, optional

Value to add to the model value to get the scaled value for the driver. adder is first in precedence. adder and scaler are an alterantive to using ref and ref0.

reffloat or ndarray, optional

Value of design var that scales to 1.0 in the driver.

ref0float or ndarray, optional

Value of design var that scales to 0.0 in the driver.

set_objective_options(name, ref=UNDEFINED, ref0=UNDEFINED, adder=UNDEFINED, scaler=UNDEFINED, alias=UNDEFINED)

Set options for objectives in the model.

Can be used to set options after they have been set by add_objective.

Parameters:

namestr

Name of the response variable in the system, or alias if given.

reffloat or ndarray, optional

Value of response variable that scales to 1.0 in the driver.

ref0float or ndarray, optional

Value of response variable that scales to 0.0 in the driver.

adderfloat or ndarray, optional

Value to add to the model value to get the scaled value for the driver. adder is first in precedence. adder and scaler are an alterantive to using ref and ref0.

scalerfloat or ndarray, optional

Value to multiply the model value to get the scaled value for the driver. scaler is second in precedence. adder and scaler are an alterantive to using ref and ref0.

aliasstr

Alias for this response. Used to disambiguate variable names when adding multiple objectives on different indices or slices of a single variable. Deprecated.

set_output_solver_options(name, lower=UNDEFINED, upper=UNDEFINED, ref=UNDEFINED, ref0=UNDEFINED, res_ref=UNDEFINED)

Set solver output options.

Allows the user to set output solver options after the output has been defined and metadata set using the add_ouput method.

Parameters:

namestr

Name of the variable in this system’s namespace.

lowerfloat or list or tuple or ndarray or None

Lower bound(s) in user-defined units. It can be (1) a float, (2) an array_like consistent with the shape arg (if given), or (3) an array_like matching the shape of val, if val is array_like. A value of None means this output has no lower bound. Default is None.

upperfloat or list or tuple or ndarray or None

Upper bound(s) in user-defined units. It can be (1) a float, (2) an array_like consistent with the shape arg (if given), or (3) an array_like matching the shape of val, if val is array_like. A value of None means this output has no upper bound. Default is None.

reffloat

Scaling parameter. The value in the user-defined units of this output variable when the scaled value is 1. Default is 1.

ref0float

Scaling parameter. The value in the user-defined units of this output variable when the scaled value is 0. Default is 0.

res_reffloat

Scaling parameter. The value in the user-defined res_units of this output’s residual when the scaled value is 1. Default is None, which means residual scaling matches output scaling.

set_solver_print(level=2, depth=1e+99, type_='all')

Control printing for solvers and subsolvers in the model.

Parameters:

levelint

Iprint level. Set to 2 to print residuals each iteration; set to 1 to print just the iteration totals; set to 0 to disable all printing except for failures, and set to -1 to disable all printing including failures.

depthint

How deep to recurse. For example, you can set this to 0 if you only want to print the top level linear and nonlinear solver messages. Default prints everything.

type_str

Type of solver to set: ‘LN’ for linear, ‘NL’ for nonlinear, or ‘all’ for all.

set_val(name, val, units=None, indices=None)

Set an input or output variable.

Parameters:

namestr

Promoted or relative variable name in the system’s namespace.

valobject

Value to assign to this variable.

unitsstr, optional

Units of the value.

indicesint or list of ints or tuple of ints or int ndarray or Iterable or None, optional

Indices or slice to set.

system_iter(include_self=False, recurse=True, typ=None)

Yield a generator of local subsystems of this system.

Parameters:

include_selfbool

If True, include this system in the iteration.

recursebool

If True, iterate over the whole tree under this system.

typtype

If not None, only yield Systems that match that are instances of the given type.

Yields:

type or None

property under_approx

Return True if under complex step or finite difference.

Returns:

bool

True if under CS or FD.

use_fixed_coloring(coloring=<object object>, recurse=True)

Use a precomputed coloring for this System.

Parameters:

coloringstr

A coloring filename. If no arg is passed, filename will be determined automatically.

recursebool

If True, set fixed coloring in all subsystems that declare a coloring. Ignored if a specific coloring is passed in.

openmdao.core.system.collect_errors(method)

Decorate a method so that it will collect any exceptions for later display.

Parameters:

methodmethod

The method to be decorated.

Returns:

method

The wrapped method.