add_subtract_comp.py

Definition of the Add/Subtract Component.

class openmdao.components.add_subtract_comp.AddSubtractComp(output_name=None, input_names=None, vec_size=1, length=1, val=1.0, scaling_factors=None, **kwargs)

Bases: ExplicitComponent

Compute a vectorized element-wise addition or subtraction.

Use the add_equation method to define any number of add/subtract relations User defines the names of the input and output variables using add_equation(output_name=’my_output’, input_names=[‘a’,’b’, ‘c’, …])

\[result = a * \textrm{scaling factor}_a + b * \textrm{scaling factor}_b + c * \textrm{scaling factor}_c + ...\]

where all inputs shape (vec_size, n)

b is of shape (vec_size, n) c is of shape (vec_size, n) result is of shape (vec_size, n)

All input vectors must be of the same shape, specified by the options ‘vec_size’ and ‘length’. Use scaling factor -1 for subtraction.

Parameters:

output_namestr

(Required) name of the result variable in this component’s namespace.

input_namesiterable of str

(Required) names of the input variables for this system.

vec_sizeint

Length of the first dimension of the input and output vectors (i.e number of rows, or vector length for a 1D vector) Default is 1.

lengthint

Length of the second dimension of the input and ouptut vectors (i.e. number of columns) Default is 1 which results in input/output vectors of size (vec_size,).

valfloat or list or tuple or ndarray

The initial value of the variable being added in user-defined units. Default is 1.0.

scaling_factorsiterable of numeric

Scaling factors to apply to each input. Use [1,1,…] for addition, [1,-1,…] for subtraction Must be same length as input_names Default is None which results in a scaling factor of 1 on each input (element-wise addition).

**kwargsstr

Any other arguments to pass to the addition system (same as add_output method for ExplicitComponent) Examples include units (str or None), desc (str).

Attributes:

_equationslist

List of equation systems to be initialized with the system.

_input_namesdict

Dictionary of input names and key associated options for inputs so that a given input name can be used in multiple equations.

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_equation(output_name, input_names[, ...])	Add an addition/subtraction relation.
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])	Use add_equation instead of add_output to define equation systems.
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 the element wise addition or subtraction of inputs using numpy + operator.
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()	Declare options.
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__(output_name=None, input_names=None, vec_size=1, length=1, val=1.0, scaling_factors=None, **kwargs)

Allow user to create an addition/subtracton system with one-liner.

add_equation(output_name, input_names, vec_size=1, length=1, val=1.0, units=None, res_units=None, desc='', lower=None, upper=None, ref=1.0, ref0=0.0, res_ref=None, scaling_factors=None, tags=None)

Add an addition/subtraction relation.

Parameters:

output_namestr

(required) Name of the result variable in this component’s namespace.

input_namesiterable

(required) names of the input variables for this system.

vec_sizeint

Length of the first dimension of the input and output vectors (i.e number of rows, or vector length for a 1D vector) Default is 1.

lengthint

Length of the second dimension of the input and output vectors (i.e. number of columns) Default is 1 which results in input/output vectors of size (vec_size,).

valfloat or list or tuple or ndarray

The initial value of the variable being added in user-defined units. Default is 1.0.

unitsstr or None

Units in which the output variables will be provided to the component during execution. Default is None, which means it has no units.

res_unitsstr or None

Units in which the residuals of this output will be given to the user when requested. Default is None, which means it has no units.

descstr

Description of the variable.

lowerfloat or list or tuple or ndarray or Iterable 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 or Iterable 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 or ndarray

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

ref0float or ndarray

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

res_reffloat or ndarray

Scaling parameter. The value in the user-defined res_units of this output’s residual when the scaled value is 1. Default is 1.

scaling_factorsiterable of numeric

Scaling factors to apply to each input. Use [1,1,…] for addition, [1,-1,…] for subtraction Must be same length as input_names Default is None which results in a scaling factor of 1 on each input (element-wise addition).

tagsstr or list of strs

User defined tags that can be used to filter what gets listed when calling list_inputs and list_outputs and also when listing results from case recorders.

add_output(name, val=1.0, **kwargs)

Use add_equation instead of add_output to define equation systems.

Parameters:

namestr

Name of the variable in this component’s namespace.

valfloat or ndarray

The initial value of the variable being added in user-defined units. Default is 1.0.

**kwargsdict

Keyword arguments.

compute(inputs, outputs)

Compute the element wise addition or subtraction of inputs using numpy + operator.

Parameters:

inputsVector

Unscaled, dimensional input variables read via inputs[key].

outputsVector

Unscaled, dimensional output variables read via outputs[key].

initialize()

Declare options.