modopt.Optimizer

class modopt.Optimizer(problem, recording=False, out_dir=None, hot_start_from=None, hot_start_atol=0.0, hot_start_rtol=0.0, visualize=[], keep_viz_open=False, turn_off_outputs=False, **kwargs)

Base class for all optimization algorithms in modOpt. This class provides the common functionalities for all the optimization algorithms, such as checking the correctness of first derivatives, recording the outputs, hot-starting the optimization, and visualizing the scalar variables. The user-defined optimization algorithms should inherit from this class.

Attributes

problemProblem or ProblemLite

The problem to be solved. Needs to be a Problem() or ProblemLite() object.

problem_namestr

The name of the problem.

solver_namestr

The name of the solver.

optionsOptionsDictionary

The options dictionary for the optimizer.

recordh5py.File

The record file to store the outputs from all iterations of the optimization.

hot_start_recordh5py.File

The record file from which to hot-start the optimization. modOpt loads and reuses the outputs stored in this file from a previous optimization.

out_dirstr

The directory to store all the output files generated from the optimization.

modopt_output_fileslist

The list of all files generated by modOpt during the optimization.

visualizerVisualizer

The visualizer object to plot the scalar variables during the optimization.

timestampstr

The timestamp for the optimization.

scalar_outputslist

The list of scalar outputs provided by the optimizer after each iteration.

available_outputsdict

The dictionary of all available outputs from the optimizer after each iteration.

resultsdict

The dictionary containing the results of the optimization.

update_outputs_countint

Number of times the update_outputs() method is called. Only relevant for development and debugging purposes.

Methods

check_first_derivatives([x, step, formulation])	Check the first derivatives of the optimization problem using finite differences.
initialize()	Set solver name and any solver-specific options.
print_results([summary_table, all])	Print the results of the optimization problem to the terminal.
setup()	Set up any solver-specific attributes or modules (e.g., merit function or Hessian approximation) required by the optimization algorithm, during optimizer instantiation.
solve()	Run the optimization algorithm to solve the problem.

__init__(problem, recording=False, out_dir=None, hot_start_from=None, hot_start_atol=0.0, hot_start_rtol=0.0, visualize=[], keep_viz_open=False, turn_off_outputs=False, **kwargs)

Initialize the Optimizer object. Sets up recording, hot-starting, and visualization.

Parameters

problemProblem or ProblemLite

The problem to be solved. Required argument for all optimizers.

recordingbool, default=False

If True, record all outputs from the optimization. This needs to be enabled for hot-starting the same problem later, if the optimization is interrupted.

out_dirstr, optional

The directory to store all the output files generated from the optimization.

hot_start_fromstr, optional

The record file from which to hot-start the optimization.

hot_start_atolfloat, default=0.

The absolute tolerance check for the inputs when reusing outputs from the hot-start record.

hot_start_rtolfloat, default=0.

The relative tolerance check for the inputs when reusing outputs from the hot-start record.

visualizelist, default=[]

The list of scalar variables to be visualized during the optimization.

keep_viz_openbool, default=False

If True, keep the visualization window open after the optimization is complete.

turn_off_outputsbool, default=False

If True, prevent modOpt from generating any output files.

**kwargs

Additional optimizer-specific keyword arguments.

check_first_derivatives(x=None, step=1e-06, formulation='rs')

Check the first derivatives of the optimization problem using finite differences.

Parameters

xnp.ndarray, optional

The design variables at which the derivatives are to be checked. If not provided, the initial design variables are used.

stepfloat, default=1e-6

The step size for the finite differences.

abstract initialize()

Set solver name and any solver-specific options.

print_results(summary_table=False, all=False)

Print the results of the optimization problem to the terminal.

Parameters

summary_tablebool, default=False

If True, print the summary table for the optimization.

allbool, default=False

If False, print only the scalar outputs of the optimization problem. Otherwise, print all the outputs of the optimization problem.

abstract setup()

Set up any solver-specific attributes or modules (e.g., merit function or Hessian approximation) required by the optimization algorithm, during optimizer instantiation. This method is called after initialize().

abstract solve()

Run the optimization algorithm to solve the problem.