aiida-optimize

AiiDA Plugin for running optimization algorithms.

status stable

AiiDA >=2.0.0,<3.0.0

General information

Install pip install aiida-optimize

Source code https://github.com/greschd/aiida-optimize

Documentation https://aiida-optimize.readthedocs.io

Author(s) Dominik Gresch

Contact greschd@gmx.ch

Python import import aiida_optimize

Latest version 1.0.2

Released 2023-03-30

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Plugins provided

Workflows 4

Entry points

WorkChains and work functions aiida.workflows

optimize.optimize

Runs an optimization procedure, given an optimization engine that defines the optimization algorithm, and a process which evaluates the function to be optimized.

Input	Required	Valid types	Description
`engine`	true	`Str`	Engine that runs the optimization.
`engine_kwargs`	true	`Dict`	Keyword arguments passed to the optimization engine.
`evaluate_process`	true	`Str`	Process which produces the result to be optimized.
`evaluate`	false		Inputs that are passed to all evaluation processes.
`metadata`	false

Output	Required	Description
`optimal_process_output`	true	Output value of the optimal evaluation process.
`optimal_process_uuid`	true	UUID of the optimal evaluation process.
`engine_outputs`	false
`optimal_process_input`	false	Input value of the optimal evaluation process.

Exit status	Message
1	The process has failed with an unspecified error.
2	The process failed with legacy failure mode.
10	The process returned an invalid output.
11	The process did not register a required output.
201	Optimization failed because one of the evaluate processes did not finish ok.
202	Optimization failed because the engine did not finish ok.

optimize.wrappers.add_inputs

Wrapper workchain that takes inputs as keys and values and passes it on to a sub-process. This enables taking a process which was not designed to be used in optimization, and optimize with respect to some arbitrary input. Inputs which always remain the same can be specified in the ``inputs`` namespace, whereas the inputs to be optimized are given through the ``added_input_keys`` and ``added_input_values`` inputs. The outputs of the wrapper workchain are the same as those of the wrapped process. The "added" inputs can only be BaseType sub-classes, or attributes of a Dict. For each input, its port location is given in the "added_input_keys" input. For example, ``x.y`` would set the ``y`` input in the ``x`` namespace. For cases where the input is a Dict attribute, the (possibly nested) attribute name is given after a colon. That means ``x:a.b`` would set the ``['a']['b']`` attribute of the ``Dict`` given in the ``x`` input. In cases where only a single input needs to be added, they can be specified directly instead of wrapped in a List.

Input	Required	Valid types	Description
`added_input_keys`	true	`List, Str`	Specifies the location of each added input.
`added_input_values`	true	`List, BaseType`	Values of the added inputs to be passed into the sub-process.
`sub_process`	true	`Str`	The class of the process that should be wrapped.
`inputs`	false		Inputs to be passed on to the sub-process.
`metadata`	false

Exit status	Message
1	The process has failed with an unspecified error.
2	The process failed with legacy failure mode.
10	The process returned an invalid output.
11	The process did not register a required output.
201	Workchain failed because the sub-process did not finish ok.

optimize.wrappers.concatenate

Allows concatenating an arbitrary number of sub-processes. A wrapper workchain that allows concatenating an arbitrary number of sub-processes. Outputs of one processes can be configured to be passed to the next one.

Input	Required	Valid types	Description
`output_input_mappings`	true	`List`	Defines how inputs are passed between sub-processes. Each list entry entry has the form `((process_label_a, process_label_b), mapping)`, and defines outputs of process A to be passed to process B. The `mapping` values are dictionaries `{'output_name': 'input_name'}` giving the output name (in process A) and input name (in process B) for each value to pass.
`process_inputs`	true		Inputs which are passed on to the sub-processes. The inputs should be grouped into a namespace identified by the process label.
`process_labels`	true	`List`	A list of pairs (label, process_name). The labels can be any string, the process_name needs to be loadable by `aiida_optimize.process_inputs.load_object`, and defines which process is being run.
`metadata`	false

Output	Required	Valid types	Description
`process_outputs`	true

Exit status	Message
1	The process has failed with an unspecified error.
2	The process failed with legacy failure mode.
10	The process returned an invalid output.
11	The process did not register a required output.
200	Workchain failed because a sub-process failed.

optimize.wrappers.create_evaluate

Wrapper workchain to combine two processes: The first process _creates_ a result, and the second _evaluates_ that result. The purpose of this workchain is to facilitate optimization of processes which don't natively produce an output that can be optimized, by only having to add the 'evaluation' part.

Input	Required	Valid types	Description
`create`	true		Inputs which are passed on to the create sub-process.
`create_process`	true	`Str`	The sub-process which performs the create step.
`evaluate_process`	true	`Str`	The sub-process which performs the evaluate step.
`output_input_mapping`	true	`Dict`	A mapping from output names of the create process to input names of the evaluate process. These outputs (if present) are forwarded to the evaluate process.
`evaluate`	false		Inputs which are passed on to the evaluate sub-process.
`metadata`	false

Output	Required	Valid types	Description
`create`	true
`evaluate`	true

Exit status	Message
1	The process has failed with an unspecified error.
2	The process failed with legacy failure mode.
10	The process returned an invalid output.
11	The process did not register a required output.
201	Workchain failed because the 'create' sub-process failed.
202	Workchain failed because the 'evaluate' sub-process failed.