modules.applications.optimization.sat.mappings.choiqubo.ChoiQUBO

class ChoiQUBO

Bases: Mapping

QUBO formulation for SAT problem by Choi (1004.2226).

__init__(): Constructor method.

Methods

`__init__`()	Constructor method.
`get_available_submodule_options`()	Gets the list of available options.
`get_available_submodules`(option)	If the module has submodules depending on certain options, this method should adjust the submodule_options accordingly.
`get_default_submodule`(option)	Returns the default submodule based on the provided option.
`get_depending_parameters`(option, config)	If the module has parameters depending on certain options, this method should return the parameters for the given option.
`get_parameter_options`()	Returns the configurable settings for this mapping.
`get_requirements`()	Return requirements of this module.
`get_submodule`(option)	Submodule is instantiated according to the information given in self.sub_options.
`map`(problem, config)	Converts a MaxSAT instance with hard and soft constraints into a graph problem -- solving MaxSAT then corresponds to solving an instance of the Maximal Independent Set problem.
`postprocess`(input_data, config, **kwargs)	Reverse transformation/mapping from the submodule's format to the mathematical formulation suitable for the parent module.
`preprocess`(input_data, config, **kwargs)	Maps the data to the correct target format.
`reverse_map`(solution)	Maps the solution back to the representation needed by the SAT class for validation/evaluation.

class Config

Bases: TypedDict

Attributes of a valid config.

hard_reward: float
soft_reward: float

clear() → None. Remove all items from D.

copy() → a shallow copy of D

fromkeys(value=None, /): Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /): Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items

keys() → a set-like object providing a view on D's keys

pop(k[, d]) → v, remove specified key and return the corresponding value.: If the key is not found, return the default if given; otherwise, raise a KeyError.

popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order. Raises KeyError if the dict is empty.

setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update([E, ]**F) → None. Update D from mapping/iterable E and F.: If E is present and has a .keys() method, then does: for k in E.keys(): D[k] = E[k] If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values

get_available_submodule_options() → list

Gets the list of available options.

Returns:: List of module options

get_available_submodules(option: list) → list

If the module has submodules depending on certain options, this method should adjust the submodule_options accordingly.

Parameters:: option -- List of chosen options
Returns:: List of available submodules

get_default_submodule(option: str) → Core

Returns the default submodule based on the provided option.

Parameters:: option -- Option specifying the submodule
Returns:: Instance of the corresponding submodule
Raises:: NotImplementedError -- If the option is not recognized

get_depending_parameters(option: str, config: dict) → dict

If the module has parameters depending on certain options, this method should return the parameters for the given option.

Parameters:

option -- The chosen option
config -- Current config dictionary

Returns:

The parameters for the given option

get_parameter_options() → dict

Returns the configurable settings for this mapping.

Returns:: Dictionary with parameter options

return {
        "hard_reward": {
            "values": [0.1, 0.5, 0.9, 0.99],
            "description": "What Bh/A ratio do you want? (How strongly to enforce hard constraints)"
        },
        "soft_reward": {
            "values": [0.1, 1, 2],
            "description": "What Bh/Bs ratio do you want? This value is multiplied with the "
            "number of tests."
        }
    }

static get_requirements() → list[dict]

Return requirements of this module.

Returns:: List of dict with requirements of this module

get_submodule(option: str) → Core

Submodule is instantiated according to the information given in self.sub_options. If self.sub_options is None, get_default_submodule is called as a fallback.

Parameters:: option -- String with the options
Returns:: Instance of a module

map(problem: tuple[And, list], config: Config) → tuple[dict, float]

Converts a MaxSAT instance with hard and soft constraints into a graph problem -- solving MaxSAT then corresponds to solving an instance of the Maximal Independent Set problem. See Andrew Lucas (2014), or the original publication by Choi (1004.2226).

Parameters:

problem -- A tuple containing hard and soft constraints
config -- Config with the parameters specified in Config class

Returns:

Dictionary containing the QUBO representation and the time taken

postprocess(input_data: any, config: dict, **kwargs) → tuple[any, float]

Reverse transformation/mapping from the submodule's format to the mathematical formulation suitable for the parent module.

Parameters:

input_data -- Data which should be reverse-mapped
config -- Config of the reverse mapping
kwargs -- Optional keyword arguments

Returns:

Tuple with reverse-mapped problem and the time it took to map it

preprocess(input_data: any, config: dict, **kwargs) → tuple[any, float]

Maps the data to the correct target format.

Parameters:

input_data -- Data which should be mapped
config -- Config of the mapping
kwargs -- Optional keyword arguments

Returns:

Tuple with mapped problem and the time it took to map it

reverse_map(solution: dict) → tuple[dict, float]

Maps the solution back to the representation needed by the SAT class for validation/evaluation.

Parameters:: solution -- Dictionary containing the solution
Returns:: Solution mapped accordingly, time it took to map it