modules.applications.optimization.sat.mappings.choiising.ChoiIsing

class ChoiIsing

Bases: Mapping

Ising formulation for SAT problem using QUBO 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)	Uses the ChoiQUBO formulation and converts it to an Ising.
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: any, config: Config) → tuple[dict, float]

Uses the ChoiQUBO formulation and converts it to an Ising.

Parameters:

• problem -- SAT problem

• config -- Dictionary with the mapping config

Returns:

Dict with the ising, time it took to map it

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