modules.applications.optimization.sat.mappings.direct.Direct

class Direct

Bases: Mapping

Maps the problem from nnf to pysat.

__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 empty dict as this mapping has no configurable settings.
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)	Map from the nnf library into the python-sat library.
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 returned by the pysat solver into the reference format.

class Config

Bases: TypedDict

Empty config as this solver has no configurable settings.

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 empty dict as this mapping has no configurable settings.

Returns:

Empty dict

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[WCNF, float]

Map from the nnf library into the python-sat library.

Parameters:

• problem -- SAT problem

• config -- Config with the parameters specified in Config class

Returns:

Mapped problem and the 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: list) → tuple[dict, float]

Maps the solution returned by the pysat solver into the reference format.

Parameters:

solution -- List containing the solution

Returns:

Solution mapped accordingly, time it took to map it