Miscellaneous

About This Package

This package has various miscellaneuos helper functions and modules

Helper Functions

Accumulation of general helper functions

games.misc.helpers.powerset(iterable: Iterable) → List[tuple]

Returns a power set from the given iterable.

Parameters

iterable (Iterable) – Iterable from which to take the power set from.

Returns

A list of tuples containing subsets of the given Iterable.

Return type

List[tuple]

games.misc.helpers.verify_player_list(game: games.types.game.Game) → None

Check that player list is nonempty and indexed from 0 to N.

Parameters

game (Game) – Game to check.

Raises

ValueError – If the player list is empty or not indexed properly.

Optimization Wrappers

Module for wrapping optimization solvers for use in the game package.

class games.misc.solver.SolverWrapper(solver: str, progress: bool)

Wrapper for solving Convex Programs.

Parameters

  • solver (str) – Which solver to use.

  • progress (bool) – Whether to show progress of solver.

SUPPORTED

Which solvers are supported overall.

Type

List(str)

LP_SUPPORTED

Which solvers are supported for solving an LP.

Type

List(str)

progress

Whether to show progress of solver.

Type

bool

returnall

Whether to wrap solver output in a dict or just return everything.

Type

bool

solver

Which solver to use.

Type

str

check_solver(solver: str) → None

check if solver is supported and perform some necessary setup.

Parameters

solver (str) – Which solver to use.

Raises

ImportError – If solver given is not an implemented solver.

lp(c: numpy.ndarray, G: numpy.ndarray, h: numpy.ndarray, A: numpy.ndarray, b: numpy.ndarray) → Optional[Dict[str, Any]]

solver for LP. Form is min c^T x subject to G x <= h , A x = b.

Parameters

  • c (np.ndarray) – Objective function.

  • G (np.ndarray) – Linear inequality constraint.

  • h (np.ndarray) – Linear inequality constraint.

  • A (np.ndarray) – Linear equality constraint.

  • b (np.ndarray) – Linear equality constraint.

Returns

If not returnall, return {‘min’: minimum of objective, ‘argmin’: value in which the minimum is obtained.}.

Return type

Optional[Dict[str, Any]]

Raises

ImportError – If specified solver is not an implemented LP solver.

games.misc.solver.lp(solver: str, c: numpy.ndarray, G: numpy.ndarray, h: numpy.ndarray, A: numpy.ndarray = None, b: numpy.ndarray = None, progress: bool = False) → Dict[str, Any]

lp solver of the standard form: min c^T x subject to G x <= h , A x = b.

Parameters

  • solver (str) – which solver to use for solving the linear program.

  • c (np.ndarray) – Objective function.

  • G (np.ndarray) – Linear inequality constraint.

  • h (np.ndarray) – Linear inequality constraint.

  • A (np.ndarray, optional) – Linear equality constraint.

  • b (np.ndarray, optional) – Linear equality constraint.

  • progress (bool, optional) – Toggle to show progress of optimization solver.

Returns

{‘min’: minimum of objective, ‘argmin’: value in which the minimum is obtained.}

Return type

Dict[str, Any]

Indices and tables