utilities

Utility routines for the game_theory submodule

class quantecon.game_theory.utilities.NashResult

Bases: dict

Contain the information about the result of Nash equilibrium computation.

Notes

This is sourced from sicpy.optimize.OptimizeResult.

There may be additional attributes not listed above depending of the routine.

Attributes

NE	(tuple(ndarray(float, ndim=1))) Computed Nash equilibrium.
converged	(bool) Whether the routine has converged.
num_iter	(int) Number of iterations.
max_iter	(int) Maximum number of iterations.
init	(scalar or array_like) Initial condition used.

Methods

clear(() -> None.  Remove all items from D.)
copy(() -> a shallow copy of D)
fromkeys	Returns a new dict with keys from iterable and values equal to value.
get((k[,d]) -> D[k] if k in D, ...)
items(...)
keys(...)
pop((k[,d]) -> v, ...)	If key is not found, d is returned if given, otherwise KeyError is raised
popitem(() -> (k, v), ...)	2-tuple; but raise KeyError if D is empty.
setdefault((k[,d]) -> D.get(k,d), ...)
update(([E, ...)	If E is present and has a .keys() method, then does: for k in E: D[k] = E[k]
values(...)