utilities¶
Utility routines for the game_theory submodule

class
quantecon.game_theory.utilities.
NashResult
[source]¶ 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
()copy
()fromkeys
(iterable[, value])Create a new dictionary with keys from iterable and values set to value. get
(key[, default])Return the value for key if key is in the dictionary, else default. items
()keys
()pop
(key[, default])If key is not found, default is returned if given, otherwise KeyError is raised popitem
(/)Remove and return a (key, value) pair as a 2tuple. setdefault
(key[, default])Insert key with a value of default if key is not in the dictionary. update
([E, ]**F)If E is present and has a .keys() method, then does: for k in E: 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
()