Integrate lrsnash with enummixed call

src/pygambit/nash.py

@@ -30,7 +30,7 @@
 
 import pygambit.gambit as libgbt
 
-from . import nashphc
+from . import nashlrs, nashphc
 
 MixedStrategyEquilibriumSet = list[libgbt.MixedStrategyProfile]
 MixedBehaviorEquilibriumSet = list[libgbt.MixedBehaviorProfile]
@@ -103,7 +103,7 @@ def enumpure_solve(game: libgbt.Game, use_strategic: bool = True) -> NashComputa
 def enummixed_solve(
         game: libgbt.Game,
         rational: bool = True,
-        use_lrs: bool = False
+        lrsnash_path: pathlib.Path | str | None = None,
 ) -> NashComputationResult:
     """Compute all :ref:`mixed-strategy Nash equilibria <gambit-enummixed>`
     of a two-player game using the strategic representation.
@@ -112,11 +112,23 @@ def enummixed_solve(
     ----------
     game : Game
         The game to compute equilibria in.
+
     rational : bool, default True
         Compute using rational numbers.  If `False`, using floating-point
         arithmetic.  Using rationals is more precise, but slower.
-    use_lrs : bool, default False
-        If `True`, use the implementation based on ``lrslib``.  This is experimental.
+
+    lrsnash_path : pathlib.Path | str | None = None,
+        If specified, use lrsnash [1]_ to solve the systems of equations.
+        This argument specifies the path to the lrsnash executable.
+
+        .. versionadded:: 16.3.0
+
+    Returns
+    -------
+    res : NashComputationResult
+        The result represented as a ``NashComputationResult`` object.
+
+    .. [1] http://cgm.cs.mcgill.ca/~avis/C/lrs.html
 
     Returns
     -------
@@ -128,14 +140,24 @@ def enummixed_solve(
     RuntimeError
         If game has more than two players.
     """
-    if use_lrs or rational:
+    if lrsnash_path is not None:
+        equilibria = nashlrs.lrsnash_solve(game, lrsnash_path=lrsnash_path)
+        return NashComputationResult(
+            game=game,
+            method="enummixed",
+            rational=True,
+            use_strategic=True,
+            parameters={"lrsnash_path": lrsnash_path},
+            equilibria=equilibria,
+        )
+    if rational:
         equilibria = libgbt._enummixed_strategy_solve_rational(game)
     else:
         equilibria = libgbt._enummixed_strategy_solve_double(game)
     return NashComputationResult(
         game=game,
         method="enummixed",
-        rational=use_lrs or rational,
+        rational=rational,
         use_strategic=True,
         equilibria=equilibria
     )

src/pygambit/nashlrs.py

@@ -2,6 +2,7 @@
 """
 
 import itertools
+import pathlib
 import subprocess
 import sys
 
@@ -33,9 +34,12 @@ def _parse_lrs_output(game: gbt.Game, txt: str) -> list[gbt.MixedStrategyProfile
     return eqa
 
 
-def lrsnash_solve(game: gbt.Game) -> list[gbt.MixedStrategyProfileRational]:
+def lrsnash_solve(game: gbt.Game,
+                  lrsnash_path: pathlib.Path | str) -> list[gbt.MixedStrategyProfileRational]:
+    if len(game.players) != 2:
+        raise RuntimeError("Method only valid for two-player games.")
     with util.make_temporary(_generate_lrs_input(game)) as infn:
-        result = subprocess.run(["./lrsnash", infn], encoding="utf-8",
+        result = subprocess.run([lrsnash_path, infn], encoding="utf-8",
                                 stdout=subprocess.PIPE, stderr=subprocess.STDOUT)
         if result.returncode != 0:
             raise ValueError(f"PHC run failed with return code {result.returncode}")
@@ -44,7 +48,7 @@ def lrsnash_solve(game: gbt.Game) -> list[gbt.MixedStrategyProfileRational]:
 
 def main():
     game = gbt.Game.parse_game(sys.stdin.read())
-    eqa = lrsnash_solve(game)
+    eqa = lrsnash_solve(game, "./lrsnash")
     for eqm in eqa:
         print("NE," +
               ",".join(str(eqm[strat]) for player in game.players for strat in player.strategies))