optimize_army.py

from scipy import optimize
import numpy as np

import board
import generate_base
import generate_army
import simulator
import util
import board_viz
from constants import *


MAIN_BOARD = board.GameBoard(generate_base.generate_main_base())


def optimize_function(z, *params):
    # create army
    pairs = util.pairs_from_list(z)
    army = generate_army.generate_army_from_row(z)

    # check if legal army
    if not all([util.in_margins(pair) for pair in pairs]):
        return np.inf
    sim = simulator.Simulator(MAIN_BOARD)
    stats = sim.run(army, debug=False)
    print(stats["percent"])
    return 1 - stats["percent"]


# generate first configuration
army0 = generate_army.generate_random_army()[0]
pairs0 = [t.get_pos() for t in army0]
x0 = util.list_from_pairs(pairs0)

# run simulated annealing
ret = optimize.basinhopping(optimize_function, x0, disp=True)
print("global minimum: x = %.4f, f(x0) = %.4f" % (ret.x, ret.fun))
army = generate_army.generate_army_from_row(ret.x)
board_viz.viz_board(viz=True, army=army, game_board=MAIN_BOARD)