本文整理汇总了Python中optimizer.Optimizer.run方法的典型用法代码示例。如果您正苦于以下问题：Python Optimizer.run方法的具体用法？Python Optimizer.run怎么用？Python Optimizer.run使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类optimizer.Optimizer的用法示例。
在下文中一共展示了Optimizer.run方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: main
# 需要导入模块: from optimizer import Optimizer [as 别名]
# 或者: from optimizer.Optimizer import run [as 别名]
def main(args, profile=False):
db = DataBase(args.games)
results = db.load_game_results(mingames=50)
print('{} games loaded.'.format(len(results)))
players = db.load_players()
optimizer = Optimizer(disp=True)
optimizer.load_games(results)
maxiter = 30 if profile else 0
ratings, f, v = optimizer.run(method='l-bfgs-b', maxiter=maxiter)
if profile:
return
print()
by_rating = []
for iplayer, rating in ratings.items():
print(players[iplayer])
mr = 0
for date, r in sorted(rating.items()):
date = datetime.date.fromtimestamp(date * 24 * 3600)
print(date.isoformat(), r)
if r > mr:
mr = r
by_rating.append((mr, players[iplayer]))
print()
print(f)
print(f.calc(0.2) - f.calc(-0.2))
best = list(sorted(by_rating))[-20:]
for r, p in reversed(best):
print('{:24} {}'.format(p, r))示例2: test_symmetric_wins
# 需要导入模块: from optimizer import Optimizer [as 别名]
# 或者: from optimizer.Optimizer import run [as 别名]
def test_symmetric_wins(self):
o = Optimizer(rand_seed=239)
o.load_games([(1, 2, 1, 1), (1, 2, 1, 0), (2, 1, 1, 1), (2, 1, 1, 0)])
rating, f, v = o.run(method='Newton-CG')
self.assertAlmostEqual(
f.calc(convert_rating_diff(rating[1][1] - rating[2][1])), 0.5, 2)
self.assertLess(abs(rating[1][1] - rating[2][1]), 5)示例3: test_draw
# 需要导入模块: from optimizer import Optimizer [as 别名]
# 或者: from optimizer.Optimizer import run [as 别名]
def test_draw(self):
o = Optimizer(rand_seed=239)
o.load_games([(1, 2, 1, 2), (2, 1, 1, 2)])
rating, f, v = o.run(method='cg')
self.assertAlmostEqual(f.calc(0), 0.5, 3)
self.assertAlmostEqual(
f.calc(convert_rating_diff(rating[1][1] - rating[2][1])), 0.5, 2)
self.assertLess(abs(rating[1][1] - rating[2][1]), 5)示例4: test_single_game
# 需要导入模块: from optimizer import Optimizer [as 别名]
# 或者: from optimizer.Optimizer import run [as 别名]
def test_single_game(self):
o = Optimizer(rand_seed=239)
o.load_games([(1, 2, 1, 1)])
ratings, f, v = o.run()
(total, likelihood, regularization, smoothness,
func_hard_reg, func_soft_reg) = o.objective(v, verbose=True)
self.assertTrue(100 < ratings[1][1] < 4000)
self.assertTrue(100 < ratings[2][1] < 4000)
self.assertGreater(
f.calc(convert_rating_diff(ratings[1][1] - ratings[2][1])), 0.5)
self.assertGreater(ratings[1][1], ratings[2][1])
total = o.objective(v)示例5: test_time_regularization
# 需要导入模块: from optimizer import Optimizer [as 别名]
# 或者: from optimizer.Optimizer import run [as 别名]
def test_time_regularization(self):
o = Optimizer(rand_seed=239)
o.load_games([(1, 2, 1, 1), (2, 1, 1, 0), (1, 2, 2, 0), (2, 1, 2, 1)])
rating, f, v = o.run()
(total1, _, reg, smoothness1, func_hard_reg,
func_soft_reg) = o.objective(v, verbose=True)
self.assertLess(func_hard_reg, 1)
self.assertGreater(smoothness1, 0.001)
self.assertGreater(rating[1][1], rating[1][2])
self.assertLess(rating[2][1], rating[2][2])
self.assertGreater(rating[1][1], rating[2][1])
self.assertLess(rating[1][2], rating[2][2])
prob1 = f.calc(convert_rating_diff(rating[1][1] - rating[2][1]))
self.assertGreater(prob1, 0.51)
prob2 = f.calc(convert_rating_diff(rating[1][2] - rating[2][2]))
self.assertLess(prob2, 0.49)示例6: test_games1
# 需要导入模块: from optimizer import Optimizer [as 别名]
# 或者: from optimizer.Optimizer import run [as 别名]
def test_games1(self):
o = Optimizer(rand_seed=239)
o.load_games(GAMES1)
rating, f, _ = o.run(method='newton-cg')