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https://gitea.wildfiregames.com/0ad/0ad
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5473393e30
Implement a simple HTTP server to start games, receive the gamestate and pass commands to the simulation. This is mainly intended for training reinforcement learning agents in 0 AD. As such, a python client and a small example are included. This option can be enabled using the -rl-interface flag. Patch by: irishninja Reviewed By: wraitii, Itms Fixes #5548 Differential Revision: https://code.wildfiregames.com/D2199 This was SVN commit r23917.
98 lines
3.5 KiB
Python
98 lines
3.5 KiB
Python
# This script provides an overview of the zero_ad wrapper for 0 AD
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from os import path
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import zero_ad
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# First, we will define some helper functions we will use later.
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import math
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def dist (p1, p2):
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return math.sqrt(sum((math.pow(x2 - x1, 2) for (x1, x2) in zip(p1, p2))))
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def center(units):
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sum_position = map(sum, zip(*map(lambda u: u.position(), units)))
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return [x/len(units) for x in sum_position]
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def closest(units, position):
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dists = (dist(unit.position(), position) for unit in units)
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index = 0
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min_dist = next(dists)
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for (i, d) in enumerate(dists):
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if d < min_dist:
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index = i
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min_dist = d
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return units[index]
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# Connect to a 0 AD game server listening at localhost:6000
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game = zero_ad.ZeroAD('http://localhost:6000')
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# Load the Arcadia map
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samples_dir = path.dirname(path.realpath(__file__))
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scenario_config_path = path.join(samples_dir, 'arcadia.json')
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with open(scenario_config_path, 'r') as f:
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arcadia_config = f.read()
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state = game.reset(arcadia_config)
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# The game is paused and will only progress upon calling "step"
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state = game.step()
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# Units can be queried from the game state
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citizen_soldiers = state.units(owner=1, type='infantry')
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# (including gaia units like trees or other resources)
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nearby_tree = closest(state.units(owner=0, type='tree'), center(citizen_soldiers))
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# Action commands can be created using zero_ad.actions
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collect_wood = zero_ad.actions.gather(citizen_soldiers, nearby_tree)
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female_citizens = state.units(owner=1, type='female_citizen')
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house_tpl = 'structures/spart_house'
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x = 680
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z = 640
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build_house = zero_ad.actions.construct(female_citizens, house_tpl, x, z, autocontinue=True)
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# These commands can then be applied to the game in a `step` command
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state = game.step([collect_wood, build_house])
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# We can also fetch units by id using the `unit` function on the game state
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female_id = female_citizens[0].id()
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female_citizen = state.unit(female_id)
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# A variety of unit information can be queried from the unit:
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print('female citizen\'s max health is', female_citizen.max_health())
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# Raw data for units and game states are available via the data attribute
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print(female_citizen.data)
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# Units can be built using the "train action"
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civic_center = state.units(owner=1, type="civil_centre")[0]
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spearman_type = 'units/spart_infantry_spearman_b'
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train_spearmen = zero_ad.actions.train([civic_center], spearman_type)
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state = game.step([train_spearmen])
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# Let's step the engine until the house has been built
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is_unit_busy = lambda state, unit_id: len(state.unit(unit_id).data['unitAIOrderData']) > 0
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while is_unit_busy(state, female_id):
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state = game.step()
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# The units for the other army can also be controlled
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enemy_units = state.units(owner=2)
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walk = zero_ad.actions.walk(enemy_units, *civic_center.position())
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game.step([walk], player=[2])
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# Step the game engine a bit to give them some time to walk
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for _ in range(150):
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state = game.step()
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# Let's attack with our entire military
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state = game.step([zero_ad.actions.chat('An attack is coming!')])
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while len(state.units(owner=2, type='unit')) > 0:
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attack_units = [ unit for unit in state.units(owner=1, type='unit') if 'female' not in unit.type() ]
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target = closest(state.units(owner=2, type='unit'), center(attack_units))
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state = game.step([zero_ad.actions.attack(attack_units, target)])
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while state.unit(target.id()):
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state = game.step()
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game.step([zero_ad.actions.chat('The enemies have been vanquished. Our home is safe again.')])
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