# Copyright (c) 2015, Florian Jung and Timm Weber # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # 1. Redistributions of source code must retain the above copyright notice, # this list of conditions and the following disclaimer. # # 2. Redistributions in binary form must reproduce the above copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # # 3. Neither the name of the copyright holder nor the names of its # contributors may be used to endorse or promote products derived from this # software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS # IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, # THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR # PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR # CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, # EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR # PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF # LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING # NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. import math from interval_utils import * import random import nogui import mechanics friendly_players=["Windfisch","windfisch","Cyanide","cyanide"] +\ ["Midna","Nayru","Farore","Din","Ezelo","Navi","Zelda","Tetra","Link","Ciela","Linebeck","Salia","Epona","Shiek"] +\ ["Vaati","Ganon","Ganondorf","Ghirahim","Agahnim"] class Strategy: def __init__(self, c, gui=None): self.target = (0,0) self.target_type = None self.target_cell = None self.color = (0,0,0) self.c = c self.do_approach_friends = True if gui != None: self.gui = gui else: self.gui = nogui def get_my_smallest(self): return sorted(self.c.player.own_cells, key = lambda x: x.mass)[0] def dist(self, cell): return math.sqrt((cell.pos[0]-self.c.player.center[0])**2 + (cell.pos[1]-self.c.player.center[1])**2) def edible(self, cell): return ((cell.is_food) or (cell.mass <= self.get_my_smallest().mass * 0.75)) and not (cell.is_virus) def threat(self, cell): if cell.is_virus and (cell.mass <= self.get_my_smallest().mass * 0.75): return True elif (cell.mass <= self.get_my_smallest().mass * 1.25): return True else: return False def rival(self, cell, food): if cell.is_virus or cell.is_food: return False if cell.cid in self.c.player.own_ids: return False if cell.mass < 1.25*self.get_my_smallest().mass: return food.is_food or cell.size > 1.25*food.size else: return False def splitkiller(self, cell): return not cell.is_virus and not cell.is_food and cell.mass+20 > 1.25*2*self.get_my_smallest().mass and cell.mass / 15. < self.c.player.total_mass def hugecell(self, cell): return not cell.is_virus and not cell.is_food and cell.mass / 15. >= self.c.player.total_mass def nonsplitkiller(self, cell): return not cell.is_virus and not cell.is_food and 1.20*self.get_my_smallest().mass < cell.mass and cell.mass+20 < 1.25*2*self.get_my_smallest().mass def quality(self, cell, cells, myspeed): dd_sq = max((cell.pos[0]-self.c.player.center[0])**2 + (cell.pos[1]-self.c.player.center[1])**2,0.001) sigma = 500 * max(cell.mass,1) # TODO FIXME don't try to eat running away cells if mechanics.speed(cell) - myspeed >= 0: sigma = sigma / 3 / math.exp((mechanics.speed(cell)-myspeed)/10) dist_score = -math.exp(-dd_sq/(2*sigma**2)) rivals = filter(lambda r : self.rival(r,cell), cells) hugecells = filter(self.hugecell, cells) splitkillers = filter(self.splitkiller, cells) nonsplitkillers = filter(self.nonsplitkiller, cells) rival_score = 0 for r in rivals: dd_sq = max(0.001, (r.pos[0]-cell.pos[0])**2 + (r.pos[1]-cell.pos[1])**2) sigma = r.size + 100 rival_score += math.exp(-dd_sq/(2*sigma**2)) hugecell_score = 0 for s in hugecells: dd_sq = max(0.001, (s.pos[0]-cell.pos[0])**2 + (s.pos[1]-cell.pos[1])**2) sigma = s.size + 10 hugecell_score += math.exp(-dd_sq/(2*sigma**2)) splitkill_score = 0 for s in splitkillers: dd_sq = max(0.001, (s.pos[0]-cell.pos[0])**2 + (s.pos[1]-cell.pos[1])**2) sigma = s.size + 650 + 250 splitkill_score += math.exp(-dd_sq/(2*sigma**2)) nonsplitkill_score = 0 for s in nonsplitkillers: dd_sq = max(0.001, (s.pos[0]-cell.pos[0])**2 + (s.pos[1]-cell.pos[1])**2) sigma = (75+s.size) + 250 nonsplitkill_score += math.exp(-dd_sq/(2*sigma**2)) density_score = 0 sigma = 300 #for f in filter(lambda c : c.is_food and c!=cell, self.c.world.cells.values()): # dd_sq = (f.pos[0]-cell.pos[0])**2 + (f.pos[1]-cell.pos[1])**2 # density_score -= math.exp(-dd_sq/(2*sigma**2)) wall_score = 0 wall_dist = min( cell.pos[0]-self.c.world.top_left[1], self.c.world.bottom_right[1]-cell.pos[0], cell.pos[1]-self.c.world.top_left[0], self.c.world.bottom_right[0]-cell.pos[1] ) sigma = 100 wall_score = math.exp(-wall_dist**2/(2*sigma**2)) return 0.5*dist_score + 0.2*rival_score + 5.0*hugecell_score + 5.0*nonsplitkill_score + 15*splitkill_score + 0.1*density_score + 5*wall_score ##print (density_score) #return density_score def process_frame(self): runaway = False my_smallest = min(self.c.player.own_cells, key=lambda cell : cell.mass) my_largest = max(self.c.player.own_cells, key=lambda cell : cell.mass) cells = filter(lambda r : not r.is_food and not r.is_virus, self.c.world.cells.values()) friendly_cells = list(filter(lambda c : c.is_virus or c.name in friendly_players, self.c.world.cells.values())) if friendly_cells: dist_to_friend = min(map(lambda c : (self.c.player.center-c.pos).len() - max(my_largest.size, c.size), friendly_cells)) else: dist_to_friend = float('inf') if dist_to_friend < 20 or my_largest.mass < 36: if self.do_approach_friends: print("not approaching friends") self.do_approach_friends = False elif dist_to_friend > 200 and my_largest.mass > 36 + 10*16: if not self.do_approach_friends: print("approaching friends") self.do_approach_friends = True if friendly_cells and self.do_approach_friends: friend_to_feed = max(friendly_cells, key=lambda c:c.mass) if friend_to_feed.mass < 1.25 * my_largest.mass: print("friend too small") friend_to_feed = None if friend_to_feed: self.gui.hilight_cell(friend_to_feed, (255,255,255),(255,127,127),30) self.target_cell = friend_to_feed self.target_type = 'friend' if self.do_approach_friends: for c in self.c.player.own_cells: self.gui.hilight_cell(c, (255,255,255), (255,127,127), 20) # can this cell feed that cell? # "False" means "No, definitely not" # "True" means "Maybe" def can_feed(this, that): if that.is_food or that.is_ejected_mass or that.size < 43: # too small cells cannot eat the ejected mass return False relpos = this.pos-that.pos dist = relpos.len() if dist == 0 or dist >= 700 + this.size + that.size: return False return check_cell_in_interval(this.pos, that, (this.movement_angle - 10*math.pi/180, this.movement_angle + 10*math.pi/180)) success_rate = 0 for my_cell in self.c.player.own_cells: try: my_cell.movement_angle except AttributeError: print("cannot calculate shoot angle, too few backlog") continue # check if ejecting mass would feed a friend possibly_feedable_cells = list(filter(lambda c : can_feed(my_cell, c), self.c.world.cells.values())) possibly_feedable_cells.sort(key = lambda c : (my_cell.pos - c.pos).len()) good_intervals = [] for feedable in possibly_feedable_cells: self.gui.hilight_cell(feedable, (255,192,127), (127,127,255)) if feedable not in friendly_cells: break good_intervals += canonicalize_angle_interval( interval_occupied_by_cell(my_cell.pos, feedable) ) good_intervals = merge_intervals(good_intervals) area = interval_area( intersection(good_intervals, canonicalize_angle_interval((my_cell.movement_angle - mechanics.eject_delta*math.pi/180, my_cell.movement_angle + mechanics.eject_delta*math.pi/180))) ) success_rate += area / (2*mechanics.eject_delta*math.pi/180) / len(list(self.c.player.own_cells)) self.gui.draw_bar(((100,40),(500,24)), success_rate, thresh=.80, color=(0,0,127)) if success_rate >= 0.80: self.c.send_shoot() # enemy/virus/friend-we-would-kill avoidance forbidden_intervals = [] for cell in self.c.world.cells.values(): relpos = ((cell.pos[0]-self.c.player.center[0]),(cell.pos[1]-self.c.player.center[1])) dist = math.sqrt(relpos[0]**2+relpos[1]**2) # find out the allowed minimum distance allowed_dist = None if cell.is_virus: if cell.mass < my_largest.mass: allowed_dist = cell.size+2 else: allowed_dist = "don't care" elif cell in friendly_cells: if 1.25 * my_largest.mass > cell.mass: # we're dangerous to our friends allowed_dist = my_largest.size + 40 elif (cell not in self.c.player.own_cells and not cell.is_virus and not cell.is_ejected_mass and not cell.is_food) and cell.mass + 20 > 1.25 * my_smallest.mass: # our enemy is, or will be dangerous to us if (cell.mass + 20) / 2 < 1.25 * my_smallest.mass: # they can't splitkill us (soon) allowed_dist = cell.size + 75 elif cell.mass / 15. < self.c.player.total_mass: # they can and they will splitkill us allowed_dist = 650 + cell.size else: # we're too small, not worth a splitkill. they have absolutely no # chance to chase us allowed_dist = cell.size + 10 else: allowed_dist = "don't care" if allowed_dist != "don't care" and dist < allowed_dist: try: angle = math.atan2(relpos[1],relpos[0]) corridor_halfwidth = math.asin(min(1, cell.size / dist)) forbidden_intervals += canonicalize_angle_interval((angle-corridor_halfwidth, angle+corridor_halfwidth)) runaway = True except: print("TODO FIXME: need to handle enemy cell which is in our centerpoint!") print("dist=%.2f, allowed_dist=%.2f" % (dist, allowed_dist)) # wall avoidance if self.c.player.center[0] < self.c.world.top_left[1]+(self.c.player.total_size*2): forbidden_intervals += [(0.5*pi, 1.5*pi)] if self.c.player.center[0] > self.c.world.bottom_right[1]-(self.c.player.total_size*2): forbidden_intervals += [(0,0.5*pi), (1.5*pi, 2*pi)] if self.c.player.center[1] < self.c.world.top_left[0]+(self.c.player.total_size*2): forbidden_intervals += [(pi, 2*pi)] if self.c.player.center[1] > self.c.world.bottom_right[0]-(self.c.player.total_size*2): forbidden_intervals += [(0, pi)] # if there's actually an enemy to avoid: if (runaway): # find the largest non-forbidden interval, and run into this direction. forbidden_intervals = merge_intervals(forbidden_intervals) allowed_intervals = invert_angle_intervals(forbidden_intervals) try: (a,b) = find_largest_angle_interval(allowed_intervals) except: print("TODO FIXME: need to handle no runaway direction being available!") (a,b) = (0,0) runaway_angle = (a+b)/2 runaway_x, runaway_y = (self.c.player.center[0]+int(100*math.cos(runaway_angle))), (self.c.player.center[1]+int(100*math.sin(runaway_angle))) self.target = (runaway_x, runaway_y) self.target_type = None self.target_cell = None self.color = (255,0,0) # a bit of debugging information for i in forbidden_intervals: self.gui.draw_arc(self.c.player.center, self.c.player.total_size+10, i, (255,0,255)) # if however there's no enemy to avoid, try to feed a friend. or chase food or fly randomly around else: if self.target_cell != None: self.target = tuple(self.target_cell.pos) # check if target went out of sight, or became infeasible if self.target_cell not in self.c.world.cells.values() or (not self.edible(self.target_cell) and not self.target_cell in friendly_cells): self.target_cell = None self.target_type = None elif self.target == tuple(self.c.player.center): self.target_type = None print("Reached random destination") if not self.target_type == 'friend': # i.e. None, random or food food = list(filter(self.edible, self.c.world.cells.values())) myspeed = mechanics.speed(my_largest) food = sorted(food, key = lambda c : self.quality(c, cells, myspeed)) if len(food) > 0: food_candidate = food[0] if self.target_type == None or self.target_type == 'random' or (self.target_type == 'food' and self.quality(food_candidate, cells, myspeed) < self.quality(self.target_cell, cells, myspeed)-1): if self.target_type == 'food': print("abandoning food of value %.3f for %.3f" % (self.quality(self.target_cell, cells, myspeed),self.quality(food_candidate, cells, myspeed))) self.target_cell = food_candidate self.target = (self.target_cell.pos[0], self.target_cell.pos[1]) self.target_type = 'food' self.color = (0,0,255) if self.target == None: rx = self.c.player.center[0] + random.randrange(-400, 401) ry = self.c.player.center[1] + random.randrange(-400, 401) self.target = (rx, ry) self.target_type = 'random' self.color = (0,255,0) print("Nothing to do, heading to random targetination: " + str((rx, ry))) # more debugging self.gui.draw_line(self.c.player.center, self.target, self.color) return self.target