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import math
from interval_utils import *
import gui
import random
class Strategy:
def __init__(self, c):
self.target = (0,0)
self.has_target = False
self.target_cell = None
self.color = (0,0,0)
self.c = c
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 > 1.25*2*self.get_my_smallest().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 < 1.25*2*self.get_my_smallest().mass
def quality(self, cell):
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
dist_score = -math.exp(-dd_sq/(2*sigma**2))
rivals = filter(lambda r : self.rival(r,cell), self.c.world.cells.values())
splitkillers = filter(self.splitkiller, self.c.world.cells.values())
nonsplitkillers = filter(self.nonsplitkiller, self.c.world.cells.values())
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))
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 = (500+2*s.size)
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 = (300+s.size)
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 2.5*dist_score + 0.2*rival_score + nonsplitkill_score + 5*splitkill_score + 0.1*density_score + 5*wall_score
##print (density_score)
#return density_score
def weight_cell(self, cell):
df = (10/self.dist(cell))
if self.edible(cell):
quality = self.quality(cell)
if cell.is_food:
return 1 + cell.mass * df * quality
else:
mf = 1 / ((self.get_my_smallest().mass * 0.75) + 1) - cell.mass
return cell.mass * df * quality * mf
elif self.threat(cell):
if cell.is_virus:
return -cell.mass * df * 100
else:
return -cell.mass * df
else:
return 0
def weight_cells(self, cells):
weight = 0
for cell in cells:
if cell not in self.c.player.own_cells: #probably unnecessary but list filtering didnt work
weight += self.weight_cell(cell)
return weight
def process_frame(self):
intervals = []
last = math.radians(45)
num = 36
for i in range(num):
ang = last + math.radians((360/num))
intervals.append([last, ang])
last = ang
cells = list(map(lambda x: get_cells_in_interval(self.c.player.center, x, self.c.world.cells.values()), intervals))
cells = list(filter(lambda x: x not in self.c.player.own_cells, cells))
weights = list(map(lambda x: self.weight_cells(x), cells))
zipped = zip(intervals, weights)
zipped = sorted(zipped, key = lambda x: x[1], reverse = True)
bi = zipped[0][0]
ang = bi[0] + ((bi[1] - bi[0]) / 2)
tx = self.c.player.center[0] + (200*math.cos(ang))
ty = self.c.player.center[1] + (200*math.sin(ang))
self.target = (tx, ty)
def gradient(value):
return (255-value, value, 0)
def mapped_gradient(min, max, value):
i = max - min
s = 255/i
v = abs(int(value*s))
return gradient(v)
for z in zipped:
gui.draw_arc(self.c.player.center, 200, z[0], mapped_gradient(zipped[0][1], zipped[-1][1], z[1]))
gui.draw_line(self.c.player.center, self.target, (255,0,0))
gui.draw_arc(self.c.player.center, 210, bi, (255,0,0))
return self.target
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