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-rw-r--r--main.py4
-rw-r--r--strategy.py65
2 files changed, 39 insertions, 30 deletions
diff --git a/main.py b/main.py
index d747869..ee053ea 100644
--- a/main.py
+++ b/main.py
@@ -37,7 +37,7 @@ c.player.nick="test cell pls ignore"
gui.set_client(c)
# initialize strategy
-strategy = Strategy()
+strategy = Strategy(c)
# main loop
while True:
@@ -46,7 +46,7 @@ while True:
gui.draw_frame()
if len(list(c.player.own_cells)) > 0:
- target = strategy.process_frame(c)
+ target = strategy.process_frame()
if gui.bot_input:
c.send_target(target[0], target[1])
diff --git a/strategy.py b/strategy.py
index 1f1249f..5b8ca5a 100644
--- a/strategy.py
+++ b/strategy.py
@@ -4,23 +4,33 @@ import gui
import random
class Strategy:
- def __init__(self):
+ def __init__(self, c):
self.target = (0,0)
self.has_target = False
self.target_cell = None
self.color = (0,0,0)
-
- def process_frame(self,c):
+ self.c = c
+
+ 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 <= sorted(self.c.player.own_cells, key = lambda x: x.mass)[0].mass * 0.75) and not (cell.is_virus)
+
+ def weight_cell(self, cell):
+ pass
+
+ def process_frame(self):
runaway = False
- my_smallest = min(map(lambda cell : cell.mass, c.player.own_cells))
- my_largest = max(map(lambda cell : cell.mass, c.player.own_cells))
+ my_smallest = min(map(lambda cell : cell.mass, self.c.player.own_cells))
+ my_largest = max(map(lambda cell : cell.mass, self.c.player.own_cells))
# enemy/virus avoidance
forbidden_intervals = []
- for cell in c.world.cells.values():
- relpos = ((cell.pos[0]-c.player.center[0]),(cell.pos[1]-c.player.center[1]))
+ 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)
if (not cell.is_virus and dist < ((500+2*cell.size) if cell.mass > 1.25*my_smallest*2 else (300+cell.size)) and cell.mass > 1.25 * my_smallest) or (cell.is_virus and dist < my_largest and cell.mass < my_largest):
@@ -30,13 +40,13 @@ class Strategy:
runaway = True
# wall avoidance
- if c.player.center[0] < c.world.top_left[1]+(c.player.total_size*2):
+ 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 c.player.center[0] > c.world.bottom_right[1]-(c.player.total_size*2):
+ 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 c.player.center[1] < c.world.top_left[0]+(c.player.total_size*2):
+ if self.c.player.center[1] < self.c.world.top_left[0]+(self.c.player.total_size*2):
forbidden_intervals += [(pi, 2*pi)]
- if c.player.center[1] > c.world.bottom_right[0]-(c.player.total_size*2):
+ 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:
@@ -49,25 +59,24 @@ class Strategy:
(a,b) = find_largest_angle_interval(allowed_intervals)
runaway_angle = (a+b)/2
- runaway_x, runaway_y = (c.player.center[0]+int(100*math.cos(runaway_angle))), (c.player.center[1]+int(100*math.sin(runaway_angle)))
+ 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.has_target = False
self.target_cell = None
self.color = (255,0,0)
- print ("Running away: " + str((runaway_x-c.player.center[0], runaway_y-c.player.center[1])))
+ print ("Running away: " + str((runaway_x-self.c.player.center[0], runaway_y-self.c.player.center[1])))
# a bit of debugging information
for i in forbidden_intervals:
- gui.draw_arc(c.player.center, c.player.total_size+10, i, (255,0,255))
+ 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, chase food or jizz randomly around
else:
- def edible(cell): return (cell.is_food) or (cell.mass <= sorted(c.player.own_cells, key = lambda x: x.mass)[0].mass * 0.75) and not (cell.is_virus)
def rival(cell, food):
if cell.is_virus or cell.is_food: return False
- if cell.cid in c.player.own_ids: return False
+ if cell.cid in self.c.player.own_ids: return False
if cell.mass < 1.25*my_smallest:
return food.is_food or cell.size > 1.25*food.size
@@ -81,25 +90,25 @@ class Strategy:
if self.target_cell != None:
self.target = tuple(self.target_cell.pos)
- if self.target_cell not in c.world.cells.values() or not edible(self.target_cell):
+ if self.target_cell not in self.c.world.cells.values() or not self.edible(self.target_cell):
self.target_cell = None
self.has_target = False
print("target_cell does not exist any more")
- elif self.target == tuple(c.player.center):
+ elif self.target == tuple(self.c.player.center):
self.has_target = False
print("Reached random destination")
if not self.has_target:
- food = list(filter(edible, c.world.cells.values()))
+ food = list(filter(self.edible, self.c.world.cells.values()))
def quality(cell):
- dd_sq = max((cell.pos[0]-c.player.center[0])**2 + (cell.pos[1]-c.player.center[1])**2,0.001)
+ 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 : rival(r,cell), c.world.cells.values())
- splitkillers = filter(splitkiller, c.world.cells.values())
- nonsplitkillers = filter(nonsplitkiller, c.world.cells.values())
+ rivals = filter(lambda r : rival(r,cell), self.c.world.cells.values())
+ splitkillers = filter(splitkiller, self.c.world.cells.values())
+ nonsplitkillers = filter(nonsplitkiller, self.c.world.cells.values())
rival_score = 0
for r in rivals:
@@ -121,12 +130,12 @@ class Strategy:
density_score = 0
sigma = 300
- for f in filter(lambda c : c.is_food and c!=cell, c.world.cells.values()):
+ 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]-c.world.top_left[1], c.world.bottom_right[1]-cell.pos[0], cell.pos[1]-c.world.top_left[0], c.world.bottom_right[0]-cell.pos[1] )
+ 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))
@@ -143,8 +152,8 @@ class Strategy:
self.color = (0,0,255)
print("Found food at: " + str(food[0].pos))
else:
- rx = c.player.center[0] + random.randrange(-400, 401)
- ry = c.player.center[1] + random.randrange(-400, 401)
+ 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.has_target = True
self.color = (0,255,0)
@@ -152,6 +161,6 @@ class Strategy:
# more debugging
- gui.draw_line(c.player.center, self.target, self.color)
+ gui.draw_line(self.c.player.center, self.target, self.color)
return self.target