Added creepTracker

Author: jonomon

sc2reader/factories/plugins/replay.py

@@ -120,6 +120,238 @@ def APMTracker(replay):
 
     return replay
 
+@plugin
+def CreepTracker(replay):
+    from itertools import izip_longest, dropwhile
+    from random import random
+    from math import sqrt, pi
+    
+    def add_to_list(control_pid,unit_id,unit_location,\
+                unit_type,event_time, creep_generating_units_list):
+        length_cgu_list = len(creep_generating_units_list[control_pid])
+        if length_cgu_list==0:
+            creep_generating_units_list[control_pid].append([(unit_id, unit_location,unit_type,event_time)])
+        else:
+            previous_list = creep_generating_units_list[control_pid][length_cgu_list-1][:]
+            previous_list.append((unit_id, unit_location,unit_type,event_time))
+            creep_generating_units_list[control_pid].append(previous_list)
+                                                
+    def in_circles(point_x,point_y,cgu_radius):
+        for cgu in cgu_radius:
+            circle_x = cgu[0][0]
+            circle_y = cgu[0][1]
+            radius = cgu[1]
+            distance = (circle_x-point_x)**2 + (circle_y-point_y)**2
+            if distance < (radius*radius):
+                return 1
+        return 0
+
+    def distance(point1,point2):
+        distance = (point1[0]-point2[0])**2  + (point1[1]-point2[1])**2
+        return distance
+
+    def calculate_area(cgu_radius):
+        if len(cgu_radius)==1:
+            print "Area Calculated",pi*(cgu_radius[0][1]**2)
+            return pi*(cgu_radius[0][1]**2)
+        
+         # from cgu_radius get a square which surrounds maximum
+            # possible area that the creep lies in           
+        max_x = max(cgu_radius, key=lambda x: x[0][0]+x[1])
+        max_y = max(cgu_radius, key=lambda x: x[0][1]+x[1])
+        min_x =  min(cgu_radius, key=lambda x: x[0][0] - x[1])
+        min_y =  min(cgu_radius, key=lambda x: x[0][1] - x[1])
+
+        max_x = max_x[0][0] + max_x[1]
+        max_y = max_y[0][1] + max_y[1]
+        min_x = min_x[0][0] - min_x[1]
+        min_y = min_y[0][1] - min_y[1]
+
+        area = 0
+        for x in range(min_x,max_x):
+            for y in range(min_y,max_y):
+                if in_circles(x,y,cgu_radius):
+                        area+=1
+        return area
+        
+
+    def single_linkage_clustering(cgu_points, maxR,labels=0,cgu_length = 0):
+        inf = -1000
+        if labels==0:
+            labels = [0 for x in cgu_points]
+            cgu_length = len(cgu_points)
+        if len(cgu_points) ==1:
+            return [0]
+        
+        # calculate distance array
+        distance_array = list()
+        for i in range (len(cgu_points)):
+            i_lengths = list()
+            for j in range(len(cgu_points)):
+                if i !=j:
+                    if cgu_points[i][0] == inf and cgu_points [j][0] == inf:
+                        i_lengths.append(-inf)
+                    else:
+                        i_lengths.append(distance(cgu_points[i], cgu_points[j]))
+                
+            distance_array.append(i_lengths)
+        
+        #Find closest point distance for each point
+        min_array = map(lambda x:min(x), distance_array)
+
+        #combine 2 points with smallest distance
+        min_distance = min(min_array)
+        if min_distance < maxR:
+            point1 = min_array.index(min_distance)
+            point2 = min_array[point1+1:].index(min_distance)+point1+1
+            #label each cgu points
+            current_label = max(labels)+1 if labels[point1] ==0 and\
+                             labels[point2] ==0 else max(labels[point1],labels[point2])
+            labels[point1] = current_label
+            labels[point2] = current_label
+            labels.append(current_label)
+
+            new_x = (cgu_points[point1][0] + cgu_points[point2][0])/2
+            new_y = (cgu_points[point1][1] + cgu_points[point2][1])/2
+            cgu_points[point1]=(inf,inf)
+            cgu_points[point2]=(inf,inf)
+            cgu_points.append((new_x,new_y))
+            
+            labels = single_linkage_clustering(cgu_points,maxR,labels,cgu_length)
+            return labels[0:cgu_length]
+        else:
+            return_value = labels[0:cgu_length]
+            return return_value
+        
+    
+    #Get Map Size
+    mapinfo = replay.map.archive.read_file('MapInfo')
+    mapSizeX = ord(mapinfo[16])
+    mapSizeY = ord(mapinfo[20])
+    mapSize = mapSizeX * mapSizeX/100
+
+    creep_generating_units_list = dict()
+    
+    for player in replay.players:
+        player.creep_spread_by_minute = defaultdict(int)
+        player.max_creep_spread = int()
+        creep_generating_units_list[player.pid] = list()
+    try:
+        replay.tracker_events
+    except AttributeError:
+        print "Replay does not have tracker events"
+        return replay
+
+    for tracker_event,game_event in izip_longest(replay.tracker_events,replay.game_events):
+        
+        # First search things that generate creep
+        # Tumor, hatcheries, nydus and overlords generating creep
+
+        if tracker_event and tracker_event.name == "UnitInitEvent":
+            units = ["CreepTumor", "Hatchery","Nydus"] # check nydus name
+            if tracker_event.unit_type_name in units:
+                add_to_list(tracker_event.control_pid,tracker_event.unit_id,\
+                            (tracker_event.x, tracker_event.y), \
+                            tracker_event.unit_type_name,\
+                            tracker_event.second,\
+                            creep_generating_units_list)
+
+        if game_event and game_event.name == "AbilityEvent":
+            
+            if game_event.ability_name == "GenerateCreep":
+                add_to_list(game_event.control_pid,game_event.unit_id,\
+                            (game_event.x, game_event.y), \
+                            game_event.unit_type_name,\
+                            game_event.second,\
+                            creep_generating_units_list)
+               
+        # # Removes creep generating units that were destroyed
+        if tracker_event and tracker_event.name == "UnitDiedEvent":
+            for player in creep_generating_units_list:
+                length_cgu_list = len(creep_generating_units_list[player])
+                if length_cgu_list ==0:
+                    break
+                cgu_per_player = creep_generating_units_list[player][length_cgu_list-1]
+                creep_generating_died = dropwhile(lambda x: x[0] != tracker_event.unit_id, \
+                                            cgu_per_player)
+                for creep_generating_died_unit in creep_generating_died:
+
+                    cgu_per_player.remove(creep_generating_died_unit)
+                    creep_generating_units_list[player].append(cgu_per_player)
+            
+    #reduce all events to last event in the minute
+    last_minute_found = 0
+    for player in replay.player:
+        cgu_per_player_new = list()
+        for cgu_per_player in creep_generating_units_list[player]:
+            if len(cgu_per_player) ==0:
+                continue
+            cgu_last_event_time = cgu_per_player[-1][3]
+        
+            if (cgu_last_event_time/60)>last_minute_found:
+                last_minute_found = cgu_last_event_time/60
+                cgu_per_player_new.append(cgu_per_player)
+        cgu_per_player = cgu_per_player_new
+    
+
+    max_creep_spread=defaultdict()
+    for player in replay.player:
+        # convert cg u list into centre of circles and radius
+        unit_name_to_radius = {'CreepTumor': 15, "Hatchery":17,\
+                            "GenerateCreep": 10, "Nydus": 5 }
+        
+        max_creep_spread[player] = 0
+        
+        for index,cgu_per_player in enumerate(creep_generating_units_list[player]):
+            
+            cgu_radius = map(lambda x: (x[1],   unit_name_to_radius[x[2]]),\
+                                  cgu_per_player)
+            cgu_points  = map(lambda x: x[0],cgu_radius)
+
+            if cgu_points:
+                labels = single_linkage_clustering(cgu_points,350)
+            else:
+                if index != 0:
+                    replay.player[player].creep_spread_by_minute[cgu_last_event_time+1] = 0
+                continue
+            
+            area = 0
+            #if all labels 0 (all separate clusters) calculate it separately
+            if max(labels) ==0:
+                for cgu_radi in cgu_radius:
+                    area+= pi * cgu_radi[1]**2
+ 
+                cgu_last_event_time = cgu_per_player[-1][3]/60
+                replay.player[player].creep_spread_by_minute[cgu_last_event_time] = area/mapSize
+                continue
+
+            count =0
+            while True:
+                clusters = filter(lambda x : True if x[0] == count else\
+                  False , zip(labels,cgu_radius)  )
+               
+                cgu_clusters = map(lambda x:x[1], clusters)
+                if count==0:
+                    for cgu_radi in cgu_clusters:
+                        area+= pi * cgu_radi[1]**2
+                    count+=1
+                    continue
+                if len(clusters) ==0:
+                    break
+                count+=1
+                area += calculate_area(cgu_clusters)
+            cgu_last_event_time = cgu_per_player[-1][3]/60
+            replay.player[player].creep_spread_by_minute[cgu_last_event_time] = area/mapSize
+
+            if area>max_creep_spread[player]:
+                 max_creep_spread[player] =area
+
+
+    for player in replay.player:
+        replay.player[player].max_creep_spread = max_creep_spread[player]/mapSize
+
+    return replay 
+
 
 @plugin
 def SelectionTracker(replay):