Add A*

UI/Apath.py

@@ -0,0 +1,70 @@
+import numpy
+from heapq import *
+
+def heuristic(a, b, pathing):
+    
+    x = abs(a[0]-b[0])
+    y = abs(a[1]-b[1])
+
+    if pathing == '*':
+
+        if x > y:
+            return 14*y + 10*(x - y)
+        else:
+            return 14*x + 10*(y - x)
+    else:
+        return 10*(x + y)
+
+def astar(array, start, goal, pathing):
+
+    if pathing == '+':
+        neighbors = [(0,1),(0,-1),(1,0),(-1,0)]
+    else:
+        neighbors = [(0,1),(0,-1),(1,0),(-1,0),(1,1),(1,-1),(-1,1),(-1,-1)]
+
+    came_from = {}
+    gscore = {start:0}
+    fscore = {start:heuristic(start, goal, pathing)}
+    oheap = []
+    checked = []
+
+    heappush(oheap, (fscore[start], start))
+    
+    while oheap:
+
+        current = heappop(oheap)[1]
+        checked.append(current)
+
+        if current == goal:
+            data = []
+            while current in came_from:
+                data.append(current)
+                current = came_from[current]
+
+            return list(reversed(data)), checked
+
+        array[current[0], current[1]] = 2
+        for i, j in neighbors:
+            neighbor = current[0] + i, current[1] + j            
+            tentative_g_score = gscore[current] + heuristic(current, neighbor, pathing)
+            if 0 <= neighbor[0] < array.shape[0]:
+                if 0 <= neighbor[1] < array.shape[1]:                
+                    if array.flat[array.shape[1] * neighbor[0]+neighbor[1]] == 1:
+                        continue
+                else:
+                    # array bound y walls
+                    continue
+            else:
+                # array bound x walls
+                continue
+                
+            if array[neighbor[0]][neighbor[1]] == 2 and tentative_g_score >= gscore.get(neighbor, 0):
+                continue
+                
+            if  tentative_g_score < gscore.get(neighbor, 0) or neighbor not in [i[1]for i in oheap]:
+                came_from[neighbor] = current
+                gscore[neighbor] = tentative_g_score
+                fscore[neighbor] = tentative_g_score + heuristic(neighbor, goal, pathing)
+                heappush(oheap, (fscore[neighbor], neighbor))
+                
+    return False