Tori Shade | c17 | Otters

graphs/minimum_effort_path.py

@@ -1,3 +1,5 @@
+import heapq
+
 def min_effort_path(heights):
     """ Given a 2D array of heights, write a function to return
         the path with minimum effort.
@@ -15,4 +17,35 @@ def min_effort_path(heights):
         int
             minimum effort required to navigate the path from (0, 0) to heights[rows - 1][columns - 1]
     """
-    pass
+    if not heights:
+        return 0
+
+    rows = len(heights)
+    columns = len(heights[0])
+
+    pq = [[0,0,0]]  ##diff,x,y
+
+    visited = set()
+    directions = [[0, 1], [1, 0], [0, -1], [-1, 0]]
+    ans = float('-inf')
+
+    while pq:
+        diff,x,y=heapq.heappop(pq)
+        ans=max(diff,ans)
+        if x==rows-1 and y==columns-1:
+            return ans
+
+        if (x,y) in visited:
+            continue
+
+        visited.add((x,y))
+
+        for dx,dy in directions:
+            new_x = x+dx
+            new_y = y+dy
+
+            if new_x>=0 and new_x<rows and new_y>=0 and new_y<columns and (new_x,new_y) not in visited:
+                diff = abs(heights[x][y]-heights[new_x][new_y])
+                heapq.heappush(pq,(diff,new_x,new_y))
+
+    return -1