Eunice Gonzalez SeaTurtles-b

graphs/minimum_effort_path.py

@@ -1,3 +1,5 @@
+from collections import deque
+import heapq
 def min_effort_path(heights):
     """ Given a 2D array of heights, write a function to return
         the path with minimum effort.
@@ -16,3 +18,35 @@ def min_effort_path(heights):
             minimum effort required to navigate the path from (0, 0) to heights[rows - 1][columns - 1]
     """
     pass
+    if heights == None:
+        return 0
+    H = len(heights)
+    W = len(heights[0])
+
+    directions = [[1,0], [0,1], [-1,0], [0,-1]]
+    def inside(row, col):
+        return 0 <= row < H and 0 <= col < W
+    if len(heights) >0:
+
+        queue = deque([])
+        queue.append((0, 0))
+
+        cost = { (row, col): float('inf') for col in range(W) for row in range(H) }
+        cost[(0, 0)] = 0
+
+    while queue:
+        row, col = queue.popleft()
+        current_height = heights[row][col]
+        current_cost = cost[(row, col)]
+        for d_row, d_col in directions:
+            new_row = row + d_row
+            new_col = col + d_col
+            if inside(new_row, new_col):
+                neighbor_height = heights[new_row][new_col]
+                new_cost = max(current_cost, abs(neighbor_height - current_height))
+                if new_cost < cost[(new_row, new_col)]:
+                    cost[(new_row, new_col)] = new_cost
+                    queue.append((new_row, new_col))
+
+    return cost[(H - 1, W - 1)]
+