C17/CSFunA/HumaHameed

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 +17,27 @@ 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, columns = len(heights), len(heights[0])
+
+    distances = [[float("inf")] * columns for row in range(rows)]
+
+    distances[0][0] = 0
+    priority_queue = [(0, 0, 0)]
+    visited = set()
+
+    while priority_queue:
+        dist, row, col = heapq.heappop(priority_queue)
+        if (row, col) == (rows-1, columns -1):
+            return dist
+        visited.add((row, col))
+        neighbors = [(row-1, col), (row+1, col), (row, col-1), (row, col+1)]
+        for neighbor in neighbors:
+            neighbor_row, neighbor_col = neighbor
+            if (0 <= neighbor_row < rows and 0 <=neighbor_col < columns) and neighbor not in visited:
+                 new_dist = max(dist, abs(heights[row][col] - heights[neighbor_row][neighbor_col]))
+                 if distances[neighbor_row][neighbor_col] > new_dist:
+                    distances[neighbor_row][neighbor_col] = new_dist
+                    heapq.heappush(priority_queue, (max(dist, new_dist), neighbor_row, neighbor_col))