Minimum Cells to Bridge a Magic Grid
AppleSoftware Engineer · Technical ScreenLast updated
Tests graph modeling and shortest-path optimization on a 2D grid with zero-weight transitions and unit-weight bridges using 0-1 BFS or Dijkstra's algorithm.
Problem Statement
You are given an m x n 2D integer array grid, along with starting coordinates start = [sr, sc] and target coordinates target = [tr, tc].
The grid represents a mystical floating realm where each cell (r, c) has a specific property:
-1: An unstable rift. This cell is completely impassable and cannot be bridged.0: A void cell. Moving onto this cell requires placing 1 bridge cell.1: An ancient magic conduit. Moving onto or across this cell requires 0 bridge cells.2through9: A resonance portal. Stepping onto this cell costs 0 bridge cells. Furthermore, all cells sharing the exact same resonance valuek(k >= 2) are instantaneously linked; you may teleport between any two cells with the same resonance value at a cost of 0 bridge cells.
From any cell, you can move to its 4-directionally adjacent neighbors (up, down, left, right), provided the neighbor is within grid bounds and not an unstable rift (-1). You may also use resonance portals when currently on a portal cell.
If the initial cell start is a void cell (0), you must place a bridge cell there first (costing 1). Otherwise, starting on a conduit or portal costs 0.
Return the minimum number of bridge cells needed to travel from start to target. If it is impossible to reach target, return -1.
Function Signature
def min_bridge_cells(grid: list[list[int]], start: list[int], target: list[int]) -> int:
pass
Input Format
grid: A 2D list of integers of dimensionsm x n.start: A list of two integers[sr, sc].target: A list of two integers[tr, tc].
Output Format
- An integer representing the minimum number of bridge cells required, or
-1if unreachable.
Constraints
m == len(grid)n == len(grid[0])1 <= m, n <= 500grid[r][c] in [-1, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9]0 <= sr, tr < m0 <= sc, tc < n
Examples
Example 1
Input:
grid = [
[1, 0, -1],
[0, 2, 0],
[-1, 0, 2]
]
start = [0, 0]
target = [2, 2]
Output: 1
Explanation:
- Start at (0, 0) which is a conduit (cost = 0).
- Move down to (1, 0), placing 1 bridge cell (cost = 1).
- Move right to (1, 1), which is resonance portal 2 (cost = 1).
- Teleport from (1, 1) to (2, 2), which also has resonance portal 2 (cost = 1).
Total bridge cells used: 1.
Example 2
Input:
grid = [
[0, -1],
[-1, 1]
]
start = [0, 0]
target = [1, 1]
Output: -1
Explanation:
All paths from (0, 0) to (1, 1) are blocked by unstable rifts (-1).
Edge Cases
start == target: The answer is1ifgrid[sr][sc] == 0, and0ifgrid[sr][sc] >= 1(or-1if it is an impassable cell-1).grid[sr][sc] == -1orgrid[tr][tc] == -1: Impossible from the beginning, return-1.- Multiple portals of the same value: Ensure teleportation edges do not cause redundant quadratic iterations.
Hints
Hint 1
Notice that every movement or teleportation has an edge weight of either 0 (conduits/portals) or 1 (void cells), which suggests using 0-1 BFS via a double-ended queue (deque).
Hint 2
Pre-group the coordinates of all resonance portal cells (values 2 through 9) before starting the search.
Hint 3
To maintain an O(m * n) time complexity, once a portal network of type k is activated, teleport to all other cells of type k and mark the portal type as depleted so its list is never traversed again.
Follow-up questions
- How would you modify the algorithm if bridging void cells had different costs depending on terrain depth (e.g., costs between 1 and 100)?
- What changes would be required if portal teleportation had a limited range or could only be used at most K times throughout the journey?
- If you needed to find the minimum bridge cells to connect three specific locations (A, B, and C) rather than just a single pair, how would you approach the problem?
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