import heapq import collections class Graph: def __init__(self, size): self.size = size self.graph = [[] for i in range(size)] def add_edge(self, source, target, cost): self.graph[source].append(self.Edge(target, cost)) def add_bidirectional_edge(self, source, target, cost): self.add_edge(source, target, cost) self.add_edge(target, source, cost) def min_dist_dijkstra(self, s): dist = [float('inf')] * self.size dist[s] = 0 q = [(0, s)] while q: node = self.Node(*heapq.heappop(q)) v = node.id if dist[v] < node.dist: continue for e in self.graph[v]: if dist[e.target] > dist[v] + e.cost: dist[e.target] = dist[v] + e.cost heapq.heappush(q, (dist[e.target], e.target)) return dist def min_path_dijkstra(self, s, t): dist = [float('inf')] * self.size prev = [-1] * self.size dist[s] = 0 q = [(0, s)] while q: node = self.Node(*heapq.heappop(q)) v = node.id if dist[v] < node.dist: continue for e in self.graph[v]: if dist[e.target] > dist[v] + e.cost: dist[e.target] = dist[v] + e.cost heapq.heappush(q, (dist[e.target], e.target)) prev[e.target] = v if v == t: break path = [t] while path[-1] > -1: path.append(prev[path[-1]]) return path[1:] def min_dist_queue(self, s): dist = [float('inf')] * self.size dist[s] = 0 q = collections.deque() q.append(s) while q: v = q.popleft() for e in self.graph[v]: if dist[e.target] > dist[v] + e.cost: dist[e.target] = dist[v] + e.cost if e.cost == 0: q.appendleft(e.target) else: q.append(e.target) return dist def __str__(self): res = '' for i in range(self.size): res += str(i) for e in self.graph[i]: res += ' ' + str(e.target) res += '\n' return res class Edge: def __init__(self, target, cost): self.target = target self.cost = cost class Node: def __init__(self, dist, i): self.dist = dist self.id = i def __cmp__(self, other): if self.dist < other.dist: return -1 elif self.dist == other.dist: return 0 else: return 1 N, V, X, Y = map(int, input().split()) goal = N*N-1 L = [list(map(int, input().split())) for i in range(N)] g = Graph(N * N) d = [0, 1, 0, -1, 0] for y in range(N): for x in range(N): for i in range(4): if 0 <= y + d[i] < N and 0 <= x + d[i + 1] < N: g.add_edge((y + d[i]) * N + x + d[i + 1], y * N + x, L[y][x]) if X==0 and Y==0: dist = g.min_dist_dijkstra(0) if dist[goal] < V: print('YES') else: print('NO') exit() else: dist = g.min_dist_dijkstra(0) if dist[goal] < V: print('YES') exit() dist = g.min_dist_dijkstra((Y-1)*N+(X-1)) if dist[0]< V and dist[goal] < 2*(V-(dist[0]+L[Y-1][X-1])): print('YES') else: print('NO')