def reconstruct_path(self, path):
"""
Reconstructs the complete path inserting nodes which
were "jumped" by the generating function. This is possible
because JPS generates jump only in straight or diagonal lines.
For example:
[(0,0),(4,4)] -> [(0,0),(1,1),(2,2),(3,3),(4,4)].
"""
def pairwise(iterable):
a, b = it.tee(iterable)
next(b, None)
return zip(a, b)
cost = 0
expanded_path = [path[0]]
sqrt_2 = 2 ** 0.5
for cur_node, next_node in pairwise(path):
cur_node = np.array(cur_node)
next_node = np.array(next_node)
direction = normalize(next_node - cur_node)
cost_unit = sqrt_2 if np.all(direction) else 1
while not np.array_equal(cur_node, next_node):
cur_node = tuple(int(x) for x in cur_node + direction)
expanded_path.append(cur_node)
cost += cost_unit
return expanded_path, cost
def reconstruct_path(path, labyrinth):
"""
Reconstructs the complete path inserting nodes which
were "jumped" by the generating function. This is possible
because JPS generates jump only in straight or diagonal lines.
For example:
[(0,0),(4,4)] -> [(0,0),(1,1),(2,2),(3,3),(4,4)].
"""
expanded_path = [path[0]]
for cur_node, next_node in pairwise(path):
cur_node = np.array(cur_node)
next_node = np.array(next_node)
direction = lab_module.normalize(next_node - cur_node)
while not np.array_equal(cur_node, next_node):
cur_node = tuple(int(x) for x in cur_node + direction)
expanded_path.append(cur_node)
return expanded_path
