def test_mutated_tree(self):
for _ in range(100):
tree1 = pt_create.apply(random.randint(10, 35))
tree2 = copy.deepcopy(tree1)
sub1, sub2 = pt_mutate.change_node_operator(tree2, None)
com_res = pt_compare.apply(tree1, tree2)
self.assertEqual(str(sub1), str(com_res.subtree1))
self.assertEqual(str(sub2), str(com_res.subtree2))
tree2 = copy.deepcopy(tree1)
sub1, sub2 = pt_mutate.add_new_node(tree2, None)
com_res = pt_compare.apply(tree1, tree2)
if sub1.operator == Operator.LOOP and sub1.children[
1].operator is not None:
self.assertEqual(str(sub1.children[1]), str(com_res.subtree1))
self.assertEqual(str(sub2.children[1]), str(com_res.subtree2))
else:
self.assertEqual(str(sub1), str(com_res.subtree1))
self.assertEqual(str(sub2), str(com_res.subtree2))
tree2 = copy.deepcopy(tree1)
sub1, sub2 = pt_mutate.remove_node(tree2, None)
com_res = pt_compare.apply(tree1, tree2)
if (len(sub1.children) == 2 and
(sub1.parent is None or
(sub2.operator is not None and
(sub1.parent is not None
and sub2.operator != sub1.parent.operator)) or sub2.operator
== Operator.LOOP)) or (len(sub1.children) > 2):
self.assertEqual(str(sub1), str(com_res.subtree1))
self.assertEqual(str(sub2), str(com_res.subtree2))
else:
self.assertEqual(str(sub1.parent), str(com_res.subtree1))
self.assertEqual(str(sub2.parent), str(com_res.subtree2))
def compute_run_time():
no_tree, no_event, pro, mutated_num = 10, 10, 0.9, 5
tree1 = [pt_create.apply(random.randint(11, 15)) for _ in range(no_tree)]
m_tree1 = [[pt_mutate.apply(tree) for _ in range(mutated_num)]
for tree in tree1]
log1 = [log_create.apply(tree, no_event, pro) for tree in tree1]
tree2 = [pt_create.apply(random.randint(16, 20)) for _ in range(no_tree)]
m_tree2 = [[pt_mutate.apply(tree) for _ in range(mutated_num)]
for tree in tree2]
log2 = [log_create.apply(tree, no_event, pro) for tree in tree2]
tree3 = [pt_create.apply(random.randint(21, 25)) for _ in range(no_tree)]
m_tree3 = [[pt_mutate.apply(tree) for _ in range(mutated_num)]
for tree in tree3]
log3 = [log_create.apply(tree, no_event, pro) for tree in tree3]
tree4 = [pt_create.apply(random.randint(26, 30)) for _ in range(no_tree)]
log4 = [log_create.apply(tree, no_event, pro) for tree in tree4]
m_tree4 = [[pt_mutate.apply(tree) for _ in range(mutated_num)]
for tree in tree4]
# tree5 = [pt_create.apply(random.randint(31, 33)) for _ in range(no_tree)]
# log5 = [log_create.apply(tree, no_event, pro) for tree in tree5]
# m_tree5 = [[pt_mutate.apply(tree) for _ in range(mutated_num)] for tree in tree5]
# tree6 = [pt_create.apply(random.randint(34, 35)) for _ in range(no_tree)]
# log6 = [log_create.apply(tree, no_event, pro) for tree in tree6]
# m_tree6 = [[pt_mutate.apply(tree) for _ in range(mutated_num)] for tree in tree6]
l_without_lock = list(
map(
lambda tree_log: avg_runtime_without_lock(tree_log[0], tree_log[
1], tree_log[2]), [(tree1, m_tree1, log1),
(tree2, m_tree2, log2),
(tree3, m_tree3, log3),
(tree4, m_tree4, log4)]))
# , (tree5, m_tree5, log5), (tree6, m_tree6, log6)
l_with_lock = list(
map(
lambda tree_log: avg_runtime_with_lock(tree_log[0], tree_log[
1], tree_log[2]), [(tree1, m_tree1, log1),
(tree2, m_tree2, log2),
(tree3, m_tree3, log3),
(tree4, m_tree4, log4)]))
# , (tree5, m_tree5, log5), (tree6, m_tree6, log6)
plot_histogram_lock_runtime(l_without_lock, l_with_lock)
def create_pts():
pts = list()
for node_num in PT_RANGE:
trees = pd.DataFrame(columns=['tree', '#node', 'depth', 'root-op'])
for i in range(pt_num):
tree = pt_create.apply(random.randint(node_num[0], node_num[1]))
num_nodes = pt_number.apply(tree, 'D')
trees.loc[i] = [
str(tree), num_nodes,
pt_mani_utils.pt_depth(tree),
str(tree.operator)
]
pts.append(trees)
return pts
def test_random_create_tree(self):
for _ in range(100):
tree1 = pt_create.apply(random.randint(10, 35))
tree2 = pt_utils.parse(str(tree1))
q1, q2 = list(), list()
q1.append(tree1)
q2.append(tree2)
while len(q1) != 0:
node1 = q1.pop(0)
node2 = q2.pop(0)
self.assertEqual(str(node1.parent), str(node2.parent))
self.assertEqual(str(node1.children), str(node2.children))
for i in range(len(node1.children)):
q1.append(node1.children[i])
q2.append(node2.children[i])
def pt_write_to_table(tab, mutate_tabs, num, l, u, mutate_num, mutate_level):
for _ in range(num):
row = tab.row
# TODO: 一定时间内没有找到
no_node = random.randint(l, u)
tree = pt_create.apply(no_node)
info = [
no_node, " " + str(tree),
pt_mani_utils.leaves_number(tree),
pt_mani_utils.pt_depth(tree)
]
for i, mutate_tab in enumerate(mutate_tabs):
for m_tree in uniq_mutate_tree(tree, mutate_num, mutate_level[i]):
mutate_tree_write_to_table(mutate_tab, m_tree, [row] + info)
excel_utils.write_row_to_table(tab.table, row, info)
def creat_non_fitting_based_on_tree2(file, name, node_num, parameters):
num = [
"node", "best_worst_cost", "optimal_cost", "optimal_time",
"repaired_cost", "repaired_time", "scope_repair_cost",
"scope_repair_time", "grade1", "grade2"
]
tree_num, mutated_num, log_num, non_fit_pro = 25, 1, 1, 0.9
tree = [
pt_create.apply(random.randint(node_num[0], node_num[1]))
for _ in range(tree_num)
]
m_tree = [[pt_mutate.apply(tree) for _ in range(mutated_num)]
for tree in tree]
log = [[
log_create.apply(m_tree, log_num, non_fit_pro) for m_tree in m_tr4
] for m_tr4 in m_tree]
for i in range(len(tree)):
for j in range(len(m_tree[0])):
result = compute_cost_and_time(tree[i], m_tree[i][j], log[i][j],
parameters)
print_tree_align_compare(result)
def creat_non_fitting_based_on_tree1(file, name, node_num):
num = [
"node", "best_worst_cost", "optimal_cost", "optimal_time",
"repaired_cost", "repaired_time", "scope_repair_cost",
"scope_repair_time", "grade1", "grade2"
]
tree_num, mutated_num, log_num, non_fit_pro = 5, 1, 5, 0.9
tree = [
pt_create.apply(random.randint(node_num[0], node_num[1]))
for _ in range(tree_num)
]
m_tree = [[pt_mutate.apply(tree) for _ in range(mutated_num)]
for tree in tree]
log = [log_create.apply(tree, log_num, non_fit_pro) for tree in tree]
for i in range(len(tree)):
node_num = pt_mani_utils.non_none_leaves_number(tree[i])
for j in range(len(m_tree[0])):
param1 = {'ret_tuple_as_trans_desc': True, 'COMPARE_OPTION': 1}
result = compute_cost_and_time(tree[i], m_tree[i][j], log[i],
param1)
print_tree_align_compare(result)
result["node"] = node_num
def test_random_create_tree_node(self):
for _ in range(100):
no_num = random.randint(10, 35)
tree = pt_create.apply(no_num)
index_num = pt_number.apply(tree, 'D', 1)
self.assertEqual(no_num, index_num)
