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_logs(pts):
logs_list = list()
for trees in pts:
logs = pd.DataFrame(columns=['log'])
for i, s_tree in enumerate(trees['tree']):
tree = pt_utils.parse(s_tree)
logs.loc[i] = [
parse_string_list(
log_create.apply(tree, trace_num, non_fit_pro))
]
logs_list.append(logs)
return logs_list
def create_log():
"""
Create specified number of event logs of each tree, not including Empty Trace.
The event log in the same column belong to the same process tree.
"""
base = excel_utils.create_workbook()
trees = object_read.read_trees_from_file(PT_FILE_NAME)
log_e_table = None
for row, tree in enumerate(trees):
if row % PT_NUM[0] == 0:
log_e_table = ExcelTable(
base.add_sheet(LOG_SHEET_NAME[row // PT_NUM[0]]))
log = log_create.apply(tree, TRACE_NUM, 0.8)
trace_list = [[event[DEFAULT_NAME_KEY] for event in trace]
for trace in log]
excel_utils.write_column_to_table(log_e_table.table,
log_e_table.column, trace_list)
excel_utils.save(base, LOG_FILE_NAME)
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