def test_optimal_tree3():
records = parse_data(r"test_optimal_tree3.txt")
tree = optimal_tree(records, ["fever","cough","headache"],2)
assert "influenza" == tree.positive_child.positive_child.data
assert "meningitis" == tree.positive_child.negative_child.data
assert "cold" == tree.negative_child.positive_child.data
assert "healthy" == tree.negative_child.negative_child.data
def test_optimal_tree(capsys):
symptoms = [
'congestion', 'cough', 'fatigue', 'fever', 'headache', 'irritability',
'muscle_ache', 'nausea', 'rigidity', 'sore_throat'
]
for fn, successes in {
r'data/tiny_data.txt':
[1 / 6, 2 / 6, 4 / 6, 5 / 6, 1, 1, 1, 1, 1, 1, 1],
r'data/small_data.txt': [
10 / 60, 20 / 60, 36 / 60, 49 / 60, 52 / 60, 53 / 60, 55 / 60,
56 / 60, 56 / 60, 56 / 60, 56 / 60
],
r'data/medium_data.txt': [
100 / 600, 195 / 600, 346 / 600, 445 / 600, 491 / 600,
517 / 600, 534 / 600, 540 / 600, 543 / 600, 544 / 600,
545 / 600
],
r'data/big_data.txt':
[1000 / 6000, 1951 / 6000, 3359 / 6000, 4403 / 6000],
}.items():
records = ex11.parse_data(fn)
for i in range(len(symptoms) + 1):
if fn.endswith('big_data.txt') and i > 3:
continue
tree = ex11.optimal_tree(records, symptoms, i)
if CHECK_OPTIMAL_TREE:
actual = repr_tree(tree)
# open(fn + '.4expected' + str(i), 'w').write(actual)
expected1 = open(fn + '.expected' + str(i)).read()
expected2 = open(fn + '.2expected' + str(i)).read()
expected3 = open(fn + '.3expected' + str(i)).read()
expected4 = open(fn + '.4expected' + str(i)).read()
assert actual in (expected1, expected2, expected3, expected4), \
"Maybe your answer is correct, check it carefully. " \
"If it's OK, remove this assert."
cur_diagnoser = ex11.Diagnoser(tree)
# print(diagnoser.calculate_success_rate(records), end=', ')
actual = cur_diagnoser.calculate_success_rate(records)
expected = successes[i]
assert actual == expected, \
f"tree: {repr_tree(cur_diagnoser.root)}\n" \
f"records from: {fn}\n" \
f"num of symptoms: {i}\n" \
f"expected: {expected}\n" \
f"actual: {actual}"
# if fn.endswith('big_data.txt') and i == 3:
# with open('data/big_diagnoser.dmp', 'wb') as f:
# pickle.dump(diagnoser, f)
# if fn.endswith('medium_data.txt') and i == 6:
# with open('data/medium_diagnoser.dmp', 'wb') as f:
# pickle.dump(diagnoser, f)
# print()
out, err = capsys.readouterr()
assert not out and not err, f"Don't print. out: '{out}', err: '{err}'"
# test 5
expected = [[True, False, True], [False, True, False]]
result = diagnoser.paths_to_illness("influenza")
check(5, expected, result, "influenza", list_check)
# test 6
result = build_tree(records, ["cough", "sneezing", "fever"])
check(6, root, result, "", tree_check)
if not tree_check(result, root):
print("expected: ")
print_tree(root)
print("result: ")
print_tree(result)
# test 7
result = optimal_tree(records, ["cough", "sneezing", "fever"], 2)
new_leaf1 = Node("influenza", None, None)
new_leaf2 = Node("cold", None, None)
new_fever1 = Node("fever", new_leaf1, new_leaf2)
new_leaf3 = Node("dead", None, None)
new_leaf4 = Node("healthy", None, None)
new_fever2 = Node("fever", new_leaf3, new_leaf4)
new_root = Node("cough", new_fever1, new_fever2)
if not tree_check(result, new_root):
print("expected: ")
print_tree(new_root)
print("result: ")
print_tree(result)
def test_optimal_tree2():
records = parse_data(r"test_optimal_tree2.txt")
tree = optimal_tree(records,["cough", "fever", "headache"],1)
assert "fever" == tree.data or "headache" == tree.data
def test_optimal_tree1():
records = parse_data(r"test_optimal_tree1.txt")
tree = optimal_tree(records, ["cough", "fever", "headache"], 2)
assert "cough" == tree.data or "fever" == tree.data
assert "cough" == tree.positive_child.data or "fever" == tree.positive_child.data