def test_group_random1():
"""Testing that the group_random() function creates the
appropriate number of groups with the appropriate number"""
lst = [
"Austin",
"Dan",
"Angie",
"Cullen",
"Chase",
"Vinny",
"Nick",
"Jeff",
"James",
"Kelly",
"Nikki",
"Robert",
]
lst2 = ["Dan", "Angie", "Austin", "Izaak", "Nick", "Jeff"]
group_size = 3
group_size2 = 2
num_group = 2
num_group2 = 3
actual_output = group_creation.group_random_group_size(lst, group_size)
actual_output2 = group_creation.group_random_group_size(lst2, group_size2)
actual_output3 = group_creation.group_random_num_group(lst, num_group)
actual_output4 = group_creation.group_random_num_group(lst2, num_group2)
assert len(actual_output) == 4
assert len(actual_output[0]) == 3
assert len(actual_output2) == 3
assert len(actual_output2[0]) == 2
assert len(actual_output3) == 2
assert len(actual_output3[0]) == 6
assert len(actual_output4) == 3
assert len(actual_output4[0]) == 2
def input_interface(
students,
method=None,
num_group=None,
preferences=None,
preferences_weight=None,
preferences_weight_match=None,
objective_weights=None,
objective_measures=None,
):
""" Run conditional logic statment to ran different methods """
students_reshuffle = group_creation.shuffle_students(students)
if method == constants.ALGORITHM_ROUND_ROBIN:
# Note that this only checks the first student
if len(students_reshuffle[0]) < 2:
grouped_students = group_creation.group_random_num_group(
students_reshuffle, num_group)
else:
grouped_students = group_creation.group_rrobin_num_group(
students_reshuffle, num_group)
elif method == constants.ALGORITHM_GRAPH:
grouped_students = group_graph.group_graph_partition(
students_reshuffle,
num_group,
preferences=preferences,
preferences_weight=preferences_weight,
preferences_weight_match=preferences_weight_match,
objective_weights=objective_weights,
objective_measures=objective_measures,
)
else:
grouped_students = group_creation.group_random_num_group(
students_reshuffle, num_group)
return grouped_students
def test_hypothesis_group_random(numgrp):
"""Testing the random type of grouping with everyone in an assigned group with hypothesis"""
responses = [
["Nick", True, False, True, False],
["Marvin", False, False, True, True],
["Evin", True, True, True, False],
["Nikki", True, True, False, False],
["Dan", False, True, False, True],
["Michael", True, True, False, False],
]
num_group = numgrp
returned_groups1 = group_creation.group_random_num_group(
responses, num_group)
assert len(returned_groups1[0]) == len(responses) / num_group
def test_group_random_extra():
"""Testing the random type of grouping with a group of extra people not assigned
to their own group"""
responses = [
["Nick", True, False, True, False],
["Marvin", False, False, True, True],
["Evin", True, True, True, False],
["Nikki", True, True, False, False],
["Dan", False, True, False, True],
]
num_group = 2
returned_groups1 = group_creation.group_random_num_group(
responses, num_group)
assert len(returned_groups1) == 2
assert num_group == 2
def test_group_random():
"""Testing the random type of grouping with everyone in an assigned group"""
responses = [
["Nick", True, False, True, False],
["Marvin", False, False, True, True],
["Evin", True, True, True, False],
["Nikki", True, True, False, False],
["Dan", False, True, False, True],
["Michael", True, True, False, False],
]
grpsize = 2
num_group = 3
returned_groups = group_creation.group_random_group_size(
responses, grpsize)
returned_groups1 = group_creation.group_random_num_group(
responses, num_group)
assert len(returned_groups) == 3
assert len(returned_groups1[0]) == 2
def test_hypothesis_random(numgrp):
"""Testing the random grouping function to assure proper output"""
lst = [
["Dan", True, True, True],
["Jesse", True, True, True],
["Austin", True, True, True],
["Nick", False, False, False],
["Nikki", False, False, False],
["Maria", False, False, False],
["Jeff", False, False, False],
["Simon", False, False, False],
["Jon", False, False, False],
["Angie", False, False, False],
["Izaak", False, False, False],
["Jacob", False, False, False],
]
num_group = numgrp
actual_output1 = group_creation.group_random_num_group(lst, num_group)
assert len(actual_output1) == num_group
assert len(actual_output1[0]) == len(lst) / numgrp
def test_group_random_conflict_numgrp():
"""
Test that groups are still created randomly, even when given
conflict tuples as input. Note that there is no guarantee that
a conflict will be avoided, but rather that it is more likely that
the conflict will be avoided than it won't. Perfect group creation
with guaranteed conflict avoidance is an NP-Hard problem. To test
that conflict management is effective at least most of the time
(>90%), groups will be generated multiple times, and results will
be collected as a 0 (conflict avoided) or 1 (conflict still present),
and the test case will pass as long as more than 90% of the results as
a 0 and not a 1.
"""
responses = [
["Nick", True, False, True, False],
["Marvin", False, False, True, True],
["Evin", True, True, True, False],
["Nikki", True, True, False, False],
["Dan", False, True, False, True],
["Michael", True, True, False, False],
]
num_group = 3
# A conflict is added.
conflict = ("Nick", "Marvin", 5)
results = []
# Run 1000 tests for significance
for _x in range(0, 1000):
returned_groups = group_creation.group_random_num_group(
responses, num_group)
for grp in returned_groups:
# if both members of the conflict relation are in a group, avoidance failed
if (conflict[0] in grp) and (conflict[1] in grp):
# 1 denotes conflict avoidance failure
results.append(1)
else:
# 0 denotes conflict avoidance failure
results.append(0)
# calculate the average of the results
results_avg = sum(results) / len(results)
# assert that the success rate of conflict avoidance is 90% minimum
assert results_avg < 0.9
def test_random():
"""Testing the random grouping function to assure proper output"""
lst = [
["Dan", True, True, True],
["Jesse", True, True, True],
["Austin", True, True, True],
["Nick", False, False, False],
["Nikki", False, False, False],
["Maria", False, False, False],
["Jeff", False, False, False],
["Simon", False, False, False],
["Jon", False, False, False],
["Angie", False, False, False],
["Izaak", False, False, False],
["Jacob", False, False, False],
]
group_size = 4
num_group = 3
actual_output = group_creation.group_random_group_size(lst, group_size)
actual_output1 = group_creation.group_random_num_group(lst, num_group)
assert len(actual_output) == 3
assert len(actual_output[0]) == 4
assert len(actual_output1) == 3
assert len(actual_output1[0]) == 4