def test_bad_heterogeneity():
main_structure = [
('participant',
Design(ivs={
'a': [1, 2],
'b': [1, 2]
}, ordering=Shuffle(3))),
('session',
Design(ivs={'design': ['practice', 'test']},
design_matrix=[[0], [1], [1]])),
]
other_structures = {
'practice': [
('block', Design()),
('trial', Design(ivs={'difficulty': [1, 2]},
ordering=Shuffle(20))),
],
'test': [
('block', Design(ordering=CompleteCounterbalance(2))),
('trial',
Design(ivs={'difficulty': [1, 3, 5, 7]}, ordering=Shuffle(5))),
],
}
with pytest.raises(ValueError):
DesignTree.new(main_structure, **other_structures)
def make_heterogeneous_tree():
main_structure = [
('participant',
Design(ivs={
'a': [1, 2],
'b': [1, 2]
}, ordering=Shuffle(3))),
('session',
Design(ivs={'design': ['practice', 'test']},
design_matrix=[[0], [1], [1]])),
]
other_structures = {
'practice': [
('block', Design()),
('trial', Design(ivs={'difficulty': [1, 2]},
ordering=Shuffle(20))),
],
'test': [
('block', Design(ordering=Ordering(2))),
('trial',
Design(ivs={'difficulty': [1, 3, 5, 7]}, ordering=Shuffle(5))),
],
}
return DesignTree.new(main_structure, **other_structures)
def make_manual_exp():
tree = DesignTree.new([('participant', [Design(ordering=Shuffle(2))]),
('block', [Design(ivs={'b': [0, 1, 2]}, ordering=CompleteCounterbalance())]),
('trial', [Design({'a': [False, True]}, ordering=Shuffle(4))]),
])
exp = Experiment.new(tree)
exp.add_callback('trial', trial)
return exp
def make_standard_exp():
exp = Experiment.basic(('participant', 'block', 'trial'),
{'block': [('b', [0, 1, 2])],
'trial': [('a', [False, True])]},
ordering_by_level={'trial': Shuffle(4),
'block': CompleteCounterbalance(),
'participant': Shuffle(2)})
exp.add_callback('trial', trial)
return exp
def test_design_from_spec():
spec = {
'name': 'test1',
'order': 'Shuffle',
'n': 2,
'ivs': {
'a': [True, False],
'b': [1, 2, 3]
},
}
assert Design.from_dict(spec) == ('test1',
Design(
{
'a': [True, False],
'b': [1, 2, 3]
},
ordering=Shuffle(2)))
spec = {
'name': 'test2',
'some_extra_field': ['blah'],
'number': 3,
}
assert Design.from_dict(spec) == ('test2',
Design(extra_data={
'some_extra_field': ['blah']
},
ordering=Shuffle(3)))
spec = {
'name': 'test3',
'ordering': {
'class': 'Sorted',
'order': 'ascending',
},
'ivs': {
'a': [1, 2, 3]
},
}
assert Design.from_dict(spec) == ('test3',
Design(
ivs={'a': [1, 2, 3]},
ordering=Sorted(order='ascending')))
spec = {
'name': 'test4',
'order': ['CompleteCounterbalance', 3],
}
assert Design.from_dict(spec) == ('test4',
Design(
ordering=CompleteCounterbalance(3)))
spec.pop('name')
assert Design.from_dict(spec) == Design(ordering=CompleteCounterbalance(3))
def test_shuffle_generator_condition():
n = 3
o = Shuffle(number=n)
o.first_pass(c for c in CONDITIONS_3)
yield check_shuffle, o, len(CONDITIONS_3)
o = Shuffle(n, avoid_repeats=True)
o.first_pass(c for c in CONDITIONS_3)
yield check_shuffle, o, len(CONDITIONS_3)
yield check_repeats, o.get_order()
def test_shuffle():
for n in range(1, 6, 2):
for conditions in (CONDITIONS_6, CONDITIONS_2_3, CONDITIONS_2_3_2):
o = Shuffle(number=n)
o.first_pass(conditions)
yield check_shuffle, o, len(conditions)
o = Shuffle(n, avoid_repeats=True)
o.first_pass(conditions)
yield check_shuffle, o, len(conditions)
yield check_repeats, o.get_order()
def test_shuffle_generator_condition():
n = 3
o = Shuffle(number=n)
o.first_pass(c for c in CONDITIONS_3)
yield check_shuffle, o, len(CONDITIONS_3)
o = Shuffle(n, avoid_repeats=True)
o.first_pass(c for c in CONDITIONS_3)
yield check_shuffle, o, len(CONDITIONS_3)
yield check_repeats, o.get_order()
def test_shuffle():
for n in range(1, 6, 2):
for conditions in (CONDITIONS_6, CONDITIONS_2_3, CONDITIONS_2_3_2):
o = Shuffle(number=n)
o.first_pass(conditions)
yield check_shuffle, o, len(conditions)
o = Shuffle(n, avoid_repeats=True)
o.first_pass(conditions)
yield check_shuffle, o, len(conditions)
yield check_repeats, o.get_order()
def make_blocked_exp():
exp = Experiment.blocked({'a': [False, True]}, 2,
block_ivs={'b': [0, 1, 2]},
orderings={'trial': Shuffle(4), 'block': CompleteCounterbalance()})
exp.add_callback('trial', trial)
return exp
def make_simple_exp():
ivs = {'a': [False, True], 'b': [0, 1, 2]}
exp = Experiment.within_subjects(ivs, 10, ordering=Shuffle(4))
exp.add_callback('trial', trial)
return exp
def test_schema_list():
assert OrderSchema.from_any(['Shuffle', 2]) == Shuffle(2)
def test_bizarre_inequality():
assert (Shuffle() == 1) is False
def test_reprs():
for ord in (CompleteCounterbalance(), Shuffle(), LatinSquare(), Ordering(),
Sorted()):
yield check_repr, ord
def test_design_tree():
trial_matrix = np.array(
[[-1, -1], [1, -1], [-1, 1], [1, 1], [0, 0], [0, 0], [0, 0], [0, 0],
[-1.41421356, 0.1],
[1.41421356, 0.1], [0, -1.41421356], [0,
1.41421356],
[0, 0], [0, 0], [0,
0], [0, 0]]
) # pyDOE.ccdesign(2) with two 0.1 elements to prevent symmetry in the IVs.
trial_iv_names = ['a', 'b']
trial_iv_values = [None, None]
block_ivs = {'block': [1, 2]}
participant_iv_names = ('A', 'B')
participant_iv_values = [[1, 2], [1, 2, 3]]
trial_design = Design(ivs=zip(trial_iv_names, trial_iv_values),
ordering=Shuffle(3),
design_matrix=trial_matrix)
block_design = Design(block_ivs, ordering=CompleteCounterbalance())
practice_block_design = Design()
participant_design = Design(dict(
zip(participant_iv_names, participant_iv_values)),
ordering=Ordering(10))
levels_and_designs = OrderedDict([('participant', participant_design),
('block',
[practice_block_design, block_design]),
('trial', trial_design)])
tree = DesignTree.new(levels_and_designs)
tree.add_base_level()
levels, designs = zip(*tree.levels_and_designs)
yield check_identity, designs[1][0], participant_design
yield check_identity, designs[2][0], practice_block_design
yield check_identity, designs[2][1], block_design
yield check_identity, designs[3][0], trial_design
yield check_equality, len(tree), 4
yield check_equality, tree[3], ('trial', [trial_design])
yield check_equality, next(tree).levels_and_designs, next(
tree).levels_and_designs, tree.levels_and_designs[1:]
tree_with_participant_base = next(tree)
tree_with_block_base = next(tree_with_participant_base)
yield (check_equality, tree_with_block_base.levels_and_designs,
next(next(tree)).levels_and_designs,
[('block', [practice_block_design, block_design]),
('trial', [trial_design])])
tree_with_trial_base = next(tree_with_block_base)
yield (check_equality, tree_with_trial_base.levels_and_designs, [
('trial', [trial_design])
], next(tree_with_block_base).levels_and_designs)
with pytest.raises(StopIteration):
next(tree_with_trial_base)
for design, iv_names, iv_values, n, data, matrix in zip(
[designs[1][0], designs[2][0], designs[2][1], designs[3][0]],
[['A', 'B', CompleteCounterbalance.iv_name], [], ['block'], ['a', 'b']
], [[[1, 2], [1, 2, 3], [0, 1]], [], [[1, 2]], [None, None]],
[10 * 2 * 2 * 3, 1, 2, 3 * len(trial_matrix)],
[{}, {}, {
CompleteCounterbalance.iv_name: 0
}, {}], [None, None, None, trial_matrix]):
yield check_design, design, iv_names, iv_values, n, data, matrix
yield check_design_matrix, designs[3][0].get_order(), ['a', 'b'
], [None, None
], trial_matrix