def test_different_bad_design_matrix(): iv_names = ('a', 'b', 'c') iv_values = [[1, 2], [1, 2, 3], [1, 2]] matrix = np.array([[-1., -1., 1.], [1., -1., -1.], [-1., 1., -1.], [1., 1., 1.]]) # pyDOE.fracfact('a b ab') d = Design(ivs=zip(iv_names, iv_values), design_matrix=matrix) with pytest.raises(ValueError): d.first_pass()
def test_factorial(): iv_names = ("a", "b") iv_values = [[1, 2, 3], [1, 2]] conditions = [ {"a": 1, "b": 1}, {"a": 1, "b": 2}, {"a": 2, "b": 1}, {"a": 2, "b": 2}, {"a": 3, "b": 1}, {"a": 3, "b": 2}, ] assert list(Design.full_cross(iv_names, iv_values)) == conditions d = Design(zip(iv_names, iv_values)) d.first_pass() for _ in range(3): yield check_sequences, d.get_order(), conditions iv_names = ("a", "b", "c") iv_values = [[1, 2], [1, 2], [1, 2]] conditions = [ {"a": 1, "b": 1, "c": 1}, {"a": 1, "b": 1, "c": 2}, {"a": 1, "b": 2, "c": 1}, {"a": 1, "b": 2, "c": 2}, {"a": 2, "b": 1, "c": 1}, {"a": 2, "b": 1, "c": 2}, {"a": 2, "b": 2, "c": 1}, {"a": 2, "b": 2, "c": 2}, ] assert list(Design.full_cross(iv_names, iv_values)) == conditions d = Design(zip(iv_names, iv_values)) d.first_pass() for _ in range(3): yield check_sequences, d.get_order(), conditions
def test_factorial(): iv_names = ('a', 'b') iv_values = [[1, 2, 3], [1, 2]] conditions = [ {'a': 1, 'b': 1}, {'a': 1, 'b': 2}, {'a': 2, 'b': 1}, {'a': 2, 'b': 2}, {'a': 3, 'b': 1}, {'a': 3, 'b': 2}, ] assert list(Design.full_cross(iv_names, iv_values)) == conditions d = Design(zip(iv_names, iv_values)) d.first_pass() for _ in range(3): yield check_sequences, d.get_order(), conditions iv_names = ('a', 'b', 'c') iv_values = [[1, 2], [1, 2], [1, 2]] conditions = [ {'a': 1, 'b': 1, 'c': 1}, {'a': 1, 'b': 1, 'c': 2}, {'a': 1, 'b': 2, 'c': 1}, {'a': 1, 'b': 2, 'c': 2}, {'a': 2, 'b': 1, 'c': 1}, {'a': 2, 'b': 1, 'c': 2}, {'a': 2, 'b': 2, 'c': 1}, {'a': 2, 'b': 2, 'c': 2}, ] assert list(Design.full_cross(iv_names, iv_values)) == conditions d = Design(zip(iv_names, iv_values)) d.first_pass() for _ in range(3): yield check_sequences, d.get_order(), conditions
def test_design_matrix_with_continuous_iv(): matrix = np.array( [ [-1, -1], [1, -1], [-1, 1], [1, 1], [0, 0], [0, 0], [0, 0], [0, 0], [-1.41421356, 0], [1.41421356, 0], [0, -1.41421356], [0, 1.41421356], [0, 0], [0, 0], [0, 0], [0, 0], ] ) # pyDOE.ccdesign(2) iv_names = ["a", "b"] iv_values = [None, None] d = Design(zip(iv_names, iv_values), design_matrix=matrix) d.first_pass() for _ in range(3): yield check_design_matrix, d.get_order(), iv_names, iv_values, matrix
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_different_bad_design_matrix(): iv_names = ('a', 'b', 'c') iv_values = [[1, 2], [1, 2, 3], [1, 2]] matrix = np.array([[-1., -1., 1.], [1., -1., -1.], [-1., 1., -1.], [1., 1., 1.]]) # pyDOE.fracfact('a b ab') d = Design(ivs=zip(iv_names, iv_values), design_matrix=matrix) with pytest.raises(ValueError): d.first_pass()
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 test_design_matrix_with_continuous_iv(): matrix = np.array([[-1, -1], [1, -1], [-1, 1], [1, 1], [0, 0], [0, 0], [0, 0], [0, 0], [-1.41421356, 0], [1.41421356, 0], [0, -1.41421356], [0, 1.41421356], [0, 0], [0, 0], [0, 0], [0, 0]]) # pyDOE.ccdesign(2) iv_names = ['a', 'b'] iv_values = [None, None] d = Design(zip(iv_names, iv_values), design_matrix=matrix) d.first_pass() for _ in range(3): yield check_design_matrix, d.get_order(), iv_names, iv_values, matrix
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_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_design_matrix(): iv_names = ('a', 'b', 'c') iv_values = [[1, 2], [1, 2], [1, 2]] conditions = [ {'a': 1, 'b': 1, 'c': 2}, {'a': 1, 'b': 2, 'c': 1}, {'a': 2, 'b': 1, 'c': 1}, {'a': 2, 'b': 2, 'c': 2}, ] matrix = np.array([[-1., -1., 1.], [1., -1., -1.], [-1., 1., -1.], [1., 1., 1.]]) # pyDOE.fracfact('a b ab') d = Design(ivs=zip(iv_names, iv_values), design_matrix=matrix) d.first_pass() for _ in range(3): yield check_sequences, d.get_order(), conditions yield check_design_matrix, d.get_order(), iv_names, iv_values, matrix
def test_design_matrix(): iv_names = ("a", "b", "c") iv_values = [[1, 2], [1, 2], [1, 2]] conditions = [ {"a": 1, "b": 1, "c": 2}, {"a": 1, "b": 2, "c": 1}, {"a": 2, "b": 1, "c": 1}, {"a": 2, "b": 2, "c": 2}, ] matrix = np.array( [[-1.0, -1.0, 1.0], [1.0, -1.0, -1.0], [-1.0, 1.0, -1.0], [1.0, 1.0, 1.0]] ) # pyDOE.fracfact('a b ab') d = Design(ivs=zip(iv_names, iv_values), design_matrix=matrix) d.first_pass() for _ in range(3): yield check_sequences, d.get_order(), conditions yield check_design_matrix, d.get_order(), iv_names, iv_values, matrix
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 test_design_matrix(): iv_names = ('a', 'b', 'c') iv_values = [[1, 2], [1, 2], [1, 2]] conditions = [ { 'a': 1, 'b': 1, 'c': 2 }, { 'a': 1, 'b': 2, 'c': 1 }, { 'a': 2, 'b': 1, 'c': 1 }, { 'a': 2, 'b': 2, 'c': 2 }, ] matrix = np.array([[-1., -1., 1.], [1., -1., -1.], [-1., 1., -1.], [1., 1., 1.]]) # pyDOE.fracfact('a b ab') d = Design(ivs=zip(iv_names, iv_values), design_matrix=matrix) d.first_pass() for _ in range(3): yield check_sequences, d.get_order(), conditions yield check_design_matrix, d.get_order(), iv_names, iv_values, matrix
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
def make_tree(levels, data): designs = [[Design([('a', range(len(levels))), ('b', [False, True])], extra_data=data, ordering=Ordering())] for _ in levels] return DesignTree.new(list(zip(levels, designs)))
def test_factorial(): iv_names = ('a', 'b') iv_values = [[1, 2, 3], [1, 2]] conditions = [ { 'a': 1, 'b': 1 }, { 'a': 1, 'b': 2 }, { 'a': 2, 'b': 1 }, { 'a': 2, 'b': 2 }, { 'a': 3, 'b': 1 }, { 'a': 3, 'b': 2 }, ] assert list(Design.full_cross(iv_names, iv_values)) == conditions d = Design(zip(iv_names, iv_values)) d.first_pass() for _ in range(3): yield check_sequences, d.get_order(), conditions iv_names = ('a', 'b', 'c') iv_values = [[1, 2], [1, 2], [1, 2]] conditions = [ { 'a': 1, 'b': 1, 'c': 1 }, { 'a': 1, 'b': 1, 'c': 2 }, { 'a': 1, 'b': 2, 'c': 1 }, { 'a': 1, 'b': 2, 'c': 2 }, { 'a': 2, 'b': 1, 'c': 1 }, { 'a': 2, 'b': 1, 'c': 2 }, { 'a': 2, 'b': 2, 'c': 1 }, { 'a': 2, 'b': 2, 'c': 2 }, ] assert list(Design.full_cross(iv_names, iv_values)) == conditions d = Design(zip(iv_names, iv_values)) d.first_pass() for _ in range(3): yield check_sequences, d.get_order(), conditions
def test_bad_design_matrix(): with pytest.raises(TypeError): design = Design(ivs=[('a', [1]), ('b', [1])], design_matrix=np.ones((3, 3))) design.first_pass()
def test_continuous_ivs_without_design_matrix(): with pytest.raises(TypeError): Design(ivs=[('a', None)])
def test_bad_design_matrix(): with pytest.raises(TypeError): design = Design(ivs=[('a', [1]), ('b', [1])], design_matrix=np.ones((3, 3))) design.first_pass()
def test_bizarre_equality(): design = Design() assert (design == 1) is False tree = DesignTree.new([('a', design)]) assert (tree == 1) is False