def test_stack_config_idx(self):
"""Test if config_idx is updated correctly after stack."""
stimulus_set = np.array((
(0, 1, 2, 3, -1, -1, -1, -1, -1),
(9, 12, 7, 1, -1, -1, -1, -1, -1),
(3, 4, 5, 6, 7, -1, -1, -1, -1),
(3, 4, 2, 6, 7, -1, -1, -1, -1),
(3, 4, 5, 6, 13, 14, 15, 16, 17)))
# Create first set of original trials.
n_select = np.array((1, 1, 1, 1, 1))
trials_0 = trials.RankObservations(stimulus_set, n_select=n_select)
desired_config_idx = np.array((0, 0, 1, 1, 2))
np.testing.assert_array_equal(trials_0.config_idx, desired_config_idx)
# Create second set of original trials, with non-overlapping
# configuration.
n_select = np.array((2, 2, 2, 2, 2))
trials_1 = trials.RankObservations(stimulus_set, n_select=n_select)
desired_config_idx = np.array((0, 0, 1, 1, 2))
np.testing.assert_array_equal(trials_1.config_idx, desired_config_idx)
# Stack trials
trials_stack = trials.stack((trials_0, trials_1))
desired_config_idx = np.array((0, 0, 1, 1, 2, 3, 3, 4, 4, 5))
np.testing.assert_array_equal(
trials_stack.config_idx, desired_config_idx)
def test_invalid_stimulus_set(self):
"""Test handling of invalid `stimulus_set` argument."""
# Non-integer input.
stimulus_set = np.array((
(0., 1, 2, -1, -1, -1, -1, -1, -1),
(9, 12, 7, -1, -1, -1, -1, -1, -1),
(3, 4, 5, 6, 7, -1, -1, -1, -1),
(3, 4, 5, 6, 13, 14, 15, 16, 17)))
with pytest.raises(Exception) as e_info:
obs = trials.RankObservations(stimulus_set)
# Contains integers below -1.
stimulus_set = np.array((
(0, 1, -2, -1, -1, -1, -1, -1, -1),
(9, 12, 7, -1, -1, -1, -1, -1, -1),
(3, 4, 5, 6, 7, -1, -1, -1, -1),
(3, 4, 5, 6, 13, 14, 15, 16, 17)))
with pytest.raises(Exception) as e_info:
obs = trials.RankObservations(stimulus_set)
# Does not contain enough references for each trial.
stimulus_set = np.array((
(0, 1, 2, -1, -1, -1, -1, -1, -1),
(9, 12, 7, -1, -1, -1, -1, -1, -1),
(3, 4, -1, -1, -1, -1, -1, -1, -1),
(3, 4, 5, 6, 13, 14, 15, 16, 17)))
with pytest.raises(Exception) as e_info:
obs = trials.RankObservations(stimulus_set)
def setup_obs_1():
"""
"""
stimulus_set = np.array(((0, 1, 2, -1, -1, -1, -1, -1, -1),
(9, 12, 7, -1, -1, -1, -1, -1, -1),
(3, 4, 5, 6, 7, -1, -1, -1, -1),
(3, 4, 5, 6, 13, 14, 15, 16, 17)), dtype=np.int32)
n_trial = 4
n_select = np.array((1, 1, 1, 2), dtype=np.int32)
n_reference = np.array((2, 2, 4, 8), dtype=np.int32)
is_ranked = np.array((True, True, True, True))
group_id = np.array((0, 0, 1, 1), dtype=np.int32)
configurations = pd.DataFrame(
{
'n_reference': np.array([2, 4, 8], dtype=np.int32),
'n_select': np.array([1, 1, 2], dtype=np.int32),
'is_ranked': [True, True, True],
'group_id': np.array([0, 1, 1], dtype=np.int32),
'session_id': np.array([0, 0, 0], dtype=np.int32),
'n_outcome': np.array([2, 4, 56], dtype=np.int32)
},
index=[0, 2, 3])
configuration_id = np.array((0, 0, 1, 2), dtype=np.int32)
obs = trials.RankObservations(
stimulus_set, n_select=n_select, group_id=group_id)
return {
'n_trial': n_trial, 'stimulus_set': stimulus_set,
'n_reference': n_reference, 'n_select': n_select,
'is_ranked': is_ranked, 'group_id': group_id, 'obs': obs,
'configurations': configurations,
'configuration_id': configuration_id
}
def test_invalid_group_id(self):
"""Test handling of invalid `group_id` argument."""
stimulus_set = np.array((
(0, 1, 2, -1, -1, -1, -1, -1, -1),
(9, 12, 7, -1, -1, -1, -1, -1, -1),
(3, 4, 5, 6, 7, -1, -1, -1, -1),
(3, 4, 5, 6, 13, 14, 15, 16, 17)))
# Mismatch in number of trials
group_id = np.array((0, 0, 1))
with pytest.raises(Exception) as e_info:
obs = trials.RankObservations(stimulus_set, group_id=group_id)
# Below support.
group_id = np.array((0, -1, 1, 0))
with pytest.raises(Exception) as e_info:
obs = trials.RankObservations(stimulus_set, group_id=group_id)
def test_subset_config_idx(self):
"""Test if config_idx is updated correctly after subset."""
stimulus_set = np.array((
(0, 1, 2, -1, -1, -1, -1, -1, -1),
(9, 12, 7, -1, -1, -1, -1, -1, -1),
(3, 4, 5, 6, 7, -1, -1, -1, -1),
(3, 4, 2, 6, 7, -1, -1, -1, -1),
(3, 4, 5, 6, 13, 14, 15, 16, 17)))
# Create original trials.
n_select = np.array((1, 1, 1, 1, 2))
obs = trials.RankObservations(stimulus_set, n_select=n_select)
desired_config_idx = np.array((0, 0, 1, 1, 2))
np.testing.assert_array_equal(obs.config_idx, desired_config_idx)
# Grab subset and check that config_idx is updated to start at 0.
trials_subset = obs.subset(np.array((2, 3, 4)))
desired_config_idx = np.array((0, 0, 1))
np.testing.assert_array_equal(
trials_subset.config_idx, desired_config_idx)