class TestAsArrayMethod(TestCase):
def setUp(self):
conditional_array = np.array([0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1])
condition = (conditional_array > 0)
self.events = Events(condition)
def test_default_parameters(self):
"""Test as_array() with default settings"""
validation_array = np.array([0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1])
npt.assert_array_equal(validation_array, self.events.as_array())
def test_as_array_false_value(self):
"""Test as_array() with low value"""
validation_array = np.array([-1, 1, 1, 1, -1, -1, -1, 1, 1, -1, 1, 1])
npt.assert_array_equal(validation_array,
self.events.as_array(false_values=-1))
def test_as_array_true_value(self):
"""Test as_array() with high value"""
validation_array = np.array([0, 5, 5, 5, 0, 0, 0, 5, 5, 0, 5, 5])
npt.assert_array_equal(validation_array,
self.events.as_array(true_values=5))
def test_as_array_false_and_true_value(self):
"""Test as_array() with low and high values"""
validation_array = np.array([-1, 5, 5, 5, -1, -1, -1, 5, 5, -1, 5, 5])
npt.assert_array_equal(
validation_array,
self.events.as_array(false_values=-1, true_values=5))
def test_event_always_active(self):
"""Test arrays that has an event active throughout entire array"""
validation_array = np.ones(10, dtype='i1')
condition = (validation_array > 0)
events = Events(condition)
npt.assert_array_equal(validation_array, events.as_array())
def test_stop_index_offset(self):
validation_array = np.array([1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1])
validation_stops_index = np.array([2, 7, 11, 13])
events = Events(self.condition, stop_offset=1)
npt.assert_array_equal(validation_array, events.as_array())
npt.assert_array_equal(validation_stops_index, events.stops)
def test_array_with_event_active_at_end(self):
"""Test arrays that have events active at the end"""
validation_array = np.zeros(10, dtype='i1')
validation_array[-1:] = 1
condition = (validation_array > 0)
events = Events(condition)
npt.assert_array_equal(validation_array, events.as_array())
def test_no_events_found(self):
"""Test arrays that have no active events"""
conditional_array = np.ones(10, dtype='i1')
validation_array = np.zeros(10, dtype='i1')
condition = (conditional_array > 5)
events = Events(condition)
npt.assert_array_equal(validation_array, events.as_array())
def test_default_parameters(self):
"""Test event detection with only a supplied condition"""
np.random.seed(10)
validation_array = np.random.random_integers(0, 1, 100)
condition = (validation_array > 0)
events = Events(condition)
npt.assert_array_equal(validation_array, events.as_array())
def test_max_and_min_event_window_length(self):
validation_array = np.array(
[0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
events = Events(self.condition,
sample_rate=3,
min_event_length=0.5,
max_event_length=1)
npt.assert_array_equal(validation_array, events.as_array())
def test_multi_input_condition_event(self):
"""Test arrays that have multi-input conditions"""
x = np.array([0, 1, 1, 1, 0, 0, 0, 1, 1, 0])
y = np.array([0, 0, 1, 1, 1, 0, 0, 1, 0, 1])
validation_array = np.array([0, 0, 1, 1, 0, 0, 0, 1, 0, 0])
condition = ((x > 0) & (y > 0))
events = Events(condition)
npt.assert_array_equal(validation_array, events.as_array())
def test_entry_and_exit_debounce(self):
validation_array = np.array(
[0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])
events = Events(self.condition,
sample_rate=3,
entry_debounce=0.5,
exit_debounce=1)
npt.assert_array_equal(validation_array, events.as_array())
def test_max_event_window_length(self):
validation_array = np.array([0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1])
events = Events(self.condition, max_event_length=3)
npt.assert_array_equal(validation_array, events.as_array())
def test_entry_and_exit_debounce(self):
validation_array = np.array([0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1])
events = Events(self.condition, entry_debounce=2, exit_debounce=2)
npt.assert_array_equal(validation_array, events.as_array())
