def test_get_switching_matrix(num_tracks=1000,
p_binding=0.01,
p_unbinding=0.1):
tracks = simulate.tracks(
num_tracks=num_tracks,
p_binding=p_binding,
p_unbinding=p_unbinding,
use_tqdm=False,
)
switching_matrix = switch.get_switching_matrix(tracks,
column="free",
n_states=2)
assert switching_matrix.shape == (2, 2)
np.testing.assert_almost_equal(switching_matrix[1, 0],
p_binding,
decimal=abs(
np.log10(p_binding).astype(int)))
np.testing.assert_almost_equal(
switching_matrix[0, 1],
p_unbinding,
decimal=abs(np.log10(p_unbinding).astype(int)),
)
switching_matrix, raw_matrix = switch.get_switching_matrix(
tracks, column="free", n_states=2, return_raw_counts=True)
assert raw_matrix.shape == (2, 2)
with pytest.raises(ValueError):
tr = simulate.track(min_len=3)
tr1 = tr.add_column("states", np.arange(len(tr)), "test")
switch.get_switching_matrix([tr1], column="states", n_states=2)
def test_get_item_vector():
track = simulate.track()
sub_track = track[track.frame < 3]
assert len(sub_track) == 3
def test_add_seg_id_to_track():
track = simulate.track()
new_track = segments.add_seg_id_to_track(
track,
column_with_states="free",
start_id=0,
new_column="seg_id",
return_new_id=False,
)
assert isinstance(new_track.seg_id, np.ndarray)
def test_big_lag():
track = simulate.track()
assert bayes.get_jd(track, lag=len(track)) == []
def test_repr():
track = simulate.track()
assert isinstance(repr(track), str)
def test_bad_column():
track = simulate.track()
with pytest.raises(ValueError):
track.xyz