def test_Exceptions(self, universe, leaflets, lipid_sel="name ROH"):
match = (
"'leaflets' must be a 2D array of shape \\(n_residues, n_frames\\)"
" containing the leaflet id of each lipid at each frame.")
with pytest.raises(ValueError, match=match):
FlipFlop(
universe=universe,
lipid_sel=lipid_sel,
leaflets=leaflets[0] # wrong dimensions
)
with pytest.raises(ValueError, match=match):
FlipFlop(
universe=universe,
lipid_sel=lipid_sel,
leaflets=np.concatenate(
(leaflets, leaflets)) # wrong number of residues
)
match = ("The frames to analyse must be identical to those used "
"in assigning lipids to leaflets.")
with pytest.raises(ValueError, match=match):
flip_flop = FlipFlop(
universe=universe,
lipid_sel=lipid_sel,
leaflets=leaflets[:, ::
2] # not enough frames for the trajectory
)
flip_flop.run(start=None, stop=None, step=None)
with pytest.raises(ValueError, match=match):
flip_flop = FlipFlop(universe=universe,
lipid_sel=lipid_sel,
leaflets=leaflets)
flip_flop.run(
start=None,
stop=None,
step=2 # different number of frames to what is in 'leaflets'
)
match = "'frame_cutoff' must be greater than or equal to 1"
with pytest.raises(ValueError, match=match):
FlipFlop(universe=universe,
lipid_sel=lipid_sel,
leaflets=leaflets,
frame_cutoff=0)
def test_flip_flop(self, universe, leaflets, lipid_sel="name ROH"):
# 3 flip-flop events with the second one a failure (remains in the upper leaflet)
flip_flop = FlipFlop(
universe=universe,
lipid_sel=lipid_sel,
leaflets=leaflets,
frame_cutoff=1,
)
flip_flop.run()
reference = {
'events': [[0, 5, 8, 1], [0, 8, 11, 1], [0, 17, 19, -1]],
'success': ["Success", "Fail", "Success"]
}
assert_array_equal(flip_flop.flip_flops, reference['events'])
assert_array_equal(flip_flop.flip_flop_success, reference['success'])
def test_flip_flop_same_leaflet(self,
universe,
leaflets,
lipid_sel="name ROH"):
flip_flop = FlipFlop(
universe=universe,
lipid_sel=lipid_sel,
leaflets=np.ones_like(leaflets, dtype=np.int8),
)
flip_flop.run()
reference = {
'events': np.array([[], [], [], []]).T,
'success': np.array([])
}
assert_array_equal(flip_flop.flip_flops, reference['events'])
assert_array_equal(flip_flop.flip_flop_success, reference['success'])
def test_flip_flop_lower_mid_only(self,
universe,
leaflets,
lipid_sel="name ROH"):
leaflets = np.ones_like(leaflets, dtype=np.int8) * -1
leaflets[0, 1] = 0
flip_flop = FlipFlop(universe=universe,
lipid_sel=lipid_sel,
leaflets=leaflets)
flip_flop.run()
reference = {
'events': np.array([[0], [0], [2], [-1]]).T,
'success': np.array(["Fail"])
}
assert_array_equal(flip_flop.flip_flops, reference['events'])
assert_array_equal(flip_flop.flip_flop_success, reference['success'])
def test_flip_flop_framecut2(self,
universe,
leaflets,
lipid_sel="name ROH"):
# only two flip-flop events found now, both successful
flip_flop = FlipFlop(
universe=universe,
lipid_sel=lipid_sel,
leaflets=leaflets,
frame_cutoff=2,
)
flip_flop.run()
reference = {
'events': [[0, 5, 11, 1], [0, 17, 19, -1]],
'success': ["Success", "Success"]
}
assert_array_equal(flip_flop.flip_flops, reference['events'])
assert_array_equal(flip_flop.flip_flop_success, reference['success'])
def test_flip_flop_framecut8(self,
universe,
leaflets,
lipid_sel="name ROH"):
# No flip-flop events found now
# Cholesterol doesn't remain in opposing lealet for long enough
flip_flop = FlipFlop(
universe=universe,
lipid_sel=lipid_sel,
leaflets=leaflets,
frame_cutoff=8,
)
flip_flop.run()
reference = {
'events': np.array([[], [], [], []]).T,
'success': np.array([])
}
assert_array_equal(flip_flop.flip_flops, reference['events'])
assert_array_equal(flip_flop.flip_flop_success, reference['success'])