def plot_adjacent_unifrac(
sid_data,
dm_header,
dm_data,
map_data,
time_field="WeeksSinceStart",
line_color="blue",
disturbance_colors=["blue", "green", "red", "orange"],
):
disturbed_weeks = []
disturbance_types = []
for e in sid_data:
for d in e[2]:
disturbed_weeks.append((float(e[0]), d))
disturbance_types.append(d)
disturbance_types = list(set(disturbance_types))
disturbance_colors = dict(zip(disturbance_types, disturbance_colors))
adjacent_distances = get_adjacent_distances(dm_header, dm_data, [e[1] for e in sid_data])
x = map(float, [map_data[e[1]][time_field] for e in adjacent_distances[1]])
y = adjacent_distances[0]
plot(x, y, "-.", c=line_color)
ylim(0, 1)
ymin, ymax = ylim()
for dw, dt in disturbed_weeks:
line_color = disturbance_colors[dt]
dw_w_offset = dw + (disturbance_types.index(dt) * 0.1)
plot([dw_w_offset, dw_w_offset], [ymin, ymax], "--", c=line_color)
def test_get_adjacent_distances(self):
""" extracting adjacent distances works as expected
"""
dm_str = ["\ts1\ts2\ts3", "s1\t0\t2\t4", "s2\t2\t0\t3.2", "s3\t4\t3.2\t0"]
dm_header, dm = parse_distmat(dm_str)
# error cases: fewer than 2 valid sample ids
self.assertRaises(ValueError, get_adjacent_distances, dm_header, dm, [])
self.assertRaises(ValueError, get_adjacent_distances, dm_header, dm, ["s1"])
self.assertRaises(ValueError, get_adjacent_distances, dm_header, dm, ["s0", "s1"])
self.assertRaises(ValueError, get_adjacent_distances, dm_header, dm, ["s1", "s4"])
# one pair of valid distances
self.assertEqual(get_adjacent_distances(dm_header, dm, ["s1", "s2"]), ([2], [("s1", "s2")]))
self.assertEqual(get_adjacent_distances(dm_header, dm, ["s1", "s1"]), ([0], [("s1", "s1")]))
self.assertEqual(get_adjacent_distances(dm_header, dm, ["s1", "s3"]), ([4], [("s1", "s3")]))
self.assertEqual(get_adjacent_distances(dm_header, dm, ["s2", "s3"]), ([3.2], [("s2", "s3")]))
# multiple valid distances
self.assertEqual(
get_adjacent_distances(dm_header, dm, ["s1", "s2", "s3"]), ([2, 3.2], [("s1", "s2"), ("s2", "s3")])
)
self.assertEqual(
get_adjacent_distances(dm_header, dm, ["s1", "s3", "s2", "s1"]),
([4, 3.2, 2], [("s1", "s3"), ("s3", "s2"), ("s2", "s1")]),
)
# mixed valid and invalid distances ignores invalid distances
self.assertEqual(
get_adjacent_distances(dm_header, dm, ["s1", "s3", "s4", "s5", "s6", "s2", "s1"]),
([4, 3.2, 2], [("s1", "s3"), ("s3", "s2"), ("s2", "s1")]),
)
# strict=True results in missing sample ids raising an error
self.assertRaises(
ValueError, get_adjacent_distances, dm_header, dm, ["s1", "s3", "s4", "s5", "s6", "s2", "s1"], strict=True
)
def rank_adjacent_unifrac(sid_data, dm_header, dm_data, map_data, time_field="WeeksSinceStart", line_color="blue"):
disturbed_weeks = [float(e[0]) for e in sid_data if e[2]]
if len(disturbed_weeks) < 1:
raise ValueError, "Must be some disturbance events."
adjacent_distances = get_adjacent_distances(dm_header, dm_data, [e[1] for e in sid_data])
distance_to_disturbance = []
for d, sample_ids in zip(adjacent_distances[0], adjacent_distances[1]):
distance_to_disturbance.append((d, map_data[sample_ids[1]]["SampleAntibioticDisturbance"]))
distance_to_disturbance.sort()
result = []
for i, dd in enumerate(distance_to_disturbance):
result.append((i, dd[1], dd[0]))
return result
def test_get_adjacent_distances(self):
""" extracting adjacent distances works as expected
"""
dm_str = ["\ts1\ts2\ts3", "s1\t0\t2\t4", "s2\t2\t0\t3.2",
"s3\t4\t3.2\t0"]
dm_header, dm = parse_distmat(dm_str)
# error cases: fewer than 2 valid sample ids
self.assertRaises(ValueError,
get_adjacent_distances,dm_header, dm,
[])
self.assertRaises(ValueError,
get_adjacent_distances,dm_header, dm,
['s1'])
self.assertRaises(ValueError,
get_adjacent_distances,dm_header, dm,
['s0','s1'])
self.assertRaises(ValueError,
get_adjacent_distances,dm_header, dm,
['s1','s4'])
# one pair of valid distances
self.assertEqual(get_adjacent_distances(dm_header, dm, ['s1','s2']),
([2],[('s1','s2')]))
self.assertEqual(get_adjacent_distances(dm_header, dm, ['s1','s1']),
([0],[('s1','s1')]))
self.assertEqual(get_adjacent_distances(dm_header, dm, ['s1','s3']),
([4],[('s1','s3')]))
self.assertEqual(get_adjacent_distances(dm_header, dm, ['s2','s3']),
([3.2],[('s2','s3')]))
# multiple valid distances
self.assertEqual(get_adjacent_distances(dm_header,
dm,
['s1','s2','s3']),
([2,3.2],[('s1','s2'),('s2','s3')]))
self.assertEqual(get_adjacent_distances(dm_header,
dm,
['s1','s3','s2','s1']),
([4,3.2,2],[('s1','s3'),('s3','s2'),('s2','s1')]))
# mixed valid and invalid distances ignores invalid distances
self.assertEqual(get_adjacent_distances(dm_header,
dm,
['s1','s3','s4','s5','s6','s2','s1']),
([4,3.2,2],[('s1','s3'),('s3','s2'),('s2','s1')]))
# strict=True results in missing sample ids raising an error
self.assertRaises(ValueError,get_adjacent_distances,
dm_header,
dm,
['s1','s3','s4','s5','s6','s2','s1'],
strict=True)
