def test_add_pos_and_negbinary_areas(self):
touched_nodes = set()
graph = obg.Graph({1: obg.Block(100)}, {})
pos_starts = np.array([0] + [i * 10 for i in range(9)])
pos_ends = np.array([100] + [(i + 2) * 10 for i in range(9)])
neg_starts = np.array([0] + [i * 10 + 5 for i in range(9)])
neg_ends = np.array([100] + [(i + 1) * 10 + 5 for i in range(9)])
bin_areas = []
for start, end in zip(pos_starts, pos_ends):
binary_connected_areas = BinaryContinousAreas(graph)
binary_connected_areas.add(1, start, end)
binary_connected_areas.sanitize()
bin_areas.append(binary_connected_areas)
for start, end in zip(neg_starts, neg_ends):
binary_connected_areas = BinaryContinousAreas(graph)
binary_connected_areas.add(-1, start, end)
binary_connected_areas.sanitize()
bin_areas.append(binary_connected_areas)
valued_areas = ValuedAreas(graph)
for bin_area in bin_areas:
valued_areas.add_binary_areas(bin_area,
touched_nodes=touched_nodes)
true_starts = np.sort(np.concatenate([pos_starts, 100 - neg_ends]))
true_ends = np.sort(np.concatenate([pos_ends, 100 - neg_starts]))
self.assertTrue(
np.all(np.sort(valued_areas.get_starts_array(1)) == true_starts))
self.assertTrue(
np.all(np.sort(valued_areas.get_ends_array(1)) == true_ends))
def graph():
return obg.Graph({i + 1: obg.Block(10)
for i in range(4)}, {
1: [2, 3],
2: [4],
3: [4]
})
def hierarchical_graph():
nodes = {i: obg.Block(i - 90) for i in range(100, 106)}
edges = {
100: [101, 102],
101: [105],
102: [103, 104],
103: [105],
104: [105]
}
return obg.Graph(nodes, edges)
def snp_graph():
nodes = {i: obg.Block((i % 2) + 1) for i in range(100, 106)}
edges = {
100: [101, 102],
101: [105],
102: [103, 104],
103: [105],
104: [105]
}
return obg.Graph(nodes, edges)
def graph():
nodes = {i: obg.Block(10) for i in range(10, 18)}
edges = {
10: [11],
11: [12, 13],
12: [14],
13: [14],
14: [15, 16, 17],
15: [16],
16: [17]
}
return obg.Graph(nodes, edges)
def test_add_binary_areas(self):
touched_nodes = set()
graph = obg.Graph({1: obg.Block(100)}, {})
starts = np.array([0] + [i * 10 for i in range(9)])
ends = np.array([100] + [(i + 2) * 10 for i in range(9)])
bin_areas = []
for start, end in zip(starts, ends):
binary_connected_areas = BinaryContinousAreas(graph)
binary_connected_areas.add(1, start, end)
binary_connected_areas.sanitize()
bin_areas.append(binary_connected_areas)
valued_areas = ValuedAreas(graph)
for bin_area in bin_areas:
valued_areas.add_binary_areas(bin_area,
touched_nodes=touched_nodes)
self.assertTrue(
np.all(valued_areas.get_starts_array(1) == np.sort(starts)))
self.assertTrue(
np.all(valued_areas.get_ends_array(1) == np.sort(ends)))
def test_get_p_value_track(self):
graph = one_block_graph
sample_intervals = [
Interval(1, 10, [1], graph),
Interval(5, 7, [1], graph)
]
control_intervals = [Interval(0, 10, [1], graph)]
sample = Pileup(graph)
sample.add_intervals(sample_intervals)
control = Pileup(graph)
control.add_intervals(control_intervals)
self._test_get_p_value_track(graph, sample, control)
# case 2
graph = offsetbasedgraph.Graph({1: Block(10), 2: Block(10)}, {1: [2]})
sample_intervals = [
Interval(1, 10, [1], graph),
Interval(5, 7, [1], graph),
Interval(4, 6, [1], graph),
Interval(0, 10, [2], graph),
Interval(1, 3, [2], graph)
]
control_intervals = [
Interval(0, 10, [1], graph),
Interval(0, 10, [2], graph),
Interval(5, 5, [1, 2], graph)
]
sample = Pileup(graph)
sample.add_intervals(sample_intervals)
control = Pileup(graph)
control.add_intervals(control_intervals)
self._test_get_p_value_track(graph, sample, control)
def graph():
nodes = [9, 10, 11, 12, 13, 14]
nodes = {i: obg.Block(10) for i in nodes}
edges = {9: [10], 10: [11, 12], 11: [13], 12: [13], 13: [14]}
return obg.Graph(nodes, edges)
def graph():
nodes = {i: obg.Block(5) for i in range(1, 5)}
edges = {1: [2, 3], 2: [4], 3: [4]}
return obg.Graph(nodes, edges)