def test_collect_Loactions(self):

# TODO: mock optics or use namedtuple

class OPTICS:

def __init__(self):

pass

mockClusters = [[1,7], [8,15],[16,20],[0,25],[32,40],

[30,49],[0,50],[85,98],[80,99],[0,99]

]

optics = OPTICS()

optics.cluster_hierarchy_ = mockClusters

r = util.build_tree(optics)

f = lambda cnodes: [cnode.cluster for cnode in cnodes]

actual1 = f(inferring.collect_locations(1, r))

actual2 = f(inferring.collect_locations(2, r))

actual3 = f(inferring.collect_locations(3, r))

actual4 = f(inferring.collect_locations(4, r))

actual = [actual1, actual2, actual3, actual4]

expected1 = [[0,50], [80, 99]]

expected2 = [[0,25], [30, 49], [85,98]]

expected3 = [[1,7], [8,15], [16,20], [32,40]]

expected4 = []

expected = [expected1, expected2, expected3, expected4]

for i, r, e in zip(range(len(actual)), actual, expected):

with self.subTest(i=i):

self.assertCountEqual(r, e, "i")

def test_build_matrix1(self):

c1 = modeling.CNode()

c2 = modeling.CNode()

c3 = modeling.CNode()

c4 = modeling.CNode()

c5 = modeling.CNode()

c6 = modeling.CNode()

def f(c, u, t):

c.visits[u] = t

visits = [

(c1,0,1), (c1,1,1), (c2,0,1), (c2,1,1), (c3,1,2),

(c3,2,1), (c4,2,2),(c4,3,1), (c5,3,1), (c5,4,1),

(c6,4,1)

]

for v in visits:

f(*v)

mock_locH = [i for i in range(5)]

clusters = [c1, c2, c3, c4, c5, c6]

actual = inferring.build_matrix(clusters, mock_locH)

expect = np.array([

[1,1,0,0,0,0],

[1,1,2,0,0,0],

[0,0,1,2,0,0],

[0,0,0,1,1,0],

[0,0,0,0,1,1]

])

np.testing.assert_equal(expect, actual)

def test_HIST_inference(self):

matrix = np.array([

[1,1,0,0,0,0],

[1,1,2,0,0,0],

[0,0,1,2,0,0],

[0,0,0,1,1,0],

[0,0,0,0,1,1]

])

actual_a, actual_b = inferring.HITS_inference(matrix, 3)

expect_a = np.array([228, 722, 609, 223, 53])

expect_b = np.array([374, 374, 791, 538, 108, 24])

np.testing.assert_equal(actual_a, expect_a)