def test_proportions():
a_dense = np.ones((100, 100))
a_sparse = sparse.csr_matrix(a_dense)
prop_dense = top_proportions(a_dense, 100)
assert (prop_dense[:, -1] == 1).all()
assert np.array_equal(np.sort(prop_dense, axis=1), prop_dense)
assert np.apply_along_axis(lambda x: len(np.unique(x)) == 1, 0,
prop_dense).all()
assert (prop_dense[:, 49] == .5).all()
prop_sparse = top_proportions(a_sparse, 100)
assert (prop_sparse[:, -1] == 1).all()
assert np.array_equal(np.sort(prop_sparse, axis=1), prop_sparse)
assert np.apply_along_axis(lambda x: len(np.unique(x)) == 1, 0,
prop_sparse).all()
assert (prop_sparse[:, 49] == .5).all()
def test_top_segments_dense():
a = np.ones((300, 100))
seg = top_segment_proportions(a, [50, 100])
assert (seg[:, 0] == .5).all()
assert (seg[:, 1] == 1.).all()
segfull = top_segment_proportions(a, np.arange(100) + 1)
propfull = top_proportions(a, 100)
assert (segfull == propfull).all()
def test_top_segments(cls):
a = cls(np.ones((300, 100)))
seg = top_segment_proportions(a, [50, 100])
assert (seg[:, 0] == 0.5).all()
assert (seg[:, 1] == 1.0).all()
segfull = top_segment_proportions(a, np.arange(100) + 1)
propfull = top_proportions(a, 100)
assert (segfull == propfull).all()
def test_top_segments_sparse():
a_dense = np.ones((300, 100))
for fmt in [sparse.csr_matrix, sparse.csc_matrix, sparse.coo_matrix]:
a = fmt(a_dense)
seg = top_segment_proportions(a, [50, 100])
assert (seg[:, 0] == .5).all()
assert (seg[:, 1] == 1.).all()
segfull = top_segment_proportions(a, np.arange(100) + 1)
propfull = top_proportions(a, 100)
assert (segfull == propfull).all()
def test_segments_binary():
a = np.concatenate([np.zeros((300, 50)), np.ones((300, 50))], 1)
a = np.apply_along_axis(np.random.permutation, 1, a)
seg = top_segment_proportions(a, [25, 50, 100])
assert (seg[:, 0] == .5).all()
assert (top_segment_proportions(a, [25]) == .5).all()
assert (seg[:, 1] == 1.).all()
assert (seg[:, 2] == 1.).all()
segfull = top_segment_proportions(a, np.arange(100) + 1)
propfull = top_proportions(a, 100)
assert (segfull == propfull).all()
def test_proportions(a):
prop = top_proportions(a, 100)
assert (prop[:, -1] == 1).all()
assert np.array_equal(np.sort(prop, axis=1), prop)
assert np.apply_along_axis(lambda x: len(np.unique(x)) == 1, 0, prop).all()
assert (prop[:, 49] == 0.5).all()