def test_detect_rare_samples_wrong_args(self):
rsd = knn.RareSampleDetection(self.tsdm)
# Invalid parameters
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(0, 1, 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, 0, 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, 1, 0)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, 1, 0.5)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(0.5, 1, 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, -0.1, 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, 1, 1, 0.5)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(self.tsdm._x.shape[0], 1, 1, 1)
# Parameters of different length
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples([1, 2], 1, 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, [1, 2], 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, 1, [1, 2])
def test_no_pdist_detect_rare_samples_wrong_args(self):
tsdm = eda.SampleDistanceMatrix(
[[0, 0], [1, 1], [200, 200], [200, 200], [200, 200], [100, 100],
[101, 101], [99, 99], [100, 100], [102, 102]],
metric="euclidean",
use_pdist=False)
rsd = knn.RareSampleDetection(tsdm)
# Invalid parameters
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(0, 1, 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, 0, 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, 1, 0)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, 1, 0.5)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(0.5, 1, 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, -0.1, 1)
# Parameters of different length
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples([1, 2], 1, 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, [1, 2], 1)
with pytest.raises(ValueError) as excinfo:
rsd.detect_rare_samples(1, 1, [1, 2])
def test_detect_rare_samples_empty_subset(self):
rsd = knn.RareSampleDetection(self.tsdm)
resl = rsd.detect_rare_samples(1, 10, 5)
resl2 = rsd.detect_rare_samples([1], [10], 5)
# scalar and list params should have the same results
assert resl == resl2
# result lut should be the same length
assert len(rsd._res_lut) == 1
assert rsd._res_lut[(1, 10, 5)][1][-1] == resl[0]
def test_detect_rare_samples_single_run(self):
tsdm = eda.SampleDistanceMatrix(
[[0, 0], [1, 1], [200, 200], [101, 101], [99, 99], [100, 100],
[102, 102]],
metric="euclidean")
rsd = knn.RareSampleDetection(tsdm)
resl = rsd.detect_rare_samples(1, 0.1, 1)
assert resl[0] == []
resl2 = rsd.detect_rare_samples(1, 0.1, 5)
assert resl2[0] == []
def test_detect_rare_samples_par(self):
rsd = knn.RareSampleDetection(self.tsdm)
d = rsd._sdm._d.copy()
resl = rsd.detect_rare_samples([3, 4, 5], [10] * 3, [5, 6, 7], 3)
assert resl == [list(range(5, 10)), list(range(5, 10)), []]
assert len(rsd._res_lut) == 3
assert rsd._res_lut[(3, 10, 5)][1][-1] == resl[0]
assert rsd._res_lut[(4, 10, 6)][1][-1] == resl[1]
assert rsd._res_lut[(5, 10, 7)][1][-1] == resl[2]
# d should not be changed
np.testing.assert_equal(rsd._sdm._d, d)
def test_hnsw_detect_rare_samples_single_run(self):
tsdm = eda.SampleDistanceMatrix(
[[0.00001, 0.00001], [1, 1], [200, 200], [101, 101], [99, 99],
[100, 100], [102, 102]],
metric="euclidean",
use_pdist=False)
rsd = knn.RareSampleDetection(tsdm)
res = rsd._no_pdist_rare_s_detect(1, 0.1, 1)
resl = rsd.detect_rare_samples(1, 0.1, 1, use_pca=True, use_hnsw=True)
assert resl[0] == []
resl2 = rsd.detect_rare_samples(1, 0.1, 5, use_pca=True, use_hnsw=True)
assert resl2[0] == []
def test_no_pdist_detect_rare_samples_par(self):
tsdm = eda.SampleDistanceMatrix(
[[0, 0], [1, 1], [200, 200], [200, 200], [200, 200], [100, 100],
[101, 101], [99, 99], [100, 100], [102, 102]],
metric="euclidean",
use_pdist=False)
rsd = knn.RareSampleDetection(tsdm)
resl = rsd.detect_rare_samples([3, 4, 5], [10] * 3, [5, 6, 7], 3)
assert resl == [list(range(5, 10)), list(range(5, 10)), []]
assert len(rsd._res_lut) == 3
assert rsd._res_lut[(3, 10, 5)][1][-1] == resl[0]
assert rsd._res_lut[(4, 10, 6)][1][-1] == resl[1]
assert rsd._res_lut[(5, 10, 7)][1][-1] == resl[2]
def test_no_pdist_detect_rare_samples_empty_subset(self):
tsdm = eda.SampleDistanceMatrix(
[[0, 0], [1, 1], [200, 200], [200, 200], [200, 200], [100, 100],
[101, 101], [99, 99], [100, 100], [102, 102]],
metric="euclidean",
use_pdist=False)
rsd = knn.RareSampleDetection(tsdm)
resl = rsd.detect_rare_samples(1, 10, 5)
resl2 = rsd.detect_rare_samples([1], [10], 5)
# scalar and list params should have the same results
assert resl == resl2
# result lut should be the same length
assert len(rsd._res_lut) == 1
assert rsd._res_lut[(1, 10, 5)][1][-1] == resl[0]