def test_gini_simpson_diversity():
"""
USED FOR RESEARCH PURPOSES ONLY
"""
# just run for now to check against unexpectedly thrown errors
for counts, probs in mock.mock_species_data():
diversity.gini_simpson_diversity(counts)
def test_shannon_diversity():
"""
USED FOR RESEARCH PURPOSES ONLY
"""
# test against scipy entropy
for counts, probs in mock.mock_species_data():
assert abs(entropy(probs) - diversity.shannon_diversity(probs)) < 0.0000000001
def test_raos_quadratic_diversity():
"""
USED FOR RESEARCH PURPOSES ONLY
"""
# just run for now to check against unexpectedly thrown errors
for counts, probs in mock.mock_species_data():
mock_matrix = np.full((len(counts), len(counts)), 1)
diversity.raos_quadratic_diversity(counts, mock_matrix)
def test_hill_diversity():
# test hill diversity against scipy entropy
for counts, probs in mock.mock_species_data():
# check hill q=1 - this can be tested against scipy because hill q=1 is exponential of entropy
assert np.allclose(diversity.hill_diversity(counts, q=1), np.exp(entropy(probs)), atol=0.001, rtol=0)
# check that hill q<1 and q>1 is reasonably close to scipy entropy
# (different internal computation)
assert np.allclose(diversity.hill_diversity(counts, 0.99999999), np.exp(entropy(probs)), atol=0.001, rtol=0)
assert np.allclose(diversity.hill_diversity(counts, 1.00000001), np.exp(entropy(probs)), atol=0.001, rtol=0)
# check for malformed q
with pytest.raises(ValueError):
diversity.hill_diversity(counts, q=-1)
def test_hill_diversity_pairwise_matrix_wt():
for counts, probs in mock.mock_species_data():
non_matrix = np.full((len(counts), len(counts)), 1)
for q in [0, 1, 2]:
# what to test against? For now, check successful run
diversity.hill_diversity_pairwise_matrix_wt(counts, non_matrix, q)
# check for malformed signatures
with pytest.raises(ValueError):
diversity.hill_diversity_pairwise_matrix_wt(counts[:-1], non_matrix, q=1)
with pytest.raises(ValueError):
diversity.hill_diversity_pairwise_matrix_wt(counts, non_matrix[:-1], q=1)
with pytest.raises(ValueError):
diversity.hill_diversity_pairwise_matrix_wt(counts, non_matrix[:, :-1], q=1)
with pytest.raises(ValueError):
diversity.hill_diversity_pairwise_matrix_wt(counts, non_matrix, q=-1)
def test_hill_diversity_pairwise_distance_wt():
for counts, probs in mock.mock_species_data():
non_weights = np.full(len(counts), 1)
non_beta = -0
for q in [0, 1, 2]:
# what to test against? For now, check successful run
diversity.hill_diversity_pairwise_distance_wt(counts, non_weights, q, non_beta)
# check for malformed signatures
with pytest.raises(ValueError):
diversity.hill_diversity_pairwise_distance_wt(counts[:-1], non_weights, q=1, beta=0.005)
with pytest.raises(ValueError):
diversity.hill_diversity_pairwise_distance_wt(counts, non_weights[:-1], q=1, beta=0.005)
with pytest.raises(ValueError):
diversity.hill_diversity_pairwise_distance_wt(counts, non_weights, q=1, beta=-0.005)
with pytest.raises(ValueError):
diversity.hill_diversity_pairwise_distance_wt(counts, non_weights, q=-1, beta=0.005)
def test_hill_diversity_branch_distance_wt():
# test against hill diversity by setting all weights = 1
for counts, probs in mock.mock_species_data():
non_weights = np.full(len(counts), 1)
non_beta = -0
for q in [0, 1, 2]:
assert np.allclose(diversity.hill_diversity(counts, q),
diversity.hill_diversity_branch_distance_wt(counts, non_weights, q, non_beta),
atol=0.001, rtol=0)
# check for malformed signatures
with pytest.raises(ValueError):
diversity.hill_diversity_branch_distance_wt(counts[:-1], non_weights, q=1, beta=0.005)
with pytest.raises(ValueError):
diversity.hill_diversity_branch_distance_wt(counts, non_weights[:-1], q=1, beta=0.005)
with pytest.raises(ValueError):
diversity.hill_diversity_branch_distance_wt(counts, non_weights, q=1, beta=-0.005)
with pytest.raises(ValueError):
diversity.hill_diversity_branch_distance_wt(counts, non_weights, q=-1, beta=0.005)
def test_mock_species_data():
for counts, probs in mock.mock_species_data():
assert np.allclose(counts / counts.sum(), probs, atol=0.001, rtol=0)
assert round(probs.sum(), 8) == 1