def test_modularity_finetune_und():
x = load_sample(thres=.4)
seed = 94885236
_, q = bc.modularity.modularity_finetune_und(x, seed=seed)
assert np.allclose(q, .25879794)
fails = 0
for i in range(100):
_, q = bc.modularity.modularity_finetune_und(x)
try:
assert np.allclose(q, .25, atol=0.03)
except AssertionError:
if fails >= 5:
raise
else:
fails += 1
seed = 71040925
ci, oq = bc.modularity.modularity_louvain_und(x, seed=seed)
_, q = bc.modularity.modularity_finetune_und(x, ci=ci, seed=seed)
print(q, oq)
# assert np.allclose(q, .25892588)
assert np.allclose(q, .25856714)
assert q - oq >= -1e6
ci, oq = bc.modularity.modularity_und(x)
for i in range(100):
_, q = bc.modularity.modularity_finetune_und(x, ci=ci)
assert np.allclose(q, .25, atol=0.002)
assert q - oq >= -1e6
def test_shannon_entropy():
x = load_sample(thres=0.4)
ci = np.load(op.join(MAT_DIR, 'sample_partition.npy'))
hpos, _ = centrality.diversity_coef_sign(x, ci)
print(np.sum(hpos))
print(hpos[-1])
assert np.allclose(np.sum(hpos), 102.6402, atol=.01)
def test_breadthdist():
x = load_sample(thres=.02)
r, d = bc.distance.breadthdist(x)
d[np.where(np.isinf(d))] = 0
print(np.sum(r), np.sum(d))
assert np.sum(r) == 5804
assert np.sum(d) == 30762
def test_consensus():
x = load_sample(thres=.38)
ci = bc.clustering.consensus_und(x, .1, reps=50)
print(np.max(ci), 4)
assert np.max(ci) == 4
_, q = bc.modularity.modularity_und(x, kci=ci)
print(q, 0.27)
assert np.allclose(q, 0.27, atol=.01)
def test_distance_wei():
x = load_sample(thres=.02)
d, e = bc.distance.distance_wei(x)
d[np.where(np.isinf(d))] = 0
print(np.sum(d), np.sum(e))
assert np.allclose(np.sum(d), 155650.1, atol=.01)
assert np.sum(e) == 30570
def test_charpath():
x = load_sample(thres=.02)
d, e = bc.distance.distance_wei(x)
l, eff, ecc, radius, diameter = bc.distance.charpath(d)
assert np.any(np.isinf(d))
assert not np.isnan(radius)
assert not np.isnan(diameter)
def test_zi():
x = load_sample(thres=.4)
ci = np.load(op.join(MAT_DIR, 'sample_partition.npy'))
zi = np.load(op.join(MAT_DIR, 'sample_zi.npy'))
zi_ = centrality.module_degree_zscore(x, ci)
print(list(zip(zi, zi_)))
assert np.allclose(zi, zi_, atol=0.05)
def test_glob_eff_bin():
x = load_sample(thres=.4)
geff = bc.distance.efficiency_bin(x)
y = bc.utils.binarize(x)
geff2 = bc.distance.efficiency_bin(y)
print(geff, geff2, 0.6999)
assert np.allclose(geff, 0.6999, atol=1e-4)
assert np.allclose(geff2, 0.6999, atol=1e-4)
def test_loc_eff_bin():
x = load_sample(thres=.4)
leff = bc.distance.efficiency_bin(x, local=True)
y = bc.utils.binarize(x)
leff2 = bc.distance.efficiency_bin(y, local=True)
print(np.sum(leff), np.sum(leff2), 105.5111)
assert np.allclose(np.sum(leff), 105.5111, atol=0.1)
assert np.allclose(np.sum(leff2), 105.5111, atol=0.1)
def test_pc():
x = load_sample(thres=.4)
# ci,q = bc.modularity_und(x)
ci = np.load(op.join(MAT_DIR, 'sample_partition.npy'))
pc = np.load(op.join(MAT_DIR, 'sample_pc.npy'))
pc_ = centrality.participation_coef(x, ci)
print(list(zip(pc, pc_)))
assert np.allclose(pc, pc_, atol=0.02)
def test_gateway():
x = load_sample(thres=.1)
ci = np.load(op.join(MAT_DIR, 'sample_partition.npy'))
g_pos, _ = centrality.gateway_coef_sign(x, ci)
print(np.sum(g_pos), 43.4382)
assert np.allclose(np.sum(g_pos), 43.4382, atol=.001)
gpb, _ = centrality.gateway_coef_sign(x, ci, centrality_type='betweenness')
print(np.sum(gpb), 43.4026)
assert np.allclose(np.sum(gpb), 43.4026, atol=.001)
def test_reachdist():
x = load_sample(thres=.02)
r, d = bc.distance.reachdist(x)
d[np.where(np.isinf(d))] = 0
print(np.sum(r), np.sum(d))
assert np.sum(r) == 5804
assert np.sum(d) == 30762
bx = bc.utils.binarize(x, copy=False)
br, bd = bc.distance.reachdist(bx)
bd[np.where(np.isinf(bd))] = 0
print(np.sum(br), np.sum(bd))
assert np.sum(br) == 5804
assert np.sum(bd) == 30762
def test_modularity_louvain_und():
x = load_sample(thres=.4)
seed = 38429004
_, q = bc.modularity.modularity_louvain_und(x, seed=seed)
assert np.allclose(q, 0.25892588)
fails = 0
for i in range(100):
ci, q = bc.modularity.modularity_louvain_und(x)
try:
assert np.allclose(q, .25, atol=0.01)
except AssertionError:
if fails >= 5:
raise
else:
fails += 1
seed = 94885236
_, q = bc.modularity.modularity_finetune_und(x, seed=seed)
assert np.allclose(q, .25879794)
def test_community_louvain():
x = load_sample(thres=0.4)
seed = 39185
ci, q = bc.modularity.community_louvain(x, seed=seed)
print(q)
assert np.allclose(q, 0.2583, atol=0.015)
def test_transitivity_bu():
x = bc.utils.binarize(load_sample(thres=.17), copy=False)
t = bc.clustering.transitivity_bu(x)
print(t, 0.42763)
assert np.allclose(t, 0.42763107)
def test_cluscoef_bu():
x = bc.utils.binarize(load_sample(thres=.17), copy=False)
cc = bc.clustering.clustering_coef_bu(x)
print(np.sum(cc), 60.1016)
assert np.allclose(np.sum(cc), 60.10160458)
def test_strengths_und():
x = load_sample()
s = bc.degree.strengths_und(x)
assert np.allclose(np.sum(s), 38967.38702018)
def test_transitivity_wu():
x = load_sample(thres=.23)
t = bc.clustering.transitivity_wu(x)
print(t, 1.32927829)
assert np.allclose(t, 1.32927829)
def test_cluscoef_wu():
x = load_sample(thres=.23)
cc = bc.clustering.clustering_coef_wu(x)
print(np.sum(cc), 187.95878414)
assert np.allclose(np.sum(cc), 187.95878414)
def test_threshold_absolute():
x = load_sample()
x = bc.utils.threshold_absolute(x, 2.1)
assert np.allclose(np.sum(x), 13280.17768104)
def test_glob_eff():
x = load_sample(thres=.4)
geff = bc.distance.efficiency_wei(x)
print(geff, 1.8784)
assert np.allclose(geff, 1.8784, atol=1e-4)
def test_distance_bin():
x = bc.utils.binarize(load_sample(thres=.02), copy=False)
d = bc.distance.distance_bin(x)
d[np.where(np.isinf(d))] = 0
print(np.sum(d))
assert np.sum(d) == 30506 # deals with diagonals differently
def test_degrees_und():
x = load_sample()
s = bc.degree.degrees_und(bc.utils.threshold_proportional(x, .26))
assert np.sum(s) == 4916
def test_invert():
x = load_sample()
s = bc.utils.invert(bc.utils.threshold_proportional(x, .13))
assert np.allclose(np.sum(s), 790.43107587)
def test_normalize():
x = load_sample()
s = bc.utils.normalize(bc.utils.threshold_proportional(x, .79))
assert np.allclose(np.sum(s), 3327.96285964)
def test_binarize():
x = load_sample()
s = bc.utils.binarize(bc.utils.threshold_proportional(x, .41))
assert np.sum(s) == 7752
def test_link_communities():
x = load_sample(thres=0.4)
M = bc.modularity.link_communities(x)
assert np.max(M) == 1
def test_modularity_und():
x = load_sample(thres=.4)
_, q = bc.modularity.modularity_und(x)
assert np.allclose(q, 0.24097717)
def test_threshold_proportional():
x = load_sample()
x = bc.utils.threshold_proportional(x, .5, copy=True)
assert np.allclose(np.sum(x), 22548.51206965)
def test_threshold_proportional_nocopy():
x = load_sample()
bc.utils.threshold_proportional(x, .3, copy=False)
assert np.allclose(np.sum(x), 15253.75425406)
