def test_weighted_auc1d():
# CAVE: In python the ranking databases are 0-based. The only difference a 1-based system has on the calc
# of the AUC is that in the latter the rank threshold would not be included. This has an infuence on the
# normalization factor max AUC but nothing else.
total_genes = 100
auc_rank_threshold = 8
ranking = np.asarray([2, 4, 6]) - 1 # The databases have a zero-based ranking system
weights = np.ones(len(ranking))
auc_max = 1.0 # Disable normalization.
assert 15.0 == weighted_auc1d(ranking, weights, auc_rank_threshold, auc_max)
def test_weighted_auc1d_batch():
# The assumption taken here is that for weights uniformely being set to 1.0, auc1d and
# weighted_auc1d should always have the same output.
N = 100000
total_genes = 100
for _ in range(N):
auc_rank_threshold = np.random.randint(2, high=total_genes)
n_genes = np.random.randint(20, high=total_genes)
ranking = np.random.randint(low=0, high=total_genes, size=n_genes)
weights = np.ones(n_genes)
auc_max = 1.0 # Disable normalization.
assert auc1d(ranking, auc_rank_threshold, auc_max) == weighted_auc1d(ranking, weights, auc_rank_threshold, auc_max)
def test_weighted_rcc2d_batch():
# The assumption taken here is that for weights uniformly being set to 1.0,
# auc1d and weighted_auc1d should always have the same output.
N = 100000
total_genes = 100
for _ in range(N):
# rccs[row_idx, :] = np.cumsum(np.bincount(curranking, weights=weights)[:rank_threshold])
# ValueError: could not broadcast input array from shape (89) into shape (97)
auc_rank_threshold = np.random.randint(2, high=total_genes)
n_genes = np.random.randint(20, high=total_genes)
ranking = np.random.randint(low=0, high=total_genes, size=n_genes)
rankings = ranking.reshape((1, n_genes))
rankings = np.append(rankings,
np.full(shape=(1, 1), fill_value=total_genes),
axis=1)
weights = np.ones(n_genes)
# Disable normalization.
auc_max = 1.0
assert rcc2d(rankings, np.insert(weights, len(weights), 0.0), total_genes)[:, :auc_rank_threshold].sum(axis=1) \
== weighted_auc1d(ranking, weights, auc_rank_threshold, auc_max)
