def test_fit_transform():
"""
Assert that fit_one and transform_one methods returns waited ouput.
"""
lda = LDA(n_components=2,
number_of_documents=60,
vocab_prune_interval=2,
maximum_size_vocabulary=3,
seed=42)
components_list = []
for document in DOC_SET:
tokens = {token: 1 for token in document.split(' ')}
lda = lda.fit_one(x=tokens)
components_list.append(lda.transform_one(x=tokens))
for index, component in enumerate(components_list):
assert np.array_equal(a1=list(component.values()),
a2=REFERENCE_FIT_ONE_PREDICT_ONE[index])
def test_fit_transform():
'''
Assert that fit_one and transform_one methods returns waited ouput.
'''
np.random.seed(42)
online_lda = LDA(
n_components=2,
number_of_documents=60,
vocab_prune_interval=2,
maximum_size_vocabulary=3,
)
components_list = []
for document in DOC_SET:
online_lda = online_lda.fit_one(x=document)
components_list.append(online_lda.transform_one(x=document))
for index, component in enumerate(components_list):
assert np.array_equal(a1=list(component.values()),
a2=REFERENCE_FIT_ONE_PREDICT_ONE[index])