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# built-in
from math import isclose
# external
import hypothesis
import pytest
# project
import textdistance
ALG = textdistance.entropy_ncd
@pytest.mark.parametrize('left, right, expected', [
('test', 'test', 1),
('aaa', 'bbb', 0),
('test', 'nani', 0.6),
])
def test_similarity(left, right, expected):
actual = ALG.similarity(left, right)
assert isclose(actual, expected)
@hypothesis.given(text=hypothesis.strategies.text(min_size=1))
def test_simmetry_compressor(text):
rev = ''.join(reversed(text))
assert isclose(ALG._compress(text), ALG._compress(rev))
@hypothesis.given(text=hypothesis.strategies.text(min_size=1))
def test_idempotency_compressor(text):
# I've modified idempotency to some kind of distributivity for constant.
# Now it indicates that compressor actually does compression.
assert ALG._get_size(text * 2) < ALG._get_size(text) * 2
@hypothesis.given(
left=hypothesis.strategies.text(min_size=1),
right=hypothesis.strategies.characters(),
)
def test_monotonicity_compressor(left, right):
if right in left:
return
assert ALG._get_size(left) <= ALG._get_size(left + right)
@hypothesis.given(
left1=hypothesis.strategies.text(min_size=1),
left2=hypothesis.strategies.text(min_size=1),
right=hypothesis.strategies.characters(),
)
def test_distributivity_compressor(left1, left2, right):
if right in left1 or right in left2:
return
actual1 = ALG._get_size(left1 + left2) + ALG._get_size(right)
actual2 = ALG._get_size(left1 + right) + ALG._get_size(left2 + right)
assert actual1 <= actual2
@hypothesis.given(text=hypothesis.strategies.text(min_size=1))
def test_normalization_range(text):
assert 0 <= ALG.normalized_similarity(text, text) <= 1
assert 0 <= ALG.normalized_distance(text, text) <= 1
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