def test_noisy_sorted_sampler_sort_key_noise():
data_source = [2, 6, 10]
# `sort_key_noise` does not affect values 2, 6, 10
indexes = list(
NoisySortedSampler(data_source, get_noise=lambda e: e * 0.25))
for i, j in enumerate(indexes):
assert i == j
def test_noisy_sorted_sampler_sort_key_noise():
data_source = [[2], [6], [10]]
sort_key = lambda r: r[0]
# `sort_key_noise` does not affect values 2, 6, 10
indexes = list(NoisySortedSampler(data_source, sort_key, sort_key_noise=0.25))
for i, j in enumerate(indexes):
assert i == j
def test_noisy_sorted_sampler_sorted():
data_source = [[1], [2], [3], [4], [5], [6]]
sort_key = lambda r: r[0]
indexes = list(NoisySortedSampler(data_source, sort_key, sort_key_noise=0.0))
assert len(indexes) == len(data_source)
for i, j in enumerate(indexes):
assert i == j
def test_noisy_sorted_sampler():
data_source = [[1], [2], [3], [4], [5], [6]]
sort_key = lambda r: r[0]
indexes = list(NoisySortedSampler(data_source, sort_key=sort_key))
assert len(indexes) == len(data_source)
def test_noisy_sorted_sampler():
data_source = [1, 2, 3, 4, 5, 6]
indexes = list(NoisySortedSampler(data_source))
assert len(indexes) == len(data_source)
def test_pickleable():
data_source = [1, 2, 3, 4, 5, 6]
sampler = NoisySortedSampler(data_source)
pickle.dumps(sampler)
def test_noisy_sorted_sampler_sorted():
data_source = [1, 2, 3, 4, 5, 6]
indexes = list(NoisySortedSampler(data_source, get_noise=lambda e: 0.0))
assert len(indexes) == len(data_source)
for i, j in enumerate(indexes):
assert i == j
def test_pickleable():
data_source = [[1], [2], [3], [4], [5], [6]]
sampler = NoisySortedSampler(data_source)
pickle.dumps(sampler)