def _get_weighted_choices(rng, sub_rate, indel_rate):
choices_by_nt = {}
for src_nt in "ACGT":
choices = "ACGTID"
probs = [sub_rate / 4] * 4 # ACGT
probs += [indel_rate / 2] * 2 # ID
probs[choices.index(src_nt)] = 1 - sum(probs) + sub_rate / 4
choices_by_nt[src_nt] = weighted_sampling(choices, probs, rng)
return choices_by_nt
def _get_weighted_choices(rng, sub_rate, indel_rate):
choices_by_nt = {}
for src_nt in "ACGT":
choices = "ACGTID"
probs = [sub_rate / 4] * 4 # ACGT
probs += [indel_rate / 2] * 2 # ID
probs[choices.index(src_nt)] = 1 - sum(probs) + sub_rate / 4
choices_by_nt[src_nt] = weighted_sampling(choices, probs, rng)
return choices_by_nt
def test_weighted_sampling__non_numerical_weight_raises_type_error():
choices = range(3)
weights = [1, "foo", 3]
iterator = sampling.weighted_sampling(choices, weights)
assert_raises(TypeError, iterator.next)
def test_weighted_sampling__zero_weight_raises_value_error():
choices = range(3)
weights = [1, 0, 3]
iterator = sampling.weighted_sampling(choices, weights)
assert_raises(ValueError, iterator.next)
def _do_different_length_input_raises(choices, weights):
iterator = sampling.weighted_sampling(choices, weights)
assert_raises(ValueError, iterator.next)
def _do_empty_input_raises(choices, weights):
iterator = sampling.weighted_sampling(choices, weights)
assert_raises(ValueError, iterator.next)
def _do_select_by_weight(value, expectation):
choices = "abc"
weights = (1, 2, 3)
rng = flexmock(random=lambda: value)
iterator = sampling.weighted_sampling(choices, weights, rng)
assert_equal(iterator.next(), expectation)
def test_weighted_sampling__non_numerical_weight_raises_type_error():
choices = range(3)
weights = [1, "foo", 3]
iterator = sampling.weighted_sampling(choices, weights)
assert_raises(TypeError, iterator.next)
def test_weighted_sampling__zero_weight_raises_value_error():
choices = range(3)
weights = [1, 0, 3]
iterator = sampling.weighted_sampling(choices, weights)
assert_raises(ValueError, iterator.next)
def _do_different_length_input_raises(choices, weights):
iterator = sampling.weighted_sampling(choices, weights)
assert_raises(ValueError, iterator.next)
def _do_empty_input_raises(choices, weights):
iterator = sampling.weighted_sampling(choices, weights)
assert_raises(ValueError, iterator.next)
def _do_select_by_weight(value, expectation):
choices = "abc"
weights = (1, 2, 3)
rng = flexmock(random = lambda: value)
iterator = sampling.weighted_sampling(choices, weights, rng)
assert_equal(iterator.next(), expectation)
