def test_random_choice_with_one_true_element():
"""
Case: test random choice with zeros probabilities and one true element.
Expect: one element same times is returned.
"""
tests_number = 10_00
infimum = -1_000
supremum = 1_000
number_quantity = abs(infimum) + abs(supremum)
fast_random = FastRandomChoice()
numbers = list(range(infimum, supremum))
numbers_probabilities = [0] * number_quantity
random_index = random.randint(infimum, supremum)
numbers_probabilities[random_index] = 1
random_numbers = []
for _ in range(tests_number):
random_numbers.append(
fast_random.choice(seq=numbers, p=numbers_probabilities))
random_numbers_set = set(random_numbers)
assert len(random_numbers_set) == 1
def test_random_choice_with_big_range():
"""
Case: test random choice with a lot of elements.
Expect: random choice is returned.
"""
infimum = -10_000
supremum = 10_000
number_quantity = abs(infimum) + abs(supremum)
fast_random = FastRandomChoice()
numbers = list(range(infimum, supremum))
numbers_probabilities = [1 / number_quantity] * number_quantity
random_number = fast_random.choice(seq=numbers, p=numbers_probabilities)
assert infimum <= random_number <= supremum
def test_random_choice_with_empty_sequence():
"""
Case: test random choice with empty sequence.
Expect: cannot choose from an empty sequence error message.
"""
infimum = -10_000
supremum = 10_000
number_quantity = abs(infimum) + abs(supremum)
numbers = []
fast_random = FastRandomChoice()
numbers_probabilities = [0] * number_quantity
random_index = random.randint(infimum, supremum)
numbers_probabilities[random_index] = 1
with pytest.raises(IndexError):
fast_random.choice(seq=numbers, p=numbers_probabilities)
def test_random_choice_with_invalid_probability_sum():
"""
Case: with the sum of the probabilities less than one.
Expect: probabilities do not sum to 1 error message.
"""
infimum = -10_000
supremum = 10_000
number_quantity = abs(infimum) + abs(supremum)
fast_random = FastRandomChoice()
numbers = list(range(infimum, supremum))
numbers_probabilities = [0] * number_quantity
random_index = random.randint(infimum, supremum)
numbers_probabilities[random_index] = 0.5
with pytest.raises(ValueError):
fast_random.choice(seq=numbers, p=numbers_probabilities)
def test_random_choice_with_negative_probability():
"""
Case: test random choice with negative probability.
Expect: probabilities are not non-negative error message.
"""
infimum = -10_000
supremum = 10_000
number_quantity = abs(infimum) + abs(supremum)
fast_random = FastRandomChoice()
numbers = list(range(infimum, supremum))
numbers_probabilities = [0] * number_quantity
random_index = random.randint(infimum, supremum)
numbers_probabilities[random_index] = -1
with pytest.raises(ValueError):
fast_random.choice(seq=numbers, p=numbers_probabilities)
def test_random_choice_with_different_lengths_sequence_and_probabilities():
"""
Case: test random choice with different lengths sequence and probabilities.
Expect: `seq` and `p` must have same size error message.
"""
infimum = -10_000
supremum = 10_000
number_quantity = abs(infimum) + abs(supremum)
fast_random = FastRandomChoice()
numbers = list(range(infimum, supremum))
numbers_probabilities = [0] * (number_quantity - 1)
random_index = random.randint(infimum, supremum - 1)
numbers_probabilities[random_index] = 1
with pytest.raises(ValueError):
fast_random.choice(seq=numbers, p=numbers_probabilities)
def test_random_choice_collision_with_uniform_distribution():
"""
Case: test random choice collision number.
Expect: elements is returned.
"""
accuracy = 0.15
tests_number = 10_00
infimum = -1_000
supremum = 1_000
number_quantity = abs(infimum) + abs(supremum)
fast_random = FastRandomChoice()
numbers = list(range(infimum, supremum))
numbers_probabilities = [1 / number_quantity] * number_quantity
random_numbers = []
for _ in range(tests_number):
random_numbers.append(
fast_random.choice(seq=numbers, p=numbers_probabilities))
random_numbers_set = set(random_numbers)
error_range = len(random_numbers) - len(random_numbers_set)
assert error_range < accuracy * number_quantity
""" Provide constants for command line interface. """ from numpy import random from eos_name_generator.utils import FastRandomChoice PASSED_EXIT_FROM_COMMAND_CODE = 0 FAILED_EXIT_FROM_COMMAND_CODE = -1 INCORRECT_ENTERED_COMMAND_CODE = 2 NUMPY_RANDOM_PROVIDER = random FAST_RANDOM_CHOICE_PROVIDER = FastRandomChoice() NUMBERS_PROBABILITY = 0.1
""" Provide constants for BaseGenerator interface. """ from os.path import dirname from eos_name_generator.utils import FastRandomChoice EOS_NAME_LENGTH = 12 SEED_DATA_PATH = dirname(__file__) + '/' + 'random_generator/seed_data/nounlist.txt' NUMBERS_PROBABILITIES = 0.1 RANDOM_PROVIDER_INSTANCE = FastRandomChoice()