Hypothesis Module Tests

TestChiSquareParamObservedNums

Description: Test the observed_numbers parameter.

test_none

  • Description: Test the observed_numbers parameter with None.
  • Code Snippet:
def test_none(self, hypothesis):
        """ Test the `observed_numbers` parameter with None."""

        with pytest.raises(RandomGenTypeError):
            hypothesis.set_observed_numbers(None)
            hypothesis.validate_observed_numbers()

test_empty

  • Description: Test the observed_numbers parameter with an empty list.
  • Code Snippet:
def test_empty(self, hypothesis):
        """ Test the `observed_numbers` parameter with an empty list."""

        with pytest.raises(RandomGenEmptyError):
            hypothesis.set_observed_numbers([])
            hypothesis.validate_observed_numbers()

test_int

  • Description: Test the observed_numbers parameter with an integer.
  • Code Snippet:
def test_int(self, hypothesis):
        """ Test the `observed_numbers` parameter with an integer."""

        with pytest.raises(RandomGenTypeError):
            hypothesis.set_observed_numbers(123)
            hypothesis.validate_observed_numbers()

test_int_list

  • Description: Test the observed_numbers parameter with an integer list.
  • Code Snippet:
def test_int_list(self, hypothesis):
        """ Test the `observed_numbers` parameter with an integer list."""

        hypothesis.set_observed_numbers([-1, 0, 1, 2, 3])
        hypothesis.validate_observed_numbers()
        assert hypothesis.numbers == [-1, 0, 1, 2, 3]

test_int_tuple

  • Description: Test the observed_numbers parameter with an integer tuple.
  • Code Snippet:
def test_int_tuple(self, hypothesis):
        """ Test the `observed_numbers` parameter with an integer tuple."""

        hypothesis.set_observed_numbers((-1, 0, 1, 2, 3))
        hypothesis.validate_observed_numbers()
        assert hypothesis.numbers == (-1, 0, 1, 2, 3)

test_int_set

  • Description: Test the observed_numbers parameter with an integer set.
  • Code Snippet:
def test_int_set(self, hypothesis):
        """ Test the `observed_numbers` parameter with an integer set."""

        hypothesis.set_observed_numbers({-1, 0, 1, 2, 3})
        hypothesis.validate_observed_numbers()
        assert hypothesis.numbers == {-1, 0, 1, 2, 3}

test_float

  • Description: Test the observed_numbers parameter with a float.
  • Code Snippet:
def test_float(self, hypothesis):
        """ Test the `observed_numbers` parameter with a float."""

        with pytest.raises(RandomGenTypeError):
            hypothesis.set_observed_numbers(123.45)
            hypothesis.validate_observed_numbers()

test_float_list

  • Description: Test the observed_numbers parameter with a float list.
  • Code Snippet:
def test_float_list(self, hypothesis):
        """ Test the `observed_numbers` parameter with a float list."""

        hypothesis.set_observed_numbers([-1.0, 0.0, 1.0, 2.0, 3.0])
        hypothesis.validate_observed_numbers()
        assert hypothesis.numbers == [-1.0, 0.0, 1.0, 2.0, 3.0]

test_float_tuple

  • Description: Test the observed_numbers parameter with a float tuple.
  • Code Snippet:
def test_float_tuple(self, hypothesis):
        """ Test the `observed_numbers` parameter with a float tuple."""

        hypothesis.set_observed_numbers((-1.0, 0.0, 1.0, 2.0, 3.0))
        hypothesis.validate_observed_numbers()
        assert hypothesis.numbers == (-1.0, 0.0, 1.0, 2.0, 3.0)

test_float_set

  • Description: Test the observed_numbers parameter with a float set.
  • Code Snippet:
def test_float_set(self, hypothesis):
        """ Test the `observed_numbers` parameter with a float set."""

        hypothesis.set_observed_numbers({-1.0, 0.0, 1.0, 2.0, 3.0})
        hypothesis.validate_observed_numbers()
        assert hypothesis.numbers == {-1.0, 0.0, 1.0, 2.0, 3.0}

test_string

  • Description: Test the observed_numbers parameter with a string.
  • Code Snippet:
def test_string(self, hypothesis):
        """ Test the `observed_numbers` parameter with a string."""

        with pytest.raises(RandomGenTypeError):
            hypothesis.set_observed_numbers("123")
            hypothesis.validate_observed_numbers()

test_string_list

  • Description: Test the observed_numbers parameter with a string list.
  • Code Snippet:
def test_string_list(self, hypothesis):
        """ Test the `observed_numbers` parameter with a string list."""

        with pytest.raises(RandomGenTypeError):
            hypothesis.set_observed_numbers(["-1", "0", "1", "2", "3"])
            hypothesis.validate_observed_numbers()

test_dict

  • Description: Test the observed_numbers parameter with a dictionary.
  • Code Snippet:
def test_dict(self, hypothesis):
        """ Test the `observed_numbers` parameter with a dictionary."""

        with pytest.raises(RandomGenTypeError):
            hypothesis.set_observed_numbers({-1: 1, 0: 1, 1: 1, 2: 1, 3: 1})
            hypothesis.validate_observed_numbers()

test_mixed_types

  • Description: Test the observed_numbers parameter with mixed types.
  • Code Snippet:
def test_mixed_types(self, hypothesis):
        """ Test the `observed_numbers` parameter with mixed types."""

        with pytest.raises(RandomGenTypeError):
            hypothesis.set_observed_numbers([-1, 0.0, "1", 2.0, 3])
            hypothesis.validate_observed_numbers()

test_mixed_numbers

  • Description: Test the observed_numbers parameter with mixed numbers.
  • Code Snippet:
hypothesis.set_observed_numbers([-1, 0, 1, 2.0, 3])
hypothesis.validate_observed_numbers()
assert hypothesis.numbers == [-1, 0, 1, 2.0, 3]

TestChiSquareParamProbabilities

Description: Test the expected_probabilities parameter.

test_none

  • Description: Test the expected_probabilities parameter with None.
  • Code Snippet:
with pytest.raises(RandomGenTypeError):
    hypothesis.set_observed_numbers(None)
    hypothesis.validate_observed_numbers()

test_empty

  • Description: Test the expected_probabilities parameter with an empty list.
  • Code Snippet:
with pytest.raises(RandomGenEmptyError):
    hypothesis.set_observed_numbers([])
    hypothesis.validate_observed_numbers()

test_int

  • Description: Test the expected_probabilities parameter with an integer.
  • Code Snippet:
with pytest.raises(RandomGenTypeError):
    hypothesis.set_observed_numbers(123)
    hypothesis.validate_observed_numbers()

test_int_list

  • Description: Test the expected_probabilities parameter with an integer list.
  • Code Snippet:
hypothesis.set_observed_numbers([-1, 0, 1, 2, 3])
hypothesis.validate_observed_numbers()
assert hypothesis.numbers == [-1, 0, 1, 2, 3]

test_int_tuple

  • Description: Test the expected_probabilities parameter with an integer tuple.
  • Code Snippet:
hypothesis.set_observed_numbers((-1, 0, 1, 2, 3))
hypothesis.validate_observed_numbers()
assert hypothesis.numbers == (-1, 0, 1, 2, 3)

test_int_set

  • Description: Test the expected_probabilities parameter with an integer set.
  • Code Snippet:
hypothesis.set_observed_numbers({-1, 0, 1, 2, 3})
hypothesis.validate_observed_numbers()
assert hypothesis.numbers == {-1, 0, 1, 2, 3}

test_float

  • Description: Test the expected_probabilities parameter with a float.
  • Code Snippet:
with pytest.raises(RandomGenTypeError):
    hypothesis.set_observed_numbers(123.45)
    hypothesis.validate_observed_numbers()

test_float_list

  • Description: Test the expected_probabilities parameter with a float list.
  • Code Snippet:
hypothesis.set_observed_numbers([-1.0, 0.0, 1.0, 2.0, 3.0])
hypothesis.validate_observed_numbers()
assert hypothesis.numbers == [-1.0, 0.0, 1.0, 2.0, 3.0]

test_float_tuple

  • Description: Test the expected_probabilities parameter with a float tuple.
  • Code Snippet:
hypothesis.set_observed_numbers((-1.0, 0.0, 1.0, 2.0, 3.0))
hypothesis.validate_observed_numbers()
assert hypothesis.numbers == (-1.0, 0.0, 1.0, 2.0, 3.0)

test_float_set

  • Description: Test the expected_probabilities parameter with a float set.
  • Code Snippet:
hypothesis.set_observed_numbers({-1.0, 0.0, 1.0, 2.0, 3.0})
hypothesis.validate_observed_numbers()
assert hypothesis.numbers == {-1.0, 0.0, 1.0, 2.0, 3.0}

test_string

  • Description: Test the expected_probabilities parameter with a string.
  • Code Snippet:
with pytest.raises(RandomGenTypeError):
    hypothesis.set_observed_numbers("123")
    hypothesis.validate_observed_numbers()

test_string_list

  • Description: Test the expected_probabilities parameter with a string list.
  • Code Snippet:
with pytest.raises(RandomGenTypeError):
    hypothesis.set_observed_numbers(["-1", "0", "1", "2", "3"])
    hypothesis.validate_observed_numbers()

test_dict

  • Description: Test the expected_probabilities parameter with a dictionary.
  • Code Snippet:
with pytest.raises(RandomGenTypeError):
    hypothesis.set_observed_numbers({-1: 1, 0: 1, 1: 1, 2: 1, 3: 1})
    hypothesis.validate_observed_numbers()

test_mixed_types

  • Description: Test the expected_probabilities parameter with mixed types.
  • Code Snippet:
With pytest.raises(RandomGenTypeError):
    hypothesis.set_observed_numbers([-1, 0.0, "1", 2.0, 3])
    hypothesis.validate_observed_numbers()

test_mixed_numbers

  • Description: Test the expected_probabilities parameter with mixed numbers.
  • Code Snippet:
hypothesis.set_observed_numbers([-1, 0, 1, 2.0, 3])
hypothesis.validate_observed_numbers()
assert hypothesis.numbers == [-1, 0, 1, 2.0, 3]

TestChiSquareFunctional

Description: Test the functional aspects of the ChiSquareTest class.

test_chi_square_pass

  • Description: Test the ChiSquareTest class with a passing test.
  • Code Snippet:
(
    hypothesis
    .set_observed_numbers([1, 1, 1, 2, 2, 2])
    .set_expected_probabilities([0.5, 0.5])
    .calc()
)

assert hypothesis.is_null() is True

test_chi_square_fail

  • Description: Test the ChiSquareTest class with a failing test.
  • Code Snippet:
(
    hypothesis
    .set_observed_numbers([1, 1, 1, 2, 2, 2])
    .set_expected_probabilities([0.5, 0.5])
    .calc()
)

assert hypothesis.is_null() is True

def test_chi_square_fail(self, hypothesis):
""" Test the ChiSquareTest class with a failing test."""

(
    hypothesis
    .set_observed_numbers([1, 1, 1, 2, 2, 2])
    .set_expected_probabilities([0.1, 0.9])
    .calc()
)

assert hypothesis.is_null() is False