Example #1
0
def test_normalize_integer():
    for dtype in ['int', 'int8', 'int16', 'int32', 'int64',
                  'uint8', 'uint16', 'uint32', 'uint64']:
        a = Integer(2, 30, transform="normalize", dtype=dtype)
        for X in range(2, 31):
            X_orig = a.inverse_transform(a.transform(X))
            assert_array_equal(X_orig, X)
    for dtype in [int, np.int8, np.int16, np.int32, np.int64,
                  np.uint8, np.uint16, np.uint32, np.uint64]:
        a = Integer(2, 30, transform="normalize", dtype=dtype)
        for X in range(2, 31):
            X_orig = a.inverse_transform(a.transform(X))
            assert_array_equal(X_orig, X)
            assert isinstance(X_orig, dtype)
Example #2
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def test_integer():
    a = Integer(1, 10)
    for i in range(50):
        yield (check_limits, a.rvs(random_state=i), 1, 11)
    random_values = a.rvs(random_state=0, n_samples=10)
    assert_array_equal(random_values.shape, (10))
    assert_array_equal(a.transform(random_values), random_values)
    assert_array_equal(a.inverse_transform(random_values), random_values)
Example #3
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def test_integer():
    a = Integer(1, 10)
    for i in range(50):
        yield (check_limits, a.rvs(random_state=i), 1, 11)
    random_values = a.rvs(random_state=0, n_samples=10)
    assert_array_equal(random_values.shape, (10))
    assert_array_equal(a.transform(random_values), random_values)
    assert_array_equal(a.inverse_transform(random_values), random_values)
Example #4
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def test_integer():
    a = Integer(1, 10)
    for i in range(50):
        r = a.rvs(random_state=i)
        assert_less_equal(1, r)
        assert_greater_equal(11, r)
        assert_true(r in a)

    random_values = a.rvs(random_state=0, n_samples=10)
    assert_array_equal(random_values.shape, (10))
    assert_array_equal(a.transform(random_values), random_values)
    assert_array_equal(a.inverse_transform(random_values), random_values)
Example #5
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def test_integer():
    a = Integer(1, 10)
    for i in range(50):
        r = a.rvs(random_state=i)
        assert 1 <= r
        assert 11 >= r
        assert r in a

    random_values = a.rvs(random_state=0, n_samples=10)
    assert_array_equal(random_values.shape, (10))
    assert_array_equal(a.transform(random_values), random_values)
    assert_array_equal(a.inverse_transform(random_values), random_values)
Example #6
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def test_normalize_integer():
    a = Integer(2, 30, transform="normalize")
    for i in range(50):
        check_limits(a.rvs(random_state=i), 2, 30)
    assert_array_equal(a.transformed_bounds, (0, 1))

    X = rng.randint(2, 31, dtype=np.int64)
    # Check transformed values are in [0, 1]
    assert np.all(a.transform(X) <= np.ones_like(X))
    assert np.all(np.zeros_like(X) <= a.transform(X))

    # Check inverse transform
    X_orig = a.inverse_transform(a.transform(X))
    assert isinstance(X_orig, np.int64)
    assert_array_equal(X_orig, X)

    a = Integer(2, 30, transform="normalize", dtype=int)
    X = rng.randint(2, 31, dtype=int)
    # Check inverse transform
    X_orig = a.inverse_transform(a.transform(X))
    assert isinstance(X_orig, int)

    a = Integer(2, 30, transform="normalize", dtype='int')
    X = rng.randint(2, 31, dtype=int)
    # Check inverse transform
    X_orig = a.inverse_transform(a.transform(X))
    assert isinstance(X_orig, int)

    a = Integer(2,
                30,
                prior="log-uniform",
                base=2,
                transform="normalize",
                dtype=int)
    for i in range(50):
        check_limits(a.rvs(random_state=i), 2, 30)
    assert_array_equal(a.transformed_bounds, (0, 1))

    X = rng.randint(2, 31, dtype=int)
    # Check transformed values are in [0, 1]
    assert np.all(a.transform(X) <= np.ones_like(X))
    assert np.all(np.zeros_like(X) <= a.transform(X))

    # Check inverse transform
    X_orig = a.inverse_transform(a.transform(X))
    assert isinstance(X_orig, int)
    assert_array_equal(X_orig, X)