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find_equal_in_lists(a, b)

Find equal values in two lists.

Parameters:

Name Type Description Default
a list

list with a values

 required
b list

list with b values

 required

Returns:

Name Type Description
list List[int]

list with 1 if equal, otherwise 0

Examples:

>>> from spotPython.utils.compare import find_equal_in_lists
    a = [1, 2, 3, 4, 5]
    b = [1, 2, 3, 4, 5]
    find_equal_in_lists(a, b)
    [1, 1, 1, 1, 1]
Source code in spotPython/utils/compare.py 
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def find_equal_in_lists(a: List[int], b: List[int]) -> List[int]:
    """Find equal values in two lists.

    Args:
        a (list): list with a values
        b (list): list with b values

    Returns:
        list: list with 1 if equal, otherwise 0

    Examples:
        >>> from spotPython.utils.compare import find_equal_in_lists
            a = [1, 2, 3, 4, 5]
            b = [1, 2, 3, 4, 5]
            find_equal_in_lists(a, b)
            [1, 1, 1, 1, 1]
    """
    equal = [1 if a[i] == b[i] else 0 for i in range(len(a))]
    return equal

selectNew(A, X, tolerance=0)

Select rows from A that are not in X.

Parameters:

Name Type Description Default
A ndarray

A array with new values

 required
X ndarray

X array with known values

 required
tolerance float

tolerance value for comparison

 0

Returns:

Type Description
ndarray

array with unknown (new) values
ndarray

array with True if value is new, otherwise False.

Examples:

from spotPython.utils.compare import selectNew import numpy as np A = np.array([[1,2,3],[4,5,6]]) X = np.array([[1,2,3],[4,5,6]]) B, ind = selectNew(A, X) assert B.shape[0] == 0 assert np.equal(ind, np.array([False, False])).all() from spotPython.utils.compare import selectNew A = np.array([[1,2,3],[4,5,7]]) X = np.array([[1,2,3],[4,5,6]]) B, ind = selectNew(A, X) assert B.shape[0] == 1 assert np.equal(ind, np.array([False, True])).all()

Source code in spotPython/utils/compare.py 
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def selectNew(A: np.ndarray, X: np.ndarray, tolerance: float = 0) -> Tuple[np.ndarray, np.ndarray]:
    """
    Select rows from A that are not in X.

    Args:
        A (numpy.ndarray): A array with new values
        X (numpy.ndarray): X array with known values
        tolerance (float): tolerance value for comparison

    Returns:
        (numpy.ndarray): array with unknown (new) values
        (numpy.ndarray): array with `True` if value is new, otherwise `False`.

    Examples:
    >>> from spotPython.utils.compare import selectNew
        import numpy as np
        A = np.array([[1,2,3],[4,5,6]])
        X = np.array([[1,2,3],[4,5,6]])
        B, ind  = selectNew(A, X)
        assert B.shape[0] == 0
        assert np.equal(ind, np.array([False, False])).all()
    >>> from spotPython.utils.compare import selectNew
        A = np.array([[1,2,3],[4,5,7]])
        X = np.array([[1,2,3],[4,5,6]])
        B, ind  = selectNew(A, X)
        assert B.shape[0] == 1
        assert np.equal(ind, np.array([False, True])).all()
    """
    B = np.abs(A[:, None] - X)
    ind = np.any(np.all(B <= tolerance, axis=2), axis=1)
    return A[~ind], ~ind