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Added Manhattan distance algorithm (#7790)
* Added Manhattan distance algorithm, Fixes: #7776 * Forgot that isinstance can accept a tuple * Apply suggestions from code review * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update manhattan_distance.py * Update manhattan_distance.py Co-authored-by: Christian Clauss <cclauss@me.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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maths/manhattan_distance.py
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126
maths/manhattan_distance.py
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def manhattan_distance(point_a: list, point_b: list) -> float:
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"""
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Expectts two list of numbers representing two points in the same
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n-dimensional space
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https://en.wikipedia.org/wiki/Taxicab_geometry
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>>> manhattan_distance([1,1], [2,2])
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2.0
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>>> manhattan_distance([1.5,1.5], [2,2])
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1.0
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>>> manhattan_distance([1.5,1.5], [2.5,2])
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1.5
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>>> manhattan_distance([-3, -3, -3], [0, 0, 0])
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9.0
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>>> manhattan_distance([1,1], None)
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Traceback (most recent call last):
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...
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ValueError: Missing an input
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>>> manhattan_distance([1,1], [2, 2, 2])
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Traceback (most recent call last):
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...
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ValueError: Both points must be in the same n-dimensional space
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>>> manhattan_distance([1,"one"], [2, 2, 2])
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Traceback (most recent call last):
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...
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TypeError: Expected a list of numbers as input, found str
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>>> manhattan_distance(1, [2, 2, 2])
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Traceback (most recent call last):
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...
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TypeError: Expected a list of numbers as input, found int
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>>> manhattan_distance([1,1], "not_a_list")
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Traceback (most recent call last):
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...
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TypeError: Expected a list of numbers as input, found str
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"""
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_validate_point(point_a)
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_validate_point(point_b)
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if len(point_a) != len(point_b):
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raise ValueError("Both points must be in the same n-dimensional space")
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return float(sum(abs(a - b) for a, b in zip(point_a, point_b)))
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def _validate_point(point: list[float]) -> None:
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"""
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>>> _validate_point(None)
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Traceback (most recent call last):
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...
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ValueError: Missing an input
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>>> _validate_point([1,"one"])
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Traceback (most recent call last):
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...
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TypeError: Expected a list of numbers as input, found str
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>>> _validate_point(1)
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Traceback (most recent call last):
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...
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TypeError: Expected a list of numbers as input, found int
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>>> _validate_point("not_a_list")
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Traceback (most recent call last):
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...
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TypeError: Expected a list of numbers as input, found str
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"""
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if point:
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if isinstance(point, list):
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for item in point:
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if not isinstance(item, (int, float)):
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raise TypeError(
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f"Expected a list of numbers as input, "
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f"found {type(item).__name__}"
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)
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else:
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raise TypeError(
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f"Expected a list of numbers as input, found {type(point).__name__}"
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)
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else:
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raise ValueError("Missing an input")
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def manhattan_distance_one_liner(point_a: list, point_b: list) -> float:
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"""
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Version with one liner
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>>> manhattan_distance_one_liner([1,1], [2,2])
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2.0
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>>> manhattan_distance_one_liner([1.5,1.5], [2,2])
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1.0
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>>> manhattan_distance_one_liner([1.5,1.5], [2.5,2])
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1.5
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>>> manhattan_distance_one_liner([-3, -3, -3], [0, 0, 0])
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9.0
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>>> manhattan_distance_one_liner([1,1], None)
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Traceback (most recent call last):
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...
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ValueError: Missing an input
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>>> manhattan_distance_one_liner([1,1], [2, 2, 2])
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Traceback (most recent call last):
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...
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ValueError: Both points must be in the same n-dimensional space
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>>> manhattan_distance_one_liner([1,"one"], [2, 2, 2])
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Traceback (most recent call last):
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...
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TypeError: Expected a list of numbers as input, found str
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>>> manhattan_distance_one_liner(1, [2, 2, 2])
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Traceback (most recent call last):
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...
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TypeError: Expected a list of numbers as input, found int
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>>> manhattan_distance_one_liner([1,1], "not_a_list")
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Traceback (most recent call last):
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...
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TypeError: Expected a list of numbers as input, found str
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"""
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_validate_point(point_a)
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_validate_point(point_b)
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if len(point_a) != len(point_b):
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raise ValueError("Both points must be in the same n-dimensional space")
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return float(sum(abs(x - y) for x, y in zip(point_a, point_b)))
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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