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c026b1952f
* adding a matrix equalization algorithm * Adding url for more details * Implementing suggestions
56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
from sys import maxsize
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def array_equalization(vector: list[int], step_size: int) -> int:
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"""
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This algorithm equalizes all elements of the input vector
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to a common value, by making the minimal number of
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"updates" under the constraint of a step size (step_size).
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>>> array_equalization([1, 1, 6, 2, 4, 6, 5, 1, 7, 2, 2, 1, 7, 2, 2], 4)
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4
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>>> array_equalization([22, 81, 88, 71, 22, 81, 632, 81, 81, 22, 92], 2)
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5
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>>> array_equalization([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 5)
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0
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>>> array_equalization([22, 22, 22, 33, 33, 33], 2)
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2
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>>> array_equalization([1, 2, 3], 0)
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Traceback (most recent call last):
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ValueError: Step size must be positive and non-zero.
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>>> array_equalization([1, 2, 3], -1)
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Traceback (most recent call last):
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ValueError: Step size must be positive and non-zero.
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>>> array_equalization([1, 2, 3], 0.5)
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Traceback (most recent call last):
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ValueError: Step size must be an integer.
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>>> array_equalization([1, 2, 3], maxsize)
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1
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"""
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if step_size <= 0:
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raise ValueError("Step size must be positive and non-zero.")
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if not isinstance(step_size, int):
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raise ValueError("Step size must be an integer.")
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unique_elements = set(vector)
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min_updates = maxsize
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for element in unique_elements:
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elem_index = 0
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updates = 0
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while elem_index < len(vector):
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if vector[elem_index] != element:
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updates += 1
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elem_index += step_size
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else:
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elem_index += 1
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min_updates = min(min_updates, updates)
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return min_updates
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if __name__ == "__main__":
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from doctest import testmod
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testmod()
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