feat/implementation of Booth's Algorithm

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rudrajiii 2024-10-28 22:14:48 +05:30
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class BoothsAlgorithm:
"""
Booth's Algorithm finds the lexicographically minimal rotation of a string.
Time Complexity: O(n) - Linear time where n is the length of input string
Space Complexity: O(n) - Linear space for failure function array
For More Visit - https://en.wikipedia.org/wiki/Booth%27s_multiplication_algorithm
"""
def find_minimal_rotation(self, string: str) -> str:
"""
Find the lexicographically minimal rotation of the input string.
Args:
string (str): Input string to find minimal rotation.
Returns:
str: Lexicographically minimal rotation of the input string.
Raises:
ValueError: If the input is not a string or is empty.
Examples:
>>> ba = BoothsAlgorithm()
>>> ba.find_minimal_rotation("baca")
'abac'
>>> ba.find_minimal_rotation("aaab")
'aaab'
>>> ba.find_minimal_rotation("abcd")
'abcd'
>>> ba.find_minimal_rotation("dcba")
'adcb'
>>> ba.find_minimal_rotation("aabaa")
'aaaab'
"""
if not isinstance(string, str) or not string:
raise ValueError("Input must be a non-empty string")
n = len(string)
s = string + string # Double the string to handle all rotations
f = [-1] * (2 * n) # Initialize failure function array with twice the length
k = 0 # Starting position of minimal rotation
for j in range(1, 2 * n):
sj = s[j]
i = f[j - k - 1]
while i != -1 and sj != s[k + i + 1]:
if sj < s[k + i + 1]:
k = j - i - 1
i = f[i]
if i == -1 and sj != s[k]:
if sj < s[k]:
k = j
f[j - k] = -1
else:
f[j - k] = i + 1
return s[k : k + n]
if __name__ == "__main__":
ba = BoothsAlgorithm()
print(ba.find_minimal_rotation("bca")) # output is 'abc'