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Misc fixes across multiple algorithms (#6912)

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Source: Snyk code quality
Add scikit-fuzzy to requirements

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Dhruv Manilawala <dhruvmanila@gmail.com>
This commit is contained in:
CenTdemeern1
2022-10-15 22:25:38 -07:00
committed by GitHub
parent c94e215c8d
commit 04698538d8
19 changed files with 40 additions and 48 deletions
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5
maths/extended_euclidean_algorithm.py
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@ -75,11 +75,12 @@ def main():
"""Call Extended Euclidean Algorithm."""
if len(sys.argv) < 3:
print("2 integer arguments required")
exit(1)
return 1
a = int(sys.argv[1])
b = int(sys.argv[2])
print(extended_euclidean_algorithm(a, b))
return 0
if __name__ == "__main__":
main()
raise SystemExit(main())

15
maths/jaccard_similarity.py
View File

@ -14,7 +14,7 @@ Jaccard similarity is widely used with MinHashing.
"""
def jaccard_similariy(set_a, set_b, alternative_union=False):
def jaccard_similarity(set_a, set_b, alternative_union=False):
"""
Finds the jaccard similarity between two sets.
Essentially, its intersection over union.
@ -35,18 +35,18 @@ def jaccard_similariy(set_a, set_b, alternative_union=False):
Examples:
>>> set_a = {'a', 'b', 'c', 'd', 'e'}
>>> set_b = {'c', 'd', 'e', 'f', 'h', 'i'}
>>> jaccard_similariy(set_a, set_b)
>>> jaccard_similarity(set_a, set_b)
0.375
>>> jaccard_similariy(set_a, set_a)
>>> jaccard_similarity(set_a, set_a)
1.0
>>> jaccard_similariy(set_a, set_a, True)
>>> jaccard_similarity(set_a, set_a, True)
0.5
>>> set_a = ['a', 'b', 'c', 'd', 'e']
>>> set_b = ('c', 'd', 'e', 'f', 'h', 'i')
>>> jaccard_similariy(set_a, set_b)
>>> jaccard_similarity(set_a, set_b)
0.375
"""
@ -67,14 +67,15 @@ def jaccard_similariy(set_a, set_b, alternative_union=False):
if alternative_union:
union = len(set_a) + len(set_b)
return len(intersection) / union
else:
union = set_a + [element for element in set_b if element not in set_a]
return len(intersection) / len(union)
return len(intersection) / len(union)
if __name__ == "__main__":
set_a = {"a", "b", "c", "d", "e"}
set_b = {"c", "d", "e", "f", "h", "i"}
print(jaccard_similariy(set_a, set_b))
print(jaccard_similarity(set_a, set_b))