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estimated error

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This commit is contained in:
Isidro Arias 2023-04-07 17:31:08 +02:00
parent 28e66913b0
commit 2fd71965f1
1 changed files with 13 additions and 1 deletions
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14
data_structures/hashing/bloom_filter.py
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@ -13,7 +13,7 @@ Initially the filter contains all zeros:
'00000000' '00000000'
When an element is added, two bits are set to 1 When an element is added, two bits are set to 1
since there are 2 hash functions: since there are 2 hash functions in this implementation:
>>> b.add("Titanic") >>> b.add("Titanic")
>>> b.bitstring >>> b.bitstring
'01100000' '01100000'
@ -35,10 +35,16 @@ False
'00011000' '00011000'
>>> "Interstellar" in b >>> "Interstellar" in b
False False
>>> b.format_hash("Interstellar")
'00000011'
>>> "Parasite" in b >>> "Parasite" in b
False False
>>> b.format_hash("Parasite")
'00010010'
>>> "Pulp Fiction" in b >>> "Pulp Fiction" in b
False False
>>> b.format_hash("Pulp Fiction")
'10000100'
but sometimes there are false positives: but sometimes there are false positives:
>>> "Ratatouille" in b >>> "Ratatouille" in b
@ -46,8 +52,14 @@ True
>>> b.format_hash("Ratatouille") >>> b.format_hash("Ratatouille")
'01100000' '01100000'
The probability increases with the number of added elements
>>> b.estimated_error_rate() >>> b.estimated_error_rate()
0.140625 0.140625
>>> b.add("The Goodfather")
>>> b.estimated_error_rate()
0.390625
>>> b.bitstring
'01111100'
""" """
from hashlib import md5, sha256 from hashlib import md5, sha256