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Edit_Distance_Formula.py
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60 lines (49 loc) · 2.16 KB
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# A Dynamic Programming based Python program for edit
# distance problem
def editDistDP(str1, str2, m, n):
# Create a table to store results of subproblems
dp = [[0 for x in range(n + 1)] for x in range(m + 1)]
# Fill d[][] in bottom up manner
for i in range(m + 1):
for j in range(n + 1):
# If first string is empty, only option is to
# insert all characters of second string
if i == 0:
dp[i][j] = j # Min. operations = j
# If second string is empty, only option is to
# remove all characters of second string
elif j == 0:
dp[i][j] = i # Min. operations = i
# If last characters are same, ignore last char
# and recur for remaining string
elif str1[i - 1] == str2[j - 1]:
dp[i][j] = dp[i - 1][j - 1]
# If last character are different, consider all
# possibilities and find minimum
else:
dp[i][j] = 1 + min(dp[i][j - 1], # Insert
dp[i - 1][j], # Remove
dp[i - 1][j - 1]) # Replace
return dp[m][n]
def editDistance(str1, str2, m, n):
# If first string is empty, the only option is to
# insert all characters of second string into first
if m == 0:
return n
# If second string is empty, the only option is to
# remove all characters of first string
if n == 0:
return m
# If last characters of two strings are same, nothing
# much to do. Ignore last characters and get count for
# remaining strings.
if str1[m - 1] == str2[n - 1]:
return editDistance(str1, str2, m - 1, n - 1)
# If last characters are not same, consider all three
# operations on last character of first string, recursively
# compute minimum cost for all three operations and take
# minimum of three values.
return 1 + min(editDistance(str1, str2, m, n - 1), # Insert
editDistance(str1, str2, m - 1, n), # Remove
editDistance(str1, str2, m - 1, n - 1) # Replace
)