Below is the pseudocode to calculate an adaptation of the Levenstein minimum distance. I have the first part decoded for python but I can't figure out the bottom part, denoted with ***.
Algorithm of distance calculation (pseudocode) using dynamical programming:
First Part:
int function distance(Sequence sequence1, Sequence sequence2)
set length_1 to length of sequence1
set length_2 to length of sequence2
declare distances[length_1+1][length_2+1]
for i from 0 to length_1
set distances[i][0] to i
for j from 0 to length_2
set distances[0][j] to j
// Classical Levenshtein part
for i = 1 to length_1
for j = 1 to length_2
set cost to 0
if (sequence1[i-1] not equal to sequence[j-1])
set cost to 1
set distances[i][j] to minimum of
distances[i-1][j-1] + cost,// Substitution
distances[i][j-1] + 1, // Insertion
distances[i-1][j] + 1 // Deletion
set min_distance to distances[length_1][length_2]
******New Part- Help!*******
// Truncating
for i from 0 to length_1
set min_distance to minimum of min_distance and distances[i][length_2]
// Elongating
for j from 0 to length_2
set min_distance to minimum of min_distance and distances[length_1][j]
return min_distance
return min(itertools.chain((x[length_2] for x in distances),
distances[length_1]))