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/*
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* Copyright 2010 Google Inc.
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*
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* Licensed under the Apache License, Version 2.0 (the "License"); you may not
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* use this file except in compliance with the License. You may obtain a copy of
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* the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations under
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* the License.
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*/
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using System;
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using System.Diagnostics;
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namespace NzbDrone.Common.Extensions
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{
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/**
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* A modified version of a string edit distance described by Berghel and
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* Roach that uses only O(d) space and O(n*d) worst-case time, where n is
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* the pattern string length and d is the edit distance computed.
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* We achieve the space reduction by keeping only those sub-computations
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* required to compute edit distance, giving up the ability to
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* reconstruct the edit path.
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*/
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public static class ModifiedBerghelRoachEditDistance
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{
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/*
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* This is a modification of the original Berghel-Roach edit
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* distance (based on prior work by Ukkonen) described in
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* ACM Transactions on Information Systems, Vol. 14, No. 1,
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* January 1996, pages 94-106.
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*
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* I observed that only O(d) prior computations are required
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* to compute edit distance. Rather than keeping all prior
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* f(k,p) results in a matrix, we keep only the two "outer edges"
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* in the triangular computation pattern that will be used in
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* subsequent rounds. We cannot reconstruct the edit path,
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* but many applications do not require that; for them, this
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* modification uses less space (and empirically, slightly
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* less time).
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*
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* First, some history behind the algorithm necessary to understand
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* Berghel-Roach and our modification...
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*
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* The traditional algorithm for edit distance uses dynamic programming,
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* building a matrix of distances for substrings:
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* D[i,j] holds the distance for string1[0..i]=>string2[0..j].
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* The matrix is initially populated with the trivial values
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* D[0,j]=j and D[i,0]=i; and then expanded with the rule:
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* <pre>
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* D[i,j] = min( D[i-1,j]+1, // insertion
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* D[i,j-1]+1, // deletion
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* (D[i-1,j-1]
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* + (string1[i]==string2[j])
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* ? 0 // match
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* : 1 // substitution ) )
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* </pre>
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*
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* Ukkonen observed that each diagonal of the matrix must increase
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* by either 0 or 1 from row to row. If D[i,j] = p, then the
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* matching rule requires that D[i+x,j+x] = p for all x
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* where string1[i..i+x) matches string2[j..j+j+x). Ukkonen
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* defined a function f(k,p) as the highest row number in which p
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* appears on the k-th diagonal (those D[i,j] where k=(i-j), noting
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* that k may be negative). The final result of the edit
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* distance is the D[n,m] cell, on the (n-m) diagonal; it is
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* the value of p for which f(n-m, p) = m. The function f can
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* also be computed dynamically, according to a simple recursion:
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* <pre>
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* f(k,p) {
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* contains_p = max(f(k-1,p-1), f(k,p-1)+1, f(k+1,p-1)+1)
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* while (string1[contains_p] == string2[contains_p + k])
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* contains_p++;
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* return contains_p;
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* }
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* </pre>
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* The max() expression finds a row where the k-th diagonal must
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* contain p by virtue of an edit from the prior, same, or following
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* diagonal (corresponding to an insert, substitute, or delete);
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* we need not consider more distant diagonals because row-to-row
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* and column-to-column changes are at most +/- 1.
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*
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* The original Ukkonen algorithm computed f(k,p) roughly as
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* follows:
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* <pre>
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* for (p = 0; ; p++) {
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* compute f(k,p) for all valid k
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* if (f(n-m, p) == m) return p;
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* }
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* </pre>
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*
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* Berghel and Roach observed that many values of f(k,p) are
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* computed unnecessarily, and reorganized the computation into
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* a just-in-time sequence. In each iteration, we are primarily
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* interested in the terminating value f(main,p), where main=(n-m)
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* is the main diagonal. To compute that we need f(x,p-1) for
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* three values of x: main-1, main, and main+1. Those depend on
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* values for p-2, and so forth. We will already have computed
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* f(main,p-1) in the prior round, and thus f(main-1,p-2) and
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* f(main+1,p-2), and so forth. The only new values we need to compute
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* are on the edges: f(main-i,p-i) and f(main+i,p-i). Noting that
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* f(k,p) is only meaningful when abs(k) is no greater than p,
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* one of the Berghel-Roach reviewers noted that we can compute
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* the bounds for i:
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* <pre>
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* (main+i &le p-i) implies (i ≤ (p-main)/2)
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* </pre>
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* (where main+i is limited on the positive side) and similarly
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* <pre>
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* (-(main-i) &le p-i) implies (i ≤ (p+main)/2).
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* </pre>
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* (where main-i is limited on the negative side).
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*
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* This reduces the computation sequence to
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* <pre>
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* for (i = (p-main)/2; i > 0; i--) compute f(main+i,p-i);
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* for (i = (p+main)/2; i > 0; i--) compute f(main-i,p-i);
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* if (f(main, p) == m) return p;
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* </pre>
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*
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* The original Berghel-Roach algorithm recorded prior values
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* of f(k,p) in a matrix, using O(distance^2) space, enabling
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* reconstruction of the edit path, but if all we want is the
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* edit *distance*, we only need to keep O(distance) prior computations.
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*
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* The requisite prior k-1, k, and k+1 values are conveniently
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* computed in the current round and the two preceding it.
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* For example, on the higher-diagonal side, we compute:
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* <pre>
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* current[i] = f(main+i, p-i)
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* </pre>
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* We keep the two prior rounds of results, where p was one and two
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* smaller. So, from the preceidng round
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* <pre>
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* last[i] = f(main+i, (p-1)-i)
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* </pre>
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* and from the prior round, but one position back:
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* <pre>
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* prior[i-1] = f(main+(i-1), (p-2)-(i-1))
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* </pre>
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* In the current round, one iteration earlier:
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* <pre>
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* current[i+1] = f(main+(i+1), p-(i+1))
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* </pre>
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* Note that the distance in all of these evaluates to p-i-1,
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* and the diagonals are (main+i) and its neighbors... just
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* what we need. The lower-diagonal side behaves similarly.
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*
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* We need to materialize values that are not computed in prior
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* rounds, for either of two reasons: <ul>
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* <li> Initially, we have no prior rounds, so we need to fill
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* all of the "last" and "prior" values for use in the
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* first round. The first round uses only on one side
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* of the main diagonal or the other.
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* <li> In every other round, we compute one more diagonal than before.
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* </ul>
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* In all of these cases, the missing f(k,p) values are for abs(k) > p,
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* where a real value of f(k,p) is undefined. [The original Berghel-Roach
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* algorithm prefills its F matrix with these values, but we fill
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* them as we go, as needed.] We define
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* <pre>
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* f(-p-1,p) = p, so that we start diagonal -p with row p,
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* f(p+1,p) = -1, so that we start diagonal p with row 0.
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* </pre>
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* (We also allow f(p+2,p)=f(-p-2,p)=-1, causing those values to
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* have no effect in the starting row computation.]
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*
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* We only expand the set of diagonals visited every other round,
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* when (p-main) or (p+main) is even. We keep track of even/oddness
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* to save some arithmetic. The first round is always even, as p=abs(main).
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* Note that we rename the "f" function to "computeRow" to be Googley.
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*/
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public static int LevenshteinDistance(this string text, string other)
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{
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return ModifiedBerghelRoachEditDistance.GetDistance(text, other);
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}
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public static int GetDistance(string target, string pattern, int limit = 20)
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{
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return GetDistance(target.ToCharArray(), pattern.ToCharArray(), limit);
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}
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public static int GetDistance(char[] target, char[] pattern, int limit = 20)
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{
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var currentLeft = new int[limit];
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var currentRight = new int[limit];
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var lastLeft = new int[limit];
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var lastRight = new int[limit];
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var priorLeft = new int[limit];
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var priorRight = new int[limit];
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var targetLength = target.Length;
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/*
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* Compute the main diagonal number.
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* The final result lies on this diagonal.
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*/
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var main = pattern.Length - targetLength;
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/*
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* Compute our initial distance candidate.
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* The result cannot be less than the difference in
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* string lengths, so we start there.
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*/
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var distance = Math.Abs(main);
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if (distance > limit)
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{
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/* More than we wanted. Give up right away */
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return int.MaxValue;
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}
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/*
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* In the main loop below, the current{Right,Left} arrays record results
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* from the current outer loop pass. The last{Right,Left} and
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* prior{Right,Left} arrays hold the results from the preceding two passes.
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* At the end of the outer loop, we shift them around (reusing the prior
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* array as the current for the next round, to avoid reallocating).
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* The Right reflects higher-numbered diagonals, Left lower-numbered.
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*/
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/*
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* Fill in "prior" values for the first two passes through
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* the distance loop. Note that we will execute only one side of
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* the main diagonal in these passes, so we only need
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* initialize one side of prior values.
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*/
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if (main <= 0)
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{
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EnsureCapacityRight(ref currentRight, ref lastRight, ref priorRight, distance, false);
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for (var j = 0; j <= distance; j++)
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{
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lastRight[j] = distance - j - 1; /* Make diagonal -k start in row k */
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priorRight[j] = -1;
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}
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}
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else
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{
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EnsureCapacityLeft(ref currentLeft, ref lastLeft, ref priorLeft, distance, false);
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for (var j = 0; j <= distance; j++)
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{
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lastLeft[j] = -1; /* Make diagonal +k start in row 0 */
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priorLeft[j] = -1;
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}
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}
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/*
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* Keep track of even rounds. Only those rounds consider new diagonals,
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* and thus only they require artificial "last" values below.
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*/
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var even = true;
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/*
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* MAIN LOOP: try each successive possible distance until one succeeds.
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*/
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while (true)
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{
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/*
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* Before calling computeRow(main, distance), we need to fill in
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* missing cache elements. See the high-level description above.
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*/
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/*
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* Higher-numbered diagonals
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*/
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var offDiagonal = (distance - main) / 2;
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EnsureCapacityRight(ref currentRight, ref lastRight, ref priorRight, offDiagonal, true);
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if (even)
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{
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/* Higher diagonals start at row 0 */
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lastRight[offDiagonal] = -1;
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}
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var immediateRight = -1;
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for (; offDiagonal > 0; offDiagonal--)
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{
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currentRight[offDiagonal] = immediateRight = ComputeRow(
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main + offDiagonal,
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distance - offDiagonal,
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pattern,
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target,
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priorRight[offDiagonal - 1],
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lastRight[offDiagonal],
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immediateRight);
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}
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/*
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* Lower-numbered diagonals
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*/
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offDiagonal = (distance + main) / 2;
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EnsureCapacityLeft(ref currentLeft, ref lastLeft, ref priorLeft, offDiagonal, true);
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if (even)
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{
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/* Lower diagonals, fictitious values for f(-x-1,x) = x */
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lastLeft[offDiagonal] = ((distance - main) / 2) - 1;
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}
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var immediateLeft = even ? -1 : (distance - main) / 2;
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for (; offDiagonal > 0; offDiagonal--)
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{
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currentLeft[offDiagonal] = immediateLeft = ComputeRow(
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main - offDiagonal,
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distance - offDiagonal,
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pattern,
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target,
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immediateLeft,
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lastLeft[offDiagonal],
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priorLeft[offDiagonal - 1]);
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}
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/*
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* We are done if the main diagonal has distance in the last row.
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*/
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var mainRow = ComputeRow(main, distance, pattern, target, immediateLeft, lastLeft[0], immediateRight);
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if ((mainRow == targetLength) || (++distance > limit) || (distance < 0))
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{
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break;
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}
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/* The [0] element goes to both sides. */
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currentLeft[0] = currentRight[0] = mainRow;
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/* Rotate rows around for next round: current=>last=>prior (=>current) */
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var tmp = priorLeft;
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priorLeft = lastLeft;
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lastLeft = currentLeft;
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currentLeft = priorLeft;
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tmp = priorRight;
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priorRight = lastRight;
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lastRight = currentRight;
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currentRight = tmp;
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/* Update evenness, too */
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even = !even;
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}
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return distance;
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}
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/**
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* Computes the highest row in which the distance {@code p} appears
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* in diagonal {@code k} of the edit distance computation for
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* strings {@code a} and {@code b}. The diagonal number is
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* represented by the difference in the indices for the two strings;
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* it can range from {@code -b.length()} through {@code a.length()}.
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*
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* More precisely, this computes the highest value x such that
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* <pre>
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* p = edit-distance(a[0:(x+k)), b[0:x)).
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* </pre>
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*
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* This is the "f" function described by Ukkonen.
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*
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* The caller must assure that abs(k) ≤ p, the only values for
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* which this is well-defined.
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*
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* The implementation depends on the cached results of prior
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* computeRow calls for diagonals k-1, k, and k+1 for distance p-1.
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* These must be supplied in {@code knownLeft}, {@code knownAbove},
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* and {@code knownRight}, respectively.
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* @param k diagonal number
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* @param p edit distance
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* @param a one string to be compared
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* @param b other string to be compared
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* @param knownLeft value of {@code computeRow(k-1, p-1, ...)}
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* @param knownAbove value of {@code computeRow(k, p-1, ...)}
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* @param knownRight value of {@code computeRow(k+1, p-1, ...)}
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*/
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private static int ComputeRow(int k,
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int p,
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char[] a,
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char[] b,
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int knownLeft,
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int knownAbove,
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int knownRight)
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{
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Debug.Assert(Math.Abs(k) <= p);
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Debug.Assert(p >= 0);
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/*
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* Compute our starting point using the recurrance.
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* That is, find the first row where the desired edit distance
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* appears in our diagonal. This is at least one past
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* the highest row for
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*/
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int t;
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if (p == 0)
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{
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t = 0;
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}
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else
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{
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/*
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* We look at the adjacent diagonals for the next lower edit distance.
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* We can start in the next row after the prior result from
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* our own diagonal (the "substitute" case), or the next diagonal
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* ("delete"), but only the same row as the prior result from
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* the prior diagonal ("insert").
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*/
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t = Math.Max(Math.Max(knownAbove, knownRight) + 1, knownLeft);
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}
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/*
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* Look down our diagonal for matches to find the maximum
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* row with edit-distance p.
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*/
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var tmax = Math.Min(b.Length, a.Length - k);
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while ((t < tmax) && b[t] == a[t + k])
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{
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t++;
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}
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return t;
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}
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/*
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* Ensures that the Left arrays can be indexed through {@code index},
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* inclusively, resizing (and copying) as necessary.
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*/
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private static void EnsureCapacityLeft(ref int[] currentLeft, ref int[] lastLeft, ref int[] priorLeft, int index, bool copy)
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{
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if (currentLeft.Length <= index)
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{
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index++;
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Resize(ref priorLeft, index, copy);
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Resize(ref lastLeft, index, copy);
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Resize(ref currentLeft, index, false);
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}
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}
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/*
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* Ensures that the Right arrays can be indexed through {@code index},
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* inclusively, resizing (and copying) as necessary.
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*/
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private static void EnsureCapacityRight(ref int[] currentRight, ref int[] lastRight, ref int[] priorRight, int index, bool copy)
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{
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if (currentRight.Length <= index)
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{
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index++;
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Resize(ref priorRight, index, copy);
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Resize(ref lastRight, index, copy);
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Resize(ref currentRight, index, false);
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}
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}
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/* Resize an array, copying old contents if requested */
|
||||
private static void Resize(ref int[] array, int size, bool copy)
|
||||
{
|
||||
if (copy)
|
||||
{
|
||||
Array.Resize(ref array, size);
|
||||
}
|
||||
else
|
||||
{
|
||||
array = new int[size];
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,61 +0,0 @@
|
||||
using System;
|
||||
|
||||
namespace NzbDrone.Common.Extensions
|
||||
{
|
||||
public static class LevenstheinExtensions
|
||||
{
|
||||
public static int LevenshteinDistance(this string text, string other, int costInsert = 1, int costDelete = 1, int costSubstitute = 1)
|
||||
{
|
||||
if (text == other)
|
||||
{
|
||||
return 0;
|
||||
}
|
||||
|
||||
if (text.Length == 0)
|
||||
{
|
||||
return other.Length * costInsert;
|
||||
}
|
||||
|
||||
if (other.Length == 0)
|
||||
{
|
||||
return text.Length * costDelete;
|
||||
}
|
||||
|
||||
int[] matrix = new int[other.Length + 1];
|
||||
|
||||
for (var i = 1; i < matrix.Length; i++)
|
||||
{
|
||||
matrix[i] = i * costInsert;
|
||||
}
|
||||
|
||||
for (var i = 0; i < text.Length; i++)
|
||||
{
|
||||
int topLeft = matrix[0];
|
||||
matrix[0] = matrix[0] + costDelete;
|
||||
|
||||
for (var j = 0; j < other.Length; j++)
|
||||
{
|
||||
int top = matrix[j];
|
||||
int left = matrix[j + 1];
|
||||
|
||||
var sumIns = top + costInsert;
|
||||
var sumDel = left + costDelete;
|
||||
var sumSub = topLeft + (text[i] == other[j] ? 0 : costSubstitute);
|
||||
|
||||
topLeft = matrix[j + 1];
|
||||
matrix[j + 1] = Math.Min(Math.Min(sumIns, sumDel), sumSub);
|
||||
}
|
||||
}
|
||||
|
||||
return matrix[other.Length];
|
||||
}
|
||||
|
||||
public static int LevenshteinDistanceClean(this string expected, string other)
|
||||
{
|
||||
expected = expected.ToLower().Replace(".", "");
|
||||
other = other.ToLower().Replace(".", "");
|
||||
|
||||
return expected.LevenshteinDistance(other, 1, 3, 3);
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,71 +0,0 @@
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
using FluentAssertions;
|
||||
using NUnit.Framework;
|
||||
using NzbDrone.Core.Books;
|
||||
using NzbDrone.Core.MetadataSource;
|
||||
using NzbDrone.Core.Test.Framework;
|
||||
|
||||
namespace NzbDrone.Core.Test.MetadataSource
|
||||
{
|
||||
[TestFixture]
|
||||
public class SearchAuthorComparerFixture : CoreTest
|
||||
{
|
||||
private List<Author> _author;
|
||||
|
||||
[SetUp]
|
||||
public void Setup()
|
||||
{
|
||||
_author = new List<Author>();
|
||||
}
|
||||
|
||||
private void WithSeries(string name)
|
||||
{
|
||||
_author.Add(new Author { Name = name });
|
||||
}
|
||||
|
||||
[Test]
|
||||
public void should_prefer_the_walking_dead_over_talking_dead_when_searching_for_the_walking_dead()
|
||||
{
|
||||
WithSeries("Talking Dead");
|
||||
WithSeries("The Walking Dead");
|
||||
|
||||
_author.Sort(new SearchAuthorComparer("the walking dead"));
|
||||
|
||||
_author.First().Name.Should().Be("The Walking Dead");
|
||||
}
|
||||
|
||||
[Test]
|
||||
public void should_prefer_the_walking_dead_over_talking_dead_when_searching_for_walking_dead()
|
||||
{
|
||||
WithSeries("Talking Dead");
|
||||
WithSeries("The Walking Dead");
|
||||
|
||||
_author.Sort(new SearchAuthorComparer("walking dead"));
|
||||
|
||||
_author.First().Name.Should().Be("The Walking Dead");
|
||||
}
|
||||
|
||||
[Test]
|
||||
public void should_prefer_blacklist_over_the_blacklist_when_searching_for_blacklist()
|
||||
{
|
||||
WithSeries("The Blacklist");
|
||||
WithSeries("Blacklist");
|
||||
|
||||
_author.Sort(new SearchAuthorComparer("blacklist"));
|
||||
|
||||
_author.First().Name.Should().Be("Blacklist");
|
||||
}
|
||||
|
||||
[Test]
|
||||
public void should_prefer_the_blacklist_over_blacklist_when_searching_for_the_blacklist()
|
||||
{
|
||||
WithSeries("Blacklist");
|
||||
WithSeries("The Blacklist");
|
||||
|
||||
_author.Sort(new SearchAuthorComparer("the blacklist"));
|
||||
|
||||
_author.First().Name.Should().Be("The Blacklist");
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -1,95 +0,0 @@
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Text.RegularExpressions;
|
||||
using NzbDrone.Common.Extensions;
|
||||
using NzbDrone.Core.Books;
|
||||
|
||||
namespace NzbDrone.Core.MetadataSource
|
||||
{
|
||||
public class SearchAuthorComparer : IComparer<Author>
|
||||
{
|
||||
private static readonly Regex RegexCleanPunctuation = new Regex("[-._:]", RegexOptions.Compiled);
|
||||
private static readonly Regex RegexCleanCountryYearPostfix = new Regex(@"(?<=.+)( \([A-Z]{2}\)| \(\d{4}\)| \([A-Z]{2}\) \(\d{4}\))$", RegexOptions.Compiled);
|
||||
private static readonly Regex ArticleRegex = new Regex(@"^(a|an|the)\s", RegexOptions.IgnoreCase | RegexOptions.Compiled);
|
||||
|
||||
public string SearchQuery { get; private set; }
|
||||
|
||||
private readonly string _searchQueryWithoutYear;
|
||||
private int? _year;
|
||||
|
||||
public SearchAuthorComparer(string searchQuery)
|
||||
{
|
||||
SearchQuery = searchQuery;
|
||||
|
||||
var match = Regex.Match(SearchQuery, @"^(?<query>.+)\s+(?:\((?<year>\d{4})\)|(?<year>\d{4}))$");
|
||||
if (match.Success)
|
||||
{
|
||||
_searchQueryWithoutYear = match.Groups["query"].Value.ToLowerInvariant();
|
||||
_year = int.Parse(match.Groups["year"].Value);
|
||||
}
|
||||
else
|
||||
{
|
||||
_searchQueryWithoutYear = searchQuery.ToLowerInvariant();
|
||||
}
|
||||
}
|
||||
|
||||
public int Compare(Author x, Author y)
|
||||
{
|
||||
int result = 0;
|
||||
|
||||
// Prefer exact matches
|
||||
result = Compare(x, y, s => CleanPunctuation(s.Name).Equals(CleanPunctuation(SearchQuery)));
|
||||
if (result != 0)
|
||||
{
|
||||
return -result;
|
||||
}
|
||||
|
||||
// Remove Articles (a/an/the)
|
||||
result = Compare(x, y, s => CleanArticles(s.Name).Equals(CleanArticles(SearchQuery)));
|
||||
if (result != 0)
|
||||
{
|
||||
return -result;
|
||||
}
|
||||
|
||||
// Prefer close matches
|
||||
result = Compare(x, y, s => CleanPunctuation(s.Name).LevenshteinDistance(CleanPunctuation(SearchQuery)) <= 1);
|
||||
if (result != 0)
|
||||
{
|
||||
return -result;
|
||||
}
|
||||
|
||||
return Compare(x, y, s => SearchQuery.LevenshteinDistanceClean(s.Name));
|
||||
}
|
||||
|
||||
public int Compare<T>(Author x, Author y, Func<Author, T> keySelector)
|
||||
where T : IComparable<T>
|
||||
{
|
||||
var keyX = keySelector(x);
|
||||
var keyY = keySelector(y);
|
||||
|
||||
return keyX.CompareTo(keyY);
|
||||
}
|
||||
|
||||
private string CleanPunctuation(string title)
|
||||
{
|
||||
title = RegexCleanPunctuation.Replace(title, "");
|
||||
|
||||
return title.ToLowerInvariant();
|
||||
}
|
||||
|
||||
private string CleanTitle(string title)
|
||||
{
|
||||
title = RegexCleanPunctuation.Replace(title, "");
|
||||
title = RegexCleanCountryYearPostfix.Replace(title, "");
|
||||
|
||||
return title.ToLowerInvariant();
|
||||
}
|
||||
|
||||
private string CleanArticles(string title)
|
||||
{
|
||||
title = ArticleRegex.Replace(title, "");
|
||||
|
||||
return title.Trim().ToLowerInvariant();
|
||||
}
|
||||
}
|
||||
}
|
||||
Loading…
Reference in new issue