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git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@236392 91177308-0d34-0410-b5e6-96231b3b80d8
103 lines
3.4 KiB
C++
103 lines
3.4 KiB
C++
//===-- llvm/ADT/edit_distance.h - Array edit distance function --- C++ -*-===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// This file defines a Levenshtein distance function that works for any two
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// sequences, with each element of each sequence being analogous to a character
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// in a string.
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//
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//===----------------------------------------------------------------------===//
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#ifndef LLVM_ADT_EDIT_DISTANCE_H
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#define LLVM_ADT_EDIT_DISTANCE_H
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#include "llvm/ADT/ArrayRef.h"
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#include <algorithm>
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#include <memory>
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namespace llvm {
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/// \brief Determine the edit distance between two sequences.
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///
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/// \param FromArray the first sequence to compare.
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///
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/// \param ToArray the second sequence to compare.
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///
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/// \param AllowReplacements whether to allow element replacements (change one
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/// element into another) as a single operation, rather than as two operations
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/// (an insertion and a removal).
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///
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/// \param MaxEditDistance If non-zero, the maximum edit distance that this
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/// routine is allowed to compute. If the edit distance will exceed that
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/// maximum, returns \c MaxEditDistance+1.
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///
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/// \returns the minimum number of element insertions, removals, or (if
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/// \p AllowReplacements is \c true) replacements needed to transform one of
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/// the given sequences into the other. If zero, the sequences are identical.
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template<typename T>
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unsigned ComputeEditDistance(ArrayRef<T> FromArray, ArrayRef<T> ToArray,
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bool AllowReplacements = true,
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unsigned MaxEditDistance = 0) {
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// The algorithm implemented below is the "classic"
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// dynamic-programming algorithm for computing the Levenshtein
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// distance, which is described here:
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//
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// http://en.wikipedia.org/wiki/Levenshtein_distance
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//
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// Although the algorithm is typically described using an m x n
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// array, only two rows are used at a time, so this implementation
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// just keeps two separate vectors for those two rows.
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typename ArrayRef<T>::size_type m = FromArray.size();
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typename ArrayRef<T>::size_type n = ToArray.size();
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const unsigned SmallBufferSize = 64;
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unsigned SmallBuffer[SmallBufferSize];
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std::unique_ptr<unsigned[]> Allocated;
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unsigned *Previous = SmallBuffer;
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if (2*(n + 1) > SmallBufferSize) {
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Previous = new unsigned [2*(n+1)];
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Allocated.reset(Previous);
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}
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unsigned *Current = Previous + (n + 1);
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for (unsigned i = 0; i <= n; ++i)
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Previous[i] = i;
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for (typename ArrayRef<T>::size_type y = 1; y <= m; ++y) {
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Current[0] = y;
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unsigned BestThisRow = Current[0];
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for (typename ArrayRef<T>::size_type x = 1; x <= n; ++x) {
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if (AllowReplacements) {
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Current[x] = std::min(
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Previous[x-1] + (FromArray[y-1] == ToArray[x-1] ? 0u : 1u),
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std::min(Current[x-1], Previous[x])+1);
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}
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else {
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if (FromArray[y-1] == ToArray[x-1]) Current[x] = Previous[x-1];
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else Current[x] = std::min(Current[x-1], Previous[x]) + 1;
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}
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BestThisRow = std::min(BestThisRow, Current[x]);
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}
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if (MaxEditDistance && BestThisRow > MaxEditDistance)
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return MaxEditDistance + 1;
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unsigned *tmp = Current;
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Current = Previous;
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Previous = tmp;
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}
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unsigned Result = Previous[n];
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return Result;
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}
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} // End llvm namespace
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#endif
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