ortools-clone/ortools/lp_data/sparse_column.h

// Copyright 2010-2024 Google LLC
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.

#ifndef OR_TOOLS_LP_DATA_SPARSE_COLUMN_H_
#define OR_TOOLS_LP_DATA_SPARSE_COLUMN_H_

#include <vector>

#include "ortools/lp_data/lp_types.h"
#include "ortools/lp_data/permutation.h"
#include "ortools/lp_data/sparse_vector.h"

namespace operations_research {
namespace glop {

// TODO(user): Consider using kInvalidRow for this?
const RowIndex kNonPivotal(-1);

// Specialization of SparseVectorEntry and SparseColumnIterator for the
// SparseColumn class. In addition to index(), it also provides row() for better
// readability on the client side.
class SparseColumnEntry : public SparseVectorEntry<RowIndex> {
 public:
  // Returns the row of the current entry.
  RowIndex row() const { return index(); }

 protected:
  SparseColumnEntry(const RowIndex* indices, const Fractional* coefficients,
                    EntryIndex i)
      : SparseVectorEntry<RowIndex>(indices, coefficients, i) {}
};
using SparseColumnIterator = VectorIterator<SparseColumnEntry>;

class ColumnView;

// A SparseColumn is a SparseVector<RowIndex>, with a few methods renamed
// to help readability on the client side.
class SparseColumn : public SparseVector<RowIndex, SparseColumnIterator> {
  friend class ColumnView;

 public:
  SparseColumn() : SparseVector<RowIndex, SparseColumnIterator>() {}

  // Use a separate API to get the row and coefficient of entry #i.
  RowIndex EntryRow(EntryIndex i) const { return GetIndex(i); }
  Fractional EntryCoefficient(EntryIndex i) const { return GetCoefficient(i); }
  RowIndex GetFirstRow() const { return GetFirstIndex(); }
  RowIndex GetLastRow() const { return GetLastIndex(); }
  void ApplyRowPermutation(const RowPermutation& p) {
    ApplyIndexPermutation(p);
  }
  void ApplyPartialRowPermutation(const RowPermutation& p) {
    ApplyPartialIndexPermutation(p);
  }
};

// Class to iterate on the entries of a given column with the same interface
// as for SparseColumn.
class ColumnView {
 public:
  // Clients should pass Entry by value rather than by reference.
  // This is because SparseColumnEntry is small (2 pointers and an index) and
  // previous profiling of this type of use showed no performance penalty
  // (see cl/51057736).
  // Example: for(const Entry e : column_view)
  typedef SparseColumnEntry Entry;
  typedef VectorIterator<Entry> Iterator;

  ColumnView(EntryIndex num_entries, const RowIndex* rows,
             const Fractional* const coefficients)
      : num_entries_(num_entries), rows_(rows), coefficients_(coefficients) {}
  explicit ColumnView(const SparseColumn& column)
      : num_entries_(column.num_entries()),
        rows_(column.index_),
        coefficients_(column.coefficient_) {}
  EntryIndex num_entries() const { return num_entries_; }
  Fractional EntryCoefficient(EntryIndex i) const {
    return coefficients_[i.value()];
  }
  Fractional GetFirstCoefficient() const {
    return EntryCoefficient(EntryIndex(0));
  }
  RowIndex EntryRow(EntryIndex i) const { return rows_[i.value()]; }
  RowIndex GetFirstRow() const { return EntryRow(EntryIndex(0)); }

  Iterator begin() const {
    return Iterator(this->rows_, this->coefficients_, EntryIndex(0));
  }

  Iterator end() const {
    return Iterator(this->rows_, this->coefficients_, num_entries_);
  }

  Fractional LookUpCoefficient(RowIndex index) const {
    Fractional value(0.0);
    for (const auto e : *this) {
      if (e.row() == index) {
        // Keep in mind the vector may contains several entries with the same
        // index. In such a case the last one is returned.
        // TODO(user): investigate whether an optimized version of
        // LookUpCoefficient for "clean" columns yields speed-ups.
        value = e.coefficient();
      }
    }
    return value;
  }

  bool IsEmpty() const { return num_entries_ == EntryIndex(0); }

 private:
  const EntryIndex num_entries_;
  const RowIndex* const rows_;
  const Fractional* const coefficients_;
};

// --------------------------------------------------------
// RandomAccessSparseColumn
// --------------------------------------------------------
// A RandomAccessSparseColumn is a mix between a DenseColumn and a SparseColumn.
// It makes it possible to populate a dense column from a sparse column in
// O(num_entries) instead of O(num_rows), and to access an entry in O(1).
// As the constructor runs in O(num_rows), a RandomAccessSparseColumn should be
// used several times to amortize the creation cost.
class RandomAccessSparseColumn {
 public:
  // Creates a RandomAccessSparseColumn.
  // Runs in O(num_rows).
  explicit RandomAccessSparseColumn(RowIndex num_rows);

  // This type is neither copyable nor movable.
  RandomAccessSparseColumn(const RandomAccessSparseColumn&) = delete;
  RandomAccessSparseColumn& operator=(const RandomAccessSparseColumn&) = delete;

  virtual ~RandomAccessSparseColumn();

  // Clears the column.
  // Runs in O(num_entries).
  void Clear();

  void Resize(RowIndex num_rows);

  // Sets value at row.
  // Runs in O(1).
  void SetCoefficient(RowIndex row, Fractional value) {
    column_[row] = value;
    MarkRowAsChanged(row);
  }

  // Adds value to the current value at row.
  // Runs in O(1).
  void AddToCoefficient(RowIndex row, Fractional value) {
    column_[row] += value;
    MarkRowAsChanged(row);
  }

  // Populates from a sparse column.
  // Runs in O(num_entries).
  void PopulateFromSparseColumn(const SparseColumn& sparse_column);

  // Populates a sparse column from the lazy dense column.
  // Runs in O(num_entries).
  void PopulateSparseColumn(SparseColumn* sparse_column) const;

  // Returns the number of rows.
  // Runs in O(1).
  RowIndex GetNumberOfRows() const { return RowIndex(column_.size()); }

  // Returns the value in position row.
  // Runs in O(1).
  Fractional GetCoefficient(RowIndex row) const { return column_[row]; }

 private:
  // Keeps a trace of which rows have been changed.
  void MarkRowAsChanged(RowIndex row) {
    if (!changed_[row]) {
      changed_[row] = true;
      row_change_.push_back(row);
    }
  }

  // The dense version of the column.
  DenseColumn column_;

  // Dense Boolean vector used to mark changes.
  DenseBooleanColumn changed_;

  // Stack to store changes.
  std::vector<RowIndex> row_change_;
};

}  // namespace glop
}  // namespace operations_research

#endif  // OR_TOOLS_LP_DATA_SPARSE_COLUMN_H_