c34026b101
note: done using ```sh git grep -l "2010-2024 Google" | xargs sed -i 's/2010-2024 Google/2010-2025 Google/' ```
59 lines
2.6 KiB
C++
59 lines
2.6 KiB
C++
// Copyright 2010-2025 Google LLC
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of 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,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef OR_TOOLS_LP_DATA_MATRIX_UTILS_H_
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#define OR_TOOLS_LP_DATA_MATRIX_UTILS_H_
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#include "ortools/lp_data/lp_types.h"
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#include "ortools/lp_data/sparse.h"
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namespace operations_research {
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namespace glop {
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// Finds the proportional columns of the given matrix: all the pairs of columns
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// such that one is a non-zero scalar multiple of the other. The returned
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// mapping for a given column will either be:
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// - The index of the first column which is proportional with this one.
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// - Or kInvalidCol if this column is not proportional to any other.
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//
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// Because of precision errors, two columns are declared proportional if the
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// multiples (>= 1.0) defined by all the couple of coefficients of the same row
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// are equal up to the given absolute tolerance.
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//
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// The complexity is in most cases O(num entries of the matrix). However,
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// compared to the less efficient algorithm below, it is highly unlikely but
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// possible that some pairs of proportional columns are not detected.
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ColMapping FindProportionalColumns(const SparseMatrix& matrix,
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Fractional tolerance);
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// A simple version of FindProportionalColumns() that compares all the columns
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// pairs one by one. This is slow, but here for reference. The complexity is
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// O(num_cols * num_entries).
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ColMapping FindProportionalColumnsUsingSimpleAlgorithm(
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const SparseMatrix& matrix, Fractional tolerance);
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// Returns true iff the two given matrices have exactly the same first num_rows
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// entries on the first num_cols columns. The two given matrices must be ordered
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// by rows (this is DCHECKed, but only for the first one at this point).
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bool AreFirstColumnsAndRowsExactlyEquals(RowIndex num_rows, ColIndex num_cols,
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const SparseMatrix& matrix_a,
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const CompactSparseMatrix& matrix_b);
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// Returns true iff the rightmost square matrix is an identity matrix.
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bool IsRightMostSquareMatrixIdentity(const SparseMatrix& matrix);
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} // namespace glop
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} // namespace operations_research
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#endif // OR_TOOLS_LP_DATA_MATRIX_UTILS_H_
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