LinearExpr.java

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// Copyright 2010-2021 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.
 
package com.google.ortools.sat;
 
import com.google.ortools.sat.CpModelProto;
import com.google.ortools.sat.LinearExpressionProto;
 
public interface LinearExpr {
  int numElements();
 
  IntVar getVariable(int index);
 
  long getCoefficient(int index);
 
  long getOffset();
 
  static LinearExpr sum(IntVar[] variables) {
    return new SumOfVariables(variables);
  }
 
  static LinearExpr booleanSum(Literal[] literals) {
    // We need the scalar product for the negative coefficient of negated Boolean variables.
    return new ScalProd(literals);
  }
 
  static LinearExpr scalProd(IntVar[] variables, long[] coefficients) {
    if (variables.length != coefficients.length) {
      throw new CpModel.MismatchedArrayLengths("LinearExpr.scalProd", "variables", "coefficients");
    }
    return new ScalProd(variables, coefficients);
  }
 
  static LinearExpr scalProd(IntVar[] variables, int[] coefficients) {
    if (variables.length != coefficients.length) {
      throw new CpModel.MismatchedArrayLengths("LinearExpr.scalProd", "variables", "coefficients");
    }
    long[] tmp = new long[coefficients.length];
    for (int i = 0; i < coefficients.length; ++i) {
      tmp[i] = coefficients[i];
    }
    return new ScalProd(variables, tmp);
  }
 
  static LinearExpr booleanScalProd(Literal[] literals, long[] coefficients) {
    if (literals.length != coefficients.length) {
      throw new CpModel.MismatchedArrayLengths("LinearExpr.scalProd", "literals", "coefficients");
    }
    return new ScalProd(literals, coefficients);
  }
 
  static LinearExpr booleanScalProd(Literal[] literals, int[] coefficients) {
    if (literals.length != coefficients.length) {
      throw new CpModel.MismatchedArrayLengths("LinearExpr.scalProd", "literals", "coefficients");
    }
 
    long[] tmp = new long[coefficients.length];
    for (int i = 0; i < coefficients.length; ++i) {
      tmp[i] = coefficients[i];
    }
    return new ScalProd(literals, tmp);
  }
 
  static LinearExpr term(IntVar variable, long coefficient) {
    return new ScalProd(variable, coefficient, 0);
  }
 
  static LinearExpr term(Literal lit, long coefficient) {
    return new ScalProd(lit, coefficient, 0);
  }
 
  static LinearExpr affine(IntVar variable, long coefficient, long offset) {
    return new ScalProd(variable, coefficient, offset);
  }
 
  static LinearExpr affine(Literal lit, long coefficient, long offset) {
    return new ScalProd(lit, coefficient, offset);
  }
 
  static LinearExpr constant(long value) {
    return new Constant(value);
  }
 
  static LinearExpr rebuildFromLinearExpressionProto(
      LinearExpressionProto proto, CpModelProto.Builder builder) {
    int numElements = proto.getVarsCount();
    if (numElements == 0) {
      return constant(proto.getOffset());
    } else if (numElements == 1) {
      return affine(new IntVar(builder, proto.getVars(0)), proto.getCoeffs(0), proto.getOffset());
    } else {
      IntVar[] vars = new IntVar[numElements];
      long[] coeffs = new long[numElements];
      long offset = proto.getOffset();
      boolean allOnes = true;
      for (int i = 0; i < numElements; ++i) {
        vars[i] = new IntVar(builder, proto.getVars(i));
        coeffs[i] = proto.getCoeffs(i);
        if (coeffs[i] != 1) {
          allOnes = false;
        }
      }
      if (allOnes) {
        return new SumOfVariables(vars, offset);
      } else {
        return new ScalProd(vars, coeffs, offset);
      }
    }
  }
}