package org.djunits.value.vdouble.vector.data;
   
   import java.util.Arrays;
   import java.util.stream.IntStream;
   
   import org.djunits.value.storage.StorageType;
   import org.djunits.value.vdouble.function.DoubleFunction;
   import org.djunits.value.vdouble.function.DoubleFunction2;
   
  /**
   * Stores dense data for a DoubleVector and carries out basic operations.
   * <p>
   * Copyright (c) 2013-2024 Delft University of Technology, PO Box 5, 2600 AA, Delft, the Netherlands. All rights reserved. <br>
   * BSD-style license. See <a href="https://djunits.org/docs/license.html">DJUNITS License</a>.
   * </p>
   * @author <a href="https://www.tudelft.nl/averbraeck">Alexander Verbraeck</a>
   * @author <a href="https://www.tudelft.nl/staff/p.knoppers/">Peter Knoppers</a>
   */
  public class DoubleVectorDataDense extends DoubleVectorData
  {
      /** */
      private static final long serialVersionUID = 1L;
  
      /**
       * Create a vector with dense data.
       * @param vectorSI double[]; the data to store
       */
      public DoubleVectorDataDense(final double[] vectorSI)
      {
          super(StorageType.DENSE);
          this.vectorSI = new double[vectorSI.length];
          System.arraycopy(vectorSI, 0, this.vectorSI, 0, vectorSI.length);
      }
  
      @Override
      public final int cardinality()
      {
          return (int) Arrays.stream(this.vectorSI).parallel().filter(d -> d != 0.0).count();
      }
  
      @Override
      public final DoubleVectorDataDense assign(final DoubleFunction doubleFunction)
      {
          IntStream.range(0, size()).parallel().forEach(i -> this.vectorSI[i] = doubleFunction.apply(this.vectorSI[i]));
          return this;
      }
  
      @Override
      public final DoubleVectorDataDense assign(final DoubleFunction2 doubleFunction2, final DoubleVectorData right)
      {
          if (right.isDense())
          {
              IntStream.range(0, size()).parallel()
                      .forEach(i -> this.vectorSI[i] = doubleFunction2.apply(this.vectorSI[i], right.vectorSI[i]));
          }
          else
          { // right is sparse
              IntStream.range(0, size()).parallel()
                      .forEach(i -> this.vectorSI[i] = doubleFunction2.apply(this.vectorSI[i], right.getSI(i)));
          }
          return this;
      }
  
      @Override
      public final DoubleVectorDataDense toDense()
      {
          return this;
      }
  
      @Override
      public final DoubleVectorDataSparse toSparse()
      {
          return DoubleVectorDataSparse.instantiate(this.vectorSI);
      }
  
      @Override
      public final int size()
      {
          return this.vectorSI.length;
      }
  
      @Override
      public final double getSI(final int index)
      {
          return this.vectorSI[index];
      }
  
      @Override
      public final void setSI(final int index, final double valueSI)
      {
          this.vectorSI[index] = valueSI;
      }
  
      @Override
      public final double[] getDenseVectorSI()
      {
          return this.vectorSI.clone();
      }
  
     @Override
     public final DoubleVectorDataDense copy()
     {
         double[] vCopy = new double[this.vectorSI.length];
         System.arraycopy(this.vectorSI, 0, vCopy, 0, this.vectorSI.length);
         return new DoubleVectorDataDense(vCopy);
     }
 
     @Override
     public final DoubleVectorDataDense plus(final DoubleVectorData right)
     {
         checkSizes(right);
         return new DoubleVectorDataDense(
                 IntStream.range(0, size()).parallel().mapToDouble(i -> getSI(i) + right.getSI(i)).toArray());
     }
 
     @Override
     public final DoubleVectorDataDense minus(final DoubleVectorData right)
     {
         checkSizes(right);
         return new DoubleVectorDataDense(
                 IntStream.range(0, size()).parallel().mapToDouble(i -> getSI(i) - right.getSI(i)).toArray());
     }
 
     @Override
     public final DoubleVectorData times(final DoubleVectorData right)
     {
         if (right.isSparse())
         {
             // result shall be sparse
             return right.times(this);
         }
         // Both are dense
         checkSizes(right);
         return this.copy().multiplyBy(right);
     }
 
     @Override
     public final DoubleVectorData divide(final DoubleVectorData right)
     {
         checkSizes(right);
         return this.copy().divideBy(right);
     }
 
 }