// <copyright file="SparseVectorStorage.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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//
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// Copyright (c) 2009-2015 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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using System;
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using System.Collections.Generic;
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using System.Diagnostics;
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using System.Linq;
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using System.Runtime.Serialization;
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using IStation.Numerics.Threading;
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namespace IStation.Numerics.LinearAlgebra.Storage
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{
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[Serializable]
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[DataContract(Namespace = "urn:IStation/Numerics/LinearAlgebra")]
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public class SparseVectorStorage<T> : VectorStorage<T>
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where T : struct, IEquatable<T>, IFormattable
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{
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// [ruegg] public fields are OK here
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/// <summary>
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/// Array that contains the indices of the non-zero values.
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/// </summary>
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[DataMember(Order = 1)]
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public int[] Indices;
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/// <summary>
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/// Array that contains the non-zero elements of the vector.
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/// </summary>
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[DataMember(Order = 2)]
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public T[] Values;
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/// <summary>
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/// Gets the number of non-zero elements in the vector.
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/// </summary>
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[DataMember(Order = 3)]
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public int ValueCount;
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internal SparseVectorStorage(int length)
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: base(length)
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{
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Indices = new int[0];
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Values = new T[0];
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ValueCount = 0;
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}
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/// <summary>
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/// True if the vector storage format is dense.
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/// </summary>
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public override bool IsDense => false;
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/// <summary>
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/// Retrieves the requested element without range checking.
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/// </summary>
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public override T At(int index)
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{
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// Search if item index exists in NonZeroIndices array in range "0 - nonzero values count"
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var itemIndex = Array.BinarySearch(Indices, 0, ValueCount, index);
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return itemIndex >= 0 ? Values[itemIndex] : Zero;
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}
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/// <summary>
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/// Sets the element without range checking.
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/// </summary>
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public override void At(int index, T value)
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{
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// Search if "index" already exists in range "0 - nonzero values count"
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var itemIndex = Array.BinarySearch(Indices, 0, ValueCount, index);
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if (itemIndex >= 0)
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{
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// Non-zero item found in matrix
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if (Zero.Equals(value))
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{
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// Delete existing item
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RemoveAtIndexUnchecked(itemIndex);
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}
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else
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{
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// Update item
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Values[itemIndex] = value;
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}
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}
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else
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{
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// Item not found. Add new value
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if (!Zero.Equals(value))
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{
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InsertAtIndexUnchecked(~itemIndex, index, value);
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}
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}
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}
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internal void InsertAtIndexUnchecked(int itemIndex, int index, T value)
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{
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// Check if the storage needs to be increased
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if ((ValueCount == Values.Length) && (ValueCount < Length))
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{
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// Value and Indices arrays are completely full so we increase the size
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var size = Math.Min(Values.Length + GrowthSize(), Length);
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Array.Resize(ref Values, size);
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Array.Resize(ref Indices, size);
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}
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// Move all values (with a position larger than index) in the value array to the next position
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// Move all values (with a position larger than index) in the columIndices array to the next position
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Array.Copy(Values, itemIndex, Values, itemIndex + 1, ValueCount - itemIndex);
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Array.Copy(Indices, itemIndex, Indices, itemIndex + 1, ValueCount - itemIndex);
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// Add the value and the column index
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Values[itemIndex] = value;
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Indices[itemIndex] = index;
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// increase the number of non-zero numbers by one
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ValueCount += 1;
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}
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internal void RemoveAtIndexUnchecked(int itemIndex)
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{
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// Value is zero. Let's delete it from Values and Indices array
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Array.Copy(Values, itemIndex + 1, Values, itemIndex, ValueCount - itemIndex - 1);
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Array.Copy(Indices, itemIndex + 1, Indices, itemIndex, ValueCount - itemIndex - 1);
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ValueCount -= 1;
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// Check whether we need to shrink the arrays. This is reasonable to do if
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// there are a lot of non-zero elements and storage is two times bigger
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if ((ValueCount > 1024) && (ValueCount < Indices.Length / 2))
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{
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Array.Resize(ref Values, ValueCount);
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Array.Resize(ref Indices, ValueCount);
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}
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}
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/// <summary>
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/// Calculates the amount with which to grow the storage array's if they need to be
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/// increased in size.
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/// </summary>
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/// <returns>The amount grown.</returns>
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int GrowthSize()
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{
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int delta;
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if (Values.Length > 1024)
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{
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delta = Values.Length / 4;
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}
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else
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{
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if (Values.Length > 256)
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{
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delta = 512;
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}
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else
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{
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delta = Values.Length > 64 ? 128 : 32;
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}
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}
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return delta;
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}
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public override bool Equals(VectorStorage<T> other)
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{
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// Reject equality when the argument is null or has a different shape.
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if (other == null || Length != other.Length)
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{
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return false;
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}
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// Accept if the argument is the same object as this.
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if (ReferenceEquals(this, other))
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{
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return true;
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}
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if (other is SparseVectorStorage<T> otherSparse)
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{
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int i = 0, j = 0;
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while (i < ValueCount || j < otherSparse.ValueCount)
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{
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if (j >= otherSparse.ValueCount || i < ValueCount && Indices[i] < otherSparse.Indices[j])
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{
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if (!Zero.Equals(Values[i++]))
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{
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return false;
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}
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continue;
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}
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if (i >= ValueCount || j < otherSparse.ValueCount && otherSparse.Indices[j] < Indices[i])
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{
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if (!Zero.Equals(otherSparse.Values[j++]))
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{
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return false;
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}
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continue;
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}
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if (!Values[i].Equals(otherSparse.Values[j]))
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{
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return false;
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}
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i++;
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j++;
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}
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return true;
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}
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return base.Equals(other);
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}
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/// <summary>
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/// Returns a hash code for this instance.
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/// </summary>
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/// <returns>
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/// A hash code for this instance, suitable for use in hashing algorithms and data structures like a hash table.
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/// </returns>
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public override int GetHashCode()
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{
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var values = Values;
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var hashNum = Math.Min(ValueCount, 25);
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int hash = 17;
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unchecked
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{
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for (var i = 0; i < hashNum; i++)
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{
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hash = hash * 31 + values[i].GetHashCode();
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}
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}
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return hash;
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}
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// CLEARING
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public override void Clear()
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{
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ValueCount = 0;
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}
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public override void Clear(int index, int count)
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{
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if (index == 0 && count == Length)
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{
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Clear();
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return;
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}
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var first = Array.BinarySearch(Indices, 0, ValueCount, index);
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var last = Array.BinarySearch(Indices, 0, ValueCount, index + count - 1);
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if (first < 0) first = ~first;
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if (last < 0) last = ~last - 1;
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int itemCount = last - first + 1;
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if (itemCount > 0)
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{
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Array.Copy(Values, first + itemCount, Values, first, ValueCount - first - itemCount);
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Array.Copy(Indices, first + itemCount, Indices, first, ValueCount - first - itemCount);
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ValueCount -= itemCount;
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}
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// Check whether we need to shrink the arrays. This is reasonable to do if
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// there are a lot of non-zero elements and storage is two times bigger
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if ((ValueCount > 1024) && (ValueCount < Indices.Length / 2))
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{
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Array.Resize(ref Values, ValueCount);
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Array.Resize(ref Indices, ValueCount);
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}
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}
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// INITIALIZATION
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public static SparseVectorStorage<T> OfVector(VectorStorage<T> vector)
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{
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var storage = new SparseVectorStorage<T>(vector.Length);
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vector.CopyToUnchecked(storage, ExistingData.AssumeZeros);
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return storage;
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}
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public static SparseVectorStorage<T> OfValue(int length, T value)
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{
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if (Zero.Equals(value))
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{
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return new SparseVectorStorage<T>(length);
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}
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if (length < 0)
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{
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throw new ArgumentOutOfRangeException(nameof(length), "Value must not be negative (zero is ok).");
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}
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var indices = new int[length];
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var values = new T[length];
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for (int i = 0; i < indices.Length; i++)
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{
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indices[i] = i;
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values[i] = value;
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}
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return new SparseVectorStorage<T>(length)
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{
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Indices = indices,
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Values = values,
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ValueCount = length
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};
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}
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public static SparseVectorStorage<T> OfInit(int length, Func<int, T> init)
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{
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if (length < 0)
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{
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throw new ArgumentOutOfRangeException(nameof(length), "Value must not be negative (zero is ok).");
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}
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var indices = new List<int>();
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var values = new List<T>();
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for (int i = 0; i < length; i++)
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{
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var item = init(i);
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if (!Zero.Equals(item))
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{
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values.Add(item);
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indices.Add(i);
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}
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}
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return new SparseVectorStorage<T>(length)
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{
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Indices = indices.ToArray(),
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Values = values.ToArray(),
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ValueCount = values.Count
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};
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}
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public static SparseVectorStorage<T> OfEnumerable(IEnumerable<T> data)
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{
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if (data == null)
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{
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throw new ArgumentNullException(nameof(data));
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}
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var indices = new List<int>();
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var values = new List<T>();
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int index = 0;
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foreach (T item in data)
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{
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if (!Zero.Equals(item))
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{
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values.Add(item);
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indices.Add(index);
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}
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index++;
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}
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return new SparseVectorStorage<T>(index)
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{
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Indices = indices.ToArray(),
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Values = values.ToArray(),
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ValueCount = values.Count
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};
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}
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public static SparseVectorStorage<T> OfIndexedEnumerable(int length, IEnumerable<Tuple<int, T>> data)
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{
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if (data == null)
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{
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throw new ArgumentNullException(nameof(data));
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}
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var indices = new List<int>();
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var values = new List<T>();
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foreach (var item in data)
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{
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if (!Zero.Equals(item.Item2))
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{
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values.Add(item.Item2);
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indices.Add(item.Item1);
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}
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}
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var indicesArray = indices.ToArray();
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var valuesArray = values.ToArray();
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Sorting.Sort(indicesArray, valuesArray);
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return new SparseVectorStorage<T>(length)
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{
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Indices = indicesArray,
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Values = valuesArray,
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ValueCount = values.Count
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};
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}
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// VECTOR COPY
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internal override void CopyToUnchecked(VectorStorage<T> target, ExistingData existingData)
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{
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if (target is SparseVectorStorage<T> sparseTarget)
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{
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CopyToUnchecked(sparseTarget);
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return;
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}
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// FALL BACK
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if (existingData == ExistingData.Clear)
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{
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target.Clear();
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}
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if (ValueCount != 0)
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{
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for (int i = 0; i < ValueCount; i++)
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{
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target.At(Indices[i], Values[i]);
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}
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}
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}
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void CopyToUnchecked(SparseVectorStorage<T> target)
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{
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if (ReferenceEquals(this, target))
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{
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return;
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}
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if (Length != target.Length)
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{
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var message = $"Matrix dimensions must agree: op1 is {Length}, op2 is {target.Length}.";
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throw new ArgumentException(message, nameof(target));
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}
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target.ValueCount = ValueCount;
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target.Values = new T[ValueCount];
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target.Indices = new int[ValueCount];
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if (ValueCount != 0)
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{
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Array.Copy(Values, 0, target.Values, 0, ValueCount);
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Buffer.BlockCopy(Indices, 0, target.Indices, 0, ValueCount * Constants.SizeOfInt);
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}
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}
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// Row COPY
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internal override void CopyToRowUnchecked(MatrixStorage<T> target, int rowIndex, ExistingData existingData)
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{
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if (existingData == ExistingData.Clear)
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{
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target.ClearUnchecked(rowIndex, 1, 0, Length);
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}
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if (ValueCount == 0)
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{
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return;
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}
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for (int i = 0; i < ValueCount; i++)
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{
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target.At(rowIndex, Indices[i], Values[i]);
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}
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}
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// COLUMN COPY
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internal override void CopyToColumnUnchecked(MatrixStorage<T> target, int columnIndex, ExistingData existingData)
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{
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if (existingData == ExistingData.Clear)
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{
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target.ClearUnchecked(0, Length, columnIndex, 1);
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}
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if (ValueCount == 0)
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{
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return;
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}
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for (int i = 0; i < ValueCount; i++)
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{
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target.At(Indices[i], columnIndex, Values[i]);
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}
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}
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// SUB-VECTOR COPY
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internal override void CopySubVectorToUnchecked(VectorStorage<T> target,
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int sourceIndex, int targetIndex, int count, ExistingData existingData)
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{
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if (target is SparseVectorStorage<T> sparseTarget)
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{
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CopySubVectorToUnchecked(sparseTarget, sourceIndex, targetIndex, count, existingData);
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return;
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}
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// FALL BACK
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var offset = targetIndex - sourceIndex;
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var sourceFirst = Array.BinarySearch(Indices, 0, ValueCount, sourceIndex);
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var sourceLast = Array.BinarySearch(Indices, 0, ValueCount, sourceIndex + count - 1);
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if (sourceFirst < 0) sourceFirst = ~sourceFirst;
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if (sourceLast < 0) sourceLast = ~sourceLast - 1;
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if (existingData == ExistingData.Clear)
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{
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target.Clear(targetIndex, count);
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}
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for (int i = sourceFirst; i <= sourceLast; i++)
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{
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target.At(Indices[i] + offset, Values[i]);
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}
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}
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void CopySubVectorToUnchecked(SparseVectorStorage<T> target,
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int sourceIndex, int targetIndex, int count,
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ExistingData existingData)
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{
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var offset = targetIndex - sourceIndex;
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var sourceFirst = Array.BinarySearch(Indices, 0, ValueCount, sourceIndex);
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var sourceLast = Array.BinarySearch(Indices, 0, ValueCount, sourceIndex + count - 1);
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if (sourceFirst < 0) sourceFirst = ~sourceFirst;
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if (sourceLast < 0) sourceLast = ~sourceLast - 1;
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int sourceCount = sourceLast - sourceFirst + 1;
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// special case when copying to itself
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if (ReferenceEquals(this, target))
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{
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var values = new T[sourceCount];
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var indices = new int[sourceCount];
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Array.Copy(Values, sourceFirst, values, 0, sourceCount);
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for (int i = 0; i < indices.Length; i++)
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{
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indices[i] = Indices[i + sourceFirst];
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}
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if (existingData == ExistingData.Clear)
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{
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Clear(targetIndex, count);
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}
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for (int i = sourceFirst; i <= sourceLast; i++)
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{
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At(indices[i] + offset, values[i]);
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}
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return;
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}
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// special case for empty target - much faster
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if (target.ValueCount == 0)
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{
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var values = new T[sourceCount];
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var indices = new int[sourceCount];
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Array.Copy(Values, sourceFirst, values, 0, sourceCount);
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for (int i = 0; i < indices.Length; i++)
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{
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indices[i] = Indices[i + sourceFirst] + offset;
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}
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target.ValueCount = sourceCount;
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target.Values = values;
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target.Indices = indices;
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return;
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}
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if (existingData == ExistingData.Clear)
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{
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target.Clear(targetIndex, count);
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}
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for (int i = sourceFirst; i <= sourceLast; i++)
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{
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target.At(Indices[i] + offset, Values[i]);
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}
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}
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// EXTRACT
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public override T[] ToArray()
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{
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var ret = new T[Length];
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for (int i = 0; i < ValueCount; i++)
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{
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ret[Indices[i]] = Values[i];
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}
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return ret;
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}
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// ENUMERATION
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public override IEnumerable<T> Enumerate()
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{
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int k = 0;
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for (int i = 0; i < Length; i++)
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{
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yield return k < ValueCount && Indices[k] == i
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? Values[k++]
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: Zero;
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}
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}
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public override IEnumerable<Tuple<int, T>> EnumerateIndexed()
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{
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int k = 0;
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for (int i = 0; i < Length; i++)
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{
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yield return k < ValueCount && Indices[k] == i
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? new Tuple<int, T>(i, Values[k++])
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: new Tuple<int, T>(i, Zero);
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}
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}
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public override IEnumerable<T> EnumerateNonZero()
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{
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return Values.Take(ValueCount).Where(x => !Zero.Equals(x));
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}
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public override IEnumerable<Tuple<int, T>> EnumerateNonZeroIndexed()
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{
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for (var i = 0; i < ValueCount; i++)
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{
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if (!Zero.Equals(Values[i]))
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{
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yield return new Tuple<int, T>(Indices[i], Values[i]);
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}
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}
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}
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// FIND
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public override Tuple<int, T> Find(Func<T, bool> predicate, Zeros zeros)
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{
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for (int i = 0; i < ValueCount; i++)
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{
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if (predicate(Values[i]))
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{
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return new Tuple<int, T>(Indices[i], Values[i]);
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}
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}
|
if (zeros == Zeros.Include && ValueCount < Length && predicate(Zero))
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{
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for (int i = 0; i < Length; i++)
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{
|
if (i >= ValueCount || Indices[i] != i)
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{
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return new Tuple<int, T>(i, Zero);
|
}
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}
|
}
|
return null;
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}
|
|
internal override Tuple<int, T, TOther> Find2Unchecked<TOther>(VectorStorage<TOther> other, Func<T, TOther, bool> predicate, Zeros zeros)
|
{
|
if (other is DenseVectorStorage<TOther> denseOther)
|
{
|
TOther[] otherData = denseOther.Data;
|
int k = 0;
|
for (int i = 0; i < otherData.Length; i++)
|
{
|
if (k < ValueCount && Indices[k] == i)
|
{
|
if (predicate(Values[k], otherData[i]))
|
{
|
return new Tuple<int, T, TOther>(i, Values[k], otherData[i]);
|
}
|
k++;
|
}
|
else
|
{
|
if (predicate(Zero, otherData[i]))
|
{
|
return new Tuple<int, T, TOther>(i, Zero, otherData[i]);
|
}
|
}
|
}
|
return null;
|
}
|
|
if (other is SparseVectorStorage<TOther> sparseOther)
|
{
|
int[] otherIndices = sparseOther.Indices;
|
TOther[] otherValues = sparseOther.Values;
|
int otherValueCount = sparseOther.ValueCount;
|
TOther otherZero = BuilderInstance<TOther>.Matrix.Zero;
|
|
// Full Scan
|
int k = 0, otherk = 0;
|
if (zeros == Zeros.Include && ValueCount < Length && sparseOther.ValueCount < Length && predicate(Zero, otherZero))
|
{
|
for (int i = 0; i < Length; i++)
|
{
|
var left = k < ValueCount && Indices[k] == i ? Values[k++] : Zero;
|
var right = otherk < otherValueCount && otherIndices[otherk] == i ? otherValues[otherk++] : otherZero;
|
if (predicate(left, right))
|
{
|
return new Tuple<int, T, TOther>(i, left, right);
|
}
|
}
|
return null;
|
}
|
|
// Sparse Scan
|
k = 0;
|
otherk = 0;
|
while (k < ValueCount || otherk < otherValueCount)
|
{
|
if (k == ValueCount || otherk < otherValueCount && Indices[k] > otherIndices[otherk])
|
{
|
if (predicate(Zero, otherValues[otherk++]))
|
{
|
return new Tuple<int, T, TOther>(otherIndices[otherk - 1], Zero, otherValues[otherk - 1]);
|
}
|
}
|
else if (otherk == otherValueCount || Indices[k] < otherIndices[otherk])
|
{
|
if (predicate(Values[k++], otherZero))
|
{
|
return new Tuple<int, T, TOther>(Indices[k - 1], Values[k - 1], otherZero);
|
}
|
}
|
else
|
{
|
if (predicate(Values[k++], otherValues[otherk++]))
|
{
|
return new Tuple<int, T, TOther>(Indices[k - 1], Values[k - 1], otherValues[otherk - 1]);
|
}
|
}
|
}
|
return null;
|
}
|
|
// FALL BACK
|
|
return base.Find2Unchecked(other, predicate, zeros);
|
}
|
|
// FUNCTIONAL COMBINATORS: MAP
|
|
public override void MapInplace(Func<T, T> f, Zeros zeros)
|
{
|
var indices = new List<int>();
|
var values = new List<T>(ValueCount);
|
if (zeros == Zeros.Include || !Zero.Equals(f(Zero)))
|
{
|
int k = 0;
|
for (int i = 0; i < Length; i++)
|
{
|
var item = k < ValueCount && (Indices[k]) == i ? f(Values[k++]) : f(Zero);
|
if (!Zero.Equals(item))
|
{
|
values.Add(item);
|
indices.Add(i);
|
}
|
}
|
}
|
else
|
{
|
for (int i = 0; i < ValueCount; i++)
|
{
|
var item = f(Values[i]);
|
if (!Zero.Equals(item))
|
{
|
values.Add(item);
|
indices.Add(Indices[i]);
|
}
|
}
|
}
|
Indices = indices.ToArray();
|
Values = values.ToArray();
|
ValueCount = values.Count;
|
}
|
|
public override void MapIndexedInplace(Func<int, T, T> f, Zeros zeros)
|
{
|
var indices = new List<int>();
|
var values = new List<T>(ValueCount);
|
if (zeros == Zeros.Include)
|
{
|
int k = 0;
|
for (int i = 0; i < Length; i++)
|
{
|
var item = k < ValueCount && (Indices[k]) == i ? f(i, Values[k++]) : f(i, Zero);
|
if (!Zero.Equals(item))
|
{
|
values.Add(item);
|
indices.Add(i);
|
}
|
}
|
}
|
else
|
{
|
for (int i = 0; i < ValueCount; i++)
|
{
|
var item = f(Indices[i], Values[i]);
|
if (!Zero.Equals(item))
|
{
|
values.Add(item);
|
indices.Add(Indices[i]);
|
}
|
}
|
}
|
Indices = indices.ToArray();
|
Values = values.ToArray();
|
ValueCount = values.Count;
|
}
|
|
internal override void MapToUnchecked<TU>(VectorStorage<TU> target, Func<T, TU> f, Zeros zeros, ExistingData existingData)
|
{
|
if (target is SparseVectorStorage<TU> sparseTarget)
|
{
|
var indices = new List<int>();
|
var values = new List<TU>();
|
if (zeros == Zeros.Include || !Zero.Equals(f(Zero)))
|
{
|
int k = 0;
|
for (int i = 0; i < Length; i++)
|
{
|
var item = k < ValueCount && (Indices[k]) == i ? f(Values[k++]) : f(Zero);
|
if (!Zero.Equals(item))
|
{
|
values.Add(item);
|
indices.Add(i);
|
}
|
}
|
}
|
else
|
{
|
for (int i = 0; i < ValueCount; i++)
|
{
|
var item = f(Values[i]);
|
if (!Zero.Equals(item))
|
{
|
values.Add(item);
|
indices.Add(Indices[i]);
|
}
|
}
|
}
|
sparseTarget.Indices = indices.ToArray();
|
sparseTarget.Values = values.ToArray();
|
sparseTarget.ValueCount = values.Count;
|
return;
|
}
|
|
if (target is DenseVectorStorage<TU> denseTarget)
|
{
|
if (existingData == ExistingData.Clear)
|
{
|
denseTarget.Clear();
|
}
|
|
if (zeros == Zeros.Include || !Zero.Equals(f(Zero)))
|
{
|
int k = 0;
|
for (int i = 0; i < Length; i++)
|
{
|
denseTarget.Data[i] = k < ValueCount && (Indices[k]) == i
|
? f(Values[k++])
|
: f(Zero);
|
}
|
}
|
else
|
{
|
CommonParallel.For(0, ValueCount, 4096, (a, b) =>
|
{
|
for (int i = a; i < b; i++)
|
{
|
denseTarget.Data[Indices[i]] = f(Values[i]);
|
}
|
});
|
}
|
return;
|
}
|
|
// FALL BACK
|
|
base.MapToUnchecked(target, f, zeros, existingData);
|
}
|
|
internal override void MapIndexedToUnchecked<TU>(VectorStorage<TU> target, Func<int, T, TU> f, Zeros zeros, ExistingData existingData)
|
{
|
if (target is SparseVectorStorage<TU> sparseTarget)
|
{
|
var indices = new List<int>();
|
var values = new List<TU>();
|
if (zeros == Zeros.Include || !Zero.Equals(f(0, Zero)))
|
{
|
int k = 0;
|
for (int i = 0; i < Length; i++)
|
{
|
var item = k < ValueCount && (Indices[k]) == i ? f(i, Values[k++]) : f(i, Zero);
|
if (!Zero.Equals(item))
|
{
|
values.Add(item);
|
indices.Add(i);
|
}
|
}
|
}
|
else
|
{
|
for (int i = 0; i < ValueCount; i++)
|
{
|
var item = f(Indices[i], Values[i]);
|
if (!Zero.Equals(item))
|
{
|
values.Add(item);
|
indices.Add(Indices[i]);
|
}
|
}
|
}
|
sparseTarget.Indices = indices.ToArray();
|
sparseTarget.Values = values.ToArray();
|
sparseTarget.ValueCount = values.Count;
|
return;
|
}
|
|
if (target is DenseVectorStorage<TU> denseTarget)
|
{
|
if (existingData == ExistingData.Clear)
|
{
|
denseTarget.Clear();
|
}
|
|
if (zeros == Zeros.Include || !Zero.Equals(f(0, Zero)))
|
{
|
int k = 0;
|
for (int i = 0; i < Length; i++)
|
{
|
denseTarget.Data[i] = k < ValueCount && (Indices[k]) == i
|
? f(i, Values[k++])
|
: f(i, Zero);
|
}
|
}
|
else
|
{
|
CommonParallel.For(0, ValueCount, 4096, (a, b) =>
|
{
|
for (int i = a; i < b; i++)
|
{
|
denseTarget.Data[Indices[i]] = f(Indices[i], Values[i]);
|
}
|
});
|
}
|
return;
|
}
|
|
// FALL BACK
|
|
base.MapIndexedToUnchecked(target, f, zeros, existingData);
|
}
|
|
internal override void Map2ToUnchecked(VectorStorage<T> target, VectorStorage<T> other, Func<T, T, T> f, Zeros zeros, ExistingData existingData)
|
{
|
var processZeros = zeros == Zeros.Include || !Zero.Equals(f(Zero, Zero));
|
|
var denseTarget = target as DenseVectorStorage<T>;
|
var denseOther = other as DenseVectorStorage<T>;
|
|
if (denseTarget == null && (denseOther != null || processZeros))
|
{
|
// The handling is effectively dense but we're supposed to push
|
// to a sparse target. Let's use a dense target instead,
|
// then copy it normalized back to the sparse target.
|
var intermediate = new DenseVectorStorage<T>(target.Length);
|
Map2ToUnchecked(intermediate, other, f, zeros, ExistingData.AssumeZeros);
|
intermediate.CopyTo(target, existingData);
|
return;
|
}
|
|
if (denseOther != null)
|
{
|
T[] targetData = denseTarget.Data;
|
T[] otherData = denseOther.Data;
|
|
int k = 0;
|
for (int i = 0; i < otherData.Length; i++)
|
{
|
if (k < ValueCount && Indices[k] == i)
|
{
|
targetData[i] = f(Values[k], otherData[i]);
|
k++;
|
}
|
else
|
{
|
targetData[i] = f(Zero, otherData[i]);
|
}
|
}
|
|
return;
|
}
|
|
var sparseOther = other as SparseVectorStorage<T>;
|
if (sparseOther != null && denseTarget != null)
|
{
|
T[] targetData = denseTarget.Data;
|
int[] otherIndices = sparseOther.Indices;
|
T[] otherValues = sparseOther.Values;
|
int otherValueCount = sparseOther.ValueCount;
|
|
if (processZeros)
|
{
|
int p = 0, q = 0;
|
for (int i = 0; i < targetData.Length; i++)
|
{
|
var left = p < ValueCount && Indices[p] == i ? Values[p++] : Zero;
|
var right = q < otherValueCount && otherIndices[q] == i ? otherValues[q++] : Zero;
|
targetData[i] = f(left, right);
|
}
|
}
|
else
|
{
|
if (existingData == ExistingData.Clear)
|
{
|
denseTarget.Clear();
|
}
|
|
int p = 0, q = 0;
|
while (p < ValueCount || q < otherValueCount)
|
{
|
if (q >= otherValueCount || p < ValueCount && Indices[p] < otherIndices[q])
|
{
|
targetData[Indices[p]] = f(Values[p], Zero);
|
p++;
|
}
|
else if (p >= ValueCount || q < otherValueCount && Indices[p] > otherIndices[q])
|
{
|
targetData[otherIndices[q]] = f(Zero, otherValues[q]);
|
q++;
|
}
|
else
|
{
|
Debug.Assert(Indices[p] == otherIndices[q]);
|
targetData[Indices[p]] = f(Values[p], otherValues[q]);
|
p++;
|
q++;
|
}
|
}
|
}
|
|
return;
|
}
|
|
if (sparseOther != null && target is SparseVectorStorage<T> sparseTarget)
|
{
|
var indices = new List<int>();
|
var values = new List<T>();
|
int[] otherIndices = sparseOther.Indices;
|
T[] otherValues = sparseOther.Values;
|
int otherValueCount = sparseOther.ValueCount;
|
|
int p = 0, q = 0;
|
while (p < ValueCount || q < otherValueCount)
|
{
|
if (q >= otherValueCount || p < ValueCount && Indices[p] < otherIndices[q])
|
{
|
var value = f(Values[p], Zero);
|
if (!Zero.Equals(value))
|
{
|
indices.Add(Indices[p]);
|
values.Add(value);
|
}
|
|
p++;
|
}
|
else if (p >= ValueCount || q < otherValueCount && Indices[p] > otherIndices[q])
|
{
|
var value = f(Zero, otherValues[q]);
|
if (!Zero.Equals(value))
|
{
|
indices.Add(otherIndices[q]);
|
values.Add(value);
|
}
|
|
q++;
|
}
|
else
|
{
|
var value = f(Values[p], otherValues[q]);
|
if (!Zero.Equals(value))
|
{
|
indices.Add(Indices[p]);
|
values.Add(value);
|
}
|
|
p++;
|
q++;
|
}
|
}
|
|
sparseTarget.Indices = indices.ToArray();
|
sparseTarget.Values = values.ToArray();
|
sparseTarget.ValueCount = values.Count;
|
return;
|
}
|
|
// FALL BACK
|
|
base.Map2ToUnchecked(target, other, f, zeros, existingData);
|
}
|
|
// FUNCTIONAL COMBINATORS: MAP
|
|
internal override TState Fold2Unchecked<TOther, TState>(VectorStorage<TOther> other, Func<TState, T, TOther, TState> f, TState state, Zeros zeros)
|
{
|
if (other is SparseVectorStorage<TOther> sparseOther)
|
{
|
int[] otherIndices = sparseOther.Indices;
|
TOther[] otherValues = sparseOther.Values;
|
int otherValueCount = sparseOther.ValueCount;
|
TOther otherZero = BuilderInstance<TOther>.Vector.Zero;
|
|
if (zeros == Zeros.Include)
|
{
|
int p = 0, q = 0;
|
for (int i = 0; i < Length; i++)
|
{
|
var left = p < ValueCount && Indices[p] == i ? Values[p++] : Zero;
|
var right = q < otherValueCount && otherIndices[q] == i ? otherValues[q++] : otherZero;
|
state = f(state, left, right);
|
}
|
}
|
else
|
{
|
int p = 0, q = 0;
|
while (p < ValueCount || q < otherValueCount)
|
{
|
if (q >= otherValueCount || p < ValueCount && Indices[p] < otherIndices[q])
|
{
|
state = f(state, Values[p], otherZero);
|
p++;
|
}
|
else if (p >= ValueCount || q < otherValueCount && Indices[p] > otherIndices[q])
|
{
|
state = f(state, Zero, otherValues[q]);
|
q++;
|
}
|
else
|
{
|
Debug.Assert(Indices[p] == otherIndices[q]);
|
state = f(state, Values[p], otherValues[q]);
|
p++;
|
q++;
|
}
|
}
|
}
|
|
return state;
|
}
|
|
if (other is DenseVectorStorage<TOther> denseOther)
|
{
|
TOther[] otherData = denseOther.Data;
|
|
int k = 0;
|
for (int i = 0; i < otherData.Length; i++)
|
{
|
if (k < ValueCount && Indices[k] == i)
|
{
|
state = f(state, Values[k], otherData[i]);
|
k++;
|
}
|
else
|
{
|
state = f(state, Zero, otherData[i]);
|
}
|
}
|
|
return state;
|
}
|
|
return base.Fold2Unchecked(other, f, state, zeros);
|
}
|
}
|
}
|
