private Indexing(Tensor <Type> x, TensorList indices) : base("IndexWith", x, indices)
{
this.Indices = indices;
var indexDim = Indices[0].NDim;
this.Shape = new Dim[indexDim + x.NDim - Indices.Count];
for (int i = 1; i < Indices.Count; ++i)
{
if (!Indices[i].Shape.CanEqualTo(Indices[0].Shape))
{
throw new RankException("In advanced indexing all index array must have the same size");
}
}
// TODO : still TODO ?
for (int i = 0; i < indexDim; ++i)
{
this.Shape[i] = Indices[0].Shape[i];
}
for (int i = NDim - 1; i >= indexDim; --i)
{
this.Shape[i] = x.Shape[x.NDim + i - NDim];
}
}
private Deindexing(Tensor <T> content, XList <Scalar <int>, int> shape, TensorList indices) :
base("Deindex", content, shape, indices)
{
Content = content;
Shape = shape;
Indices = indices;
}
private Dispatch(Scalar <T> content, XList <Scalar <int>, int> shape, TensorList indices) : base("Dispatch", content, shape, indices)
{
Content = content;
Shape = shape;
Indices = indices;
}
/// <param name="x">the scalar expression used to fill the array</param> /// <param name="shape">the shape of the array</param> /// <param name="indices">the indices to fill</param> public static Tensor <T> Create(Scalar <T> x, XList <Scalar <int>, int> shape, TensorList indices) => new Dispatch <T>(x, shape, indices);
public override Binary <Tensor <Type>, Array <Type>, TensorList, Array <int>[]> Clone(Tensor <Type> x, TensorList y) => new Indexing <Type>(x, y);
/// <param name="x">the array to read values from</param>
/// <param name="shape">the shape of the original array</param>
/// <param name="indices">the indices of each values from `x`</param>
public static Tensor <T> Create(Tensor <T> x, XList <Scalar <int>, int> shape, TensorList indices)
{
switch (x)
{
case Fill <T> fill:
return(Dispatch <T> .Create(fill.x, shape, indices));
default:
return(new Deindexing <T>(x, shape, indices));
}
}
