internal override Entity InnerEval()
{
var r = DeepCopy() as Tensor;
TensorFunctional.Apply(r, e => e.InnerEval());
return(r);
}
/// <summary>
/// Collapses the entire expression into a tensor if possible
/// ( x y ) + 1 => ( x+1 y+1 )
///
/// ( 1 2 ) + ( 3 4 ) => ( 4 6 ) vectors pointwise
///
/// (( 3 )
/// (( 1 2 3 )) x ( 4 ) => (( 26 )) Matrices dot product
/// ( 5 ))
///
/// ( 1 2 ) x ( 1 3 ) => ( 1 6 ) Vectors pointwise
/// </summary>
/// <returns></returns>
public Tensor EvalTensor()
{
if (!IsTensoric())
{
throw new MathSException(
"To eval an expression as a tensor, it should contain at least one tensor (matrix, vector)");
}
if (entType == EntType.TENSOR)
{
Tensor result = this as Tensor;
TensorFunctional.Apply(result, p => MathS.CanBeEvaluated(p) ? p.Eval() : p);
return(result);
}
var r = DeepCopy();
TensorFunctional.__EvalTensor(ref r);
if (r.entType == EntType.TENSOR)
{
Tensor result = r as Tensor;
TensorFunctional.Apply(result, p => MathS.CanBeEvaluated(p) ? p.Eval() : p);
return(result);
}
else
{
throw new SysException("Unexpected behaviour");
}
}
/// <summary>
/// Compares two Tensors
/// </summary>
/// <param name="obj"></param>
/// <returns></returns>
protected override bool EqualsTo(Entity obj)
{
var t = obj as Tensor;
if (!TensorFunctional.SameShape(this, t))
{
return(false);
}
for (int i = 0; i < Data.Length; i++)
{
if (Data[i] != t.Data[i])
{
return(false);
}
}
return(true);
}
/// <summary> /// Returns scalar product of two matrices /// </summary> /// <param name="A"></param> /// <param name="B"></param> /// <returns></returns> public static Entity ScalarProduct(Tensor A, Tensor B) => TensorFunctional.ScalarProduct(A, B);
/// <summary> /// Returns dot product of two matrices /// </summary> /// <param name="A"></param> /// <param name="B"></param> /// <returns></returns> public static Tensor DotProduct(Tensor A, Tensor B) => TensorFunctional.DotProduct(A, B);
/// <summary> /// Creates an instance of vector /// </summary> /// <param name="p"></param> /// <returns></returns> public static Tensor Vector(params Entity[] values) => TensorFunctional.Vector(values);
/// <summary> /// Creates an instance of Tensor: Matrix /// Usage example: /// var t = MathS.Matrix(5, 3, /// 10, 11, 12, /// 20, 21, 22, /// 30, 31, 32, /// 40, 41, 42, /// 50, 51, 52 /// ); /// creates matrix 5x3 with the appropriate elements /// </summary> /// <param name="x"></param> /// <param name="y"></param> /// <returns></returns> public static Tensor Matrix(int rows, int columns, params Entity[] values) => TensorFunctional.Matrix(rows, columns, values);
