internal TensorIndexExpression(TensorExpression expr) : base(expr.LinqExpression)
{
if (!(expr.LinqExpression is UnaryExpression || expr.LinqExpression is BinaryExpression ||
expr.LinqExpression is MethodCallExpression))
{
throw new ArgumentException("This tensor expression cannot be used as a tensor index expression");
}
ExpressionShape = expr.Shape;
}
public TensorExpression GetDimensionProductExpression()
{
Shape exprShape = this.IndexSet != null ? this.IndexSet.Tensor.Shape : this.ExpressionShape;
TensorExpression mulExpr = exprShape.Count() > 1 ?
(Scalar)exprShape[0] * (Scalar)exprShape[1] : (Scalar)exprShape[0];
for (int i = 2; i < exprShape.Count(); i++)
{
mulExpr = mulExpr * (Scalar)exprShape[i];
}
return(mulExpr);
}
private static MethodCallExpression GetOpMethodCall(string op, params TensorIndexExpression[] args)
{
return(Expression.Call(TensorExpression.GetOpMethodInfo <TensorIndexExpression>("Op_" + op, args.Length),
args.Select(a => Expression.Convert(a, typeof(TensorIndexExpression))).ToArray()));
}
public TensorExpressionException(TensorExpression expr, string message) : base(message)
{
TensorExpression = expr;
}
public static TensorIndexExpression Min(TensorExpression l) =>
new TensorIndexExpression(GetOpMethodCall("Min", (TensorIndexExpression)l), new Dimension(0));
public static TensorIndexExpression Product(TensorExpression l) =>
new TensorIndexExpression(GetOpMethodCall("Product", (TensorIndexExpression)l), new Dimension(0));
public TensorIndexExpression this[TensorExpression e] => Operation(new TensorIndexExpression(e));
public static TensorExpression Square(TensorExpression l) => l * l;
private static TensorExpression Op_Sqrt(TensorExpression l) => null;
public static TensorExpression Sqrt(TensorExpression l) =>
new TensorExpression(Expression.Call(TensorExpression.GetOpMethodInfo <TensorExpression>("Op_Sqrt", 1),
Expression.Convert(l.LinqExpression, typeof(TensorExpression))));
private static TensorIndexExpression DummyBinary(TensorIndexExpression l, TensorExpression r) => null;
