35 references to LogOperator_Single
System.Numerics.Tensors (35)
System\Numerics\Tensors\netcore\TensorPrimitives.Cbrt.cs (6)
37return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector128.Create(3f)).As<float, T>(); 42return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector128.Create(3d)).As<double, T>(); 50return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector256.Create(3f)).As<float, T>(); 55return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector256.Create(3d)).As<double, T>(); 63return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector512.Create(3f)).As<float, T>(); 68return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector512.Create(3d)).As<double, T>();
System\Numerics\Tensors\netcore\TensorPrimitives.Log.cs (7)
33InvokeSpanIntoSpan<T, LogOperator<T>>(x, destination); 166public static Vector128<T> Invoke(Vector128<T> x, Vector128<T> y) => LogOperator<T>.Invoke(x) / LogOperator<T>.Invoke(y); 167public static Vector256<T> Invoke(Vector256<T> x, Vector256<T> y) => LogOperator<T>.Invoke(x) / LogOperator<T>.Invoke(y); 168public static Vector512<T> Invoke(Vector512<T> x, Vector512<T> y) => LogOperator<T>.Invoke(x) / LogOperator<T>.Invoke(y);
System\Numerics\Tensors\netcore\TensorPrimitives.Log10.cs (4)
39public static bool Vectorizable => LogOperator<T>.Vectorizable; 41public static Vector128<T> Invoke(Vector128<T> x) => LogOperator<T>.Invoke(x) / Vector128.Create(T.CreateTruncating(NaturalLog10)); 42public static Vector256<T> Invoke(Vector256<T> x) => LogOperator<T>.Invoke(x) / Vector256.Create(T.CreateTruncating(NaturalLog10)); 43public static Vector512<T> Invoke(Vector512<T> x) => LogOperator<T>.Invoke(x) / Vector512.Create(T.CreateTruncating(NaturalLog10));
System\Numerics\Tensors\netcore\TensorPrimitives.LogP1.cs (4)
38public static bool Vectorizable => LogOperator<T>.Vectorizable; 40public static Vector128<T> Invoke(Vector128<T> x) => LogOperator<T>.Invoke(x + Vector128<T>.One); 41public static Vector256<T> Invoke(Vector256<T> x) => LogOperator<T>.Invoke(x + Vector256<T>.One); 42public static Vector512<T> Invoke(Vector512<T> x) => LogOperator<T>.Invoke(x + Vector512<T>.One);
System\Numerics\Tensors\netcore\TensorPrimitives.Pow.cs (6)
70return ExpOperator<float>.Invoke(y.AsSingle() * LogOperator<float>.Invoke(x.AsSingle())).As<float, T>(); 75return ExpOperator<double>.Invoke(y.AsDouble() * LogOperator<double>.Invoke(x.AsDouble())).As<double, T>(); 83return ExpOperator<float>.Invoke(y.AsSingle() * LogOperator<float>.Invoke(x.AsSingle())).As<float, T>(); 88return ExpOperator<double>.Invoke(y.AsDouble() * LogOperator<double>.Invoke(x.AsDouble())).As<double, T>(); 96return ExpOperator<float>.Invoke(y.AsSingle() * LogOperator<float>.Invoke(x.AsSingle())).As<float, T>(); 101return ExpOperator<double>.Invoke(y.AsDouble() * LogOperator<double>.Invoke(x.AsDouble())).As<double, T>();
System\Numerics\Tensors\netcore\TensorPrimitives.RootN.cs (6)
39return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector128.Create((float)_n)).As<float, T>(); 44return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector128.Create((double)_n)).As<double, T>(); 52return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector256.Create((float)_n)).As<float, T>(); 57return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector256.Create((double)_n)).As<double, T>(); 65return ExpOperator<float>.Invoke(LogOperator<float>.Invoke(x.AsSingle()) / Vector512.Create((float)_n)).As<float, T>(); 70return ExpOperator<double>.Invoke(LogOperator<double>.Invoke(x.AsDouble()) / Vector512.Create((double)_n)).As<double, T>();
System\Numerics\Tensors\netcore\TensorPrimitives.Single.netcore.cs (1)
21global using LogOperator_Single = System.Numerics.Tensors.TensorPrimitives.LogOperator<float>;
System\Numerics\Tensors\TensorPrimitives.Single.cs (1)
379InvokeSpanIntoSpan<LogOperator_Single>(x, destination);