gged 0.0.1
non-jagged array and tensor library
To use this package, run the following command in your project's root directory:
Manual usage
Put the following dependency into your project's dependences section:
ggeD
A ~~ja~~gged array library that saves you from writing nested for statements in multidimensional arrays.
ジャグ配列じゃない多次元配列ライブラリです。入れ子にせずループを回すための機能を提供します。
import ggeD;
import std.range : iota;
import std.array : array;
import std.math : sin;
import std.stdio : writeln;
void main()
{
auto A = gged!double(iota(27.).array,3,3,3); // create A gged array
foreach(ijk ; A) // parallel foreach
{
A[ijk] = sin(A[ijk]); // easy to access
A[ijk] = 1.*ijk[0] + 2.*ijk[1] + 3.*ijk[2]; // ijk is vector
}
foreach(i,j,k ; A.Serial) // explicit serial foreach
{
writeln(A[i,j,k]); // also easy to access
}
}
And also included tensor library. You can use Einstein summation.
アインシュタインの縮約記法が使えるテンソルライブラリもあります。
import ggeD : tensor , Einsum;
import std.range : iota;
import std.array : array;
import std.stdio : writeln;
void main()
{
auto A = tensor!double(iota(9.).array,3,3); // 2 rank tensor(matrix)
auto B = tensor!double([3.,2,1],3); // 1 rank tensor(vector)
auto C = Einsum | A.ij*B.i; // You can write an expressions without for statement.
foreach(ijk ; C.Serial) // You can use as gged array;
{
writeln(ijk, " | " ,C[ijk]);
}
auto tr = Einsum | A.ii; // trace of A.
assert
import ggeD : BroadCast; // BroadCast makes a function usable in Einstein summation.
import std.math : sin;
auto D = Einsum | A.ij + BroadCast!sin(B.i*B.j);
}
- Registered by Zenw
- 0.0.1 released 2 years ago
- Zero-error-no-warning/gged
- MIT
- Copyright (c) 2022 Zenw
- Authors:
- Dependencies:
- none
- Versions:
-
0.0.1 2022-Jul-16 ~main 2023-Jun-15 - Download Stats:
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- Short URL:
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