feat: add new matrix addition method and improve performance of mmul and kroneckerProduct method

.github/workflows/typedoc.yml

@@ -1,32 +1,15 @@
-name: Deploy TypeDoc on GitHub pages
+name: TypeDoc
 
 on:
   workflow_dispatch:
   release:
     types: [published]
 
-env:
-  NODE_VERSION: 22.x
-  ENTRY_FILE: 'src/index.js'
-
 jobs:
-  deploy:
-    runs-on: ubuntu-latest
-    steps:
-      - uses: actions/checkout@v4
-      - uses: actions/setup-node@v4
-        with:
-          node-version: ${{ env.NODE_VERSION }}
-      - name: Install dependencies
-        run: npm install
-      - name: Build documentation
-        uses: zakodium/typedoc-action@v2
-        with:
-          entry: ${{ env.ENTRY_FILE }}
-      - name: Deploy to GitHub pages
-        uses: JamesIves/github-pages-deploy-action@releases/v4
-        with:
-          token: ${{ secrets.BOT_TOKEN }}
-          branch: gh-pages
-          folder: docs
-          clean: true
+  typedoc:
+    # Documentation: https://github.com/zakodium/workflows#typedoc
+    uses: zakodium/workflows/.github/workflows/typedoc.yml@typedoc-v1
+    with:
+      entry: 'src/index.js'
+    secrets:
+      github-token: ${{ secrets.BOT_TOKEN }}

benchmark/benchmarkLinePlot.js

@@ -0,0 +1,55 @@
+import { bench, do_not_optimize, lineplot, run } from 'mitata';
+import { xSequentialFillFromStep } from 'ml-spectra-processing';
+
+import { SparseMatrix } from '../src/index.js';
+
+import { SparseMatrix as SparseMatrixOld } from './class/SparseMatrixOld.js';
+import { randomMatrix } from './utils/randomMatrix.js';
+
+const density = 0.02; // Fixed density for this comparison;
+
+// Prepare matrices once
+const sizes = Array.from(
+  xSequentialFillFromStep({ from: 4, step: 4, size: 13 }),
+);
+lineplot(() => {
+  bench('Sparse.mmul($size)', function* (ctx) {
+    const size = ctx.get('size');
+
+    // Prepare matrices once
+    const A = new SparseMatrix(randomMatrix(size, size, density));
+    const B = new SparseMatrix(randomMatrix(size, size, density));
+    // Benchmark the multiplication
+    yield () => do_not_optimize(A.mmul(B));
+  })
+    .gc('inner')
+    .args('size', sizes); // 16, 32, 64, 128, 256
+
+  bench('SparseOld.mmul($size)', function* (ctx) {
+    const size = ctx.get('size');
+    const A = randomMatrix(size, size, density);
+    const B = randomMatrix(size, size, density);
+    const AOld = new SparseMatrixOld(A);
+    const BOld = new SparseMatrixOld(B);
+
+    // Benchmark the multiplication
+    yield () => do_not_optimize(AOld.mmul(BOld));
+  })
+    .gc('inner')
+    .args('size', sizes);
+
+  // bench('Dense.mmul($size)', function* (ctx) {
+  //   const size = ctx.get('size');
+
+  //   // Prepare matrices once
+  //   const A = randomMatrix(size, size, density);
+  //   const B = randomMatrix(size, size, density);
+  //   const ADense = new Matrix(A);
+  //   const BDense = new Matrix(B);
+
+  //   // Benchmark the multiplication
+  //   yield () => do_not_optimize(ADense.mmul(BDense));
+  // }).gc('inner').range('size', min, max, multiplier);
+});
+
+await run();