> ## Documentation Index
> Fetch the complete documentation index at: https://numpyts.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Examples

> Practical examples demonstrating numpy-ts across common domains: linear algebra, signal processing, statistics, image processing, data loading, and performance optimization.

# Examples

These guides walk through real-world patterns using numpy-ts. Each example includes complete, runnable TypeScript code that you can copy directly into your project.

<CardGroup cols={2}>
  <Card title="Linear Algebra" icon="square-root-variable" href=".//linear-algebra">
    Solve systems of equations, compute eigenvalues and SVD, invert matrices, and perform matrix multiplication with matmul and dot.
  </Card>

  <Card title="Signal Processing with FFT" icon="wave-sine" href=".//signal-processing">
    Build composite signals, compute Fourier transforms, filter frequencies, and apply convolution kernels.
  </Card>

  <Card title="Statistics & Analysis" icon="chart-bar" href=".//statistics-analysis">
    Compute descriptive statistics, build histograms, calculate correlation matrices, run Monte Carlo simulations, and weighted averages.
  </Card>

  <Card title="Image Processing Patterns" icon="image" href=".//image-processing">
    Represent images as arrays, slice regions of interest, adjust brightness and contrast, reorder channels, and apply convolution filters.
  </Card>

  <Card title="Data Loading & I/O" icon="file-import" href=".//data-loading">
    Load .npy and .npz files in Node.js and browsers, parse CSV data, and work with text-based formats.
  </Card>

  <Card title="Performance Tips" icon="gauge-high" href=".//performance-tips">
    Minimize copies with views, pick the right entry point for tree-shaking, choose efficient dtypes, and prefer vectorized operations over loops.
  </Card>
</CardGroup>

## Prerequisites

All examples assume you have numpy-ts installed:

```bash theme={null}
npm install numpy-ts
```

Most examples use the full entry point for readability:

```typescript theme={null}
import * as np from 'numpy-ts';
```

For production browser bundles, consider using `numpy-ts/core` for tree-shaking. See the [Tree-Shaking guide](../guides/tree-shaking) for details.