# Examples¶

To learn how to use geomstats, you can look at the many examples in the repository examples.

If you have installed geomstats via Git, you can run them from the command line as follows.

```
python3 examples/plot_grid_h2.py
```

These examples allow getting intuition on manifolds and concepts from differential geometry, as well as running learning algorithms.

## Learn differential geometry¶

Assume that your data naturally belongs to the hyperbolic plane H2 and you want to get intuition on the geometry of this space. The space H2 has a negative curvature. The geodesics - i.e. the curves of shortest length - on H2 are not straight lines. How do they look? To answer this question, you can run the example that plots geodesics on H2.

Next, you might be interested in the shapes of “squares” on the negatively curved manifold H2. To visualize squares on H2, you can run the examples that plot squares using the Poincare disk, the Klein disk or the Poincare half-plane representations, which are the three main visualizations of H2.

Interested in other geometries? Just adapt the corresponding codes to the manifold of interest. Note that only low-dimensional manifolds, such as 2D and 3D, come with visualizations.

## Run learning algorithms¶

Assume that you are interested in performing a clustering of data on the hyperbolic plane. This example shows how to run K-means on synthetic data on H2.

Interested in clustering data belonging to other manifolds? Check out this example for clustering on the circle or on the sphere.