# Plotting Point Clouds#

This example shows you how to plot point clouds using PyVista using both the `'point'` and `'point_gaussian'` styles.

```import numpy as np

import pyvista as pv
from pyvista import examples
```

# Compare the Plotting methods#

First, let’s create a sample point cloud using `numpy.random.random()`.

```rng = np.random.default_rng()
points = rng.random((1000, 3))
points
```
```array([[0.47218729, 0.17580516, 0.75203679],
[0.83319226, 0.25227089, 0.75359125],
[0.66820157, 0.59404529, 0.39891556],
...,
[0.91919143, 0.52924227, 0.63863153],
[0.94657529, 0.73417308, 0.19278669],
[0.928082  , 0.29735687, 0.5224433 ]])
```

# Basic Plot#

We can simply plot this point cloud using the convenience `pyvista.plot()` function.

```pv.plot(points)
```

# Plot with Scalars#

That’s quite boring, so let’s spice things up by adding color. We can either use a single scalar to plot the points. For example, the z coordinates.

For fun, let’s also render the points as spheres.

```pv.plot(
points,
scalars=points[:, 2],
render_points_as_spheres=True,
point_size=20,
show_scalar_bar=False,
)
```

# Plot with RGBA#

Alternatively, we can color the point cloud using an RGBA array. This has been normalized from (0, 1), but we could have also used a `numpy.uint8` array from 0-255.

```rgba = points - points.min(axis=0)
rgba /= rgba.max(axis=0)
pv.plot(points, scalars=rgba, render_points_as_spheres=True, point_size=20, cpos='xy', rgba=True)
```

# Point Cloud Plot Styles#

PyVista supports the `'point_gaussian'` style, which renders points as individual soft sprites. You have the option of displaying these as tight “spheres” using `render_points_as_spheres=True` (default), or disabling it to create softer points at the expense of render performance.

Here’s the basic plot again, but with the style as `'points_gaussian'`:

```pv.plot(points, style='points_gaussian', opacity=0.5, point_size=15)
```

Here’s a plotter with four combinations of the options side-by-side so you can see for yourself the different options available when plotting these points. PyVista tries to achieve sensible defaults, but should you find these insufficient for your needs, feel free to play around with the various options and find something that works for you.

```pl = pv.Plotter(shape=(2, 2))

# Standard points
points,
style='points',
emissive=False,
scalars=rgba,
rgba=True,
point_size=10,
ambient=0.7,
)

# Gaussian points
pl.subplot(0, 1)
points,
render_points_as_spheres=False,
style='points_gaussian',
emissive=False,
scalars=rgba,
rgba=True,
opacity=0.99,
point_size=10,
ambient=1.0,
)

# Gaussian points with emissive=True
pl.subplot(1, 0)
points,
render_points_as_spheres=False,
style='points_gaussian',
emissive=True,
scalars=rgba,
rgba=True,
point_size=10,
)

# With render_points_as_spheres=True
pl.subplot(1, 1)
points,
style='points_gaussian',
render_points_as_spheres=True,
scalars=rgba,
rgba=True,
point_size=10,
)

pl.background_color = 'k'
pl.camera_position = 'xy'
pl.camera.zoom(1.2)
pl.show()
```

# Orbit a Point Cloud#

Generate a plot orbiting around a point cloud. Color based on the distance from the center of the cloud.

```cloud = examples.download_cloud_dark_matter()
scalars = np.linalg.norm(cloud.points - cloud.center, axis=1)

pl = pv.Plotter(off_screen=True)
cloud,
style='points_gaussian',
color='#fff7c2',
scalars=scalars,
opacity=0.25,
point_size=4.0,
show_scalar_bar=False,
)
pl.background_color = 'k'
pl.show(auto_close=False)
path = pl.generate_orbital_path(n_points=36, shift=cloud.length, factor=3.0)
pl.open_gif("orbit_cloud.gif")
pl.orbit_on_path(path, write_frames=True)
pl.close()
```

Total running time of the script: ( 0 minutes 13.239 seconds)

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