# Sample Function: Perlin Noise in 2D#

Here we use `pyvista.core.imaging.sample_function()` to sample Perlin noise over a region to generate random terrain.

Perlin noise is atype of gradient noise often used by visual effects artists to increase the appearance of realism in computer graphics. Source: https://en.wikipedia.org/wiki/Perlin_noise

The development of Perlin Noise has allowed computer graphics artists to better represent the complexity of natural phenomena in visual effects for the motion picture industry.

```import pyvista as pv
```

# Generate Perlin Noise over a StructuredGrid#

Feel free to change the values of `freq` to change the shape of the “mountains”. For example, lowering the frequency will make the terrain seem more like hills rather than mountains.

```freq = [0.689, 0.562, 0.683]
noise = pv.perlin_noise(1, freq, (0, 0, 0))
sampled = pv.sample_function(noise, bounds=(-10, 10, -10, 10, -10, 10), dim=(500, 500, 1))
```

# Warp by scalar#

Here we warp by scalar to give the terrain some height based on the value of the Perlin noise. This is necessary to the terrain its shape.

```mesh = sampled.warp_by_scalar('scalars')
mesh = mesh.extract_surface()

# clean and smooth a little to reduce Perlin noise artifacts
mesh = mesh.smooth(n_iter=100, inplace=False, relaxation_factor=1)

# This makes the "water" level look flat.
z = mesh.points[:, 2]
diff = z.max() - z.min()

# water level at 70%  (change this to change the water level)
water_percent = 0.7
water_level = z.max() - water_percent * diff
mesh.points[z < water_level, 2] = water_level
```

Show the terrain as a contour plot

```# make the water blue
rng = z.max() - z.min()
clim = (z.max() - rng * 1.65, z.max())

pl = pv.Plotter()
mesh,
scalars=z,
cmap='gist_earth',
n_colors=10,
show_scalar_bar=False,
clim=clim,
)
pl.show()
```

Show the terrain with custom lighting and shadows

```pl = pv.Plotter(lighting=None)
pl.add_light(pv.Light((3, 1, 0.5), show_actor=True, positional=True, cone_angle=90, intensity=1.2))
pl.show()
```

Total running time of the script: ( 0 minutes 2.812 seconds)

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