# Matplotlib - Triplot

A triplot involves creating a triangular grid. The matplotlib.pyplot.triplot() function draws a unstructured triangular grid as lines and/or markers.

The triangulation to plot can be specified in one of two ways. Either:

```triplot(triangulation, ...)
```

where triangulation is a Triangulation object, or

```triplot(x, y, ...)
triplot(x, y, triangles, ...)
triplot(x, y, triangles=triangles, ...)
```

### Example: triplot

The example below illustrates the matplotlib.pyplot.triplot() function of matplotlib.pyplot.

```import matplotlib.pyplot as plt
import matplotlib.tri as mtri
import numpy as np

#creating triangulation.
x = np.asarray([0, 1, 2, 3, 0.5, 1.5,
2.5, 1, 2, 1.5])
y = np.asarray([0, 0, 0, 0, 1.0, 1.0,
1.0, 2, 2, 3.0])
triangles = [[0, 1, 4], [1, 2, 5], [2, 3, 6],
[1, 5, 4], [2, 6, 5], [4, 5, 7],
[5, 6, 8], [5, 8, 7], [7, 8, 9]]
triang = mtri.Triangulation(x, y, triangles)

z = np.cos(1.5 * x) * np.cos(1.5 * y)

#setting up the figure
fig, ax = plt.subplots()
ax.set_title('Triplot')

#plotting the triangulation
ax.tricontourf(triang, z)
ax.triplot(triang, 'bo-')

plt.show()
```

The output of the above code will be:

### Example: triplot using delaunay triangulation

Lets consider another example to understand this function. Here, no triangles are created, only delaunay triangulation is created.

```import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np

#first creating the x and y coordinates of the points
n_angles = 24

angles = np.linspace(0, 2 * np.pi, n_angles, endpoint=False)
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
angles[:, 1::2] += np.pi / n_angles

#creating the Triangulation -
#no triangles so Delaunay triangulation created
triang = tri.Triangulation(x, y)

y[triang.triangles].mean(axis=1))

#setting up the figure
fig, ax = plt.subplots()
ax.set_title('Triplot of Delaunay triangulation')
ax.set_aspect('equal')

#plotting the triangulation
ax.triplot(triang, 'go-', lw=1)

plt.show()
```

The output of the above code will be:

5