# Draw a unstructured triangular grid as lines or markers in Python using Matplotlib

• Last Updated : 08 Jun, 2020

Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.

## Unstructured Triangular Grid

An unstructured grid can be defined as the part of the Euclidean plane or diagram that can be fit together in a pattern with no spaces in between two shapes.  Unstructured grid can be  triangle or tetrahedra in an irregular pattern. Unstructured Triangular Grid can be drawn from an irregularly shaped polygon using the Ruppert’s algorithm.

Here the task is to draw a unstructured triangular grid as lines and/or markers in Python using Matplotlib. In order to do this task, you can use the triplot() function and we require some modules from matplotlib and numpy library.

Example 1: Creating and plotting unstructured triangular grids.

## Python3

 `# Importing modules``import` `matplotlib.pyplot as plt``import` `matplotlib.tri as tri``import` `numpy as np`` ` ` ` `n_angles ``=` `24``n_radii ``=` `9``min_radius ``=` `0.5``radii ``=` `np.linspace(min_radius, ``0.9``,``                    ``n_radii)`` ` `angles ``=` `np.linspace(``0``, ``6` `*` `np.pi, n_angles,``                     ``endpoint``=``False``)`` ` `angles ``=` `np.repeat(angles[..., np.newaxis],``                   ``n_radii, axis``=``1``)`` ` `angles[:, ``1``::``2``] ``+``=` `np.pi ``/` `n_angles`` ` `x ``=` `(radii ``*` `np.cos(angles)).flatten()``y ``=` `(radii ``*` `np.sin(angles)).flatten()``triang ``=` `tri.Triangulation(x, y)`` ` `triang.set_mask(np.hypot(x[triang.triangles].mean(axis``=``1``),``                         ``y[triang.triangles].mean(axis``=``1``))``                ``< min_radius)`` ` `plt.triplot(triang, ``'o-'``, lw``=``1``)``plt.title(``'Example 1'``)``plt.show()`

Output:

Example 2: Using the TriFinder object to highlight the unstructured triangular grid.

## Python3

 `# Importing modules ``import` `matplotlib.pyplot as plt``from` `matplotlib.tri ``import` `Triangulation``from` `matplotlib.patches ``import` `Polygon``import` `numpy as np`` ` ` ` `def` `Trigolo1(tri):``   ` `    ``if` `tri ``=``=` `-``1``:``        ``points ``=` `[``0``, ``0``, ``0``]``         ` `    ``else``:``        ``points ``=` `triang.triangles[tri]``         ` `    ``xs ``=` `triang.x[points]``    ``ys ``=` `triang.y[points]``    ``polygon.set_xy(np.column_stack([xs, ys]))`` ` `def` `Trigolo2(event):``   ` `    ``if` `event.inaxes ``is` `None``:``        ``tri ``=` `-``1``         ` `    ``else``:``        ``tri ``=` `trifinder(event.xdata, event.ydata)``         ` `    ``Trigolo1(tri)``    ``plt.title(``'Example 2\nTriangle No : %i'` `%` `tri)``    ``event.canvas.draw()`` ` `# Create a Triangulation.``ang ``=` `16``rad ``=` `5``mrad ``=` `0.25``radii ``=` `np.linspace(mrad, ``0.95``, rad)`` ` `angletri ``=` `np.linspace(``0``,``                       ``2` `*` `np.pi, ang, ``                       ``endpoint``=``False``)`` ` `angletri ``=` `np.repeat(angletri[..., np.newaxis], ``                     ``rad,``                     ``axis``=``1``)`` ` `angletri[:, ``1``::``2``] ``+``=` `np.pi ``/` `ang`` ` `x ``=` `(radii``*``np.cos(angletri)).flatten()``y ``=` `(radii``*``np.sin(angletri)).flatten()`` ` `triang ``=` `Triangulation(x, y)``triang.set_mask(np.hypot(x[triang.triangles].mean(axis``=``1``),``                         ``y[triang.triangles].mean(axis``=``1``))``                ``< mrad)`` ` `# Use the triangulation's default TriFinder object.``trifinder ``=` `triang.get_trifinder()`` ` `# Setup plot and callbacks.``plt.subplot(``111``, aspect``=``'equal'``)``plt.triplot(triang, ``'o-'``)``polygon ``=` `Polygon([[``0``, ``0``], [``0``, ``0``]], facecolor``=``'y'``)``Trigolo1(``-``1``)``plt.gca().add_patch(polygon)``plt.gcf().canvas.mpl_connect(``'motion_notify_event'``, Trigolo2)`` ` `plt.show()`

Output:

Example 3: Example showing the plot the triangulation.

## Python3

 `import` `matplotlib.pyplot as plt ``import` `matplotlib.tri as mtri ``import` `numpy as np `` ` `    ` `# Create 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) ``    ` `plt.tricontourf(triang, z) ``plt.triplot(triang, ``'go-'``) ``    ` `plt.title(``'Example 3'``) `` ` `plt.show()`

Output:

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