Matplotlib is a Python module which can be used for data visualization; and analyse the data graphically in the form of pie-chart, histogram, bar graph and many more. It also has an ability to generate MATLAB-like frameworks.
Unstructured triangular grid
An unstructured triangular grid contains n_points points and n_tri triangles which can either be specified by the user or automatically generated using a Delaunay triangulation.
Syntax : matplotlib.tri.Triangulation(x, y, triangles=None, mask=None)
- x, y : specifies coordinates of grid points.
- triangles : [optional] integer array-like of shape (n_tri, 3)
- mask : [optional] it specifies which triangles are masked out.
Creating a pseudocolor plot of an unstructured triangular grid
We can plot a pseudo-color unstructured triangular grid with the tripcolor() function of the pyplot library.
Syntax : matplotlib.pyplot.tripcolor(*args, cmap=None, alpha=1.0, edgecolors=None, facecolors=None, shading=’flat’, norm=None, vmax=None, vmin=None, **kwargs)
- cmap : It can be None or matplotlib has a number of built-in colormaps accessible via matplotlib.cm.get_cmap
- alpha : It can be None or alpha value between 0 to 1.
- edgecolors :
- If its None, edges will not be visible.
- ‘face’ represents the same color as faces.
- color sequence will set a color.
- facecolors : Mention the typefaces
- shading : It can be either ‘flat’ or ‘gouraud’
- norm : If its None defaults to normalize().
- vimax : It can be either None or the scalar value.
- vimin : It can be either None or the scalar value. ( vimax and vimin are used in conjunction with normalize data)
Example 1 :
Example 2 :
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