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Learning SciPy for Numerical and Scientific Computing Second Edition

You're reading from   Learning SciPy for Numerical and Scientific Computing Second Edition Quick solutions to complex numerical problems in physics, applied mathematics, and science with SciPy

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Product type Paperback
Published in Feb 2015
Publisher Packt
ISBN-13 9781783987702
Length 188 pages
Edition 2nd Edition
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A finite element solver for Laplace's equation

We use finite elements when the size of the data is so large that its results prohibit dealing with finite differences. To illustrate this case, we would like to explore the numerical solution of the Laplace equation, subject to certain boundary conditions.

We will start by defining the computational domain and produce a mesh dividing this domain using triangles as local finite elements. This will be our starting point to solve this problem using finite elements, as we will be placing on the computational domain a piecewise continuous function, whose pieces are linear and supported on each of the triangles.

We start by calling the necessary modules to build the mesh (other modules will be called as they are required):

>>> import numpy
>>> from numpy import linspace
>>> import scipy
>>> import matplotlib.pyplot as plt
>>> from scipy.spatial import Delaunay

First we define the region:

>>&gt...
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