Source code for pymordemos.elliptic2

#!/usr/bin/env python
# This file is part of the pyMOR project (http://www.pymor.org).
# Copyright 2013-2019 pyMOR developers and contributors. All rights reserved.
# License: BSD 2-Clause License (http://opensource.org/licenses/BSD-2-Clause)

"""Simple demonstration of solving the Poisson equation in 2D using pyMOR's builtin discretizations.

Usage:
    elliptic2.py [--fv] PROBLEM-NUMBER N

Arguments:
    PROBLEM-NUMBER    {0,1}, selects the problem to solve
    N                 Triangle count per direction

Options:
    -h, --help   Show this message.
    --fv         Use finite volume discretization instead of finite elements.
"""

from docopt import docopt

from pymor.analyticalproblems.elliptic import StationaryProblem
from pymor.discretizers.cg import discretize_stationary_cg
from pymor.discretizers.fv import discretize_stationary_fv
from pymor.domaindescriptions.basic import RectDomain
from pymor.functions.basic import ExpressionFunction, LincombFunction
from pymor.parameters.functionals import ProjectionParameterFunctional, ExpressionParameterFunctional
from pymor.parameters.spaces import CubicParameterSpace


[docs]def elliptic2_demo(args): args['PROBLEM-NUMBER'] = int(args['PROBLEM-NUMBER']) assert 0 <= args['PROBLEM-NUMBER'] <= 1, ValueError('Invalid problem number.') args['N'] = int(args['N']) rhss = [ExpressionFunction('ones(x.shape[:-1]) * 10', 2, ()), ExpressionFunction('(x[..., 0] - 0.5)**2 * 1000', 2, ())] rhs = rhss[args['PROBLEM-NUMBER']] problem = StationaryProblem( domain=RectDomain(), rhs=rhs, diffusion=LincombFunction( [ExpressionFunction('1 - x[..., 0]', 2, ()), ExpressionFunction('x[..., 0]', 2, ())], [ProjectionParameterFunctional('diffusionl', 0), ExpressionParameterFunctional('1', {})] ), parameter_space=CubicParameterSpace({'diffusionl': 0}, 0.1, 1), name='2DProblem' ) print('Discretize ...') discretizer = discretize_stationary_fv if args['--fv'] else discretize_stationary_cg m, data = discretizer(problem, diameter=1. / args['N']) print(data['grid']) print() print('Solve ...') U = m.solution_space.empty() for mu in m.parameter_space.sample_uniformly(10): U.append(m.solve(mu)) m.visualize(U, title='Solution for diffusionl in [0.1, 1]')
if __name__ == '__main__': args = docopt(__doc__) elliptic2_demo(args)