#!/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, ConstantFunction
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, ()),
LincombFunction(
[ExpressionFunction('ones(x.shape[:-1]) * 10', 2, ()), ConstantFunction(1.,2)],
[ProjectionParameterFunctional('mu', 0), ExpressionParameterFunctional('0.1', {})])]
dirichlets = [ExpressionFunction('zeros(x.shape[:-1])', 2, ()),
LincombFunction(
[ExpressionFunction('2 * x[..., 0]', 2, ()), ConstantFunction(1.,2)],
[ProjectionParameterFunctional('mu', 0), ExpressionParameterFunctional('0.5', {})])]
neumanns = [None,
LincombFunction(
[ExpressionFunction('1 - x[..., 1]', 2, ()), ConstantFunction(1.,2)],
[ProjectionParameterFunctional('mu', 0), ExpressionParameterFunctional('0.5**2', {})])]
robins = [None,
(LincombFunction(
[ExpressionFunction('x[..., 1]', 2, ()), ConstantFunction(1.,2)],
[ProjectionParameterFunctional('mu', 0), ExpressionParameterFunctional('1', {})]),
ConstantFunction(1.,2))]
domains = [RectDomain(),
RectDomain(right='neumann', top='dirichlet', bottom='robin')]
rhs = rhss[args['PROBLEM-NUMBER']]
dirichlet = dirichlets[args['PROBLEM-NUMBER']]
neumann = neumanns[args['PROBLEM-NUMBER']]
domain = domains[args['PROBLEM-NUMBER']]
robin = robins[args['PROBLEM-NUMBER']]
problem = StationaryProblem(
domain=RectDomain(),
rhs=rhs,
diffusion=LincombFunction(
[ExpressionFunction('1 - x[..., 0]', 2, ()), ExpressionFunction('x[..., 0]', 2, ())],
[ProjectionParameterFunctional('mu', 0), ExpressionParameterFunctional('1', {})]
),
dirichlet_data=dirichlet,
neumann_data=neumann,
robin_data=robin,
parameter_space=CubicParameterSpace({'mu': 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 mu in [0.1, 1]')
if __name__ == '__main__':
args = docopt(__doc__)
elliptic2_demo(args)