Homec4science
Diffusion RationalROMPy (feature_greedy_coarsening) Browse

RROMPy/examples/Python_FEniCS/HelmholtzLagrangeApproximantsSweep.py
6e6c171cf128feature_greedy_coarseni…

Last Change
Raw File

HelmholtzLagrangeApproximantsSweep.py
View Options

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Example homogeneous Dirichlet forcing wave SWEEP
from __future__ import print_function
import numpy as np
from context import FenicsHelmholtzEngine as HFEngine
from context import FenicsHSEngine as HSEngine
from context import ROMApproximantLagrangePade as Pade
from context import ROMApproximantLagrangeRB as RB
from context import ROMApproximantSweeper as Sweeper
npoints = 31
ktars = np.linspace(0, 21, npoints)
from Fenics_snippets import SquareHomogeneousBubble
bd, msh, f = SquareHomogeneousBubble(kappa = 12**.5, theta = np.pi / 3, n = 10)
solver = HFEngine(mesh = msh, wavenumber = 12**.5, forcingTerm = f,
FEDegree = 3, DirichletBoundary = bd)
plotter = HSEngine(solver.V)
shift = 3
nsets = 3
stride = 2
Smax = stride * (nsets - 1) + shift + 2
paramsPade = {'S':Smax, 'polyBasis':'CHEBYSHEV', 'POD':True}
paramsRB = {'S':Smax, 'nodesType':'CHEBYSHEV', 'POD':True}
paramsSetsPade = [None] * nsets
paramsSetsRB = [None] * nsets
for i in range(nsets):
paramsSetsPade[i] = {'N': stride * i + shift + 1, 'M': stride * i + shift,
'S': stride * i + shift + 2}
paramsSetsRB[i] = {'R': stride * i + shift + 1, 'S': stride * i + shift + 2}
appPade = Pade(solver, plotter, ks = [4 + .5j, 14 + .5j],
approxParameters = paramsPade)
appRB = RB(solver, plotter, ks = [4 + .5j, 14 + .5j],
approxParameters = paramsRB)
sweeper = Sweeper.ROMApproximantSweeper(ktars = ktars, mostExpensive = 'Approx')
sweeper.ROMEngine = appPade
sweeper.params = paramsSetsPade
filenamePade = sweeper.sweep('../Data/HelmholtzBubbleLagrangePadeFE.dat',
outputs = 'ALL')
sweeper.ROMEngine = appRB
sweeper.params = paramsSetsRB
filenameRB = sweeper.sweep('../Data/HelmholtzBubbleLagrangeRBFE.dat',
outputs = 'ALL')
####################
from matplotlib import pyplot as plt
for i in range(nsets):
nSamples = stride*i+shift+2
PadeOutput = sweeper.read(filenamePade, {'S':nSamples},
['kRe', 'HFNorm', 'AppNorm', 'ErrNorm'])
RBOutput = sweeper.read(filenameRB, {'S':nSamples},
['kRe', 'AppNorm', 'ErrNorm'])
ktarsF = PadeOutput['kRe']
solNormF = PadeOutput['HFNorm']
PadektarsF = PadeOutput['kRe']
PadeNormF = PadeOutput['AppNorm']
PadeErrorF = PadeOutput['ErrNorm']
RBktarsF = RBOutput['kRe']
RBNormF = RBOutput['AppNorm']
RBErrorF = RBOutput['ErrNorm']
plt.figure()
plt.semilogy(ktarsF, solNormF, 'k-', label='Sol norm')
plt.semilogy(PadektarsF, PadeNormF, 'b.--',
label='Pade'' norm, S = {}'.format(nSamples))
plt.semilogy(RBktarsF, RBNormF, 'g.--',
label='RB norm, S = {}'.format(nSamples))
plt.legend()
plt.grid()
plt.show()
plt.close()
plt.figure()
plt.semilogy(PadektarsF, PadeErrorF, 'b',
label='Pade'' error, S = {}'.format(nSamples))
plt.semilogy(RBktarsF, RBErrorF, 'g',
label='RB error, S = {}'.format(nSamples))
plt.legend()
plt.grid()
plt.show()
plt.close()
plt.figure()
plt.semilogy(ktarsF, PadeErrorF / solNormF, 'b',
label='Pade'' relative error, S = {}'.format(nSamples))
plt.semilogy(RBktarsF, RBErrorF / solNormF, 'g',
label='RB relative error, S = {}'.format(nSamples))
plt.legend()
plt.grid()
plt.show()
plt.close()
c4science · Help