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RROMPy/tests/test_2_hfengines/matrix.py
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matrix.py
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# Copyright (C) 2018 by the RROMPy authors
#
# This file is part of RROMPy.
#
# RROMPy is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# RROMPy is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with RROMPy. If not, see <http://www.gnu.org/licenses/>.
#
import numpy as np
import scipy.sparse as sp
from rrompy.hfengines.base import MatrixEngineBase as MEB
def test_deterministic():
N = 100
verb = 0
solver = MEB(verbosity = verb)
solver.nAs = 2
mu = 10. + .5j
solver.As = [sp.spdiags([np.arange(1, 1 + N)], [0], N, N),
- sp.eye(N)]
solver.nbs = 1
solver.bs = [np.exp(1.j * np.linspace(0, -np.pi, N))]
uh = solver.solve(mu)
assert np.isclose(np.linalg.norm(solver.residual(uh, mu)), 1.088e-15,
rtol = 1e-1)
def test_random():
N = 100
verb = 0
solver = MEB(verbosity = verb)
solver.nAs = 2
mu = 1. + .5j
np.random.seed(420)
solver.setSolver("SOLVE")
fftB = np.fft.fft(np.eye(N)) * N**-.5
solver.As = [fftB.dot(np.multiply(np.arange(1, 1 + N), fftB.conj()).T),
- np.eye(N)]
solver.nbs = 1
solver.bs = [np.random.randn(N) + 1.j * np.random.randn(N)]
uh = solver.solve(mu)
assert np.isclose(np.linalg.norm(solver.residual(uh, mu)), 7.18658e-14,
rtol = 1e-1)
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