matrix_solver.py
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	import numpy as np
	import scipy.sparse as sp
	from rrompy.hfengines.base import LinearAffineEngine, NumpyEngineBase

	test = 2
	N = 100
	verb = 0

	class MatrixEngineBase(LinearAffineEngine, NumpyEngineBase):
	pass

	solver = MatrixEngineBase(verbosity = verb)
	solver.npar = 1
	solver.nAs = 2
	mu = 5.001

	if test == 1:
	solver.As = [sp.spdiags([np.arange(1, 1 + N)], [0], N, N),
	- sp.eye(N)]
	elif test == 2:
	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)]
	solver._affinePoly = True
	solver.thAs = solver.getMonomialWeights(solver.nAs)
	solver.thbs = solver.getMonomialWeights(solver.nbs)

	uh = solver.solve(mu)[0]
	print(solver.norm(uh))
	solver.plot(uh)
	solver.plot(solver.residual(mu, uh)[0], name = 'res')