import scipy
import scipy.linalg
import arnoldiDTM
import NumBias
import Matrix
import gnuplotFile
if __name__ == "__main__":
numby = NumBias.NB(version=str(__version__))
A = Matrix.Diagonal(scipy.arange(numby.options.size, 0, -1))
# Calculate similarDiag matrix
adtm = arnoldiDTM.arnoldiDTM(A, Noise=0.0)
q = scipy.ones(numby.options.size)
adtm.arnoldi(q, numby.options.size)
Q = scipy.array(adtm.Q)
B = scipy.dot(scipy.dot(Q[:-1].transpose(), A), Q[:-1])
# Double-check
print "\n\nDouble-check:"
print "Eigenvalues of A:\n%s\nEigenvalues of B:\n%s\n" % (
scipy.linalg.eigvals(A), scipy.linalg.eigvals(B))
print "A: \n%s" % B
numby.printParameters()
if numby.options.run:
numby.run(A=B, q=q)
Chart = Gnuplot.Gnuplot()
Chart.xlabel('Iteration')
Chart.ylabel('Estimated eigenvalue')
Chart.title('Noise = %4G' %(Noise))
Chart('set yrange [3.0:]')
Chart('set pointsize 0.5')
Chart('set key right bottom')
Chart('set y2tics')
# Chart('set no key')
# Not Noisy
Chart.replot(Gnuplot.Data(range(iterations), scipy.ones(iterations)*scipy.pi, with='lines',
title='True eValue'))
# adtm = arnoldiDTM.arnoldiDTM(A, Noise=0.0, NoiseShape='uniform')
# ePairs = adtm.arnoldi(q, iterations)
# conData = Gnuplot.Data(adtm.convergence, with='linespoints',
# title='NotNoisy')
# Chart.replot(conData)
eValues = []
for n in xrange(20):
adtm = arnoldiDTM.arnoldiDTM(A, Noise=Noise, NoiseShape='normal')
ePairs = adtm.arnoldi(q, iterations)
eValues.append(ePairs[0][-1])
conData = Gnuplot.Data(adtm.convergence, with='linespoints',
title=None)
Chart.replot(conData)
print "Averaage eigenvalue: %.4f" %(scipy.mean(eValues))
import Gnuplot
import arnoldiDTM
import Matrix
if __name__ == "__main__":
N = 10
# A = Matrix.DingDong(N)
A = Matrix.Diagonal(scipy.arange(1,N+1))
print A
I = 11 # Arnoldi Iterations
R = 10 # Arnoldi Restarts
q = scipy.random.random(N)
adtm = arnoldiDTM.arnoldiDTM(A)
values, vectors = adtm.arnoldi(q, I)
print "Estimated Eigenvalues: %s" %(values)
realvalues, realvectors = scipy.linalg.eig(A)
realvalues.sort()
print "Real values: %i, Estimated values %i" %(len(realvalues), len(values))
# print "Real Eigenvalues: %s" %(realvalues)
# print "Difference: %s" %(abs(realvalues-values))
Chart = Gnuplot.Gnuplot()
plotData = Gnuplot.Data(vectors[:,-1], with='histeps')
Chart.plot(plotData)