def main(args):
# Generate an analytic centering problem
#
# -b1 <= Ar*x <= b2
#
# with random mxn Ar and random b1, b2.
if len(args[0]) > 0 and args[0] == "reftest":
m, n = 10, 5
# matrix in column order
A0 = matrix([[-7.44e-01, 4.59e-01, -2.95e-02, -7.75e-01, -1.80e+00],
[1.11e-01, 7.06e-01, -2.22e-01, 1.03e-01, 1.24e+00],
[1.29e+00, 3.16e-01, -2.07e-01, -1.22e+00, -2.61e+00],
[2.62e+00, -1.06e-01, -9.11e-01, -5.74e-01, -9.31e-01],
[-1.82e+00, 7.80e-01, -3.92e-01, -3.32e-01, -6.38e-01]])
b0 = matrix([
8.38e-01, 9.92e-01, 9.56e-01, 6.14e-01, 6.56e-01, 3.57e-01,
6.36e-01, 5.08e-01, 8.81e-03, 7.08e-02
])
A = matrix([A0, -A0])
b = b0
else:
m, n = 500, 500
Ar = base.normal(m, n)
A = matrix([Ar, -Ar])
b = base.uniform(2 * m, 1)
x, ntdecrs = acent(A, b)
print "solution:\n", helpers.str2(x, "%.17f")
print "ntdecrs :\n", ntdecrs
def main(args):
# Generate an analytic centering problem
#
# -b1 <= Ar*x <= b2
#
# with random mxn Ar and random b1, b2.
if len(args[0]) > 0 and args[0] == "reftest":
m, n = 10, 5
# matrix in column order
A0 = matrix([[-7.44e-01, 4.59e-01, -2.95e-02, -7.75e-01, -1.80e+00],
[ 1.11e-01, 7.06e-01, -2.22e-01, 1.03e-01, 1.24e+00],
[ 1.29e+00, 3.16e-01, -2.07e-01, -1.22e+00, -2.61e+00],
[ 2.62e+00, -1.06e-01, -9.11e-01, -5.74e-01, -9.31e-01],
[-1.82e+00, 7.80e-01, -3.92e-01, -3.32e-01, -6.38e-01]])
b0 = matrix([8.38e-01,
9.92e-01,
9.56e-01,
6.14e-01,
6.56e-01,
3.57e-01,
6.36e-01,
5.08e-01,
8.81e-03,
7.08e-02])
A = matrix([A0, -A0])
b = b0
else:
m, n = 500, 500
Ar = base.normal(m,n);
A = matrix([Ar, -Ar])
b = base.uniform(2*m,1)
x, ntdecrs = acent(A, b)
print "solution:\n", helpers.str2(x, "%.17f")
print "ntdecrs :\n", ntdecrs
while 1 - step * max(y) < 0:
step *= BETA
while True:
if -sum(log(1 - step * y)) < ALPHA * step * lam:
break
step *= BETA
x += step * v
# Generate an analytic centering problem
#
# -b1 <= Ar*x <= b2
#
# with random mxn Ar and random b1, b2.
m, n = 500, 500
Ar = base.normal(m, n)
A = matrix([Ar, -Ar])
b = base.uniform(2 * m, 1)
x, ntdecrs = acent(A, b)
try:
import pylab
except ImportError:
pass
else:
pylab.semilogy(range(len(ntdecrs)), ntdecrs, "o", range(len(ntdecrs)), ntdecrs, "-")
pylab.xlabel("Iteration number")
pylab.ylabel("Newton decrement")
pylab.show()
while 1 - step * max(y) < 0:
step *= BETA
while True:
if -sum(log(1 - step * y)) < ALPHA * step * lam: break
step *= BETA
x += step * v
# Generate an analytic centering problem
#
# -b1 <= Ar*x <= b2
#
# with random mxn Ar and random b1, b2.
m, n = 500, 500
Ar = base.normal(m, n)
A = matrix([Ar, -Ar])
b = base.uniform(2 * m, 1)
x, ntdecrs = acent(A, b)
try:
import pylab
except ImportError:
pass
else:
pylab.semilogy(range(len(ntdecrs)), ntdecrs, 'o', range(len(ntdecrs)),
ntdecrs, '-')
pylab.xlabel('Iteration number')
pylab.ylabel('Newton decrement')
pylab.show()