def main():
parser = OptionParser(usage=usage)
parser.add_option(
"-c",
"--compare",
action="store_true",
dest="compare",
default=False,
help="compare with default scipy.sparse solver [default: %default]",
)
parser.add_option(
"-p", "--plot", action="store_true", dest="plot", default=False, help="plot time statistics [default: %default]"
)
parser.add_option(
"-d",
"--default-url",
action="store_true",
dest="default_url",
default=False,
help="use default url [default: %default]",
)
parser.add_option(
"-f", "--format", type=type(""), dest="format", default="triplet", help="matrix format [default: %default]"
)
(options, args) = parser.parse_args()
if len(args) >= 1:
matrixNames = args
else:
parser.print_help(),
return
sizes, nnzs, times, errors = [], [], [], []
legends = ["umfpack", "sparse.solve"]
for ii, matrixName in enumerate(matrixNames):
print("*" * 50)
mtx = readMatrix(matrixName, options)
sizes.append(mtx.shape)
nnzs.append(mtx.nnz)
tts = np.zeros((2,), dtype=np.double)
times.append(tts)
err = np.zeros((2, 2), dtype=np.double)
errors.append(err)
print("size : %s (%d nnz)" % (mtx.shape, mtx.nnz))
sol0 = np.ones((mtx.shape[0],), dtype=np.double)
rhs = mtx * sol0
umfpack = um.UmfpackContext()
tt = time.clock()
sol = umfpack(um.UMFPACK_A, mtx, rhs, autoTranspose=True)
tts[0] = time.clock() - tt
print("umfpack : %.2f s" % tts[0])
error = mtx * sol - rhs
err[0, 0] = nla.norm(error)
print("||Ax-b|| :", err[0, 0])
error = sol0 - sol
err[0, 1] = nla.norm(error)
print("||x - x_{exact}|| :", err[0, 1])
if options.compare:
tt = time.clock()
sol = sp.solve(mtx, rhs)
tts[1] = time.clock() - tt
print("sparse.solve : %.2f s" % tts[1])
error = mtx * sol - rhs
err[1, 0] = nla.norm(error)
print("||Ax-b|| :", err[1, 0])
error = sol0 - sol
err[1, 1] = nla.norm(error)
print("||x - x_{exact}|| :", err[1, 1])
if options.plot:
try:
import pylab
except ImportError:
raise ImportError("could not import pylab")
times = np.array(times)
print(times)
pylab.plot(times[:, 0], "b-o")
if options.compare:
pylab.plot(times[:, 1], "r-s")
else:
del legends[1]
print(legends)
ax = pylab.axis()
y2 = 0.5 * (ax[3] - ax[2])
xrng = list(range(len(nnzs)))
for ii in xrng:
yy = y2 + 0.4 * (ax[3] - ax[2]) * np.sin(ii * 2 * np.pi / (len(xrng) - 1))
if options.compare:
pylab.text(
ii + 0.02,
yy,
"%s\n%.2e err_umf\n%.2e err_sp" % (sizes[ii], np.sum(errors[ii][0, :]), np.sum(errors[ii][1, :])),
)
else:
pylab.text(ii + 0.02, yy, "%s\n%.2e err_umf" % (sizes[ii], np.sum(errors[ii][0, :])))
pylab.plot([ii, ii], [ax[2], ax[3]], "k:")
pylab.xticks(xrng, ["%d" % (nnzs[ii]) for ii in xrng])
pylab.xlabel("nnz")
pylab.ylabel("time [s]")
pylab.legend(legends)
pylab.axis([ax[0] - 0.05, ax[1] + 1, ax[2], ax[3]])
pylab.show()
def main():
parser = OptionParser(usage=usage)
parser.add_option(
"-c",
"--compare",
action="store_true",
dest="compare",
default=False,
help="compare with default scipy.sparse solver [default: %default]")
parser.add_option("-p",
"--plot",
action="store_true",
dest="plot",
default=False,
help="plot time statistics [default: %default]")
parser.add_option("-d",
"--default-url",
action="store_true",
dest="default_url",
default=False,
help="use default url [default: %default]")
parser.add_option("-f",
"--format",
type=type(''),
dest="format",
default='triplet',
help="matrix format [default: %default]")
(options, args) = parser.parse_args()
if (len(args) >= 1):
matrixNames = args
else:
parser.print_help(),
return
sizes, nnzs, times, errors = [], [], [], []
legends = ['umfpack', 'sparse.solve']
for ii, matrixName in enumerate(matrixNames):
print('*' * 50)
mtx = readMatrix(matrixName, options)
sizes.append(mtx.shape)
nnzs.append(mtx.nnz)
tts = np.zeros((2, ), dtype=np.double)
times.append(tts)
err = np.zeros((2, 2), dtype=np.double)
errors.append(err)
print('size : %s (%d nnz)' % (mtx.shape, mtx.nnz))
sol0 = np.ones((mtx.shape[0], ), dtype=np.double)
rhs = mtx * sol0
umfpack = um.UmfpackContext()
tt = time.clock()
sol = umfpack(um.UMFPACK_A, mtx, rhs, autoTranspose=True)
tts[0] = time.clock() - tt
print("umfpack : %.2f s" % tts[0])
error = mtx * sol - rhs
err[0, 0] = nla.norm(error)
print('||Ax-b|| :', err[0, 0])
error = sol0 - sol
err[0, 1] = nla.norm(error)
print('||x - x_{exact}|| :', err[0, 1])
if options.compare:
tt = time.clock()
sol = sp.solve(mtx, rhs)
tts[1] = time.clock() - tt
print("sparse.solve : %.2f s" % tts[1])
error = mtx * sol - rhs
err[1, 0] = nla.norm(error)
print('||Ax-b|| :', err[1, 0])
error = sol0 - sol
err[1, 1] = nla.norm(error)
print('||x - x_{exact}|| :', err[1, 1])
if options.plot:
try:
import pylab
except ImportError:
raise ImportError("could not import pylab")
times = np.array(times)
print(times)
pylab.plot(times[:, 0], 'b-o')
if options.compare:
pylab.plot(times[:, 1], 'r-s')
else:
del legends[1]
print(legends)
ax = pylab.axis()
y2 = 0.5 * (ax[3] - ax[2])
xrng = list(range(len(nnzs)))
for ii in xrng:
yy = y2 + 0.4 * (ax[3] - ax[2])\
* np.sin( ii * 2 * np.pi / (len( xrng ) - 1) )
if options.compare:
pylab.text(
ii + 0.02, yy, '%s\n%.2e err_umf\n%.2e err_sp' %
(sizes[ii], np.sum(
errors[ii][0, :]), np.sum(errors[ii][1, :])))
else:
pylab.text(
ii + 0.02, yy,
'%s\n%.2e err_umf' % (sizes[ii], np.sum(errors[ii][0, :])))
pylab.plot([ii, ii], [ax[2], ax[3]], 'k:')
pylab.xticks(xrng, ['%d' % (nnzs[ii]) for ii in xrng])
pylab.xlabel('nnz')
pylab.ylabel('time [s]')
pylab.legend(legends)
pylab.axis([ax[0] - 0.05, ax[1] + 1, ax[2], ax[3]])
pylab.show()