spatimpoddict.update(dict(nu=cnu))
apprxl.append(comp_spatimepodgal(**spatimpoddict))
Kapprxl.append(apprxl)
leglist.append('$K={0}$'.format(K))
fctdct = dict(abscissa=nutestlist.tolist(),
datalist=Kapprxl,
leglist=leglist)
f = open(datastr, 'w')
f.write(json.dumps(fctdct))
print 'results dumped into json:', datastr
f.close()
cpu.para_plot(**fctdct)
if factest:
f0, fe, nfs = .2, .8, 7
datastr = 'results/factest{0}{1}{2}K30'.format(f0, fe, nfs)
faclist = np.linspace(f0, fe, nfs)
if nfs == 7: # TODO: softcode the adaptivity towards fac=.5
faclist = np.array([.2, .35, .425, .5, .575, .65, .8])
K = 30
nuapprxl, leglist = [], []
for cnu in smallnutestlist:
spatimpoddict.update(dict(nu=cnu))
apprxl = []
for cfac in faclist:
hq = np.floor(cfac * K)
tmesh=tmesh, zini=inival, fbd=fbd, ftd=ftd,
retaslist=True)
outlist.append(sysout)
return outlist
# Riccati solution
fbdict, ftdict = fop.solve_opt_ric(A=tA, B=tB, C=tC, tmesh=tmesh,
gamma=gamma, beta=bzero,
fpri=fpri, fdua=fdua, bt=tB.T)
outlist = inivinipcheck(inilist, fbd=fbdict, ftd=ftdict, bmo=1./bzero)
ylims = [0., 3.5]
cpu.para_plot(tmesh, outlist, leglist=leglist, fignum=44,
xlabel='time $t~[s]$', ylabel='trajectory $x_1~[m]$',
ylims=ylims,
tikzfile='{0}car_inivpert_Riccati.tikz'.format(ncar),
title=None, legloc='lower right') # 'Trajektorie')
# # direct solution
outlist = inivinipcheck(inilist, fbd=None, ftd=forcefunc, bmo=1.)
cpu.para_plot(tmesh, outlist, leglist=leglist, fignum=43,
xlabel='time $t~[s]$', ylabel='trajectory $x_1~[m]$',
ylims=ylims,
tikzfile='{0}car_inivpert_direct.tikz'.format(ncar),
title=None, legloc='lower right') # 'Trajektorie')
if opticheck:
def fone(t):
return f[0]
tmeshl.append(tmesh[1:])
verrl.append(verr[1:])
perrl.append(perr[1:])
nswtchstr = 'N' + ''.join(str(e) for e in nswtchshortlist)
legl.append('$\\mathsf{{Nts}}={0}$ (index-{1})'.
format(Nts, method))
logger.info(nswtchstr + ': Nts={0}, m={1}, veint={2}, peint={3}'.
format(Nts, method, verrint, perrint))
curptkl = []
for k in np.arange(1, len(nswtchshortlist)):
jumpindx = k*(len(tmesh)-1)/len(nswtchshortlist) # an int !!
curptkl.extend([jumpindx-1, jumpindx])
keeppointslist.append(curptkl)
# markerl = ['s', '^', '.', '*', 'o', '+']
xticks = np.linspace(t0, tE, 5)
ppltdict = dict(leglist=legl, xlabel='t', xticks=xticks, logscaley=2,
usedefaultmarkers=True)
cpu.para_plot(None, perrl, abscissal=tmeshl, fignum=11,
title='pointwise error in $p$',
tikzfile='p-pointwiseerror.tex',
xlims=[t0, tE],
downsample=50, keeppointslist=keeppointslist,
**ppltdict)
cpu.para_plot(None, verrl, abscissal=tmeshl, fignum=22,
title='pointwise error in $q$',
tikzfile='vel-pointwiseerror.tex',
xlims=[t0, tE],
downsample=50,
**ppltdict)
except IOError:
allersl, alllegsl = [], []
for nsnaps in nsnapsl:
gpderr, pderr = [], []
for poddim in poddiml:
# distance between and the indices of the snapshots
ssdist = Nts/nsnaps
ssinds = np.arange(0, Nts, ssdist).astype(int)
gYappr = solve_podapprx(M, A, Ycheck, f, B, poddim, nsnaps,
tmesh, genpod=True)
Yappr = solve_podapprx(M, A, Ycheck[:, ssinds], f, B,
poddim, nsnaps, tmesh, genpod=False)
gerrM = pdu.timespace_diff_norm(tmesh, Y, gYappr, M)
errM = pdu.timespace_diff_norm(tmesh, Y, Yappr, M)
gpderr.append(gerrM)
pderr.append(errM)
allersl.extend([pderr, gpderr])
alllegsl.extend(['pod, $k={0}$'.format(nsnaps),
'genpod, $k={0}$'.format(nsnaps)])
jsfile = open(datajsn, mode='w')
jsfile.write(json.dumps(dict(alllegsl=alllegsl,
allersl=allersl)))
jsfile.close()
print 'saved pod genpod convdata to ' + datajsn
cpu.para_plot(poddiml, allersl, leglist=alllegsl,
logscaley=10, tikzfile='ksnpoddimgpdpd.tikz')
import json
import matlibplots.conv_plot_utils as cpu
# factest
f0, fe, nfs = .2, .8, 7
datastr = 'results/factest{0}{1}{2}K30'.format(f0, fe, nfs)
fjs = open(datastr)
fctdct = json.load(fjs)
fjs.close()
cpu.para_plot(xlabel='% \\cfac',
ylabel='% \\apprxer',
title='(a)',
logscaley=10,
tikzfile='errvsfac.tikz',
fignum=123,
**fctdct)
# nutest
datastr = 'results/nutest0.01258925411790.0007943282347249K203040'
fjs = open(datastr)
fctdct = json.load(fjs)
fjs.close()
cpu.para_plot(xlabel='\\mu',
ylabel='\\apprxer',
title='(b)',
logscaley=10,
tikzfile='errvsnu.tikz',
fignum=124,
**fctdct)
