else:
return tuple(functions)
def lambda_to_S1(f, mesh, dim=1):
V = dolfin.FunctionSpace(mesh, "CG", 1)
if dim > 1:
V = dolfin.MixedFunctionSpace([V] * dim)
f1 = dolfin.Function(V)
value_shape = () if dim == 1 else (dim, )
class expr(dolfin.Expression):
def eval(self, value, x):
value[:] = f(x)
def value_shape(self):
return value_shape
f1.interpolate(expr())
return f1
if __name__ == "__main__":
from plot_forcefield import porestreamlines, plt
F = forcefieldS1(implicit=False, **default)
Fimp = forcefieldS1(implicit=True, **default)
porestreamlines(Howorka.polygon(), 6., 8., F=F) #, Fimp=Fimp)
fig = plt.figure("F")
fig.axes[1].set_ylabel("force [N]")
nanopores.showplots()
legend(loc='best')
# --- create interpolation for different h and orders ---
orders = range(1, maxorder+1)
samples = []
interpolands = []
for order in orders:
print "\n-- order = %s --" %order
u, N = interpolate(h=h, order=order)
samples.append(N)
interpolands.append(u)
dolfin.plot(u, key="u", title="interpolated potential, order %s" %order)
ulast = interpolands.pop()
Nlast = samples.pop()
def err(uh):
return errornorm(ulast, uh, "H1", degree_rise=0)/norm(ulast, "H1")
errors = [err(uh) for uh in interpolands]
label = "|Iluh - I%duh|/|I%duh|" %(maxorder, maxorder)
hplot(label, samples, errors, xlab="# samples M", ylab="relative interpolation error", hstr="M", fit=True)
list_timings()
#saveplots("mlsc", meta=PARAMS)
showplots()
interactive()
# v, cp, cm = pnps.functions["pnp"].split()
# else:
# v = pnps.functions["poisson"]
nano.plot_cross(v, mesh2D, title="potential", key="u")
nano.plot_cross(cm, mesh2D, title="negative ions", key="cm")
#dolfin.interactive()
#u = pnps.functions["stokes"].sub(0)
#nano.plot_cross_vector(u, mesh2D, title="u", key="uu")
print "v0 =", v([0., 0., -25.])
print "CPU time (solve): %.3g s" % (dolfin.toc(), )
print pnps.evaluate(phys.CurrentPNPS)
print pnps.evaluate(phys.ForcesPNPS)
# visualize
v, cp, cm, u, p = pnps.solutions()
#nano.plot_cross(v, mesh2D, title="potential")
nano.plot_cross(cm, mesh2D, title="cm")
nano.plot_cross(cp, mesh2D, title="cp")
nano.plot_cross(p, mesh2D, title="p")
nano.plot_cross_vector(u, mesh2D, title="u")
#if not solverp.cheapest:
# pb.estimators["rep"].plot()
# pb.estimators["err"].plot(rate=-2./3., fig=False)
#pnps.visualize("pore")
nano.showplots()
dolfin.interactive()