#
t3 = timer.time()
# print("3 . Xylem fluxes")
# age dependency
#kr = kr * (10*time_ + 1)
#kz = kz / (10*time_ + 1)
soil_p2 = lambda x, y, z: soil_p(x, y, z, inf.psi, soil[-1].lowerDepth
) # J/kg
if dirichlet == False: # Neumann
Q, b = xylem_flux.linear_system(seg, nodes, radius, kr, kz, rho, g,
soil_p2)
Q, b = xylem_flux.bc_neumann(Q, b, np.array([0]), pot_trans, seg,
nodes)
x = LA.spsolve(Q, b) # direct
eff_trans = xylem_flux.axial_flux0(
x, seg, nodes, kz, rho, g) # verify that eff_trans == pot_trans
print(
"using neumann ( Effective Transpiration = " + str(eff_trans) +
" m^3 s^-1)", "top potential", x[0])
if dirichlet or (x[0] < top_pot):
Q, b = xylem_flux.linear_system(seg, nodes, radius, kr, kz, rho, g,
soil_p2)
dirichlet = True
Q, b = xylem_flux.bc_dirichlet(Q, b, np.array([0]),
np.array([top_pot]))
x = LA.spsolve(Q, b) # direct
eff_trans = xylem_flux.axial_flux0(x, seg, nodes, kz, rho, g)
dirichlet = eff_trans < pot_trans
print("using dirichlet ( Effective Transpiration = " + str(eff_trans) +
" m^3 s^-1)")
Q, b = xylem_flux.bc_dirichlet(Q, b, n0, topP) # Dirichlet
#
# solve LS
#
t = time.time()
print("solve")
# x0 = d*np.ones(Q.shape[0]) # empirically proofen to be the best
# x, info = LA.cg(Q,b,x0=x0, tol=1e-12) # tested with CG, CGS, GMRES, BICG. CG by far the best
x = LA.spsolve(Q, b) # direct
print("fin")
# print("CG: " + str(time.time()-t) +" sec" )
print("spsolve: " + str(time.time() - t) + " sec")
#
# output
#
f0 = xylem_flux.axial_flux0(x, seg, nodes, kz, rho, g)
print("Effective transpiration.: ", f0, " [?]")
segP = nodes2seg(nodes, seg, x)
axial_flux = xylem_flux.axial_flux(x, seg, nodes, kz, rho, g)
radial_flux = xylem_flux.radial_flux(x, seg, nodes, radius, kr, soil_p)
net_flux = axial_flux + radial_flux
rs_ana.addUserData(a2v(segP), "pressure")
rs_ana.addUserData(a2v(axial_flux), "axial_flux")
rs_ana.addUserData(a2v(radial_flux), "radial_flux")
rs_ana.addUserData(a2v(net_flux), "net_flux")
rs_ana.write(rsname + ".vtp")