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The problem was that A_ldiv_B! does not update B in case A is a sparse lufact: https://github.com/JuliaLang/julia/issues/10787 Sparse coloring does not work yet.
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using ODE,DASSL | ||
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const T = Float64 # the datatype used, probably Float64 | ||
Tarr = SparseMatrixCSC | ||
const N = 500 # active gridpoints | ||
const dof = 2N # degrees of freedom (boundary points are not free) | ||
dx = 1/(N+1) | ||
x = dx:dx:1-dx | ||
dae = 0 # index of DAE, ==0 for ODE | ||
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# parameters | ||
alpha = 1/50 | ||
const gamma = alpha/dx^2 | ||
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# BC | ||
const one_ = one(T) | ||
const three = 3*one_ | ||
ubc1() = one_ | ||
ubc2() = one_ | ||
vbc1() = three | ||
vbc2() = three | ||
#IC | ||
u0(x) = 1 + 0.5*sin(2π*x) | ||
v0(x) = 3 * ones(length(x)) | ||
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inds(i) = (2i-1, 2i) | ||
function fn!(res, y, dydt) | ||
# the ode function res = f(y,dydt) | ||
# | ||
# Note the u and v are staggered: | ||
# u = y[1:2:end], v=y[2:2:end] | ||
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# setup for first step | ||
i = 1 | ||
iu, iv = inds(i) | ||
ui0 = ubc1(); vi0 = vbc1() # BC | ||
ui1 = y[iu]; vi1 = y[iv] | ||
ui2 = y[iu+2]; vi2 = y[iv+2] | ||
while i<=N | ||
res[iu] = 1 + ui1^2*vi1 - 4*ui1 + gamma*(ui0 - 2*ui1 + ui2) - dydt[iu] | ||
res[iv] = 3*ui1 - ui1^2*vi1 + gamma*(vi0 - 2*vi1 + vi2) - dydt[iv] | ||
# setup for next step: | ||
i += 1 | ||
iu, iv = inds(i) | ||
ui0 = ui1; vi0 = vi1 | ||
ui1 = ui2; vi1 = vi2 | ||
if i<N | ||
ui2 = y[iu+2] | ||
vi2 = y[iv+2] | ||
else # on last step do BC | ||
ui2 = ubc2() | ||
vi2 = vbc2() | ||
end | ||
end | ||
return nothing | ||
end | ||
fn!(;T_::Type=T, dof_=dof) = zeros(T_,dof_) | ||
function fn(t, y, ydot) | ||
res = fn!() | ||
fn!(res, y, ydot) | ||
return res | ||
end | ||
function fn_ex(t, y) | ||
res = fn!() | ||
fn!(res, y, 0*y) | ||
return res | ||
end | ||
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# Jacobian is a banded matrix with upper and lower bandwidth 2, | ||
# c.f. W&H p.148, but Julia does not support banded matrices yet. | ||
# Thus use a sparse matrix. | ||
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function jac!(dfdy, y, ydot, a) | ||
# The Jacobian of fn: = df/dy + a* df/dydot | ||
ii = 1 # direct index into dfdy.nzval | ||
for i=1:N # iterate over double-columns | ||
iu, iv = inds(i) | ||
ui = y[iu] | ||
vi = y[iv] | ||
# iu: column belonging to d/du(i) | ||
if iu-2>=1 | ||
# du'(i-1)/du(i) | ||
dfdy.nzval[ii] = gamma | ||
ii +=1 | ||
end | ||
if iv-2>=1 | ||
# dv'(i-1)/du(i)==0 | ||
dfdy.nzval[ii] = 0 | ||
ii +=1 | ||
end | ||
# du'(i)/du(i) | ||
dfdy.nzval[ii] = 2*ui*vi - 4 -2*gamma - a | ||
ii += 1 | ||
# dv'(i)/du(i) | ||
dfdy.nzval[ii] = 3 - 2*ui*vi | ||
ii +=1 | ||
if iu+2<=2N | ||
# du'(i+1)/du(i) | ||
dfdy.nzval[ii] = gamma | ||
ii +=1 | ||
end | ||
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# iv: column belonging to d/dv(i) | ||
if iv-2>=1 | ||
# dv'(i-1)/dv(i) | ||
dfdy.nzval[ii] = gamma | ||
ii +=1 | ||
end | ||
# du'(i)/dv(i) | ||
dfdy.nzval[ii] = ui^2 | ||
ii +=1 | ||
# dv'(i)/dv(i) | ||
dfdy.nzval[ii] = -ui^2 -2*gamma - a | ||
ii +=1 | ||
if iu+2<=2N | ||
# du'(i+1)/dv(i)==0 | ||
dfdy.nzval[ii] = 0 | ||
ii +=1 | ||
end | ||
if iv+2<=2N | ||
# dv'(i+1)/dv(i) | ||
dfdy.nzval[ii] = gamma | ||
ii +=1 | ||
end | ||
end | ||
return nothing | ||
end | ||
function jac!(;T_::Type=T, dof_=dof) | ||
B = (ones(T_,dof_-2), ones(T_,dof_-1), ones(T_,dof_), ones(T_,dof_-1), ones(T_,dof_-2)) | ||
spdiagm(B, (-2,-1,0,1,2)) | ||
end | ||
function jac(t, y, ydot, a) | ||
J = jac!() | ||
jac!(J, y, ydot, a) | ||
return J | ||
end | ||
function jac_ex(t, y) | ||
return jac(t, y, y, 0) | ||
end | ||
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refsol = T[0.9949197002317599, 3.0213845767604077, 0.9594350193986054, 3.0585989778165419, 0.9243010095428502, 3.0952478919989637, 0.8897959106772672, | ||
3.1310118289054731, 0.8561653620284367, 3.1656101198770159, 0.8236197147449046, 3.1988043370624344, 0.7923328094811884, 3.2303999530641514, | ||
0.7624421042573115, 3.2602463873623941, 0.7340499750795348, 3.2882356529108807, 0.7072259700779899, 3.3142998590079271, 0.6820097782458483, | ||
3.3384078449410937, 0.6584146743834650, 3.3605612157873943, 0.6364312187752559, 3.3807900316323134, 0.6160310186921587, 3.3991483695914764, | ||
0.5971703941198909, 3.4157099395342736, 0.5797938277687891, 3.4305638938070224, 0.5638371159206763, 3.4438109320334580, 0.5492301695479158, | ||
3.4555597666485198, 0.5358994429426996, 3.4659239846027008, 0.5237699892215797, 3.4750193162238476, 0.5127671585747183, 3.4829613034792271, | ||
0.5028179665048467, 3.4898633463634923, 0.4938521662914935, 3.4958350971335204, 0.4858030633656755, 3.5009811668111510, 0.4786081100251151, | ||
3.5054001059792705, 0.4722093177200750, 3.5091836216744015, 0.4665535216425440, 3.5124159935026285, 0.4615925290790646, 3.5151736544621075, | ||
0.4572831793403656, 3.5175249049438184, 0.4535873393501199, 3.5195297317024448, 0.4504718553589467, 3.5212397070273984, 0.4479084778719241, | ||
3.5226979467564341, 0.4458737738041973, 3.5239391090719634, 0.4443490371324889, 3.5249894191569453, 0.4433202068820853, 3.5258667077466495, | ||
0.4427777991494095, 3.5265804544017270, 0.4427168579654424, 3.5271318289682063, 0.4431369281018266, 3.5275137272135266, 0.4440420513508381, | ||
3.5277107990730161, 0.4454407863109616, 3.5276994703501980, 0.4473462502188303, 3.5274479611304068, 0.4497761798232572, 3.5269163066324394, | ||
0.4527530066369863, 3.5260563887768472, 0.4563039400688689, 3.5248119894251024, 0.4604610498812091, 3.5231188790654930, 0.4652613370907894, | ||
3.5209049576992761, 0.4707467798082714, 3.5180904678044698, 0.4769643375804777, 3.5145883024867057, 0.4839658945842979, 3.5103044351908528, | ||
0.4918081185812277, 3.5051385005173827, 0.5005522089940899, 3.4989845585737802, 0.5102635039989190, 3.4917320776245013, 0.5210109134090777, | ||
3.4832671712209993, 0.5328661417420937, 3.4734741260299615, 0.5459026646938675, 3.4622372546582585, 0.5601944229089820, 3.4494431032230182, | ||
0.5758142001453760, 3.4349830354873361, 0.5928316594749734, 3.4187562033108012, 0.6113110218368440, 3.4006728962523969, 0.6313083867734524, | ||
3.3806582409098729, 0.6528687160104193, 3.3586561928427350, 0.6760225267555723, 3.3346337311179157, 0.7007823726569721, 3.3085851288057930, | ||
0.7271392249346637, 3.2805361342349380, 0.7550589020044152, 3.2505478606008622, 0.7844787296769868, 3.2187201496972175, 0.8153046416214843, | ||
3.1851941538893653, 0.8474089465959840, 3.1501538739882800, 0.8806289904192589, 3.1138264039027113, 0.9147669230929857, 3.0764806689389470, | ||
0.9495907429372025, 3.0384245041548366, 0.9848367306701233] # reference sol from Hairer has 1.36 scd | ||
refsolinds = collect(1:7:dof) # refsol is only at components 1:7:2N | ||
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ic = zeros(T,2N) | ||
ic[1:2:2N] = u0(x) | ||
ic[2:2:2N] = v0(x) | ||
tspan = T[0.0, 10.0] # integration interval | ||
tspan0 = T[0.0, 0.001] # integration interval | ||
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#t,ydassl = dasslSolve(fn, ic, tspan, jacobian=jac) | ||
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## ode23s | ||
# tout, yout = ode23s(fn_ex, ic, tspan0, jacobian=jac_ex) | ||
# @time tout, yout = ode23s(fn_ex, ic, tspan, jacobian=jac_ex) | ||
# @show norm(abs(yout[end][refsolinds]-refsol)./refsol, Inf) | ||
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# ## DASSL | ||
# t,ydassl = dasslSolve(fn, ic, tspan0, jacobian=jac) | ||
# @time t,ydassl = dasslSolve(fn, ic, tspan, jacobian=jac) | ||
# @show norm(abs(ydassl[end][refsolinds]-refsol)./refsol, Inf) | ||
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## ROSW | ||
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# # No jac works but is slower and gives much higher precision than | ||
# # other methods. | ||
# tout, yout = ode_rosw(fn!, ic, tspan0) | ||
# @time tout, yout = ode_rosw(fn!, ic, tspan) | ||
# @show norm(abs(yout[end][refsolinds]-refsol)./refsol, Inf) | ||
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# Analytic Jacobian | ||
tout, yout = ode_rosw(fn!, ic, tspan0, jacobian=(jac!, jac!())) | ||
@time tout, yout = ode_rosw(fn!, ic, tspan, jacobian=(jac!, jac!())) | ||
@show norm(abs(yout[end][refsolinds]-refsol)./refsol, Inf) | ||
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# Numerical colored Jacobian | ||
tout, yout = ode_rosw(fn!, ic, tspan0, jacobian=jac!()) | ||
@time tout, yout = ode_rosw(fn!, ic, tspan, jacobian=jac!()) | ||
@show norm(abs(yout[end][refsolinds]-refsol)./refsol, Inf) | ||
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