NMinimize Error In Evaluation
- To: mathgroup at smc.vnet.net
- Subject: [mg84801] NMinimize Error In Evaluation
- From: "Jason S. Kong" <kongjs at gmail.com>
- Date: Tue, 15 Jan 2008 03:13:49 -0500 (EST)
Hi,
I have been having an issue with NMinimize in an attempt to try to do
some optimization routines.
First, here is the background:
I want to simulate some data that was experimentally determined, and
there are a large variety of variables involved. I do not believe
there is a simple, analytical solution to obtain my results, so I
decided to optimize it numerically, that is, NMinimize. Below I have
some data and the method by which I attempted to solve this. At the
end, you will see the error I get, preventing me from being able to
utilize NMinimize. Any help on this issue would be greatly
appreciated, as this is not the first time I have had to abandon a
problem due to the same error!
At the end, I wanted to see if NMinimize had problems with functions
inside of NMinimize by writing a quick "roar" program, but it
functioned fine.
Thanks,
-Jason S. Kong
---
xvals = {6.`, 12.`, 18.`, 24.`, 36.`, 48.`, 60.`, 75.`, 90.`, 120.`,
150.`, 180.`, 210.`, 240.`, 270.`, 300.`, 390.`, 480.`, 570.`,
660.`, 750.`, 840.`, 912.`, 930.`, 1020.`, 1110.`, 1200.`, 1350.`,
1524.`, 1800.`, 2442.`};
yvals = {0.03049534752960375`, 0.030612029204239437`,
0.03088344092567462`, 0.03106269103453524`, 0.03132902963968192`,
0.031313810290816396`, 0.03167484706668189`, 0.031816894322760116`,
0.03173995205905108`, 0.031799138415750335`, 0.03183126815224423`,
0.03200882722234201`, 0.03196570573388969`, 0.032041802478217314`,
0.03191751112914886`, 0.03214072824584322`, 0.03222950778089211`,
0.03230898660274541`, 0.03230306796707548`, 0.03227516582748868`,
0.032589699037376185`, 0.03284927348747152`, 0.03289831361159377`,
0.03300231249550818`, 0.03331853674415852`, 0.033540908341471456`,
0.03361869612456192`, 0.033647443783530136`, 0.033538371783327206`,
0.033603476775696396`, 0.03364321618662304`};
ListPlot[{xvals, yvals} // Transpose]
equilibrium[C1_, C2_, C3_, C4_, C5_] := Solve[
{C1 == var2/(var1 var5),
C2 == var3/var2,
C3 == var4/var2,
var1 + var2 + var3 + var4 == C4,
var5 + var2 + var3 + 2 var4 == C5}, {var1, var2, var3, var4,
var5}, WorkingPrecision -> 100] // N // Chop
imagine[tests_] :=
Select[tests,
And @@ {(Re[var1 /. #] == var1 /. #), (Re[var2 /. #] ==
var2 /. #), (Re[var3 /. #] == var3 /. #), (Re[var4 /. #] ==
var4 /. #), (Re[var5 /. #] == var5 /. #)} &]
dynamics[C1_, C2_, C3_, C4_, C5_] :=
Select[imagine[
equilibrium[C1, C2, C3, C4,
C5]], #[[1, 2]] > 0 && #[[2, 2]] > 0 && #[[3, 2]] > 0 &]
data1[C1_, C2_, C3_, C4_,
C5_] := {C5, var1} /. dynamics[C1, C2, C3, C4, C5] // Flatten
data2[C1_, C2_, C3_, C4_,
C5_] := {C5, var2 + var3} /. dynamics[C1, C2, C3, C4, C5] //
Flatten
data3[C1_, C2_, C3_, C4_,
C5_] := {C5, var5} /. dynamics[C1, C2, C3, C4, C5] // Flatten
go[C1_, C2_, C3_, C4_, R1_, R2_, R3_] := (
listdata1 = data1[C1, C2, C3, C4, #] & /@ xvals;
listdata2 = data2[C1, C2, C3, C4, #] & /@ xvals;
listdata3 = data3[C1, C2, C3, C4, #] & /@ xvals;
r1 = (R1 #)/C4 & /@ (listdata1 // Transpose)[[2]];
r2 = (R2 #)/C4 & /@ (listdata2 // Transpose)[[2]];
r3 = (R3 #)/C4 & /@ (listdata3 // Transpose)[[2]];
calcyvals = r1 + r2 + r3;
error = Total[(calcyvals - yvals)^2])
NMinimize[{go[c1, c2, c3, 25, ra1, ra2, ra3],
c1 > 0 && c2 > 0 && c3 > 0 && ra1 > 0 && ra2 > ra1 &&
ra3 > ra2}, {c1, c2, c3, ra1, ra2, ra3}]
NMinimize::nnum: The function value (-0.0336474+0.04 var1+0.04 \
(var2+var3)+0.04 var5)^2+(-0.0336432+0.04 var1+0.04 (var2+var3)+0.04 \
var5)^2+(-<<20>>+<<2>>+0.04 \
var5)^2+(<<1>>)^2+<<1>>^2+<<1>><<1>><<1>>+(<<1>>)^2+(<<1>>)^2+(-0.\
0328493+0.04 var1+<<1>>+0.04 var5)^2+<<21>> is not a number at \
{c1,c2,c3,ra1,ra2,ra3} = {2.,2.,2.,1.,1.,1.}. >>
NMinimize[{(-0.0336474 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.0336432 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.0336187 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0336035 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.0335409 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.0335384 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0333185 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.0330023 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.0328983 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0328493 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.0325897 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.032309 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0323031 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.0322752 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.0322295 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0321407 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.0320418 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.0320088 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0319657 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.0319175 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.0318313 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0318169 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.0317991 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.03174 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0316748 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.031329 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.0313138 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0310627 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2 + (-0.0308834 + (ra1 var1)/25 +
1/25 ra2 (var2 + var3) + (ra3 var5)/25)^2 + (-0.030612 + (
ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (ra3 var5)/
25)^2 + (-0.0304953 + (ra1 var1)/25 + 1/25 ra2 (var2 + var3) + (
ra3 var5)/25)^2,
c1 > 0 && c2 > 0 && c3 > 0 && ra1 > 0 && ra2 > ra1 &&
ra3 > ra2}, {c1, c2, c3, ra1, ra2, ra3}]
go[2., 2., 2., 25, 1., 1., 1.]
33275.9
roar[x_, y_] := x^2 + y^2
NMinimize[roar[x, y], {x, y}]
{0., {x -> 0., y -> 0.}}
--
Jason S. Kong
Graduate Student, Chen Lab
Department of Chemistry and Chemical Biology
Baker Laboratory, Cornell University
Ithaca, NY, 14853
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