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
- Follow-Ups:
- Re: Re: NMinimize Error In Evaluation
- From: "Jason S. Kong" <kongjs@gmail.com>
- Re: NMinimize Error In Evaluation
- From: "Jason S. Kong" <kongjs@gmail.com>
- Re: Re: NMinimize Error In Evaluation