* using log directory 'd:/Rcompile/CRANpkg/local64/2.11/optimx.Rcheck' * using R version 2.11.1 Patched (2010-07-29 r52657) * using session charset: ISO8859-1 * checking for file 'optimx/DESCRIPTION' ... OK * this is package 'optimx' version '0.84' * checking package name space information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK * checking whether package 'optimx' can be installed ... OK * checking package directory ... OK * checking for portable file names ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking index information ... OK * checking package subdirectories ... OK * checking R files for non-ASCII characters ... OK * checking R files for syntax errors ... OK * checking whether the package can be loaded ... OK * checking whether the package can be loaded with stated dependencies ... OK * checking whether the package can be unloaded cleanly ... OK * checking whether the name space can be loaded with stated dependencies ... OK * checking whether the name space can be unloaded cleanly ... OK * checking for unstated dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... OK * checking Rd files ... OK * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... OK * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking examples ... ERROR Running examples in 'optimx-Ex.R' failed. The error most likely occurred in: > ### * optimx > > flush(stderr()); flush(stdout()) > > ### Name: optimx > ### Title: General-purpose optimization > ### Aliases: optimx > ### Keywords: nonlinear optimize > > ### ** Examples > > require(graphics) > > fr <- function(x) { ## Rosenbrock Banana function + x1 <- x[1] + x2 <- x[2] + 100 * (x2 - x1 * x1)^2 + (1 - x1)^2 + } > grr <- function(x) { ## Gradient of 'fr' + x1 <- x[1] + x2 <- x[2] + c(-400 * x1 * (x2 - x1 * x1) - 2 * (1 - x1), + 200 * (x2 - x1 * x1)) + } > ans1<-optimx(c(-1.2,1), fr) > print(ans1) par fvalues method fns grs itns conv KKT1 KKT2 1 1.000260, 1.000506 8.825241e-08 Nelder-Mead 195 NA NULL 0 FALSE TRUE 2 0.9998044, 0.9996084 3.827383e-08 BFGS 118 38 NULL 0 TRUE TRUE xtimes 1 0 2 0.02 > print(attr(ans1,"details")) [[1]] [[1]]$par [1] 1.000260 1.000506 [[1]]$value [1] 8.825241e-08 [[1]]$convergence [1] 0 [[1]]$message NULL [[1]]$conv [1] 0 [[1]]$fevals function 195 [[1]]$gevals gradient NA [[1]]$kkt1 [1] FALSE [[1]]$kkt2 [1] TRUE [[1]]$ngatend [1] 0.006260098 -0.002869164 [[1]]$nhatend [,1] [,2] [1,] 802.4220 -400.1041 [2,] -400.1041 200.0000 [[1]]$evnhatend [1] 1002.0216761 0.4003383 [[1]]$systime user.self 0 [[1]]$method [1] "Nelder-Mead" [[2]] [[2]]$par [1] 0.9998044 0.9996084 [[2]]$value [1] 3.827383e-08 [[2]]$convergence [1] 0 [[2]]$message NULL [[2]]$conv [1] 0 [[2]]$fevals function 118 [[2]]$gevals gradient 38 [[2]]$kkt1 [1] TRUE [[2]]$kkt2 [1] TRUE [[2]]$ngatend [1] -0.0001815403 -0.0001048171 [[2]]$nhatend [,1] [,2] [1,] 801.6873 -399.9218 [2,] -399.9218 200.0000 [[2]]$evnhatend [1] 1001.2878060 0.3995274 [[2]]$systime user.self 0.02 [[2]]$method [1] "BFGS" > cat("\n\n") > ans2<-optimx(c(-1.2,1), fr, grr, method = "BFGS") > print(ans2) par fvalues method fns grs itns conv KKT1 KKT2 xtimes 1 1, 1 9.594956e-18 BFGS 110 43 NULL 0 TRUE TRUE 0 > ## The next line will fail if executed because 'hessian = TRUE' no longer allowed > # ans3<-optimx(c(-1.2,1), fr, NULL, method = "BFGS", hessian = TRUE) > cat("\n\n") > ans4<-optimx(c(-1.2,1), fr, grr, method = "CG",control=list(trace=TRUE)) fn is fr Function has 2 arguments Analytic gradient from function grr Analytic Hessian not made available. Looking for method = CG Scale check -- log parameter ratio= 0.07918125 log bounds ratio= NA Method: CG Conjugate gradients function minimizer Method: Fletcher Reeves tolerance used in gradient test=3.63798e-12 0 1 24.200000 parameters -1.20000 1.00000 **** i< 1 7 4.132161 parameters -1.02752 1.07040 * i> 2 10 4.126910 parameters -1.02855 1.06882 **** i> 3 16 4.121409 parameters -1.02924 1.06533 i> 4 18 4.106523 parameters -1.02586 1.05731 **** i> 5 24 4.100955 parameters -1.02261 1.05573 i> 6 26 4.086136 parameters -1.01839 1.04818 **** i> 7 32 4.080524 parameters -1.01914 1.04464 i> 8 34 4.065787 parameters -1.01579 1.03670 **** i> 9 40 4.060127 parameters -1.01250 1.03514 i> 10 42 4.045415 parameters -1.00824 1.02768 **** i> 11 48 4.039717 parameters -1.00900 1.02412 i> 12 50 4.025073 parameters -1.00568 1.01621 **** i> 13 56 4.019328 parameters -1.00236 1.01467 i> 14 58 4.004703 parameters -0.99804 1.00728 **** i> 15 64 3.998920 parameters -0.99880 1.00370 i> 16 66 3.984360 parameters -0.99552 0.99582 **** i> 17 72 3.978528 parameters -0.99217 0.99429 i> 18 74 3.963986 parameters -0.98779 0.98699 **** i> 19 80 3.958118 parameters -0.98855 0.98339 i> 20 82 3.943639 parameters -0.98530 0.97553 **** i> 21 88 3.937719 parameters -0.98192 0.97402 i> 22 90 3.923256 parameters -0.97749 0.96680 **** i> 23 96 3.917299 parameters -0.97824 0.96317 i> 24 98 3.902898 parameters -0.97502 0.95534 **** i> 25 104 3.896888 parameters -0.97161 0.95384 i> 26 106 3.882502 parameters -0.96712 0.94670 **** i> 27 112 3.876454 parameters -0.96787 0.94306 i> 28 114 3.862128 parameters -0.96469 0.93524 **** i> 29 120 3.856025 parameters -0.96125 0.93376 i> 30 122 3.841712 parameters -0.95669 0.92669 **** i> 31 128 3.835572 parameters -0.95743 0.92303 i> 32 130 3.821316 parameters -0.95429 0.91522 **** i> 33 136 3.815119 parameters -0.95082 0.91376 i> 34 138 3.800875 parameters -0.94618 0.90677 **** i> 35 144 3.794641 parameters -0.94692 0.90309 i> 36 146 3.780452 parameters -0.94382 0.89530 **** i> 37 152 3.774158 parameters -0.94032 0.89385 i> 38 154 3.759979 parameters -0.93561 0.88694 **** i> 39 160 3.753649 parameters -0.93635 0.88323 i> 40 162 3.739522 parameters -0.93327 0.87545 **** i> 41 168 3.733129 parameters -0.92975 0.87402 i> 42 170 3.719010 parameters -0.92496 0.86719 **** i> 43 176 3.712582 parameters -0.92569 0.86346 i> 44 178 3.698513 parameters -0.92265 0.85568 **** i> 45 184 3.692020 parameters -0.91909 0.85427 i> 46 186 3.677956 parameters -0.91422 0.84751 **** i> 47 192 3.671429 parameters -0.91495 0.84377 i> 48 194 3.657411 parameters -0.91194 0.83598 **** i> 49 200 3.650816 parameters -0.90836 0.83459 i> 50 202 3.636803 parameters -0.90340 0.82791 **** i> 51 208 3.630174 parameters -0.90412 0.82414 i> 52 210 3.616203 parameters -0.90115 0.81636 **** i> 53 216 3.609503 parameters -0.89754 0.81498 i> 54 218 3.595534 parameters -0.89249 0.80838 **** i> 55 224 3.588802 parameters -0.89320 0.80459 i> 56 226 3.574871 parameters -0.89026 0.79679 **** i> 57 232 3.568067 parameters -0.88662 0.79544 i> 58 234 3.554135 parameters -0.88148 0.78891 **** i> 59 240 3.547298 parameters -0.88217 0.78510 i> 60 242 3.533401 parameters -0.87927 0.77729 **** i> 61 248 3.526489 parameters -0.87561 0.77595 i> 62 250 3.512588 parameters -0.87036 0.76950 **** i> 63 256 3.505645 parameters -0.87105 0.76567 i> 64 258 3.491774 parameters -0.86818 0.75784 **** i> 65 264 3.484754 parameters -0.86448 0.75653 i> 66 266 3.470875 parameters -0.85914 0.75015 **** i> 67 272 3.463826 parameters -0.85981 0.74630 i> 68 274 3.449973 parameters -0.85697 0.73845 **** i> 69 280 3.442843 parameters -0.85325 0.73715 i> 70 282 3.428978 parameters -0.84779 0.73085 **** i> 71 288 3.421820 parameters -0.84844 0.72698 i> 72 290 3.407976 parameters -0.84564 0.71910 **** i> 73 296 3.400736 parameters -0.84189 0.71782 i> 74 298 3.386876 parameters -0.83632 0.71160 **** i> 75 304 3.379609 parameters -0.83696 0.70771 i> 76 306 3.365764 parameters -0.83418 0.69979 **** i> 77 312 3.358412 parameters -0.83041 0.69853 i> 78 314 3.344546 parameters -0.82472 0.69239 **** i> 79 320 3.337170 parameters -0.82533 0.68848 i> 80 322 3.323313 parameters -0.82258 0.68052 **** i> 81 328 3.315850 parameters -0.81879 0.67928 i> 82 330 3.301967 parameters -0.81297 0.67321 **** i> 83 336 3.294481 parameters -0.81356 0.66928 i> 84 338 3.280600 parameters -0.81084 0.66128 **** i> 85 344 3.273027 parameters -0.80703 0.66006 i> 86 346 3.259113 parameters -0.80108 0.65407 **** i> 87 352 3.251518 parameters -0.80164 0.65012 i> 88 354 3.237599 parameters -0.79894 0.64206 **** i> 89 360 3.229915 parameters -0.79510 0.64086 i> 90 362 3.215957 parameters -0.78902 0.63495 **** i> 91 368 3.208254 parameters -0.78955 0.63098 i> 92 370 3.194282 parameters -0.78687 0.62287 **** i> 93 376 3.186489 parameters -0.78302 0.62168 i> 94 378 3.172470 parameters -0.77678 0.61585 **** i> 95 384 3.164660 parameters -0.77729 0.61186 i> 96 386 3.150619 parameters -0.77463 0.60368 **** i> 97 392 3.142719 parameters -0.77075 0.60252 i> 98 394 3.128622 parameters -0.76437 0.59676 **** i> 99 400 3.120708 parameters -0.76484 0.59276 i> 100 402 3.106579 parameters -0.76218 0.58451 Post processing for method CG Compute gradient approximation at finish of CG Compute Hessian approximation at finish of CG Save results from method CG Assemble the answers Sort results > print(ans4) par fvalues method fns grs itns conv KKT1 KKT2 xtimes 1 -0.7648373, 0.5927588 3.106579 CG 402 101 NULL 1 FALSE FALSE 0 > cat("\n\n") > ans5<-optimx(c(-1.2,1), fr, grr, method = "CG", control=list(type=2)) > print(ans5) par fvalues method fns grs itns conv KKT1 KKT2 xtimes 1 0.9944093, 0.9888229 3.123777e-05 CG 385 101 NULL 1 FALSE TRUE 0 > cat("\n\n") > ans6<-optimx(c(-1.2,1), fr, grr, method = "L-BFGS-B") > print(ans6) par fvalues method fns grs itns conv KKT1 KKT2 xtimes 1 0.9999997, 0.9999995 2.267577e-13 L-BFGS-B 47 47 NULL 0 TRUE TRUE 0 > cat("\n\n") > > flb <- function(x) + { p <- length(x); sum(c(1, rep(4, p-1)) * (x - c(1, x[-p])^2)^2) } > ## 25-dimensional box constrained > optimx(rep(3, 25), flb, NULL, method = "L-BFGS-B", + lower=rep(2, 25), upper=rep(4, 25)) # par[24] is *not* at boundary par 1 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.000000, 2.109093, 4.000000 fvalues method fns grs itns conv KKT1 KKT2 xtimes 1 368.1059 L-BFGS-B 6 6 NULL 0 FALSE TRUE 0 > > ## "wild" function , global minimum at about -15.81515 > fw <- function (x) + 10*sin(0.3*x)*sin(1.3*x^2) + 0.00001*x^4 + 0.2*x+80 > plot(fw, -50, 50, n=1000, main = "optim() minimising 'wild function'") > > ## Suppressed for optimx() ans7 <- optimx(50, fw, method="SANN", > ## control=list(maxit=20000, temp=20, parscale=20)) > ## ans7 > ## Now improve locally {typically only by a small bit}: > ## newpar<-unlist(ans7$par) # NOTE: you need to unlist the parameters as optimx() has multiple outputs > ##(r2 <- optimx(newpar, fw, method="BFGS")) > ##points(r2$par, r2$value, pch = 8, col = "red", cex = 2) > > ## Show multiple outputs of optimx using all.methods > # genrose function code > genrose.f<- function(x, gs=NULL){ # objective function + ## One generalization of the Rosenbrock banana valley function (n parameters) + n <- length(x) + if(is.null(gs)) { gs=100.0 } + fval<-1.0 + sum (gs*(x[1:(n-1)]^2 - x[2:n])^2 + (x[2:n] - 1)^2) + return(fval) + } > > genrose.g <- function(x, gs=NULL){ + # vectorized gradient for genrose.f + # Ravi Varadhan 2009-04-03 + n <- length(x) + if(is.null(gs)) { gs=100.0 } + gg <- as.vector(rep(0, n)) + tn <- 2:n + tn1 <- tn - 1 + z1 <- x[tn] - x[tn1]^2 + z2 <- 1 - x[tn] + gg[tn] <- 2 * (gs * z1 - z2) + gg[tn1] <- gg[tn1] - 4 * gs * x[tn1] * z1 + return(gg) + } > > genrose.h <- function(x, gs=NULL) { ## compute Hessian + if(is.null(gs)) { gs=100.0 } + n <- length(x) + hh<-matrix(rep(0, n*n),n,n) + for (i in 2:n) { + z1<-x[i]-x[i-1]*x[i-1] + z2<-1.0-x[i] + hh[i,i]<-hh[i,i]+2.0*(gs+1.0) + hh[i-1,i-1]<-hh[i-1,i-1]-4.0*gs*z1-4.0*gs*x[i-1]*(-2.0*x[i-1]) + hh[i,i-1]<-hh[i,i-1]-4.0*gs*x[i-1] + hh[i-1,i]<-hh[i-1,i]-4.0*gs*x[i-1] + } + return(hh) + } > > startx<-4*seq(1:10)/3. > ans8<-optimx(startx,fn=genrose.f,gr=genrose.g, hess=genrose.h, control=list(all.methods=TRUE, save.failures=TRUE), gs=10) all.methods is TRUE -- Using all available methods [1] "BFGS" "CG" "Nelder-Mead" "L-BFGS-B" "nlm" [6] "nlminb" "spg" "ucminf" "Rcgmin" "Rvmmin" [11] "bobyqa" "uobyqa" "newuoa" Try function at initial point: [1] 1.333333 2.666667 4.000000 5.333333 6.666667 8.000000 9.333333 [8] 10.666667 12.000000 13.333333 f= 382462.7 > print(ans8) par 3 0.1485254, 0.7219329, 1.1931460, 1.2200314, -1.4280132, 0.7719437, 1.9202220, 2.1584949, 6.0673775, 35.1981635 5 -0.9723634, 0.9885277, 0.9857010, 0.9787716, 0.9815156, 0.9937781, 0.9994302, 0.9780824, 0.9047627, 0.7204988 11 0.9999989, 0.9999985, 0.9999983, 0.9999978, 0.9999978, 0.9999975, 0.9999978, 0.9999956, 0.9999925, 0.9999858 4 -0.9999983, 0.9999979, 0.9999983, 0.9999992, 0.9999992, 0.9999993, 0.9999993, 0.9999983, 0.9999952, 0.9999891 1 -1.0000000, 0.9999999, 0.9999997, 1.0000002, 1.0000004, 1.0000001, 1.0000002, 0.9999997, 0.9999996, 0.9999993 13 -1.0000000, 1.0000004, 1.0000002, 1.0000002, 1.0000001, 1.0000000, 0.9999999, 1.0000000, 0.9999996, 0.9999991 2 0.9999998, 0.9999998, 0.9999997, 0.9999996, 0.9999997, 0.9999996, 0.9999996, 0.9999996, 0.9999995, 0.9999990 6 0.9999999, 1.0000000, 1.0000000, 1.0000001, 1.0000001, 1.0000001, 0.9999999, 0.9999998, 0.9999997, 0.9999994 7 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000, 1.000000 12 -1, 1, 1, 1, 1, 1, 1, 1, 1, 1 8 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 9 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 10 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 fvalues method fns grs itns conv KKT1 KKT2 xtimes 3 1402.26 Nelder-Mead 501 NA NULL 1 FALSE FALSE 0.01 5 1.252242 nlm NA NA 100 1 FALSE TRUE 0.03 11 1 bobyqa 880 NA NULL 0 TRUE TRUE 0.06 4 1 L-BFGS-B 68 68 NULL 0 TRUE TRUE 0.02 1 1 BFGS 165 60 NULL 0 TRUE TRUE 0 13 1 newuoa 1478 NA NULL 0 TRUE TRUE 0.11 2 1 CG 262 101 NULL 1 TRUE TRUE 0.01 6 1 nlminb 62 53 52 0 TRUE TRUE 0 7 1 spg 227 NA 208 0 TRUE TRUE 0.06 12 1 uobyqa 738 NA NULL 0 TRUE TRUE 0.11 8 1 ucminf 107 107 NULL 0 TRUE TRUE 0 9 1 Rcgmin 145 71 NULL 0 TRUE TRUE 0.01 10 1 Rvmmin 147 85 NULL 0 TRUE TRUE 0.04 > > get.result(ans8, attribute="grs") method grs 12 uobyqa NA 7 spg NA 13 newuoa NA 11 bobyqa NA 5 nlm NA 3 Nelder-Mead NA 8 ucminf 107 2 CG 101 10 Rvmmin 85 9 Rcgmin 71 4 L-BFGS-B 68 1 BFGS 60 6 nlminb 53 > get.result(ans8, method="spg") $par [1] 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 [9] 1.000000 1.000000 $fvalues [1] 1 $method [1] "spg" $fns [1] 227 $grs [1] NA $itns [1] 208 $conv [1] 0 $KKT1 [1] TRUE $KKT2 [1] TRUE $xtimes user.self 0.06 > > > startx<-4*seq(1:10)/3. > cat("Polyalgorithm with 200 steps NM followed by up to 75 of ucminf\n") Polyalgorithm with 200 steps NM followed by up to 75 of ucminf > ans9<-optimx(startx,fn=genrose.f,gr=genrose.g, hess=genrose.h, method=c("Nelder-Mead","ucminf"), + itnmax=c(200,75), control=list(follow.on=TRUE, save.failures=TRUE,trace=TRUE), gs=10) fn is genrose.f Function has 10 arguments Analytic gradient from function genrose.g Analytic hessian from function genrose.h Looking for method = Nelder-Mead Looking for method = ucminf Scale check -- log parameter ratio= 1 log bounds ratio= NA Do 200 steps of Nelder-Mead Method: Nelder-Mead Nelder-Mead direct search function minimizer function value for initial parameters = 382462.740741 Scaled convergence tolerance is 0.00569914 Stepsize computed as 1.333333 BUILD 11 479479.530864 379030.740741 EXTENSION 13 451122.395062 315411.830716 LO-REDUCTION 15 428928.222222 315411.830716 LO-REDUCTION 17 412138.493827 315411.830716 LO-REDUCTION 19 399994.691358 315411.830716 LO-REDUCTION 21 391738.296296 315411.830716 EXTENSION 23 386610.790123 280586.182142 LO-REDUCTION 25 383853.654321 280586.182142 EXTENSION 27 382652.370370 243537.617869 LO-REDUCTION 29 382462.740741 243537.617869 EXTENSION 31 379030.740741 202542.563592 LO-REDUCTION 33 330891.294958 202542.563592 LO-REDUCTION 35 327988.072772 202542.563592 LO-REDUCTION 37 323526.675374 202542.563592 LO-REDUCTION 39 317293.878632 202542.563592 LO-REDUCTION 41 315411.830716 202542.563592 EXTENSION 43 291879.728673 125490.339258 LO-REDUCTION 45 280586.182142 125490.339258 LO-REDUCTION 47 256381.017344 125490.339258 LO-REDUCTION 49 244598.728203 125490.339258 LO-REDUCTION 51 243537.617869 125490.339258 LO-REDUCTION 53 233950.044601 125490.339258 LO-REDUCTION 55 225773.553345 125490.339258 LO-REDUCTION 57 220120.208605 125490.339258 LO-REDUCTION 59 217019.591800 125490.339258 LO-REDUCTION 61 202542.563592 125490.339258 LO-REDUCTION 63 186379.780089 125490.339258 EXTENSION 65 178194.844261 118071.799127 LO-REDUCTION 67 177222.185722 118071.799127 EXTENSION 69 171997.619095 102622.184082 LO-REDUCTION 71 166991.034075 102622.184082 LO-REDUCTION 73 156833.520191 102622.184082 REFLECTION 75 144807.441972 99034.978668 LO-REDUCTION 77 139398.762798 99034.978668 EXTENSION 79 136690.892560 75982.102751 LO-REDUCTION 81 129924.600377 75982.102751 EXTENSION 83 128945.770039 62119.591382 LO-REDUCTION 85 125490.339258 62119.591382 HI-REDUCTION 87 118071.799127 62119.591382 LO-REDUCTION 89 107665.616287 62119.591382 LO-REDUCTION 91 103937.163503 62119.591382 LO-REDUCTION 93 102622.184082 62119.591382 LO-REDUCTION 95 101255.539477 62119.591382 LO-REDUCTION 97 99034.978668 62119.591382 LO-REDUCTION 99 91503.348497 62119.591382 LO-REDUCTION 101 83609.636793 62119.591382 LO-REDUCTION 103 79075.722774 62119.591382 EXTENSION 105 75982.102751 53129.632893 EXTENSION 107 75336.726642 46258.611289 LO-REDUCTION 109 71078.705732 46258.611289 LO-REDUCTION 111 69019.749391 46258.611289 LO-REDUCTION 113 68807.758429 46258.611289 LO-REDUCTION 115 67325.769070 46258.611289 EXTENSION 117 65674.060299 40784.649171 LO-REDUCTION 119 64966.248487 40784.649171 LO-REDUCTION 121 63458.887121 40784.649171 LO-REDUCTION 123 62119.591382 40784.649171 LO-REDUCTION 125 58906.190299 40784.649171 LO-REDUCTION 127 57045.462104 40784.649171 REFLECTION 129 55778.274942 39861.217896 REFLECTION 131 53129.632893 38016.965432 REFLECTION 133 52311.199663 37420.173917 EXTENSION 135 46258.611289 35036.861827 EXTENSION 137 46105.209891 30982.255711 LO-REDUCTION 139 45333.504251 30982.255711 EXTENSION 141 44026.328226 30017.838292 EXTENSION 143 43439.914960 23093.315529 LO-REDUCTION 145 42808.411900 23093.315529 LO-REDUCTION 147 40784.649171 23093.315529 LO-REDUCTION 149 39861.217896 23093.315529 LO-REDUCTION 151 38016.965432 23093.315529 LO-REDUCTION 153 37420.173917 23093.315529 LO-REDUCTION 155 35036.861827 23093.315529 LO-REDUCTION 157 33121.491277 23093.315529 LO-REDUCTION 159 30982.255711 23093.315529 LO-REDUCTION 161 30366.862179 23093.315529 LO-REDUCTION 163 30022.627935 23093.315529 EXTENSION 165 30017.838292 21124.359868 LO-REDUCTION 167 28982.543527 21124.359868 LO-REDUCTION 169 27790.980241 21124.359868 EXTENSION 171 26739.739991 20636.233168 EXTENSION 173 25586.819489 18820.882765 LO-REDUCTION 175 25568.333586 18820.882765 LO-REDUCTION 177 24651.691042 18820.882765 LO-REDUCTION 179 24597.631192 18820.882765 LO-REDUCTION 181 23878.360072 18820.882765 EXTENSION 183 23600.411306 15928.093725 LO-REDUCTION 185 23278.054182 15928.093725 LO-REDUCTION 187 23093.315529 15928.093725 LO-REDUCTION 189 21278.200811 15928.093725 LO-REDUCTION 191 21124.359868 15928.093725 LO-REDUCTION 193 21049.116703 15928.093725 LO-REDUCTION 195 20851.803526 15928.093725 EXTENSION 197 20636.233168 12576.034507 LO-REDUCTION 199 19930.998024 12576.034507 Exiting from Nelder Mead minimizer 201 function evaluations used Post processing for method Nelder-Mead Compute gradient approximation at finish of Nelder-Mead Compute Hessian approximation at finish of Nelder-Mead Save results from method Nelder-Mead Assemble the answers FOLLOW ON! Do 75 steps of ucminf Method: ucminf neval = 1 F(x) = 1.258D+04 max|g(x)| = 4.346D+03 x( 1.. 5) = 1.911D+00 3.019D+00 5.120D+00 4.643D+00 -9.015D-02 x( 6.. 10) = 1.108D+00 1.450D+00 -4.135D+00 6.368D+00 3.614D+01 Line search: alpha = 1.000D+00 dphi(0) = -6.071D+03 dphi(alpha) = -3.871D+03 neval = 2 F(x) = 7.658D+03 max|g(x)| = 2.625D+03 x( 1.. 5) = 1.903D+00 2.941D+00 4.404D+00 4.050D+00 -1.914D-02 x( 6.. 10) = 1.106D+00 1.390D+00 -3.821D+00 6.216D+00 3.614D+01 Line search: alpha = 1.000D+00 dphi(0) = -9.642D+02 dphi(alpha) = 5.446D+02 neval = 3 F(x) = 7.468D+03 max|g(x)| = 3.432D+03 x( 1.. 5) = 1.843D+00 2.401D+00 4.701D+00 3.766D+00 1.461D-01 x( 6.. 10) = 1.086D+00 1.128D+00 -3.244D+00 6.533D+00 3.605D+01 Line search: alpha = 1.000D+00 dphi(0) = -5.162D+02 dphi(alpha) = 3.922D+02 neval = 4 F(x) = 7.430D+03 max|g(x)| = 3.645D+03 x( 1.. 5) = 1.708D+00 1.741D+00 4.776D+00 3.959D+00 4.090D-01 x( 6.. 10) = 1.039D+00 7.462D-01 -2.941D+00 6.105D+00 3.595D+01 Line search: alpha = 1.000D+00 dphi(0) = -3.673D+02 dphi(alpha) = 1.218D+02 neval = 5 F(x) = 7.312D+03 max|g(x)| = 2.958D+03 x( 1.. 5) = 1.498D+00 1.121D+00 4.505D+00 4.282D+00 7.966D-01 x( 6.. 10) = 9.612D-01 3.273D-01 -3.018D+00 6.227D+00 3.575D+01 Line search: alpha = 1.000D+00 dphi(0) = -3.050D+02 dphi(alpha) = -6.570D+01 neval = 6 F(x) = 7.122D+03 max|g(x)| = 2.931D+03 x( 1.. 5) = 1.240D+00 5.914D-01 4.478D+00 4.187D+00 1.314D+00 x( 6.. 10) = 8.603D-01 -4.929D-02 -3.423D+00 6.218D+00 3.551D+01 Line search: alpha = 1.000D+00 dphi(0) = -1.826D+02 dphi(alpha) = 8.012D+00 neval = 7 F(x) = 7.026D+03 max|g(x)| = 2.902D+03 x( 1.. 5) = 8.068D-01 5.599D-01 4.470D+00 4.252D+00 1.984D+00 x( 6.. 10) = 7.533D-01 2.463D-01 -3.341D+00 6.171D+00 3.501D+01 Line search: alpha = 1.000D+00 dphi(0) = -1.666D+02 dphi(alpha) = -1.492D+02 neval = 8 F(x) = 6.869D+03 max|g(x)| = 2.847D+03 x( 1.. 5) = 3.513D-01 3.768D-01 4.441D+00 4.222D+00 1.910D+00 x( 6.. 10) = 9.335D-01 4.947D-01 -3.365D+00 6.108D+00 3.420D+01 Line search: alpha = 1.000D+00 dphi(0) = -5.022D+02 dphi(alpha) = -3.623D+02 neval = 9 F(x) = 6.434D+03 max|g(x)| = 2.832D+03 x( 1.. 5) = 8.962D-02 8.466D-01 4.437D+00 4.186D+00 2.003D+00 x( 6.. 10) = 1.383D+00 -6.341D-02 -3.177D+00 5.878D+00 3.135D+01 Line search: alpha = 1.000D+00 dphi(0) = -1.510D+03 dphi(alpha) = -8.172D+02 neval = 10 F(x) = 5.295D+03 max|g(x)| = 2.596D+03 x( 1.. 5) = 5.739D-01 1.394D+00 4.323D+00 3.990D+00 1.533D+00 x( 6.. 10) = -4.858D-01 -7.946D-01 -2.835D+00 5.182D+00 2.266D+01 Line search: alpha = 1.965D-01 dphi(0) = -1.479D+03 dphi(alpha) = -1.040D+03 neval = 12 F(x) = 5.040D+03 max|g(x)| = 2.484D+03 x( 1.. 5) = 1.294D+00 1.163D+00 4.261D+00 3.963D+00 1.691D+00 x( 6.. 10) = -3.895D-01 -5.378D-01 -2.872D+00 5.059D+00 2.110D+01 Line search: alpha = 1.000D+00 dphi(0) = -4.065D+03 dphi(alpha) = -1.760D+03 neval = 13 F(x) = 2.195D+03 max|g(x)| = 1.170D+03 x( 1.. 5) = -1.020D+00 -8.913D-03 3.364D+00 3.160D+00 1.603D+00 x( 6.. 10) = -3.089D-02 2.204D-01 -2.640D+00 4.883D+00 2.208D+01 Line search: alpha = 1.000D+00 dphi(0) = -5.877D+02 dphi(alpha) = -4.609D+02 neval = 14 F(x) = 1.673D+03 max|g(x)| = 9.564D+02 x( 1.. 5) = -6.316D-01 1.345D-01 3.163D+00 2.974D+00 1.579D+00 x( 6.. 10) = -1.019D-01 1.051D-01 -2.469D+00 4.576D+00 1.899D+01 Line search: alpha = 5.210D-01 dphi(0) = -1.320D+03 dphi(alpha) = -2.289D+02 neval = 16 F(x) = 1.220D+03 max|g(x)| = 6.477D+02 x( 1.. 5) = -1.803D+00 -5.469D-01 2.819D+00 2.681D+00 1.438D+00 x( 6.. 10) = 1.088D-01 3.878D-01 -2.390D+00 4.106D+00 1.432D+01 Line search: alpha = 1.000D+00 dphi(0) = -7.420D+02 dphi(alpha) = -3.864D+02 neval = 17 F(x) = 6.722D+02 max|g(x)| = 4.223D+02 x( 1.. 5) = -1.079D+00 -2.929D-01 2.473D+00 2.360D+00 1.344D+00 x( 6.. 10) = 1.224D-01 2.261D-01 -2.118D+00 3.701D+00 1.118D+01 Line search: alpha = 1.000D+00 dphi(0) = -7.351D+02 dphi(alpha) = -2.265D+02 neval = 18 F(x) = 2.217D+02 max|g(x)| = 1.200D+02 x( 1.. 5) = -9.006D-01 -5.413D-01 1.729D+00 1.691D+00 1.123D+00 x( 6.. 10) = 4.484D-01 1.369D-01 -1.748D+00 3.212D+00 9.734D+00 Line search: alpha = 1.000D+00 dphi(0) = -1.085D+02 dphi(alpha) = -3.967D+01 neval = 19 F(x) = 1.467D+02 max|g(x)| = 1.849D+02 x( 1.. 5) = -7.727D-01 -5.975D-01 1.505D+00 1.491D+00 1.075D+00 x( 6.. 10) = 5.968D-01 1.397D-01 -1.612D+00 2.834D+00 6.472D+00 Line search: alpha = 1.000D+00 dphi(0) = -1.091D+02 dphi(alpha) = -3.746D+01 neval = 20 F(x) = 7.697D+01 max|g(x)| = 1.054D+02 x( 1.. 5) = -4.623D-01 -7.257D-01 1.083D+00 1.113D+00 9.558D-01 x( 6.. 10) = 7.992D-01 1.154D-01 -1.394D+00 2.470D+00 5.171D+00 Line search: alpha = 1.000D+00 dphi(0) = -2.735D+01 dphi(alpha) = -1.456D+01 neval = 21 F(x) = 5.654D+01 max|g(x)| = 7.825D+01 x( 1.. 5) = -2.429D-01 -7.428D-01 8.532D-01 8.967D-01 8.420D-01 x( 6.. 10) = 6.796D-01 9.171D-02 -1.250D+00 2.231D+00 4.276D+00 Line search: alpha = 1.000D+00 dphi(0) = -1.924D+01 dphi(alpha) = -9.651D+00 neval = 22 F(x) = 4.266D+01 max|g(x)| = 5.903D+01 x( 1.. 5) = 1.672D-02 -6.382D-01 6.062D-01 6.558D-01 7.077D-01 x( 6.. 10) = 5.045D-01 3.075D-02 -1.064D+00 1.942D+00 3.243D+00 Line search: alpha = 1.000D+00 dphi(0) = -1.127D+01 dphi(alpha) = -6.628D+00 neval = 23 F(x) = 3.402D+01 max|g(x)| = 4.364D+01 x( 1.. 5) = 2.629D-01 -4.693D-01 3.663D-01 4.160D-01 5.618D-01 x( 6.. 10) = 3.269D-01 -3.522D-02 -8.694D-01 1.653D+00 2.365D+00 Line search: alpha = 1.000D+00 dphi(0) = -1.088D+01 dphi(alpha) = -4.294D+00 neval = 24 F(x) = 2.606D+01 max|g(x)| = 3.531D+01 x( 1.. 5) = 5.859D-01 -1.708D-01 2.159D-02 6.702D-02 3.396D-01 x( 6.. 10) = 8.750D-02 -1.205D-01 -5.756D-01 1.234D+00 1.183D+00 Line search: alpha = 1.000D+00 dphi(0) = -9.208D+00 dphi(alpha) = 6.525D+00 neval = 25 F(x) = 2.347D+01 max|g(x)| = 1.767D+01 x( 1.. 5) = 8.706D-01 2.507D-01 -3.117D-01 -2.790D-01 1.181D-01 x( 6.. 10) = -1.365D-01 -2.032D-01 -2.580D-01 8.624D-01 7.224D-01 Line search: alpha = 1.000D+00 dphi(0) = -5.931D+00 dphi(alpha) = 3.149D-01 neval = 26 F(x) = 2.098D+01 max|g(x)| = 1.266D+01 x( 1.. 5) = 6.840D-01 1.748D-01 -1.358D-01 -1.058D-01 2.365D-01 x( 6.. 10) = 9.976D-03 -1.433D-01 -3.816D-01 1.048D+00 1.229D+00 Line search: alpha = 1.000D+00 dphi(0) = -3.742D+00 dphi(alpha) = 4.699D-01 neval = 27 F(x) = 1.934D+01 max|g(x)| = 2.704D+01 x( 1.. 5) = 6.235D-01 2.684D-01 -1.230D-01 -9.850D-02 2.609D-01 x( 6.. 10) = 8.764D-02 -9.706D-02 -3.490D-01 9.939D-01 7.462D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.725D+00 dphi(alpha) = -4.601D-01 neval = 28 F(x) = 1.824D+01 max|g(x)| = 2.073D+01 x( 1.. 5) = 6.283D-01 3.933D-01 -1.583D-01 -1.420D-01 2.358D-01 x( 6.. 10) = 9.653D-02 -6.386D-02 -2.845D-01 9.323D-01 7.662D-01 Line search: alpha = 1.000D+00 dphi(0) = -8.526D-01 dphi(alpha) = -5.343D-01 neval = 29 F(x) = 1.754D+01 max|g(x)| = 1.735D+01 x( 1.. 5) = 6.130D-01 4.035D-01 -1.594D-01 -1.487D-01 2.224D-01 x( 6.. 10) = 1.203D-01 3.019D-03 -2.684D-01 9.067D-01 7.989D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.674D+00 dphi(alpha) = -5.605D-01 neval = 30 F(x) = 1.643D+01 max|g(x)| = 1.397D+01 x( 1.. 5) = 5.732D-01 3.766D-01 -1.538D-01 -1.564D-01 1.877D-01 x( 6.. 10) = 1.722D-01 1.714D-01 -2.455D-01 8.384D-01 7.406D-01 Line search: alpha = 1.000D+00 dphi(0) = -6.435D-01 dphi(alpha) = -2.678D-01 neval = 31 F(x) = 1.598D+01 max|g(x)| = 1.370D+01 x( 1.. 5) = 5.562D-01 3.529D-01 -1.527D-01 -1.644D-01 1.588D-01 x( 6.. 10) = 1.889D-01 2.580D-01 -2.311D-01 7.805D-01 6.220D-01 Line search: alpha = 1.000D+00 dphi(0) = -5.976D-01 dphi(alpha) = -3.633D-01 neval = 32 F(x) = 1.549D+01 max|g(x)| = 1.339D+01 x( 1.. 5) = 5.471D-01 3.241D-01 -1.464D-01 -1.677D-01 1.275D-01 x( 6.. 10) = 1.847D-01 3.025D-01 -2.244D-01 7.233D-01 5.062D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.455D+00 dphi(alpha) = -7.334D-01 neval = 33 F(x) = 1.439D+01 max|g(x)| = 1.203D+01 x( 1.. 5) = 5.327D-01 2.697D-01 -1.178D-01 -1.615D-01 6.073D-02 x( 6.. 10) = 1.479D-01 3.281D-01 -2.219D-01 6.054D-01 2.966D-01 Line search: alpha = 1.000D+00 dphi(0) = -2.080D+00 dphi(alpha) = -9.378D-01 neval = 34 F(x) = 1.288D+01 max|g(x)| = 8.869D+00 x( 1.. 5) = 5.075D-01 2.076D-01 -4.745D-02 -1.244D-01 -2.050D-02 x( 6.. 10) = 7.458D-02 2.832D-01 -2.393D-01 4.649D-01 1.200D-01 Line search: alpha = 1.000D+00 dphi(0) = -2.000D+00 dphi(alpha) = -7.398D-01 neval = 35 F(x) = 1.151D+01 max|g(x)| = 5.441D+00 x( 1.. 5) = 4.699D-01 1.845D-01 5.163D-02 -5.751D-02 -7.027D-02 x( 6.. 10) = 9.187D-03 1.767D-01 -2.720D-01 3.651D-01 1.001D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.069D+00 dphi(alpha) = -4.765D-01 neval = 36 F(x) = 1.075D+01 max|g(x)| = 5.654D+00 x( 1.. 5) = 4.420D-01 2.486D-01 1.135D-01 -1.443D-02 -7.151D-02 x( 6.. 10) = 9.771D-03 9.769D-02 -2.722D-01 3.060D-01 1.166D-01 Line search: alpha = 1.000D+00 dphi(0) = -7.086D-01 dphi(alpha) = -2.044D-01 neval = 37 F(x) = 1.029D+01 max|g(x)| = 5.613D+00 x( 1.. 5) = 4.305D-01 3.541D-01 1.485D-01 8.155D-03 -5.169D-02 x( 6.. 10) = 5.340D-02 5.255D-02 -2.458D-01 2.486D-01 1.230D-01 Line search: alpha = 1.000D+00 dphi(0) = -2.371D-01 dphi(alpha) = -1.299D-01 neval = 38 F(x) = 1.011D+01 max|g(x)| = 5.568D+00 x( 1.. 5) = 4.402D-01 3.982D-01 1.610D-01 1.629D-02 -3.566D-02 x( 6.. 10) = 8.930D-02 4.683D-02 -2.268D-01 2.130D-01 1.343D-01 Line search: alpha = 1.000D+00 dphi(0) = -4.259D-01 dphi(alpha) = -2.261D-01 neval = 39 F(x) = 9.781D+00 max|g(x)| = 5.464D+00 x( 1.. 5) = 4.842D-01 4.488D-01 1.755D-01 2.402D-02 -1.164D-02 x( 6.. 10) = 1.474D-01 5.079D-02 -1.875D-01 1.303D-01 1.224D-01 Line search: alpha = 1.000D+00 dphi(0) = -6.542D-01 dphi(alpha) = -2.225D-01 neval = 40 F(x) = 9.336D+00 max|g(x)| = 4.986D+00 x( 1.. 5) = 5.892D-01 4.801D-01 1.872D-01 3.280D-02 3.359D-02 x( 6.. 10) = 2.223D-01 6.821D-02 -1.321D-01 2.014D-02 1.400D-01 Line search: alpha = 1.000D+00 dphi(0) = -3.527D-01 dphi(alpha) = -5.292D-02 neval = 41 F(x) = 9.123D+00 max|g(x)| = 4.374D+00 x( 1.. 5) = 6.761D-01 4.907D-01 1.858D-01 3.235D-02 5.894D-02 x( 6.. 10) = 2.369D-01 8.372D-02 -9.209D-02 -4.791D-02 1.113D-01 Line search: alpha = 1.000D+00 dphi(0) = -2.520D-01 dphi(alpha) = -7.151D-02 neval = 42 F(x) = 8.961D+00 max|g(x)| = 4.328D+00 x( 1.. 5) = 7.092D-01 4.725D-01 1.900D-01 4.437D-02 8.498D-02 x( 6.. 10) = 2.156D-01 9.557D-02 -9.281D-02 -1.916D-02 1.527D-01 Line search: alpha = 1.000D+00 dphi(0) = -4.306D-01 dphi(alpha) = -2.112D-01 neval = 43 F(x) = 8.641D+00 max|g(x)| = 4.079D+00 x( 1.. 5) = 7.369D-01 4.850D-01 2.128D-01 7.237D-02 1.150D-01 x( 6.. 10) = 1.507D-01 1.063D-01 -8.398D-02 5.268D-03 1.053D-01 Line search: alpha = 1.000D+00 dphi(0) = -5.383D-01 dphi(alpha) = -2.252D-01 neval = 44 F(x) = 8.260D+00 max|g(x)| = 3.686D+00 x( 1.. 5) = 7.570D-01 5.435D-01 2.803D-01 1.438D-01 1.818D-01 x( 6.. 10) = 7.735D-02 1.077D-01 -7.189D-02 4.960D-02 8.210D-02 Line search: alpha = 1.000D+00 dphi(0) = -4.551D-01 dphi(alpha) = -2.690D-01 neval = 45 F(x) = 7.901D+00 max|g(x)| = 3.176D+00 x( 1.. 5) = 8.011D-01 6.445D-01 3.929D-01 2.506D-01 2.723D-01 x( 6.. 10) = 4.574D-02 1.078D-01 -3.672D-02 3.425D-02 7.437D-02 Line search: alpha = 1.000D+00 dphi(0) = -9.615D-01 dphi(alpha) = -1.787D-01 neval = 46 F(x) = 7.187D+00 max|g(x)| = 6.103D+00 x( 1.. 5) = 8.692D-01 8.546D-01 7.090D-01 5.392D-01 4.715D-01 x( 6.. 10) = 3.436D-02 1.150D-01 2.534D-02 -3.729D-02 8.898D-02 Line search: alpha = 6.249D-01 dphi(0) = -7.100D-01 dphi(alpha) = -2.990D-02 neval = 48 F(x) = 6.924D+00 max|g(x)| = 6.794D+00 x( 1.. 5) = 9.002D-01 9.247D-01 8.514D-01 6.698D-01 5.585D-01 x( 6.. 10) = 8.413D-02 1.276D-01 4.532D-02 -7.734D-02 1.154D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.190D+00 dphi(alpha) = -4.437D-01 neval = 49 F(x) = 6.092D+00 max|g(x)| = 4.682D+00 x( 1.. 5) = 9.152D-01 9.180D-01 9.003D-01 7.169D-01 5.922D-01 x( 6.. 10) = 2.842D-01 1.607D-01 4.496D-02 -1.163D-01 1.831D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.248D+00 dphi(alpha) = 6.051D-01 neval = 50 F(x) = 5.600D+00 max|g(x)| = 5.808D+00 x( 1.. 5) = 1.028D+00 1.001D+00 9.720D-01 8.097D-01 7.397D-01 x( 6.. 10) = 5.874D-01 2.417D-01 9.447D-02 -1.227D-01 2.346D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.040D+00 dphi(alpha) = -3.797D-01 neval = 51 F(x) = 4.888D+00 max|g(x)| = 5.346D+00 x( 1.. 5) = 9.736D-01 9.539D-01 9.388D-01 7.980D-01 7.395D-01 x( 6.. 10) = 5.921D-01 3.080D-01 6.199D-02 7.876D-04 1.901D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.229D+00 dphi(alpha) = 6.673D-01 neval = 52 F(x) = 4.500D+00 max|g(x)| = 5.296D+00 x( 1.. 5) = 1.006D+00 1.011D+00 1.025D+00 9.251D-01 8.893D-01 x( 6.. 10) = 6.988D-01 4.828D-01 8.466D-02 1.536D-01 7.879D-02 Line search: alpha = 1.000D+00 dphi(0) = -4.687D-01 dphi(alpha) = 1.343D-01 neval = 53 F(x) = 4.344D+00 max|g(x)| = 4.993D+00 x( 1.. 5) = 1.012D+00 1.000D+00 9.512D-01 8.500D-01 8.283D-01 x( 6.. 10) = 6.969D-01 4.678D-01 1.013D-01 1.029D-01 6.762D-02 Line search: alpha = 1.000D+00 dphi(0) = -1.505D-01 dphi(alpha) = 1.257D-03 neval = 54 F(x) = 4.268D+00 max|g(x)| = 4.149D+00 x( 1.. 5) = 1.014D+00 1.015D+00 9.906D-01 8.853D-01 8.392D-01 x( 6.. 10) = 7.099D-01 4.616D-01 1.088D-01 7.636D-02 9.595D-02 Line search: alpha = 1.000D+00 dphi(0) = -1.001D-01 dphi(alpha) = -4.149D-02 neval = 55 F(x) = 4.197D+00 max|g(x)| = 4.306D+00 x( 1.. 5) = 1.028D+00 1.020D+00 1.000D+00 9.038D-01 8.527D-01 x( 6.. 10) = 7.048D-01 4.848D-01 1.243D-01 8.393D-02 9.890D-02 Line search: alpha = 1.000D+00 dphi(0) = -2.142D-01 dphi(alpha) = -3.964D-02 neval = 56 F(x) = 4.067D+00 max|g(x)| = 5.432D+00 x( 1.. 5) = 1.037D+00 1.029D+00 1.011D+00 9.470D-01 8.842D-01 x( 6.. 10) = 7.601D-01 5.645D-01 1.620D-01 1.226D-01 9.846D-02 Line search: alpha = 1.000D+00 dphi(0) = -2.715D-01 dphi(alpha) = -1.050D-01 neval = 57 F(x) = 3.879D+00 max|g(x)| = 4.951D+00 x( 1.. 5) = 1.039D+00 1.030D+00 9.930D-01 9.614D-01 8.719D-01 x( 6.. 10) = 7.447D-01 5.919D-01 2.152D-01 1.250D-01 1.096D-01 Line search: alpha = 1.000D+00 dphi(0) = -3.070D-01 dphi(alpha) = -1.095D-01 neval = 58 F(x) = 3.671D+00 max|g(x)| = 4.274D+00 x( 1.. 5) = 1.035D+00 1.014D+00 9.633D-01 9.791D-01 8.745D-01 x( 6.. 10) = 7.723D-01 6.103D-01 2.753D-01 1.465D-01 1.326D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.786D-01 dphi(alpha) = -6.107D-02 neval = 59 F(x) = 3.551D+00 max|g(x)| = 5.692D+00 x( 1.. 5) = 1.013D+00 1.002D+00 9.426D-01 9.884D-01 8.829D-01 x( 6.. 10) = 7.868D-01 6.097D-01 3.132D-01 1.723D-01 1.271D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.170D-01 dphi(alpha) = -5.895D-02 neval = 60 F(x) = 3.463D+00 max|g(x)| = 5.977D+00 x( 1.. 5) = 1.002D+00 9.863D-01 9.311D-01 9.956D-01 9.055D-01 x( 6.. 10) = 8.089D-01 6.199D-01 3.456D-01 1.883D-01 1.238D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.622D-01 dphi(alpha) = -6.614D-02 neval = 61 F(x) = 3.348D+00 max|g(x)| = 6.004D+00 x( 1.. 5) = 9.818D-01 9.710D-01 9.246D-01 1.003D+00 9.399D-01 x( 6.. 10) = 8.358D-01 6.501D-01 3.941D-01 2.009D-01 1.158D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.333D-01 dphi(alpha) = -5.489D-02 neval = 62 F(x) = 3.253D+00 max|g(x)| = 5.470D+00 x( 1.. 5) = 9.661D-01 9.592D-01 9.251D-01 1.002D+00 9.658D-01 x( 6.. 10) = 8.584D-01 6.894D-01 4.318D-01 2.047D-01 1.177D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.180D-01 dphi(alpha) = -5.861D-02 neval = 63 F(x) = 3.164D+00 max|g(x)| = 4.527D+00 x( 1.. 5) = 9.565D-01 9.566D-01 9.323D-01 9.961D-01 9.769D-01 x( 6.. 10) = 8.692D-01 7.227D-01 4.578D-01 2.075D-01 1.283D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.703D-01 dphi(alpha) = -9.748D-02 neval = 64 F(x) = 3.030D+00 max|g(x)| = 3.552D+00 x( 1.. 5) = 9.534D-01 9.619D-01 9.464D-01 9.891D-01 9.853D-01 x( 6.. 10) = 8.834D-01 7.630D-01 4.944D-01 2.259D-01 1.507D-01 Line search: alpha = 1.000D+00 dphi(0) = -3.691D-01 dphi(alpha) = -2.079D-01 neval = 65 F(x) = 2.740D+00 max|g(x)| = 3.929D+00 x( 1.. 5) = 9.550D-01 9.742D-01 9.699D-01 9.761D-01 9.915D-01 x( 6.. 10) = 9.032D-01 8.273D-01 5.758D-01 2.988D-01 2.006D-01 Line search: alpha = 1.000D+00 dphi(0) = -7.816D-01 dphi(alpha) = -2.808D-01 neval = 66 F(x) = 2.166D+00 max|g(x)| = 5.652D+00 x( 1.. 5) = 9.664D-01 9.960D-01 1.006D+00 9.629D-01 1.006D+00 x( 6.. 10) = 9.530D-01 9.461D-01 7.630D-01 5.210D-01 3.237D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.141D+00 dphi(alpha) = 1.089D+00 neval = 67 F(x) = 1.915D+00 max|g(x)| = 7.704D+00 x( 1.. 5) = 9.913D-01 1.014D+00 1.038D+00 9.255D-01 9.781D-01 x( 6.. 10) = 9.485D-01 9.796D-01 9.390D-01 8.598D-01 5.838D-01 Line search: alpha = 1.000D+00 dphi(0) = -1.245D+00 dphi(alpha) = 2.392D-01 neval = 68 F(x) = 1.447D+00 max|g(x)| = 3.752D+00 x( 1.. 5) = 1.017D+00 1.013D+00 1.025D+00 9.599D-01 9.663D-01 x( 6.. 10) = 9.522D-01 9.183D-01 8.827D-01 7.328D-01 6.009D-01 Line search: alpha = 1.000D+00 dphi(0) = -5.832D-01 dphi(alpha) = 2.852D-01 neval = 69 F(x) = 1.278D+00 max|g(x)| = 2.947D+00 x( 1.. 5) = 1.011D+00 1.002D+00 1.001D+00 1.014D+00 1.012D+00 x( 6.. 10) = 1.033D+00 1.002D+00 9.254D-01 8.211D-01 6.634D-01 Line search: alpha = 1.000D+00 dphi(0) = -3.893D-01 dphi(alpha) = 7.199D-02 neval = 70 F(x) = 1.123D+00 max|g(x)| = 1.997D+00 x( 1.. 5) = 9.987D-01 9.937D-01 9.902D-01 9.938D-01 9.813D-01 x( 6.. 10) = 9.716D-01 9.554D-01 9.172D-01 8.887D-01 7.540D-01 Line search: alpha = 4.421D-01 dphi(0) = -2.062D-01 dphi(alpha) = -9.090D-03 neval = 72 F(x) = 1.074D+00 max|g(x)| = 1.214D+00 x( 1.. 5) = 1.002D+00 9.983D-01 9.950D-01 9.967D-01 9.854D-01 x( 6.. 10) = 9.759D-01 9.678D-01 9.644D-01 9.228D-01 8.105D-01 Line search: alpha = 1.000D+00 dphi(0) = -7.227D-02 dphi(alpha) = -1.761D-02 neval = 73 F(x) = 1.029D+00 max|g(x)| = 1.010D+00 x( 1.. 5) = 1.007D+00 1.004D+00 1.006D+00 1.001D+00 9.958D-01 x( 6.. 10) = 9.945D-01 9.774D-01 9.741D-01 9.404D-01 8.759D-01 Line search: alpha = 1.000D+00 dphi(0) = -4.075D-02 dphi(alpha) = -1.016D-02 neval = 74 F(x) = 1.004D+00 max|g(x)| = 3.875D-01 x( 1.. 5) = 1.003D+00 1.000D+00 1.002D+00 1.002D+00 1.001D+00 x( 6.. 10) = 1.003D+00 9.974D-01 9.948D-01 9.826D-01 9.615D-01 Line search: alpha = 1.000D+00 dphi(0) = -7.421D-03 dphi(alpha) = -3.292D-06 Optimization stopped after 75 function evaluations. Stopped by function evaluation limit (maxeval) maxgradient laststep stepmax neval 0.08158646 0.03857951 0.40516875 75.00000000 ucminf message: Stopped by function evaluation limit (maxeval) Post processing for method ucminf Compute gradient approximation at finish of ucminf Compute Hessian approximation at finish of ucminf Save results from method ucminf Assemble the answers Sort results > outline-regexp: "\\(> \\)?### [*]+" *** Error: unexpected '*' in "outline-regexp: "\\(> \\)?### [*]+" ***" Execution halted