[Swift-commit] r5525 - SwiftApps/SciColSim

wilde at ci.uchicago.edu wilde at ci.uchicago.edu
Mon Jan 30 12:34:45 CST 2012


Author: wilde
Date: 2012-01-30 12:34:45 -0600 (Mon, 30 Jan 2012)
New Revision: 5525

Added:
   SwiftApps/SciColSim/sample.swift.output
   SwiftApps/SciColSim/sample.testopt.py.output
Modified:
   SwiftApps/SciColSim/README
   SwiftApps/SciColSim/TODO
   SwiftApps/SciColSim/annealing.swift
   SwiftApps/SciColSim/evolve.sh
Log:
Correct hanging situation in setting rejection[] values. Still hangs after first cycle change. Updated README for handoff to Swift developers.

Modified: SwiftApps/SciColSim/README
===================================================================
--- SwiftApps/SciColSim/README	2012-01-30 01:47:21 UTC (rev 5524)
+++ SwiftApps/SciColSim/README	2012-01-30 18:34:45 UTC (rev 5525)
@@ -64,6 +64,9 @@
 
 *** How to build
 
+Copy and untar boost graph library to the current dir:
+  TBD - see CI: /home/wilde/AndreysOptimizer/src for the tgz file, for now.
+
 Just run "make" -> uses Makefile
 
   on mac, makes:  openmp-optimizer (multi_loss() changed to use OpenMP),
@@ -74,18 +77,47 @@
 
 *** How to Run
 
-Non-swift tests:
+* Non-swift tests (py calling C++ optimizer app):
 
   cp testopt.py t1.py etc; then edit t1.py etc to set the params you want.
 
-Swift tests:
+An example of a modified parameter set for testing a fast optimization
+loop on communicado/local.xml is:
 
-  cp testswift.sh t1.sh etc; then edit t1.sh etc to set the params you want.
+> paramset="mw"
+71a73,86
+> elif paramset == "mw":  # FAST TEST PARAMETERS by Mike
+>   
+>   startTarget      = 58
+>   endTarget        = 59
+>   incrTarget       = 50
+>   optimizerRepeats = 1
+>   evolveReruns     = 100
+>   annealingSteps   = 5
+>   NWorkers         = "4"
+>   openmp           = "OMP_NUM_THREADS=" + NWorkers
+>   operation        = "n"  # n=normal, m=manual (runs 1 multi_loss call)
+>   seed             = "1234567"
+>   app              = "./openmp-optimizer";
+> 
 
+Sample output is in sample.testopt.py.output
 
-In each of the above, set the optimizer version you want to run.
+* Swift tests:
 
+   /test-swift.sh >&ts3.out &
 
+(currently, parameters are set in a few different places in annealing.swift)
+
+Sample output (w/ bugs remaining) is in sample.test-swift.output
+   
+
+Optimizer output (both from C++ optimizer and Swift) generates text
+with escape sequences to display colored text. Some versions of more
+and less need special options set (eg in env var?) to display the
+colors correctly.
+
+
 *** C++ Command line args
 
 

Modified: SwiftApps/SciColSim/TODO
===================================================================
--- SwiftApps/SciColSim/TODO	2012-01-30 01:47:21 UTC (rev 5524)
+++ SwiftApps/SciColSim/TODO	2012-01-30 18:34:45 UTC (rev 5525)
@@ -1,9 +1,12 @@
 Stopped at:
 
-Are deps working right?  why 20 in args?  (not 10?)  Why 2 calls in progress?  Whats with initial call [0][0]?
 
-trace nan error; verify if N reruns per call is working and sumloss handles it OK.
+Re-checking annealing loop
+- rejection and rj calcs
+- AR tracef's
+- cycle logic
 
+
 ---
 
 x = done, - = in progress

Modified: SwiftApps/SciColSim/annealing.swift
===================================================================
--- SwiftApps/SciColSim/annealing.swift	2012-01-30 01:47:21 UTC (rev 5524)
+++ SwiftApps/SciColSim/annealing.swift	2012-01-30 18:34:45 UTC (rev 5525)
@@ -11,16 +11,17 @@
 global boolean FIX_VARIABLES = true;
 global int var_fixed[] = [1,1,0,0,0];
 global int Nworkers = 4;
+global int rerunsPerApp;
 
 (float nx) newx(float x, float dx) 
 {
-    float r = (random()) / (pow(2.0,31.0)-1.0);
+    float r = (random()) ; # / (pow(2.0,31.0)-1.0);
     if (r > 0.5){
-        nx = x + (random())*dx/(pow(2.0,31.0)-1.0);
+        nx = x + (random())*dx; # /(pow(2.0,31.0)-1.0);
     } else {
-        nx = x - (random())*dx/(pow(2.0,31.0)-1.0);
+        nx = x - (random())*dx; # /(pow(2.0,31.0)-1.0);
     }
-    tracef("newx(%f,%f)=%f\n",x,dx,nx);
+    // tracef("newx(%f,%f)=%f\n",x,dx,nx);
 }
 
 app (file outfile, file loss) evolve (string args[], file graph)
@@ -64,7 +65,7 @@
     
     Res mlres[][];
     mlres[0][0] = multi_loss( 0, 0, params0, target_innov, evolve_reruns ); // FIXME: serves for all evolve-params ???
-    tracef("multi_annealing: AR: %f +- %f\n",mlres[0][0].loss,mlres[0][0].sdev);
+    tracef("multi_annealing: AR: initial: %f +- %f\n",mlres[0][0].loss,mlres[0][0].sdev);
 
     foreach j in [0:NEVOPARAMS-1] {
         x[0][j]=params0[j];
@@ -74,38 +75,46 @@
         curr_sdev[j] = mlres[0][0].sdev;
     }
 
-    foreach i in [1:annealing_cycles] {
+    iterate iter_i {    # foreach i in [1:annealing_cycles]
+         int i = iter_i + 1;
+
         // set new temperature, rejection threshold, and dx values for this cycle
-        float temperature = T_start*exp( @tofloat(i)*(jlog(T_end)-jlog(T_start))/@tofloat(annealing_cycles));
-        // tracef("in multi_annealing: AR: i=%i ....T=%f\n", i, temperature);
+
+        float temperature = T_start*exp( @tofloat(i-1)*(jlog(T_end)-jlog(T_start))/@tofloat(annealing_cycles));
+
+        tracef(@strcat("multi_annealing: AR: i=%i ....T = ",color(3,"%f"),"\n"), i, temperature);
+
 	// On each new "major" cycle within the annealing_cycles (other than the first) set new rejection and dx values
+
         if ( i %% cycle == 1 && i > 1 ){ 
             tracef("multi_annealing: new cycle at i=%i\n",i);
+            tracef(color(Pink, "multi_annealing: AR: New cycle at %i: prev dx[0-4]=[%f %f %f %f %f]\n"),i,dx[i-1][0],dx[i-1][1],dx[i-1][2],dx[i-1][3],dx[i-1][4]);
             foreach  k in [0:NEVOPARAMS-1] {
                 float newrejection = rejection[i-1][k] / @tofloat(cycle);
                 if (newrejection > 0.0){
                     dx[i][k] = dx[i-1][k] / (newrejection / Target_rejection);
-                    rejection[i][k]=0.0;
+                    # FIXME: re-enable: rejection[i][k]=0.0;
                 }
                 else{
                     dx[i][k] = dx[i-1][k] * 2.0;
-                    rejection[i][k]=rejection[i-1][k];
+                    # FIXME: re-enable: rejection[i][k]=rejection[i-1][k];
                 }
-                trace ("Recomputed rejection: i=%d k=%d dx[i][k]=%f\n", i, k, dx[i][k]);
+                tracef(color(Red,"Recomputed rejection: i=%d k=%d dx[i][k]=%f\n"), i, k, dx[i][k]);
             }
-            tracef("multi_annealing: AR: %f %f %f %f %f\n",dx[i][0],dx[i][1],dx[i][2],dx[i][3],dx[i][4],dx[i][5]);
+            tracef(color(Blue, "multi_annealing: AR: New cycle at %i: dx[0-4]=[%f %f %f %f %f]\n"),i,dx[i][0],dx[i][1],dx[i][2],dx[i][3],dx[i][4]);
         }
-        else { # If not new cycle, set dx from previous dx (i-1)
+        else { # If not new cycle, set dx[i][*] from previous dx ([i-1]). rejection[i]j] is set later.
             foreach  k in [0:NEVOPARAMS-1] {
                 dx[i][k] = dx[i-1][k];
             }
         }
-        foreach j in [0:NEVOPARAMS-1] { // Try a new value for each non-fixed param; then write results and accept or reject
+        #foreach j in [0:NEVOPARAMS-1] { // Try a new value for each non-fixed param; then write results and accept or reject
+        iterate j {  // Try a new value for each non-fixed param; then write results and accept or reject
             // float try_x[];
             int curr = (i * NEVOPARAMS) + j;
             int prev = curr-1;
             // tracef("in multi_annealing: i=%i j=%i curr=%i prev=%i\n", i, j, curr, prev);
-            if ( /*(!FIX_VARIABLES) || */ (var_fixed[j]==0) ) {
+            if ( /*(!FIX_VARIABLES) || */ (var_fixed[j]==0) ) {  # Adjustable vars
                 # fixed=1,1,0,0,0: FIXME: FIX_VARIABLES flag has faulty logic but OK when TRUE
                 float try_x[];
                 foreach k in [0:NEVOPARAMS-1] { // Select the evolve params to try
@@ -120,30 +129,25 @@
                             try_x[k] = x[i-1][k]; // use x[i-1][k] (from prior cycle)
                         }
                     }
-                    // tracef("in multi_annealing: i=%i j=%i k=%i try_x=%f\n", i, j, k, try_x[k]);
-                    // tracef("in multi_annealing: i=%i j=%i k=%i\n", i, j, k);
                 }
+                tracef(@strcat("multi_annealing: AR: ", color(10,"%f"), " ", color(9,"%i"),"\n"), try_x[j],j);
                 // Up to here, x[] and dx[] are only set for previous i
-                # tracef( @strcat(color(3,"in multi_annealing: "),"i=%i j=%i calling multi_loss\n"),i,j);
-                # tracef("multi_annealing: i=%i j=%i calling multi_loss try_x=%q\n",i,j,try_x);
                 mlres[i][j] = multi_loss(i,j,try_x, target_innov, evolve_reruns); # do the N evolve()'s, N=evolve_reruns
-                # tracef("multi_annealing: i=%i j=%i ret vals from multi_loss=(%f,%f)\n",i,j,mlres[i][j].loss,mlres[i][j].sdev);
-                # tracef("in multi_annealing: AR: %f+-%f\n",mlres[i][j].loss,mlres[i][j].sdev);
+                tracef("multi_annealing: AR: %f +- %f\n", mlres[i][j].loss, mlres[i][j].sdev);
                 // Beyond this point, x[] and dx[] are being set for this i,j
-                float ratio = min(1.0, exp( -(mlres[i][j].loss-curr_loss[prev]) /temperature));
-                float r = (random()) / (pow(2.0,31.0)-1.0);  // why all the 2^31's ???
-                tracef("in multi_annealing: AR: %f vs %f\n", r, ratio);
 
                 float ALOT=100000000000.0; // 100,000,000,000. = 10^11
                 if (mlres[i][j].loss < ALOT) { 
                     tracef("multi_annealing: AF: best_opt_some.txt: %f,%f,%f,%f,%f,%f,%f,%f\n",
                            target_innov,mlres[i][j].loss,try_x[0],try_x[1],try_x[2],try_x[3],try_x[4],mlres[i][j].sdev);
-                    tracef(color(Red,"multi_annealing: AR: max_dist.txt - tbd\n"));
-                           // FIXME: max_dist is global set inside evolve() - need to get to cli - perhaps as 3rd output value
+                    tracef(color(Red,"multi_annealing: AF: max_dist.txt - tbd\n")); // FIXME: max_dist is global set in evolve()
                 }
                 else {  // does this ever occur? if so did we want to still do the ratio computation above???
                     tracef("multi_annealing: Loss %f > ALOT at [i][j] = [%d][%d]\n", mlres[i][j].loss, i ,j);
                 }
+                float ratio = min(1.0, exp( -(mlres[i][j].loss-curr_loss[prev]) / temperature));
+                float r = (random()) ; # / (pow(2.0,31.0)-1.0);  // FIXME: AR: why all the 2^31's ???
+                tracef("multi_annealing: AR: %f vs %f\n", r, ratio);
                 if (r > ratio) {  // Reject new parameter
                     x[i][j] = x[i-1][j];
                     rejection[i][j] = rejection[i-1][j] + 1.0;  // FIXME: AR: Is this correct? incr rejection? 
@@ -160,38 +164,32 @@
                     tracef("multi_annealing: Accepting try_x[j], i=%i j=%i try_x[j]=%f\n",i,j,try_x[j]);
                     curr_loss[curr] = mlres[i][j].loss;
                     curr_sdev[curr] = mlres[i][j].sdev;
-                    tracef(@strcat("multi_annealing: AR: %i ", color(8,"Rejection counts: "),
-                                   color( /* 2 */ 1," %f"), "\n\n"),
-                                   i, rejection[i][j] ); // , rejection[i][1], rejection[i][2], rejection[i][3], rejection[i][4]);
-# FIXME: determine correct rejection[] values to avoid hanging:
-#                    tracef(@strcat("multi_annealing: AR: %i ", color(8,"Rejection counts: "),
-#                                   color( /* 2 */ 1," %f"), color(7," %f"), color(5," %f"), color(9," %f"), color(6," %f"), "\n\n"),
-#                                   rejection[i][0], rejection[i][1], rejection[i][2], rejection[i][3], rejection[i][4]);
-# END FIXME
                     float rj[];
                     foreach k in [0:NEVOPARAMS-1] {  # FIXME!!!
-                        if (k==j) {
-                           rj[k] = rejection[i-1][k];
+                        if (k <= j) {
+                           rj[k] = rejection[i][k]; # Was either set from previous j or just set for this j
                         }
                         else {
-                           rj[k] = rejection[i-1][k];
+                           rj[k] = rejection[i-1][k]; # Not yet set, use previous
                         }
-                        tracef(@strcat("multi_annealing: AR: [%i][%i] ", color(8,"Rejection counts: "),
-                                   color(/*2*/ 1," %f"), color(7," %f"), color(5," %f"), color(9," %f"), color(6," %f"), "\n\n"),
-                                   i, j, rj[0], rj[1], rj[2], rj[3], rj[4]);
                     }
+                    tracef(@strcat("multi_annealing: AR: [%i][%i] ", color(8,"Rejection counts: "),
+                           color(1,"%f"), " ", color(7,"%f"), " ", color(5,"%f"), " ", color(9,"%f"), " ", color(6,"%f"), "\n\n"),
+                           i, j, rj[0], rj[1], rj[2], rj[3], rj[4]);
                     tracef(@strcat("multi_annealing: AR: %i ", color(8,"***** Did accept! "),
-                                   color(/*2*/ 1," %f"), color(7," %f"), color(5," %f"), color(9," %f"), color(6," %f"), "\n\n"),
-                                   i, try_x[0], try_x[1], try_x[2], try_x[3], try_x[4]);
+                            color(1,"%f"), " ", color(7,"%f"), " ", color(5,"%f"), " ", color(9,"%f"), " ", color(6,"%f"), "\n\n"),
+                            i, try_x[0], try_x[1], try_x[2], try_x[3], try_x[4]);
                 }
             }
-            else {
+            else { # Fixed Vars
                 x[i][j] = x[i-1][j];
+                rejection[i][j] = rejection[i-1][j];
                 curr_loss[curr] = curr_loss[prev];
                 curr_sdev[curr] = curr_sdev[prev];
+                # dx[i][j] not set for fixed vars
            }
-        }
-    }
+        } until(j == NEVOPARAMS-1);
+    } until(iter_i == (annealing_cycles-1));
 }
 
 (Res r) multi_loss( int ci, int cj, float x[], float target_innov, int evolve_reruns )
@@ -199,10 +197,9 @@
   file rfile[];
   tracef("multi_loss: entered: ci=%i cj=%i target_innov=%f evolve_reruns=%i x=%q\n",ci, cj, target_innov,evolve_reruns,x);
 
-  int rerunsPerApp = 120;
   int appCalls = @toint(@tofloat(evolve_reruns) / @tofloat(rerunsPerApp));  # FIXME: handle fractional issues and rounding etc. For now must divide evenly
 
-tracef("multi_loass appCalls=%i\n", appCalls);
+tracef("multi_loss appCalls=%i\n", appCalls);
   foreach i in [1:appCalls] {  // repeats of the evolove() - same as n_reruns
     file outfile; // FIXME: map and save in future 
     string args[] = [ // FIXME: move this to a setargs() function
@@ -239,12 +236,12 @@
 {
   int minrange=58;
   int maxrange=59;
-  //int maxrange=59;
+  int rangeinc=50;
+
   //int maxrange=1009;
   //int maxrange=209;
-  int rangeinc=50;
 
-  // fixme: add provision for random priming and random param values when x[i] == -100 (see optimizer.cpp main())
+  // FIXME: add provision for random priming and random param values when x[i] == -100 (see optimizer.cpp main())
 
   int nreps=1; # 15
 
@@ -264,21 +261,23 @@
          starting_jump    = 2.3,
          params0[]        = [0.0, 0.0, 4.0, 50.0, -1.0],
          @tofloat(target_innov),
-         annealing_cycles = 1); 
+         annealing_cycles = 2); 
 */
       (outfile,lossfile) = multi_annealing(
          2.0,
          0.01,
          0.3,
-         1200,
+         100,
          2.3,
          [0.0, 0.0, 4.0, 50.0, -1.0],
          @tofloat(target_innov),
-         5);
+         30);
     }
   }
 }
 
+rerunsPerApp = 100;
+
 main()
 {
   optimizer_sweep();
@@ -335,3 +334,13 @@
   //  [FREEZE_alpha_i FREEZE_alpha_m FREEZE_beta FREEZE_gamma FREEZE_delta] [operation-code:(m,a) Nworkers]
 }
 
+######### HOLD JUNK
+
+#                    tracef(@strcat("multi_annealing: AR: %i ", color(8,"Rejection counts: "),
+#                                   color( /* 2 */ 1," %f"), "\n\n"),
+#                                   i, rejection[i][j] ); // , rejection[i][1], rejection[i][2], rejection[i][3], rejection[i][4]);
+# FIXME: determine correct rejection[] values to avoid hanging:
+#                    tracef(@strcat("multi_annealing: AR: %i ", color(8,"Rejection counts: "),
+#                                   color( /* 2 */ 1," %f"), color(7," %f"), color(5," %f"), color(9," %f"), color(6," %f"), "\n\n"),
+#                                   rejection[i][0], rejection[i][1], rejection[i][2], rejection[i][3], rejection[i][4]);
+# END FIXME

Modified: SwiftApps/SciColSim/evolve.sh
===================================================================
--- SwiftApps/SciColSim/evolve.sh	2012-01-30 01:47:21 UTC (rev 5524)
+++ SwiftApps/SciColSim/evolve.sh	2012-01-30 18:34:45 UTC (rev 5525)
@@ -2,6 +2,6 @@
 datafile=$1
 touch multi_loss.data
 shift 1
-NWORKERS=$23
+NWORKERS=${23}
 OMP_NUM_THREADS=$NWORKERS $(dirname $0)/openmp-optimizer $* 2>&1
 mv multi_loss.data $datafile

Added: SwiftApps/SciColSim/sample.swift.output
===================================================================
--- SwiftApps/SciColSim/sample.swift.output	                        (rev 0)
+++ SwiftApps/SciColSim/sample.swift.output	2012-01-30 18:34:45 UTC (rev 5525)
@@ -0,0 +1,528 @@
+Swift 0.93 swift-r5483 cog-r3339
+
+RunID: 20120130-1217-63kot916
+Progress:  time: Mon, 30 Jan 2012 12:17:12 -0600
+multi_loss appCalls=1
+multi_loss: entered: ci=0 cj=0 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,4.0,50.0,-1.0]
+multi_annealing: AR: i=1 ....T = 2.0
+multi_loss: i=1 calling evolve, args=[0,0,4,50,-1,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:16 -0600  Checking status:1
+multi_annealing: AR: initial: 124.861101 +- 3.21017
+multi_loss: returning: ci=0 cj=0 r.loss=124.861101 r.sdev=3.21017
+multi_loss appCalls=1
+multi_annealing: AR: 4.017889129124014 2
+multi_loss: entered: ci=1 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,4.017889129124014,50.0,-1.0]
+multi_loss: i=1 calling evolve, args=[0,0,4.017889129124014,50,-1,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:19 -0600  Checking status:1  Finished successfully:2
+multi_annealing: AR: 124.117401 +- 3.306
+multi_loss: returning: ci=1 cj=2 r.loss=124.117401 r.sdev=3.306
+multi_annealing: AF: best_opt_some.txt: 58.0,124.117401,0.0,0.0,4.017889129124014,50.0,-1.0,3.306
+multi_annealing: AR: 0.3916097778073887 vs 1.0
+math/min: result=1.0
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: Accepting try_x[j], i=1 j=2
+multi_annealing: Accepting try_x[j], i=1 j=2 try_x[j]=4.017889129124014
+multi_annealing: AR: [1][2] Rejection counts: 0.0 0.0 0.0 0.0 0.0
+
+multi_annealing: AR: 1 ***** Did accept! 0.0 0.0 4.017889129124014 50.0 -1.0
+
+multi_loss appCalls=1
+multi_annealing: AR: 48.711529653164106 3
+multi_loss: entered: ci=1 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,4.017889129124014,48.711529653164106,-1.0]
+multi_loss: i=1 calling evolve, args=[0,0,4.017889129124014,48.711529653164106,-1,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:22 -0600  Checking status:1  Finished successfully:4
+multi_annealing: AR: 125.18271 +- 3.599503
+multi_loss: returning: ci=1 cj=3 r.loss=125.18271 r.sdev=3.599503
+multi_annealing: AF: best_opt_some.txt: 58.0,125.18271,0.0,0.0,4.017889129124014,48.711529653164106,-1.0,3.599503
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.29338527075939624 vs 0.5870445897168992
+math/min: result=0.5870445897168992
+multi_annealing: Accepting try_x[j], i=1 j=3 try_x[j]=48.711529653164106
+multi_annealing: Accepting try_x[j], i=1 j=3
+multi_annealing: AR: 1 ***** Did accept! 0.0 0.0 4.017889129124014 48.711529653164106 -1.0
+
+multi_annealing: AR: [1][3] Rejection counts: 0.0 0.0 0.0 0.0 0.0
+
+multi_loss appCalls=1
+multi_annealing: AR: -0.0033614536445253362 4
+multi_loss: entered: ci=1 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,4.017889129124014,48.711529653164106,-0.0033614536445253362]
+multi_loss: i=1 calling evolve, args=[0,0,4.017889129124014,48.711529653164106,-0.0033614536445253362,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:26 -0600  Checking status:1  Finished successfully:6
+multi_annealing: AR: 125.933179 +- 3.36805
+multi_loss: returning: ci=1 cj=4 r.loss=125.933179 r.sdev=3.36805
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AF: best_opt_some.txt: 58.0,125.933179,0.0,0.0,4.017889129124014,48.711529653164106,-0.0033614536445253362,3.36805
+multi_annealing: AR: 0.6647548795660121 vs 0.6871281283507249
+math/min: result=0.6871281283507249
+multi_annealing: Accepting try_x[j], i=1 j=4
+multi_annealing: Accepting try_x[j], i=1 j=4 try_x[j]=-0.0033614536445253362
+multi_annealing: AR: 1 ***** Did accept! 0.0 0.0 4.017889129124014 48.711529653164106 -0.0033614536445253362
+
+multi_annealing: AR: [1][4] Rejection counts: 0.0 0.0 0.0 0.0 0.0
+
+multi_annealing: AR: i=2 ....T = 1.6762121943865207
+multi_loss appCalls=1
+multi_annealing: AR: 5.284753614883805 2
+multi_loss: entered: ci=2 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,48.711529653164106,-0.0033614536445253362]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,48.711529653164106,-0.0033614536445253362,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:29 -0600  Checking status:1  Finished successfully:8
+multi_annealing: AR: 126.145367 +- 3.119133
+multi_loss: returning: ci=2 cj=2 r.loss=126.145367 r.sdev=3.119133
+multi_annealing: AF: best_opt_some.txt: 58.0,126.145367,0.0,0.0,5.284753614883805,48.711529653164106,-0.0033614536445253362,3.119133
+multi_annealing: AR: 0.8343453829181197 vs 0.8810967932193764
+math/min: result=0.8810967932193764
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: Accepting try_x[j], i=2 j=2 try_x[j]=5.284753614883805
+multi_annealing: Accepting try_x[j], i=2 j=2
+multi_annealing: AR: 2 ***** Did accept! 0.0 0.0 5.284753614883805 48.711529653164106 -0.0033614536445253362
+
+multi_annealing: AR: [2][2] Rejection counts: 0.0 0.0 0.0 0.0 0.0
+
+multi_loss appCalls=1
+multi_annealing: AR: 47.49006278600924 3
+multi_loss: entered: ci=2 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,47.49006278600924,-0.0033614536445253362]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,47.49006278600924,-0.0033614536445253362,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:33 -0600  Checking status:1  Finished successfully:10
+multi_annealing: AR: 125.831434 +- 3.344003
+multi_loss: returning: ci=2 cj=3 r.loss=125.831434 r.sdev=3.344003
+multi_annealing: AF: best_opt_some.txt: 58.0,125.831434,0.0,0.0,5.284753614883805,47.49006278600924,-0.0033614536445253362,3.344003
+multi_annealing: AR: 0.7961447191161577 vs 1.0
+math/min: result=1.0
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: Accepting try_x[j], i=2 j=3
+multi_annealing: Accepting try_x[j], i=2 j=3 try_x[j]=47.49006278600924
+multi_annealing: AR: 2 ***** Did accept! 0.0 0.0 5.284753614883805 47.49006278600924 -0.0033614536445253362
+
+multi_annealing: AR: [2][3] Rejection counts: 0.0 0.0 0.0 0.0 0.0
+
+multi_loss appCalls=1
+multi_annealing: AR: 0.2830038287653472 4
+multi_loss: entered: ci=2 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,47.49006278600924,0.2830038287653472]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,47.49006278600924,0.2830038287653472,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:36 -0600  Checking status:1  Finished successfully:12
+multi_annealing: AR: 123.989674 +- 3.372759
+multi_loss: returning: ci=2 cj=4 r.loss=123.989674 r.sdev=3.372759
+multi_annealing: AF: best_opt_some.txt: 58.0,123.989674,0.0,0.0,5.284753614883805,47.49006278600924,0.2830038287653472,3.372759
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.19911890147442235 vs 1.0
+math/min: result=1.0
+multi_annealing: Accepting try_x[j], i=2 j=4
+multi_annealing: Accepting try_x[j], i=2 j=4 try_x[j]=0.2830038287653472
+multi_annealing: AR: [2][4] Rejection counts: 0.0 0.0 0.0 0.0 0.0
+
+multi_annealing: AR: 2 ***** Did accept! 0.0 0.0 5.284753614883805 47.49006278600924 0.2830038287653472
+
+multi_annealing: AR: i=3 ....T = 1.4048436603050374
+multi_loss appCalls=1
+multi_annealing: AR: 6.751519052449282 2
+multi_loss: entered: ci=3 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,6.751519052449282,47.49006278600924,0.2830038287653472]
+multi_loss: i=1 calling evolve, args=[0,0,6.751519052449282,47.49006278600924,0.2830038287653472,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:39 -0600  Checking status:1  Finished successfully:14
+multi_loss: returning: ci=3 cj=2 r.loss=125.83918 r.sdev=3.276288
+multi_annealing: AR: 125.83918 +- 3.276288
+multi_annealing: AF: best_opt_some.txt: 58.0,125.83918,0.0,0.0,6.751519052449282,47.49006278600924,0.2830038287653472,3.276288
+math/min: result=0.2680663186298088
+multi_annealing: AR: 3,2 3 Did not accept: 6.751519052449282 (2)
+multi_annealing: AR: 0.6852396383450929 vs 0.2680663186298088
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.0 0.0 6.751519052449282 47.49006278600924 0.2830038287653472
+multi_loss appCalls=1
+multi_annealing: AR: 49.01109219848105 3
+multi_loss: entered: ci=3 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,49.01109219848105,0.2830038287653472]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,49.01109219848105,0.2830038287653472,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:42 -0600  Checking status:1  Finished successfully:16
+multi_loss: returning: ci=3 cj=3 r.loss=126.260409 r.sdev=3.474799
+multi_annealing: AF: best_opt_some.txt: 58.0,126.260409,0.0,0.0,5.284753614883805,49.01109219848105,0.2830038287653472,3.474799
+multi_annealing: AR: 126.260409 +- 3.474799
+math/min: result=0.1986200941793068
+multi_annealing: AR: 0.6989515725257741 vs 0.1986200941793068
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 3,3 3 Did not accept: 49.01109219848105 (3)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 49.01109219848105 0.2830038287653472
+multi_loss appCalls=1
+multi_annealing: AR: 0.7184988677898592 4
+multi_loss: entered: ci=3 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,47.49006278600924,0.7184988677898592]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,47.49006278600924,0.7184988677898592,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:45 -0600  Checking status:1  Finished successfully:18
+multi_loss: returning: ci=3 cj=4 r.loss=123.593465 r.sdev=3.286319
+multi_annealing: AR: 123.593465 +- 3.286319
+multi_annealing: AF: best_opt_some.txt: 58.0,123.593465,0.0,0.0,5.284753614883805,47.49006278600924,0.7184988677898592,3.286319
+multi_annealing: AR: 0.10970841947076293 vs 1.0
+multi_annealing: AF: max_dist.txt - tbd
+math/min: result=1.0
+multi_annealing: Accepting try_x[j], i=3 j=4
+multi_annealing: Accepting try_x[j], i=3 j=4 try_x[j]=0.7184988677898592
+multi_annealing: AR: 3 ***** Did accept! 0.0 0.0 5.284753614883805 47.49006278600924 0.7184988677898592
+
+multi_annealing: AR: [3][4] Rejection counts: 0.0 0.0 1.0 1.0 0.0
+
+multi_annealing: AR: i=4 ....T = 1.1774080373049494
+multi_loss appCalls=1
+multi_annealing: AR: 4.4255186274220115 2
+multi_loss: entered: ci=4 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,4.4255186274220115,47.49006278600924,0.7184988677898592]
+multi_loss: i=1 calling evolve, args=[0,0,4.4255186274220115,47.49006278600924,0.7184988677898592,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:49 -0600  Checking status:1  Finished successfully:20
+multi_loss: returning: ci=4 cj=2 r.loss=126.444622 r.sdev=3.25147
+multi_annealing: AR: 126.444622 +- 3.25147
+multi_annealing: AF: best_opt_some.txt: 58.0,126.444622,0.0,0.0,4.4255186274220115,47.49006278600924,0.7184988677898592,3.25147
+multi_annealing: AR: 0.9535428038358379 vs 0.08878355131476454
+math/min: result=0.08878355131476454
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 4,2 4 Did not accept: 4.4255186274220115 (2)
+multi_annealing: AR: 0.0 0.0 4.4255186274220115 47.49006278600924 0.7184988677898592
+multi_loss appCalls=1
+multi_annealing: AR: 46.92686166375319 3
+multi_loss: entered: ci=4 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,46.92686166375319,0.7184988677898592]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,46.92686166375319,0.7184988677898592,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:52 -0600  Checking status:1  Finished successfully:22
+multi_annealing: AR: 124.963375 +- 3.41926
+multi_loss: returning: ci=4 cj=3 r.loss=124.963375 r.sdev=3.41926
+multi_annealing: AF: best_opt_some.txt: 58.0,124.963375,0.0,0.0,5.284753614883805,46.92686166375319,0.7184988677898592,3.41926
+multi_annealing: AR: 0.4500207377949753 vs 0.312392025102438
+math/min: result=0.312392025102438
+multi_annealing: AR: 4,3 4 Did not accept: 46.92686166375319 (3)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 46.92686166375319 0.7184988677898592
+multi_annealing: AF: max_dist.txt - tbd
+multi_loss appCalls=1
+multi_annealing: AR: -0.3320316742658884 4
+multi_loss: entered: ci=4 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,47.49006278600924,-0.3320316742658884]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,47.49006278600924,-0.3320316742658884,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:55 -0600  Checking status:1  Finished successfully:24
+multi_annealing: AR: 125.407828 +- 3.018498
+multi_loss: returning: ci=4 cj=4 r.loss=125.407828 r.sdev=3.018498
+multi_annealing: AF: best_opt_some.txt: 58.0,125.407828,0.0,0.0,5.284753614883805,47.49006278600924,-0.3320316742658884,3.018498
+multi_annealing: AR: 0.8555641933973892 vs 0.21417097212905944
+math/min: result=0.21417097212905944
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.0 0.0 5.284753614883805 47.49006278600924 -0.3320316742658884
+multi_annealing: AR: 4,4 4 Did not accept: -0.3320316742658884 (4)
+multi_annealing: AR: i=5 ....T = 0.9867928549496278
+multi_loss appCalls=1
+multi_annealing: AR: 6.833327620921641 2
+multi_loss: entered: ci=5 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,6.833327620921641,47.49006278600924,0.7184988677898592]
+multi_loss: i=1 calling evolve, args=[0,0,6.833327620921641,47.49006278600924,0.7184988677898592,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:17:58 -0600  Checking status:1  Finished successfully:26
+multi_annealing: AR: 125.250487 +- 3.078819
+multi_loss: returning: ci=5 cj=2 r.loss=125.250487 r.sdev=3.078819
+multi_annealing: AF: best_opt_some.txt: 58.0,125.250487,0.0,0.0,6.833327620921641,47.49006278600924,0.7184988677898592,3.078819
+multi_annealing: AR: 0.44288167684075663 vs 0.18652324111077032
+math/min: result=0.18652324111077032
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 5,2 5 Did not accept: 6.833327620921641 (2)
+multi_annealing: AR: 0.0 0.0 6.833327620921641 47.49006278600924 0.7184988677898592
+multi_loss appCalls=1
+multi_annealing: AR: 46.49027442733761 3
+multi_loss: entered: ci=5 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,46.49027442733761,0.7184988677898592]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,46.49027442733761,0.7184988677898592,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:01 -0600  Checking status:1  Finished successfully:28
+multi_annealing: AR: 124.663101 +- 3.485893
+multi_loss: returning: ci=5 cj=3 r.loss=124.663101 r.sdev=3.485893
+multi_annealing: AF: best_opt_some.txt: 58.0,124.663101,0.0,0.0,5.284753614883805,46.49027442733761,0.7184988677898592,3.485893
+multi_annealing: AR: 0.42913823795768913 vs 0.33825612299835406
+math/min: result=0.33825612299835406
+multi_annealing: AR: 0.0 0.0 5.284753614883805 46.49027442733761 0.7184988677898592
+multi_annealing: AR: 5,3 5 Did not accept: 46.49027442733761 (3)
+multi_annealing: AF: max_dist.txt - tbd
+multi_loss appCalls=1
+multi_annealing: AR: 2.2333217492423234 4
+multi_loss: entered: ci=5 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,47.49006278600924,2.2333217492423234]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,47.49006278600924,2.2333217492423234,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:05 -0600  Checking status:1  Finished successfully:30
+multi_annealing: AR: 125.856136 +- 3.415745
+multi_loss: returning: ci=5 cj=4 r.loss=125.856136 r.sdev=3.415745
+multi_annealing: AF: best_opt_some.txt: 58.0,125.856136,0.0,0.0,5.284753614883805,47.49006278600924,2.2333217492423234,3.415745
+multi_annealing: AR: 0.5684553851797784 vs 0.10096772364295076
+math/min: result=0.10096772364295076
+multi_annealing: AR: 5,4 5 Did not accept: 2.2333217492423234 (4)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 47.49006278600924 2.2333217492423234
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: i=6 ....T = 0.8270371084000275
+multi_loss appCalls=1
+multi_annealing: AR: 3.928981105935937 2
+multi_loss: entered: ci=6 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,3.928981105935937,47.49006278600924,0.7184988677898592]
+multi_loss: i=1 calling evolve, args=[0,0,3.928981105935937,47.49006278600924,0.7184988677898592,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:08 -0600  Checking status:1  Finished successfully:32
+multi_annealing: AR: 125.944813 +- 3.343539
+multi_loss: returning: ci=6 cj=2 r.loss=125.944813 r.sdev=3.343539
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.0737231873586417 vs 0.05824491156028037
+multi_annealing: AF: best_opt_some.txt: 58.0,125.944813,0.0,0.0,3.928981105935937,47.49006278600924,0.7184988677898592,3.343539
+multi_annealing: AR: 6,2 6 Did not accept: 3.928981105935937 (2)
+math/min: result=0.05824491156028037
+multi_annealing: AR: 0.0 0.0 3.928981105935937 47.49006278600924 0.7184988677898592
+multi_loss appCalls=1
+multi_annealing: AR: 47.456980868107266 3
+multi_loss: entered: ci=6 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,47.456980868107266,0.7184988677898592]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,47.456980868107266,0.7184988677898592,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:11 -0600  Checking status:1  Finished successfully:34
+multi_annealing: AR: 126.604462 +- 3.183016
+multi_loss: returning: ci=6 cj=3 r.loss=126.604462 r.sdev=3.183016
+multi_annealing: AR: 0.5487345599809303 vs 0.02623387861162342
+math/min: result=0.02623387861162342
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AF: best_opt_some.txt: 58.0,126.604462,0.0,0.0,5.284753614883805,47.456980868107266,0.7184988677898592,3.183016
+multi_annealing: AR: 6,3 6 Did not accept: 47.456980868107266 (3)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 47.456980868107266 0.7184988677898592
+multi_loss appCalls=1
+multi_loss: entered: ci=6 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,47.49006278600924,-1.5302000464747076]
+multi_annealing: AR: -1.5302000464747076 4
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,47.49006278600924,-1.5302000464747076,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:12 -0600  Active:1  Finished successfully:36
+Progress:  time: Mon, 30 Jan 2012 12:18:14 -0600  Checking status:1  Finished successfully:36
+multi_loss: returning: ci=6 cj=4 r.loss=125.062511 r.sdev=3.22833
+multi_annealing: AR: 125.062511 +- 3.22833
+multi_annealing: AF: best_opt_some.txt: 58.0,125.062511,0.0,0.0,5.284753614883805,47.49006278600924,-1.5302000464747076,3.22833
+multi_annealing: AR: 0.4295446121391554 vs 0.16926736066405584
+multi_annealing: AF: max_dist.txt - tbd
+math/min: result=0.16926736066405584
+multi_annealing: AR: 6,4 6 Did not accept: -1.5302000464747076 (4)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 47.49006278600924 -1.5302000464747076
+multi_annealing: AR: i=7 ....T = 0.6931448431551464
+multi_loss appCalls=1
+multi_annealing: AR: 5.698890855198198 2
+multi_loss: entered: ci=7 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.698890855198198,47.49006278600924,0.7184988677898592]
+multi_loss: i=1 calling evolve, args=[0,0,5.698890855198198,47.49006278600924,0.7184988677898592,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:17 -0600  Checking status:1  Finished successfully:38
+multi_annealing: AR: 124.92233 +- 3.519439
+multi_loss: returning: ci=7 cj=2 r.loss=124.92233 r.sdev=3.519439
+multi_annealing: AF: best_opt_some.txt: 58.0,124.92233,0.0,0.0,5.698890855198198,47.49006278600924,0.7184988677898592,3.519439
+multi_annealing: AR: 0.26061833782383614 vs 0.14702488652213752
+multi_annealing: AF: max_dist.txt - tbd
+math/min: result=0.14702488652213752
+multi_annealing: AR: 7,2 7 Did not accept: 5.698890855198198 (2)
+multi_annealing: AR: 0.0 0.0 5.698890855198198 47.49006278600924 0.7184988677898592
+multi_loss appCalls=1
+multi_annealing: AR: 48.00451051760781 3
+multi_loss: entered: ci=7 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,48.00451051760781,0.7184988677898592]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,48.00451051760781,0.7184988677898592,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:21 -0600  Checking status:1  Finished successfully:40
+multi_annealing: AR: 123.700997 +- 3.061641
+multi_loss: returning: ci=7 cj=3 r.loss=123.700997 r.sdev=3.061641
+multi_annealing: AF: best_opt_some.txt: 58.0,123.700997,0.0,0.0,5.284753614883805,48.00451051760781,0.7184988677898592,3.061641
+multi_annealing: AR: 0.04383216320955852 vs 0.8562983650405412
+math/min: result=0.8562983650405412
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: Accepting try_x[j], i=7 j=3
+multi_annealing: Accepting try_x[j], i=7 j=3 try_x[j]=48.00451051760781
+multi_annealing: AR: 7 ***** Did accept! 0.0 0.0 5.284753614883805 48.00451051760781 0.7184988677898592
+
+multi_annealing: AR: [7][3] Rejection counts: 0.0 0.0 5.0 4.0 3.0
+
+multi_loss appCalls=1
+multi_annealing: AR: -0.41452399887346414 4
+multi_loss: entered: ci=7 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,48.00451051760781,-0.41452399887346414]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,48.00451051760781,-0.41452399887346414,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:24 -0600  Checking status:1  Finished successfully:42
+multi_annealing: AR: 122.427501 +- 3.484433
+multi_loss: returning: ci=7 cj=4 r.loss=122.427501 r.sdev=3.484433
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.6794911655574871 vs 1.0
+math/min: result=1.0
+multi_annealing: AF: best_opt_some.txt: 58.0,122.427501,0.0,0.0,5.284753614883805,48.00451051760781,-0.41452399887346414,3.484433
+multi_annealing: Accepting try_x[j], i=7 j=4
+multi_annealing: Accepting try_x[j], i=7 j=4 try_x[j]=-0.41452399887346414
+multi_annealing: AR: [7][4] Rejection counts: 0.0 0.0 5.0 4.0 3.0
+
+multi_annealing: AR: 7 ***** Did accept! 0.0 0.0 5.284753614883805 48.00451051760781 -0.41452399887346414
+
+multi_annealing: AR: i=8 ....T = 0.5809289192863943
+multi_loss appCalls=1
+multi_annealing: AR: 4.228373615739721 2
+multi_loss: entered: ci=8 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,4.228373615739721,48.00451051760781,-0.41452399887346414]
+multi_loss: i=1 calling evolve, args=[0,0,4.228373615739721,48.00451051760781,-0.41452399887346414,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:27 -0600  Checking status:1  Finished successfully:44
+multi_loss: returning: ci=8 cj=2 r.loss=125.825434 r.sdev=3.06081
+multi_annealing: AR: 125.825434 +- 3.06081
+multi_annealing: AF: best_opt_some.txt: 58.0,125.825434,0.0,0.0,4.228373615739721,48.00451051760781,-0.41452399887346414,3.06081
+multi_annealing: AR: 0.43307949429152304 vs 0.0028823847709179276
+math/min: result=0.0028823847709179276
+multi_annealing: AR: 0.0 0.0 4.228373615739721 48.00451051760781 -0.41452399887346414
+multi_annealing: AR: 8,2 8 Did not accept: 4.228373615739721 (2)
+multi_annealing: AF: max_dist.txt - tbd
+multi_loss appCalls=1
+multi_annealing: AR: 46.894163840589215 3
+multi_loss: entered: ci=8 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,46.894163840589215,-0.41452399887346414]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,46.894163840589215,-0.41452399887346414,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:30 -0600  Checking status:1  Finished successfully:46
+multi_annealing: AR: 124.871719 +- 3.122439
+multi_loss: returning: ci=8 cj=3 r.loss=124.871719 r.sdev=3.122439
+multi_annealing: AF: best_opt_some.txt: 58.0,124.871719,0.0,0.0,5.284753614883805,46.894163840589215,-0.41452399887346414,3.122439
+multi_annealing: AR: 0.34644774801935974 vs 0.014884566500466245
+math/min: result=0.014884566500466245
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.0 0.0 5.284753614883805 46.894163840589215 -0.41452399887346414
+multi_annealing: AR: 8,3 8 Did not accept: 46.894163840589215 (3)
+multi_loss appCalls=1
+multi_annealing: AR: -2.2286308752011443 4
+multi_loss: entered: ci=8 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,48.00451051760781,-2.2286308752011443]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,48.00451051760781,-2.2286308752011443,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:33 -0600  Checking status:1  Finished successfully:48
+multi_annealing: AR: 125.200576 +- 3.137099
+multi_loss: returning: ci=8 cj=4 r.loss=125.200576 r.sdev=3.137099
+multi_annealing: AF: best_opt_some.txt: 58.0,125.200576,0.0,0.0,5.284753614883805,48.00451051760781,-2.2286308752011443,3.137099
+multi_annealing: AR: 0.47163119315783886 vs 0.008450593550370632
+math/min: result=0.008450593550370632
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 8,4 8 Did not accept: -2.2286308752011443 (4)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 48.00451051760781 -2.2286308752011443
+multi_annealing: AR: i=9 ....T = 0.48688006928981853
+multi_loss appCalls=1
+multi_annealing: AR: 5.695013169826046 2
+multi_loss: entered: ci=9 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.695013169826046,48.00451051760781,-0.41452399887346414]
+multi_loss: i=1 calling evolve, args=[0,0,5.695013169826046,48.00451051760781,-0.41452399887346414,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:37 -0600  Checking status:1  Finished successfully:50
+multi_annealing: AR: 125.017227 +- 3.237815
+multi_loss: returning: ci=9 cj=2 r.loss=125.017227 r.sdev=3.237815
+multi_annealing: AF: best_opt_some.txt: 58.0,125.017227,0.0,0.0,5.695013169826046,48.00451051760781,-0.41452399887346414,3.237815
+multi_annealing: AR: 0.17076495981302242 vs 0.004897539166396153
+math/min: result=0.004897539166396153
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 9,2 9 Did not accept: 5.695013169826046 (2)
+multi_annealing: AR: 0.0 0.0 5.695013169826046 48.00451051760781 -0.41452399887346414
+multi_loss appCalls=1
+multi_annealing: AR: 48.00679484464189 3
+multi_loss: entered: ci=9 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,48.00679484464189,-0.41452399887346414]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,48.00679484464189,-0.41452399887346414,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:40 -0600  Checking status:1  Finished successfully:52
+multi_annealing: AR: 125.213924 +- 3.333561
+multi_loss: returning: ci=9 cj=3 r.loss=125.213924 r.sdev=3.333561
+multi_annealing: AF: best_opt_some.txt: 58.0,125.213924,0.0,0.0,5.284753614883805,48.00679484464189,-0.41452399887346414,3.333561
+multi_annealing: AR: 0.15928070563724706 vs 0.003269830345111401
+math/min: result=0.003269830345111401
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.0 0.0 5.284753614883805 48.00679484464189 -0.41452399887346414
+multi_annealing: AR: 9,3 9 Did not accept: 48.00679484464189 (3)
+multi_loss appCalls=1
+multi_annealing: AR: -0.7507963173758503 4
+multi_loss: entered: ci=9 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,48.00451051760781,-0.7507963173758503]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,48.00451051760781,-0.7507963173758503,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:42 -0600  Active:1  Finished successfully:54
+multi_loss: returning: ci=9 cj=4 r.loss=125.856406 r.sdev=3.764608
+multi_annealing: AR: 125.856406 +- 3.764608
+multi_annealing: AF: best_opt_some.txt: 58.0,125.856406,0.0,0.0,5.284753614883805,48.00451051760781,-0.7507963173758503,3.764608
+math/min: result=8.738454465360378E-4
+multi_annealing: AR: 0.061628429129563234 vs 8.738454465360378E-4
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 9,4 9 Did not accept: -0.7507963173758503 (4)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 48.00451051760781 -0.7507963173758503
+multi_annealing: AR: i=10 ....T = 0.408057154673674
+multi_loss appCalls=1
+multi_annealing: AR: 3.29267604969456 2
+multi_loss: entered: ci=10 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,3.29267604969456,48.00451051760781,-0.41452399887346414]
+multi_loss: i=1 calling evolve, args=[0,0,3.29267604969456,48.00451051760781,-0.41452399887346414,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:46 -0600  Checking status:1  Finished successfully:56
+multi_annealing: AR: 125.360364 +- 3.317013
+multi_loss: returning: ci=10 cj=2 r.loss=125.360364 r.sdev=3.317013
+multi_annealing: AF: best_opt_some.txt: 58.0,125.360364,0.0,0.0,3.29267604969456,48.00451051760781,-0.41452399887346414,3.317013
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.27027335203696023 vs 7.56065260977875E-4
+math/min: result=7.56065260977875E-4
+multi_annealing: AR: 0.0 0.0 3.29267604969456 48.00451051760781 -0.41452399887346414
+multi_annealing: AR: 10,2 10 Did not accept: 3.29267604969456 (2)
+multi_loss appCalls=1
+multi_annealing: AR: 46.275556353155956 3
+multi_loss: entered: ci=10 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,46.275556353155956,-0.41452399887346414]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,46.275556353155956,-0.41452399887346414,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:49 -0600  Checking status:1  Finished successfully:58
+multi_annealing: AR: 126.434478 +- 3.246686
+multi_loss: returning: ci=10 cj=3 r.loss=126.434478 r.sdev=3.246686
+multi_annealing: AF: best_opt_some.txt: 58.0,126.434478,0.0,0.0,5.284753614883805,46.275556353155956,-0.41452399887346414,3.246686
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.14920802306232583 vs 5.4372803009239825E-5
+math/min: result=5.4372803009239825E-5
+multi_annealing: AR: 10,3 10 Did not accept: 46.275556353155956 (3)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 46.275556353155956 -0.41452399887346414
+multi_loss appCalls=1
+multi_annealing: AR: 1.5046793086101826 4
+multi_loss: entered: ci=10 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,48.00451051760781,1.5046793086101826]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,48.00451051760781,1.5046793086101826,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:53 -0600  Checking status:1  Finished successfully:60
+multi_loss: returning: ci=10 cj=4 r.loss=125.785376 r.sdev=3.346594
+multi_annealing: AR: 125.785376 +- 3.346594
+multi_annealing: AF: best_opt_some.txt: 58.0,125.785376,0.0,0.0,5.284753614883805,48.00451051760781,1.5046793086101826,3.346594
+multi_annealing: AR: 0.6250655950503741 vs 2.668208671281028E-4
+math/min: result=2.668208671281028E-4
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 0.0 0.0 5.284753614883805 48.00451051760781 1.5046793086101826
+multi_annealing: AR: 10,4 10 Did not accept: 1.5046793086101826 (4)
+multi_annealing: new cycle at i=11
+multi_annealing: AR: New cycle at 11: prev dx[0-4]=[2.3 2.3 2.3 2.3 2.3]
+multi_annealing: AR: i=11 ....T = 0.34199518933533946
+multi_annealing: AR: New cycle at 11: dx[0-4]=[4.6 4.6 0.8624999999999998 0.9857142857142855 1.15]
+multi_loss appCalls=1
+multi_annealing: AR: 3.791705563626845 2
+multi_loss: entered: ci=11 cj=2 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,3.791705563626845,48.00451051760781,-0.41452399887346414]
+multi_loss: i=1 calling evolve, args=[0,0,3.791705563626845,48.00451051760781,-0.41452399887346414,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:56 -0600  Checking status:1  Finished successfully:62
+multi_annealing: AF: max_dist.txt - tbd
+multi_loss: returning: ci=11 cj=2 r.loss=124.596526 r.sdev=3.176561
+multi_annealing: AR: 124.596526 +- 3.176561
+multi_annealing: AF: best_opt_some.txt: 58.0,124.596526,0.0,0.0,3.791705563626845,48.00451051760781,-0.41452399887346414,3.176561
+multi_annealing: AR: 0.9715442940965933 vs 0.001760306082349071
+math/min: result=0.001760306082349071
+multi_annealing: AR: 0.0 0.0 3.791705563626845 48.00451051760781 -0.41452399887346414
+multi_annealing: AR: 11,2 11 Did not accept: 3.791705563626845 (2)
+multi_loss appCalls=1
+multi_annealing: AR: 49.92607616034099 3
+multi_loss: entered: ci=11 cj=3 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,49.92607616034099,-0.41452399887346414]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,49.92607616034099,-0.41452399887346414,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:18:59 -0600  Checking status:1  Finished successfully:64
+multi_annealing: AR: 124.00716 +- 3.111738
+multi_loss: returning: ci=11 cj=3 r.loss=124.00716 r.sdev=3.111738
+multi_annealing: AF: best_opt_some.txt: 58.0,124.00716,0.0,0.0,5.284753614883805,49.92607616034099,-0.41452399887346414,3.111738
+multi_annealing: AR: 0.38818246796613753 vs 0.009863137695174688
+math/min: result=0.009863137695174688
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 11,3 11 Did not accept: 49.92607616034099 (3)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 49.92607616034099 -0.41452399887346414
+multi_loss appCalls=1
+multi_annealing: AR: -0.7771568808805009 4
+multi_loss: entered: ci=11 cj=4 target_innov=58.0 evolve_reruns=100 x=[0.0,0.0,5.284753614883805,48.00451051760781,-0.7771568808805009]
+multi_loss: i=1 calling evolve, args=[0,0,5.284753614883805,48.00451051760781,-0.7771568808805009,58,40000,20,100,2,1,2.,0.01,2,0.3,2.3,1,1,0,0,0,m,4,1234567]
+Progress:  time: Mon, 30 Jan 2012 12:19:02 -0600  Checking status:1  Finished successfully:66
+multi_annealing: AR: 123.567412 +- 3.66859
+multi_loss: returning: ci=11 cj=4 r.loss=123.567412 r.sdev=3.66859
+multi_annealing: AF: best_opt_some.txt: 58.0,123.567412,0.0,0.0,5.284753614883805,48.00451051760781,-0.7771568808805009,3.66859
+multi_annealing: AR: 0.5338319788181374 vs 0.03568160518248377
+math/min: result=0.03568160518248377
+multi_annealing: AF: max_dist.txt - tbd
+multi_annealing: AR: 11,4 11 Did not accept: -0.7771568808805009 (4)
+multi_annealing: AR: 0.0 0.0 5.284753614883805 48.00451051760781 -0.7771568808805009
+Progress:  time: Mon, 30 Jan 2012 12:19:12 -0600  Finished successfully:68
+No events in 10s.
+
+Registered futures:
+string[] args  Closed, 24 elements, no listeners
+string[] args  Closed, 24 elements, no listeners
+string[] args  Closed, 24 elements, no listeners
+string[] args  Closed, 24 elements, no listeners
+----
+
+Waiting threads:
+----
+
+No events in 10s.
+
+Registered futures:
+string[] args  Closed, 24 elements, no listeners
+string[] args  Closed, 24 elements, no listeners
+string[] args  Closed, 24 elements, no listeners
+string[] args  Closed, 24 elements, no listeners
+----
+
+Waiting threads:
+----
+
+No events in 10s.
+
+Registered futures:
+string[] args  Closed, 24 elements, no listeners
+string[] args  Closed, 24 elements, no listeners
+string[] args  Closed, 24 elements, no listeners
+string[] args  Closed, 24 elements, no listeners
+----
+
+Waiting threads:
+----
+
+Progress:  time: Mon, 30 Jan 2012 12:19:42 -0600  Finished successfully:68

Added: SwiftApps/SciColSim/sample.testopt.py.output
===================================================================
--- SwiftApps/SciColSim/sample.testopt.py.output	                        (rev 0)
+++ SwiftApps/SciColSim/sample.testopt.py.output	2012-01-30 18:34:45 UTC (rev 5525)
@@ -0,0 +1,243 @@
+
+**** Calling optimizer: OMP_NUM_THREADS=4 ./openmp-optimizer 0 0 4 50 -1 58 40000 20 100 2 1 2. 0.01 5 0.3 2.3 1 1 0 0 0 n 4 1234567
+
+alpha_i: 0
+alpha_m: 0
+beta: 4
+gamma: 50
+delta: -1
+target: 58
+n_epochs: 40000
+n_steps: 20
+n_reruns: 100
+range: 2
+verbose level: 1
+T_start: 2
+T_end: 0.01
+Annealing_steps: 5
+Target_rejection: 0.3
+Starting_jump: 2.3
+FREEZE_alpha_i: 1
+FREEZE_alpha_m: 1
+FREEZE_beta: 0
+FREEZE_gamma: 0
+FREEZE_delta: 0
+Operation: n
+Nworkers: 4
+initSeed: 1234567
+0 | 1 (fixed) 
+1 | 1 (fixed) 
+2 | 0 (fixed) 
+3 | 0 (fixed) 
+4 | 0 (fixed) 
+0.742788 0.631704 0.118309 0.922271 0.141282 0.80831 0.961468 0.363704 0.665483 0.683465 0.771216 0.267925 0.224677 0.153439 0.23455 0.816502 0.718347 0.371612 0.948727 0.404154 0.600908 0.766305 0.493219 0.82445 0.100233 0.672304 0.157299 0.53804 0.6794 0.57498 0.758357 0.422188 0.206684 0.876666 0.344459 0.347966 0.684976 0.305927 0.71167 0.350459 0.989392 0.482885 0.618384 0.214069 0.636325 0.852934 0.0305713 0.354672 0.224546 0.979299 0.758825 0.825454 0.745604 0.252044 0.649904 0.845837 0.924348 0.807203 0.383877 0.603748 0.382183 0.142234 0.0259353 0.588867 0.0189005 0.370394 0.936833 0.703877 0.676321 0.648502 0.0543356 0.665713 0.131387 0.672719 0.879782 0.767712 0.525653 0.910353 0.122384 0.750199 0.889652 0.881209 0.575653 0.635256 0.133253 0.225557 0.481092 0.0576008 0.0327595 0.864969 0.661348 0.414942 0.00720323 0.687284 0.00380882 0.0261037 0.0576777 0.940641 0.72998 0.733998 
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.9134 seconds 0.0485567 minutes
+
+126.43 +- 3.11244
+
+....T = 2
+
+3.77342 2
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.90873 seconds 0.0484788 minutes
+
+126.523 +- 3.32417
+0.82704 vs 0.954153
+1 Rejection counts: 0 0 0 0 0 
+
+ 1,2 ***** Did accept! 0 0 3.77342 50 -1 
+
+52.2335 3
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.93802 seconds 0.0489671 minutes
+
+130.173 +- 3.67201
+0.188468 vs 0.161259
+ 1,3 1 Did not accept 52.2335(3)
+0 0 3.77342 52.2335 -1 
+-2.00667 4
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.95626 seconds 0.049271 minutes
+
+129.554 +- 3.1612
+0.88704 vs 0.219698
+ 1,4 1 Did not accept -2.00667(4)
+0 0 3.77342 50 -2.00667 
+
+....T = 0.693145
+
+4.07035 2
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.99097 seconds 0.0498495 minutes
+
+130.603 +- 3.25174
+0.0501227 vs 0.00277796
+ 2,2 2 Did not accept 4.07035(2)
+0 0 4.07035 50 -1 
+48.5261 3
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.94022 seconds 0.0490036 minutes
+
+128.508 +- 3.34913
+0.685387 vs 0.0571204
+ 2,3 2 Did not accept 48.5261(3)
+0 0 3.77342 48.5261 -1 
+-2.2438 4
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.95557 seconds 0.0492594 minutes
+
+128.768 +- 3.41509
+0.579097 vs 0.0392132
+ 2,4 2 Did not accept -2.2438(4)
+0 0 3.77342 50 -2.2438 
+
+....T = 0.240225
+
+2.54662 2
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 3.02841 seconds 0.0504735 minutes
+
+127.262 +- 3.06273
+0.274094 vs 0.0462924
+ 3,2 3 Did not accept 2.54662(2)
+0 0 2.54662 50 -1 
+51.7319 3
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 3.00121 seconds 0.0500201 minutes
+
+128.927 +- 3.75415
+0.00641465 vs 4.52253e-05
+ 3,3 3 Did not accept 51.7319(3)
+0 0 3.77342 51.7319 -1 
+0.232896 4
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.98499 seconds 0.0497499 minutes
+
+128.55 +- 3.56206
+0.941162 vs 0.000216463
+ 3,4 3 Did not accept 0.232896(4)
+0 0 3.77342 50 0.232896 
+
+....T = 0.0832553
+
+4.37082 2
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.95775 seconds 0.0492958 minutes
+
+128.816 +- 3.45615
+0.803355 vs 1.09972e-12
+ 4,2 4 Did not accept 4.37082(2)
+0 0 4.37082 50 -1 
+49.3468 3
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.9872 seconds 0.0497866 minutes
+
+128.915 +- 3.17434
+0.126163 vs 3.35758e-13
+ 4,3 4 Did not accept 49.3468(3)
+0 0 3.77342 49.3468 -1 
+-0.0551126 4
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.93849 seconds 0.0489748 minutes
+
+125.1 +- 3.35383
+0.17234 vs 1
+4 Rejection counts: 0 0 3 4 3 
+
+ 4,4 ***** Did accept! 0 0 3.77342 50 -0.0551126 
+
+
+....T = 0.028854
+
+5.90757 2
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 3.04963 seconds 0.0508272 minutes
+
+131.481 +- 3.49648
+0.318332 vs 9.27549e-97
+ 5,2 5 Did not accept 5.90757(2)
+0 0 5.90757 50 -0.0551126 
+49.5818 3
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 3.0051 seconds 0.050085 minutes
+
+131.054 +- 3.3899
+0.854774 vs 2.47481e-90
+ 5,3 5 Did not accept 49.5818(3)
+0 0 3.77342 49.5818 -0.0551126 
+-1.93165 4
+
+multi_loss: Calling evolve_to_target_and_save i=0 N=100 step=25 istart=0 iend=25
+multi_loss: Calling evolve_to_target_and_save i=1 N=100 step=25 istart=25 iend=50
+multi_loss: Calling evolve_to_target_and_save i=2 N=100 step=25 istart=50 iend=75
+multi_loss: Calling evolve_to_target_and_save i=3 N=100 step=25 istart=75 iend=100
+multi_loss(N=100, target=58) elapsed time: 2.95204 seconds 0.0492006 minutes
+
+127.676 +- 3.04749
+0.356781 vs 1.74605e-39
+ 5,4 5 Did not accept -1.93165(4)
+0 0 3.77342 50 -1.93165 
+
+*** optimizer completed, elapsed time=47.6158 seconds 0.793596 minutes)
+
+./mw.py Done!




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