asymptote 1.80

git-svn-id: svn://tug.org/texlive/trunk@14179 c570f23f-e606-0410-a88d-b1316a301751

4 files changed, 85 insertions, 39 deletions

diff --git a/Master/texmf/asymptote/GUI/xasyVersion.py b/Master/texmf/asymptote/GUI/xasyVersion.py
index 36de0c7c4c2..bbaa05404dc 100755
--- a/Master/texmf/asymptote/GUI/xasyVersion.py
+++ b/Master/texmf/asymptote/GUI/xasyVersion.py
@@ -1,2 +1,2 @@
 #!/usr/bin/env python
-xasyVersion = "1.79"
+xasyVersion = "1.80"
diff --git a/Master/texmf/asymptote/animation.asy b/Master/texmf/asymptote/animation.asy
index 2b7519c700a..6fcd2ad70e2 100644
--- a/Master/texmf/asymptote/animation.asy
+++ b/Master/texmf/asymptote/animation.asy
@@ -38,8 +38,8 @@ struct animation {
     this.global=global;
   }
   
-  string basename(string prefix=prefix) {
-    return "_"+stripextension(prefix);
+  string basename(string prefix=stripextension(prefix)) {
+    return "_"+prefix;
   }
 
   string name(string prefix, int index) {
@@ -47,7 +47,7 @@ struct animation {
   }
 
   private string nextname() {
-    string name=name(prefix,index);
+    string name=basename(name(prefix,index));
     ++index;
     return name;
   }
@@ -61,8 +61,9 @@ struct animation {
   
   void add(picture pic=currentpicture, fit fit=NoBox) {
     if(global) {
+      ++index;
       pictures.push(pic.copy());
-    } else this.shipout(nextname(),fit(prefix,pic));
+    } else this.shipout(fit(prefix,pic));
   }
   
   void purge(bool keep=settings.keep) {
@@ -89,6 +90,7 @@ struct animation {
   void export(string prefix=prefix, fit fit=NoBox,
               bool multipage=false, bool view=false) {
     if(pictures.length == 0) return;
+    if(!global) multipage=false;
     rescale(pictures);
     frame multi;
     bool inlinetex=settings.inlinetex;
@@ -119,6 +121,7 @@ struct animation {
 
   string load(int frames, real delay=animationdelay, string options="",
               bool multipage=false) {
+    if(!global) multipage=false;
     string s="\animategraphics["+options+"]{"+format("%.18f",1000/delay,"C")+
       "}{"+basename();
     if(!multipage) s += "+";
@@ -129,13 +132,13 @@ struct animation {
   string pdf(fit fit=NoBox, real delay=animationdelay, string options="",
              bool keep=settings.keep, bool multipage=true) {
     if(settings.inlinetex) multipage=true;
+    if(!global) multipage=false;
     if(settings.tex != "pdflatex")
       abort("inline pdf animations require -tex pdflatex");
     if(settings.outformat != "") settings.outformat="pdf";
     
     string filename=basename();
     string pdfname=filename+".pdf";
-    bool single=global && multipage;
 
     if(global)
       export(filename,fit,multipage=multipage);
@@ -147,28 +150,28 @@ struct animation {
       void exitfunction() {
         if(currentexitfunction != null) currentexitfunction();
         this.purge();
-        if(single)
+        if(multipage)
           delete(pdfname);
       }
       atexit(exitfunction);
     }
 
-    if(!single)
+    if(!multipage)
       delete(pdfname);
 
-    return load(pictures.length,delay,options,multipage);
+    return load(index,delay,options,multipage);
   }
 
   int movie(fit fit=NoBox, int loops=0, real delay=animationdelay,
             string format=settings.outformat == "" ? "gif" : settings.outformat,
             string options="", bool keep=settings.keep) {
-    if(global && format == "pdf") {
-      export(fit,multipage=true,view=true);
-      return 0;
-    }
-
-    if(global)
+    if(global) {
+      if(format == "pdf") {
+        export(fit,multipage=true,view=true);
+        return 0;
+      }
       export(fit);
+    }
     return merge(loops,delay,format,options,keep);
   }
 }
diff --git a/Master/texmf/asymptote/lmfit.asy b/Master/texmf/asymptote/lmfit.asy
index d0367547b74..72745625824 100644
--- a/Master/texmf/asymptote/lmfit.asy
+++ b/Master/texmf/asymptote/lmfit.asy
@@ -23,6 +23,18 @@
 */
 
 /*
+  Fitting $n$ data points $(x_1, y_1 \pm \Delta y_1), \dots, (x_n, y_n \pm \Delta y_n)$
+  to a function $f$ that depends on $m$ parameters $a_1, \dots, a_m$ means minimizing
+  the least-squares sum
+  %
+  \begin{equation*}
+    \sum_{i = 1}^n \left( \frac{y_i - f(a_1, \dots, a_m; x_i)}{\Delta y_i} \right)^2
+  \end{equation*}
+  %
+  with respect to the parameters $a_1, \dots, a_m$.
+*/
+
+/*
   This module provides an implementation of the Levenberg--Marquardt
   (LM) algorithm, converted from the C lmfit routine by Joachim Wuttke
   (see http://www.messen-und-deuten.de/lmfit/).
@@ -747,16 +759,20 @@ void lm_minimize(int m_dat, int n_par, real[] par, lm_evaluate_ftype evaluate, l
 
 
 // convenience functions; wrappers of lm_minimize
-struct FitControl {
-  real squareSumTolerance;
-  real approximationTolerance;
-  real desiredOrthogonality;
-  real epsilon;
-  real stepBound;
-  int maxIterations;
-  bool verbose;
 
-  void operator init(real squareSumTolerance, real approximationTolerance, real desiredOrthogonality, real epsilon, real stepBound, int maxIterations, bool verbose) {
+/*
+  The structure FitControl specifies various control parameters.
+*/
+struct FitControl {
+  real squareSumTolerance;      // relative error desired in the sum of squares
+  real approximationTolerance;  // relative error between last two approximations
+  real desiredOrthogonality;    // orthogonality desired between the residue vector and its derivatives
+  real epsilon;                 // step used to calculate the jacobian
+  real stepBound;               // initial bound to steps in the outer loop
+  int maxIterations;            // maximum number of iterations
+  bool verbose;                 // whether to print detailed information about every iteration, or nothing
+
+  void operator init(real squareSumTolerance=LM_USERTOL, real approximationTolerance=LM_USERTOL, real desiredOrthogonality=LM_USERTOL, real epsilon=LM_USERTOL, real stepBound=100, int maxIterations=100, bool verbose=false) {
     this.squareSumTolerance = squareSumTolerance;
     this.approximationTolerance = approximationTolerance;
     this.desiredOrthogonality = desiredOrthogonality;
@@ -779,30 +795,44 @@ struct FitControl {
   }
 };
 
+FitControl operator init() {
+  return FitControl();
+}
+
 FitControl defaultControl;
-defaultControl.squareSumTolerance = LM_USERTOL;
-defaultControl.approximationTolerance = LM_USERTOL;
-defaultControl.desiredOrthogonality = LM_USERTOL;
-defaultControl.epsilon = LM_USERTOL;
-defaultControl.stepBound = 100;
-defaultControl.maxIterations = 100;
-defaultControl.verbose = false;
 
 
+/*
+  Upon returning, this structure provides information about the fit.
+*/
 struct FitResult {
-  restricted real norm;
-  restricted int iterations;
-  restricted int status;
+  real norm;        // norm of the residue vector
+  int iterations;   // actual number of iterations
+  int status;       // status of minimization
 
-  void operator init(real norm, int status, int iterations) {
+  void operator init(real norm, int iterations, int status) {
     this.norm = norm;
-    this.status = status;
     this.iterations = iterations;
+    this.status = status;
   }
 };
 
 
-// Fits data points (xdata, ydata ± errors) to the given function using the given parameters.
+/*
+  Fits data points to a function that depends on some parameters.
+
+  Parameters:
+   - xdata: Array of x values.
+   - ydata: Array of y values.
+   - errors: Array of experimental errors; each element must be strictly positive
+   - function: Fit function.
+   - parameters: Parameter array. Before calling fit(), this must contain the initial guesses for the parameters.
+                 Upon return, it will contain the solution parameters.
+   - control: object of type FitControl that controls various aspects of the fitting procedure.
+
+  Returns:
+  An object of type FitResult that conveys information about the fitting process.
+*/
 FitResult fit(real[] xdata, real[] ydata, real[] errors, real function(real[], real), real[] parameters, FitControl control=defaultControl) {
   int m_dat = min(xdata.length, ydata.length);
   int n_par = parameters.length;
@@ -831,7 +861,20 @@ FitResult fit(real[] xdata, real[] ydata, real[] errors, real function(real[], r
 }
 
 
-// Fits data points (xdata, ydata) to the given function using the given parameters.
+/*
+  Fits data points to a function that depends on some parameters.
+
+  Parameters:
+   - xdata: Array of x values.
+   - ydata: Array of y values.
+   - function: Fit function.
+   - parameters: Parameter array. Before calling fit(), this must contain the initial guesses for the parameters.
+                 Upon return, it will contain the solution parameters.
+   - control: object of type FitControl that controls various aspects of the fitting procedure.
+
+  Returns:
+  An object of type FitResult that conveys information about the fitting process.
+*/
 FitResult fit(real[] xdata, real[] ydata, real function(real[], real), real[] parameters, FitControl control=defaultControl) {
   return fit(xdata, ydata, array(min(xdata.length, ydata.length), 1.0), function, parameters, control);
 }
diff --git a/Master/texmf/asymptote/version.asy b/Master/texmf/asymptote/version.asy
index ab6167a50a5..f071711bae7 100644
--- a/Master/texmf/asymptote/version.asy
+++ b/Master/texmf/asymptote/version.asy
@@ -1 +1 @@
-string VERSION="1.79";
+string VERSION="1.80";