octave-cvsupdate

[Octave-cvsupdate] SF.net SVN: octave:[8343] trunk/octave-forge/main/fuzzy-logic-toolkit/inst

[<lm...@us...>]

Revision: 8343
          http://octave.svn.sourceforge.net/octave/?rev=8343&view=rev
Author:   lmarkov
Date:     2011-06-22 01:51:28 +0000 (Wed, 22 Jun 2011)

Log Message:
-----------

M    inst/addvar.m
M    inst/getfis.m
M    inst/gaussmf.m
M    inst/addmf.m
M    inst/readfis.m
M    inst/addrule.m

Modified Paths:
--------------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/readfis.m

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m	2011-06-22 01:50:32 UTC (rev 8342)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m	2011-06-22 01:51:28 UTC (rev 8343)
@@ -96,7 +96,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy membership-function membership
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      addmf.m
-## Last-Modified: 8 Jun 2011
+## Last-Modified: 20 Jun 2011
 
 function fis = addmf (fis, in_or_out, var_index, mf_name, mf_type, mf_params)
 
@@ -128,9 +128,17 @@
 
   new_mf = struct ('name', mf_name, 'type', mf_type, 'params', mf_params);
   if (strcmp (tolower (in_or_out), 'input'))
-    fis.input(var_index).mf = [fis.input(var_index).mf, new_mf];
+    if (length (fis.input(var_index).mf) == 0)
+      fis.input(var_index).mf = new_mf;
+    else
+      fis.input(var_index).mf = [fis.input(var_index).mf, new_mf];
+    endif
   else
-    fis.output(var_index).mf = [fis.output(var_index).mf, new_mf];
+    if (length (fis.output(var_index).mf) == 0)
+      fis.output(var_index).mf = new_mf;
+    else
+      fis.output(var_index).mf = [fis.output(var_index).mf, new_mf];
+    endif
   endif
 
 endfunction

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m	2011-06-22 01:50:32 UTC (rev 8342)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m	2011-06-22 01:51:28 UTC (rev 8343)
@@ -69,7 +69,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy rule
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      addrule.m
-## Last-Modified: 19 May 2011
+## Last-Modified: 21 Jun 2011
 
 function fis = addrule (fis, rule_matrix) 
 
@@ -104,6 +104,10 @@
                            'connection', connection);
   endfor
 
-  fis.rule = [fis.rule, new_rules];
+  if (length (fis.rule) == 0)
+    fis.rule = new_rules;
+  else
+    fis.rule = [fis.rule, new_rules];
+  endif
 
 endfunction

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m	2011-06-22 01:50:32 UTC (rev 8342)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m	2011-06-22 01:51:28 UTC (rev 8343)
@@ -61,7 +61,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy variable
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      addvar.m
-## Last-Modified: 8 Jun 2011
+## Last-Modified: 20 Jun 2011
 
 function fis = addvar (fis, in_or_out, var_name, var_range)
 
@@ -91,9 +91,17 @@
 
   new_variable = struct ('name', var_name, 'range', var_range, 'mf', []);
   if (strcmp (tolower (in_or_out), 'input'))
-    fis.input = [fis.input, new_variable];
+    if (length (fis.input) == 0)
+      fis.input = new_variable;
+    else
+      fis.input = [fis.input, new_variable];
+    endif
   else
-    fis.output = [fis.output, new_variable];
+    if (length (fis.output) == 0)
+      fis.output = new_variable;
+    else
+      fis.output = [fis.output, new_variable];
+    endif
   endif
 
 endfunction

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m	2011-06-22 01:50:32 UTC (rev 8342)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m	2011-06-22 01:51:28 UTC (rev 8343)
@@ -22,9 +22,9 @@
 ##
 ## For a given domain @var{x} and parameters @var{params} (or @var{[sig c]}),
 ## return the corresponding @var{y} values for the Gaussian membership
-## function, a curve shaped like the Gaussian (normal) distribution, but scaled
-## to have a maximum value of 1. By contrast, the area under the Gaussian
-## distribution curve is 1.
+## function. This membership function is shaped like the Gaussian (normal)
+## distribution, but scaled to have a maximum value of 1. By contrast, the 
+## area under the Gaussian distribution curve is 1.
 ##
 ## The argument @var{x} must be a real number or a non-empty vector of strictly
 ## increasing real numbers, and @var{sig} and @var{c} must be real numbers.
@@ -64,7 +64,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy membership-function gaussian
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gaussmf.m
-## Last-Modified: 7 Jun 2011
+## Last-Modified: 20 Jun 2011
 
 function y = gaussmf (x, params)
 
@@ -102,12 +102,13 @@
 %! params = [2 0];
 %! y3 = gaussmf(x, params);
 %! figure('NumberTitle', 'off', 'Name', 'gaussmf demo');
-%! plot(x, y1, 'r;params = [0.5 0];');
+%! plot(x, y1, 'r;params = [0.5 0];', 'LineWidth', 2);
 %! hold on ;
-%! plot(x, y2, 'b;params = [1 0];');
+%! plot(x, y2, 'b;params = [1 0];', 'LineWidth', 2);
 %! hold on ;
-%! plot(x, y3, 'g;params = [2 0];');
+%! plot(x, y3, 'g;params = [2 0];', 'LineWidth', 2);
 %! ylim([-0.1 1.1]);
 %! xlabel('Crisp Input Value');
 %! ylabel('Degree of Membership');
+%! grid;
 %! hold;

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m	2011-06-22 01:50:32 UTC (rev 8342)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m	2011-06-22 01:51:28 UTC (rev 8343)
@@ -93,7 +93,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy fuzzy-inference-system fis
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      getfis.m
-## Last-Modified: 19 May 2011
+## Last-Modified: 21 Jun 2011
 
 ##------------------------------------------------------------------------------
 
@@ -196,56 +196,92 @@
     case 'numinputmfs'
       retval = [];
       for i = 1 : columns (fis.input)
-        retval = [retval columns(fis.input(i).mf)];
+        if (i == 1)
+          retval = columns(fis.input(i).mf);
+        else
+          retval = [retval columns(fis.input(i).mf)];
+        endif
       endfor
 
     case 'numoutputmfs'
       retval = [];
       for i = 1 : columns (fis.output)
-        retval = [retval columns(fis.output(i).mf)];
+        if (i == 1)
+          retval = columns(fis.output(i).mf);
+        else
+          retval = [retval columns(fis.output(i).mf)];
+        endif
       endfor
 
     case 'inlabels'
       retval = [];
       for i = 1 : columns (fis.input)
-        retval = [retval; fis.input(i).name];
+        if (i == 1)
+          retval = fis.input(i).name;
+        else
+          retval = [retval; fis.input(i).name];
+        endif
       endfor
 
     case 'outlabels'
       retval = [];
       for i = 1 : columns (fis.output)
-        retval = [retval; fis.output(i).name];
+        if (i == 1)
+          retval = fis.output(i).name;
+        else
+          retval = [retval; fis.output(i).name];
+        endif
       endfor
 
     case 'inrange'
       retval = [];
       for i = 1 : columns (fis.input)
-        retval = [retval; fis.input(i).range];
+        if (i == 1)
+          retval = fis.input(i).range;
+        else
+          retval = [retval; fis.input(i).range];
+        endif
       endfor
 
     case 'outrange'
       retval = [];
       for i = 1 : columns (fis.output)
-        retval = [retval; fis.output(i).range];
+        if (i == 1)
+          retval = fis.output(i).range;
+        else
+          retval = [retval; fis.output(i).range];
+        endif
       endfor
 
     case 'inmfs'
       retval = [];
       for i = 1 : columns (fis.input)
-        retval = [retval columns(fis.input(i).mf)];
+        if (i == 1)
+          retval = columns(fis.input(i).mf);
+        else
+          retval = [retval columns(fis.input(i).mf)];
+        endif
       endfor
 
     case 'outmfs'
       retval = [];
       for i = 1 : columns (fis.output)
-        retval = [retval columns(fis.output(i).mf)];
+        if (i == 1)
+          retval = columns(fis.output(i).mf);
+        else
+          retval = [retval columns(fis.output(i).mf)];
+        endif
       endfor
 
     case 'inmflabels'
       retval = [];
       for i = 1 : columns (fis.input)
         for j = 1 : columns (fis.input(i).mf)
-          retval = [retval; fis.input(i).mf(j).name];
+          if (i == 1 && y == 1)
+            retval = fis.input(i).mf(j).name;
+          else
+            retval = [retval; fis.input(i).mf(j).name];
+          endif
         endfor
       endfor
 
@@ -253,7 +289,11 @@
       retval = [];
       for i = 1 : columns (fis.output)
         for j = 1 : columns (fis.output(i).mf)
-          retval = [retval; fis.output(i).mf(j).name];
+          if (i == 1 && y == 1)
+            retval = fis.output(i).mf(j).name;
+          else
+            retval = [retval; fis.output(i).mf(j).name];
+          endif
         endfor
       endfor
 
@@ -261,7 +301,11 @@
       retval = [];
       for i = 1 : columns (fis.input)
         for j = 1 : columns (fis.input(i).mf)
-          retval = [retval; fis.input(i).mf(j).type];
+          if (i == 1 && y == 1)
+            retval = fis.input(i).mf(j).type;
+          else
+            retval = [retval; fis.input(i).mf(j).type];
+          endif
         endfor
       endfor
 
@@ -269,7 +313,11 @@
       retval = [];
       for i = 1 : columns (fis.output)
         for j = 1 : columns (fis.output(i).mf)
-          retval = [retval; fis.output(i).mf(j).type];
+          if (i == 1 && y == 1)
+            retval = fis.output(i).mf(j).type;
+          else
+            retval = [retval; fis.output(i).mf(j).type];
+          endif
         endfor
       endfor
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/readfis.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/readfis.m	2011-06-22 01:50:32 UTC (rev 8342)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/readfis.m	2011-06-22 01:51:28 UTC (rev 8343)
@@ -66,7 +66,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy fuzzy-inference-system fis
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      readfis.m
-## Last-Modified: 7 Jun 2011
+## Last-Modified: 20 Jun 2011
 
 ##------------------------------------------------------------------------------
 
@@ -108,7 +108,11 @@
   for i = 1 : num_inputs
     [next_fis_input, num_mfs, line_num] = ...
       get_next_fis_io (fid, line_num, i, 'input');
-    fis.input = [fis.input, next_fis_input];
+    if (i == 1)
+      fis.input = next_fis_input;
+    else
+      fis.input = [fis.input, next_fis_input];
+    endif
 
     ##----------------------------------------------------------------------
     ## Read membership function info for the new FIS input from file.
@@ -117,7 +121,11 @@
 
     for j = 1 : num_mfs
       [next_mf, line_num] = get_next_mf (fid, line_num, i, j, 'input');
-      fis.input(i).mf = [fis.input(i).mf, next_mf];
+      if (j == 1)
+        fis.input(i).mf = next_mf;
+      else
+        fis.input(i).mf = [fis.input(i).mf, next_mf];
+      endif
     endfor
   endfor
 
@@ -129,7 +137,11 @@
   for i = 1 : num_outputs
     [next_fis_output, num_mfs, line_num] = ...
       get_next_fis_io (fid, line_num, i, 'output');
-    fis.output = [fis.output, next_fis_output];
+    if (i == 1)
+      fis.output = next_fis_output;
+    else
+      fis.output = [fis.output, next_fis_output];
+    endif
 
     ##----------------------------------------------------------------------
     ## Read membership function info for the new FIS output from file.
@@ -138,7 +150,11 @@
 
     for j = 1 : num_mfs
       [next_mf, line_num] = get_next_mf (fid, line_num, i, j, 'output');
-      fis.output(i).mf = [fis.output(i).mf, next_mf];
+      if (j == 1)
+        fis.output(i).mf = next_mf;
+      else
+        fis.output(i).mf = [fis.output(i).mf, next_mf];
+      endif
     endfor
   endfor
 
@@ -152,7 +168,11 @@
   for i = 1 : num_rules
     [next_rule, line_num] = ...
       get_next_rule (fid, line_num, num_inputs, num_outputs);
-    fis.rule = [fis.rule, next_rule];
+    if (i == 1)
+      fis.rule = next_rule;
+    else
+      fis.rule = [fis.rule, next_rule];
+    endif
   endfor
 endfunction
 


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[Octave-cvsupdate] SF.net SVN: octave:[9082] trunk/octave-forge/main/fuzzy-logic-toolkit/inst

[<lm...@us...>]

Revision: 9082
          http://octave.svn.sourceforge.net/octave/?rev=9082&view=rev
Author:   lmarkov
Date:     2011-11-13 18:37:05 +0000 (Sun, 13 Nov 2011)
Log Message:
-----------

A    inst/heart_disease_demo_1.m
M    inst/smf.m
A    inst/heart_disease_demo_2.m
M    inst/mamdani_tip_demo.m
M    inst/gauss2mf.m
M    inst/writefis.m
M    inst/zmf.m
M    inst/addvar.m
M    inst/showrule.m
M    inst/gbellmf.m
A    inst/hamacher_product.m
A    inst/algebraic_product.m
M    inst/dsigmf.m
M    inst/gensurf.m
A    inst/einstein_product.m
M    inst/sugeno_tip_demo.m
M    inst/getfis.m
M    inst/trimf.m
M    inst/showfis.m
M    inst/cubic_approx_demo.m
M    inst/psigmf.m
D    inst/heart_demo_1.m
D    inst/heart_demo_2.m
A    inst/drastic_product.m
M    inst/evalfis.m
M    inst/trapmf.m
A    inst/bounded_difference.m
M    inst/linear_tip_demo.m
M    inst/newfis.m
M    inst/pimf.m
A    inst/hamacher_sum.m
A    inst/algebraic_sum.m
A    inst/investment_portfolio_demo.m
M    inst/plotmf.m
A    inst/einstein_sum.m
A    inst/bounded_sum.m
M    inst/sigmf.m
M    inst/gaussmf.m
M    inst/evalmf.m
M    inst/sugeno_tip_calculator.fis
M    inst/addmf.m
M    inst/readfis.m
A    inst/drastic_sum.m
A    inst/investment_portfolio.fis
M    inst/cubic_approximator.fis
M    inst/addrule.m

Modified Paths:
--------------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approximator.fis
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/dsigmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gauss2mf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gbellmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gensurf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/mamdani_tip_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/newfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/pimf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/plotmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/psigmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/readfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/showfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/showrule.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sigmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/smf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_calculator.fis
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/trapmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/trimf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/writefis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/zmf.m

Added Paths:
-----------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_difference.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/investment_portfolio.fis
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/investment_portfolio_demo.m

Removed Paths:
-------------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_demo_2.m

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -51,10 +51,9 @@
 ## them for FIS inputs or Mamdani-type FIS outputs has not yet been tested.
 ##
 ## @noindent
-## To run the demonstration code below, type @t{demo('addmf')} at the
-## Octave prompt. This demo creates two FIS input variables and associated
-## membership functions and then produces two figures showing the term
-## sets for the two FIS inputs.
+## To run the demonstration code, type @t{demo('addmf')} at the Octave prompt.
+## This demo creates two FIS input variables and associated membership functions
+## and then produces two figures showing the term sets for the two FIS inputs.
 ##
 ## @seealso{rmmf, setfis}
 ## @end deftypefn
@@ -65,7 +64,7 @@
 ## Filename:      addmf.m
 ## Note:          The demo code is based on an assignment written by
 ##                Dr. Bruce Segee (University of Maine Dept. of ECE).
-## Last-Modified: 30 Aug 2011
+## Last-Modified: 28 Oct 2011
 
 function fis = addmf (fis, in_or_out, var_index, mf_name, mf_type, mf_params)
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -41,35 +41,50 @@
 ## connect == antecedent connective (1 == and; 2 == or)
 ## @end itemize
 ##
-## To express the hedge "not", prepend a minus sign to the membership function
-## index. ("Not" is the only hedge supported.) To omit an input or output, use
-## 0 for the membership function index. The consequent connective is always
-## "and".
+## To express:
+## @itemize @w
+## @item
+## "not" -- prepend a minus sign to the membership function index
+## @item
+## "somewhat" -- append ".05" to the membership function index
+## @item
+## "very" -- append ".20" to the membership function index
+## @item
+## "extremely" -- append ".30" to the membership function index
+## @item
+## "very very" -- append ".40" to the membership function index
+## @item
+## custom hedge -- append .xy, where x.y is the degree to which the membership
+##   value should be raised, to the membership function index
+## @end itemize
 ##
+## To omit an input or output, use 0 for the membership function index.
+## The consequent connective is always "and".
+##
 ## @noindent
 ## For example, to express:
 ## @example
-## "If input_1 is mf_2 or input_3 is not mf_1,
-##  then output_2 is mf_1."
+## "If (input_1 is mf_2) or (input_3 is not mf_1) or (input_4 is very mf_1),
+##  then (output_1 is mf_2) and (output_2 is mf_1^0.3)."
 ## @end example
 ##
 ## @noindent
 ## with weight 1, the corresponding row of @var{rule_matrix} would be:
 ## @example
-## [2  0  -1  0  1  1  2]
+## [2   0   -1   4.2   2   1.03   1   2]
 ## @end example
 ##
 ## @noindent
-## For a complete example that uses addrule, see heart_demo_1.m.
+## For a complete example that uses addrule, see heart_disease_demo_1.m.
 ##
-## @seealso{heart_demo_1, showrule}
+## @seealso{heart_disease_demo_1, showrule}
 ## @end deftypefn
 
 ## Author:        L. Markowsky
 ## Keywords:      fuzzy-logic-toolkit fuzzy rule
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      addrule.m
-## Last-Modified: 16 Jul 2011
+## Last-Modified: 11 Nov 2011
 
 function fis = addrule (fis, rule_matrix) 
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -38,8 +38,7 @@
 ## specify the lower and upper bounds of the variable's domain.
 ##
 ## @noindent
-## To run the demonstration code below, type @t{demo('addvar')} at the
-## Octave prompt.
+## To run the demonstration code, type @t{demo('addvar')} at the Octave prompt.
 ##
 ## @end deftypefn
 
@@ -47,7 +46,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy variable
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      addvar.m
-## Last-Modified: 30 Aug 2011
+## Last-Modified: 28 Oct 2011
 
 function fis = addvar (fis, in_or_out, var_name, var_range)
 

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_product.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_product.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,56 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} algebraic_product (@var{x})
+## @deftypefnx {Function File} {@var{retval} =} algebraic_product (@var{x}, @var{y})
+##
+## Return the algebraic product of the input.
+## The algebraic product of two real scalars x and y is: x * y
+##
+## For one vector argument, apply the algebraic product to all of elements of
+## the vector. (The algebraic product is associative.) For one two-dimensional
+## matrix argument, return a vector of the algebraic product of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise product.
+##
+## @seealso{algebraic_sum, bounded_difference, bounded_sum, drastic_product, drastic_sum, einstein_product, einstein_sum, hamacher_product, hamacher_sum}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy algebraic_product
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      algebraic_product.m
+## Last-Modified: 12 Nov 2011
+
+function retval = algebraic_product (x, y = 0)
+  if (!(isreal (x) && isreal (y)))
+    puts ("Type 'help algebraic_product' for more information.\n");
+    error ("algebraic_product requires real scalar or matrix arguments\n");
+  elseif (nargin == 2 && ...
+          (isscalar (x) || isscalar (y) || isequal (size (x), size (y))))
+    retval = x .* y;
+  elseif (nargin == 1 && ndims (x) <= 2)
+    retval = prod (x);
+  else
+    puts ("Type 'help algebraic_product' for more information.\n");
+    error ("invalid arguments to function algebraic_product\n");
+  endif
+endfunction
+

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_sum.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_sum.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,71 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} algebraic_sum (@var{x, y})
+## @deftypefnx {Function File} {@var{retval} =} algebraic_sum (@var{x, y})
+##
+## Return the algebraic sum of the input.
+## The algebraic sum of two real scalars x and y is: x + y - x * y
+##
+## For one vector argument, apply the algebraic sum to all of elements of
+## the vector. (The algebraic sum is associative.) For one two-dimensional
+## matrix argument, return a vector of the algebraic sum of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise algebraic sum.
+##
+## @seealso{algebraic_product, bounded_difference, bounded_sum, drastic_product, drastic_sum, einstein_product, einstein_sum, hamacher_product, hamacher_sum}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy algebraic_sum
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      algebraic_sum.m
+## Last-Modified: 12 Nov 2011
+
+function retval = algebraic_sum (x, y = 0)
+  if (!(isreal (x) && isreal (y)))
+    puts ("Type 'help algebraic_sum' for more information.\n");
+    error ("algebraic_sum requires real scalar or matrix arguments\n");
+  elseif (nargin == 2 && ...
+          (isscalar (x) || isscalar (y) || isequal (size (x), size (y))))
+    retval = x .+ y .- x .* y;
+  elseif (nargin == 1 && isvector (x))
+    retval = algebraic_sum_of_vector (x);
+  elseif (nargin == 1 && ndims (x) == 2)
+    num_cols = columns (x);
+    retval = zeros (1, num_cols);
+    for i = 1 : num_cols
+      retval(i) = algebraic_sum_of_vector (x(:, i));
+    endfor
+  else
+    puts ("Type 'help algebraic_sum' for more information.\n");
+    error ("invalid arguments to function algebraic_sum\n");
+  endif
+endfunction
+
+function retval = algebraic_sum_of_vector (real_vector)
+  x = 0;
+  for i = 1 : length (real_vector)
+    y = real_vector(i);
+    x = x + y - x * y;
+  endfor
+  retval = x;
+endfunction
+

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_difference.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_difference.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_difference.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,72 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} bounded_difference (@var{x})
+## @deftypefnx {Function File} {@var{retval} =} bounded_difference (@var{x}, @var{y})
+##
+## Return the bounded difference of the input.
+## The bounded difference of two real scalars x and y is: max (0, x + y - 1)
+##
+## For one vector argument, apply the bounded difference to all of the elements
+## of the vector. (The bounded difference is associative.) For one
+## two-dimensional matrix argument, return a vector of the bounded difference
+## of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise bounded difference.
+##
+## @seealso{algebraic_product, algebraic_sum, bounded_sum, drastic_product, drastic_sum, einstein_product, einstein_sum, hamacher_product, hamacher_sum}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy bounded_difference
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      bounded_difference.m
+## Last-Modified: 12 Nov 2011
+
+function retval = bounded_difference (x, y = 0)
+  if (!(isreal (x) && isreal (y)))
+    puts ("Type 'help bounded_difference' for more information.\n");
+    error ("bounded_difference requires real scalar or matrix arguments\n");
+  elseif (nargin == 2 && ...
+          (isscalar (x) || isscalar (y) || isequal (size (x), size (y))))
+    retval = max (0, (x .+ y - 1));
+  elseif (nargin == 1 && isvector (x))
+    retval = bounded_difference_of_vector (x);
+  elseif (nargin == 1 && ndims (x) == 2)
+    num_cols = columns (x);
+    retval = zeros (1, num_cols);
+    for i = 1 : num_cols
+      retval(i) = bounded_difference_of_vector (x(:, i));
+    endfor
+  else
+    puts ("Type 'help bounded_difference' for more information.\n");
+    error ("invalid arguments to function bounded_difference\n");
+  endif
+endfunction
+
+function retval = bounded_difference_of_vector (real_vector)
+  x = 1;
+  for i = 1 : length (real_vector)
+    y = real_vector(i);
+    x = max (0, (x + y - 1));
+  endfor
+  retval = x;
+endfunction
+

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_sum.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_sum.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,71 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} bounded_sum (@var{x})
+## @deftypefnx {Function File} {@var{retval} =} bounded_sum (@var{x}, @var{y})
+##
+## Return the bounded sum of the input.
+## The bounded sum of two real scalars x and y is: min (1, x + y)
+##
+## For one vector argument, apply the bounded sum to all of elements of
+## the vector. (The bounded sum is associative.) For one two-dimensional
+## matrix argument, return a vector of the bounded sum of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise bounded sum.
+##
+## @seealso{algebraic_product, algebraic_sum, bounded_difference, drastic_product, drastic_sum, einstein_product, einstein_sum, hamacher_product, hamacher_sum}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy bounded_sum
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      bounded_sum.m
+## Last-Modified: 12 Nov 2011
+
+function retval = bounded_sum (x, y = 0)
+  if (!(isreal (x) && isreal (y)))
+    puts ("Type 'help bounded_sum' for more information.\n");
+    error ("bounded_sum requires real scalar or matrix arguments\n");
+  elseif (nargin == 2 && ...
+          (isscalar (x) || isscalar (y) || isequal (size (x), size (y))))
+    retval = min (1, (x .+ y));
+  elseif (nargin == 1 && isvector (x))
+    retval = bounded_sum_of_vector (x);
+  elseif (nargin == 1 && ndims (x) == 2)
+    num_cols = columns (x);
+    retval = zeros (1, num_cols);
+    for i = 1 : num_cols
+      retval(i) = bounded_sum_of_vector (x(:, i));
+    endfor
+  else
+    puts ("Type 'help bounded_sum' for more information.\n");
+    error ("invalid arguments to function bounded_sum\n");
+  endif
+endfunction
+
+function retval = bounded_sum_of_vector (real_vector)
+  x = 0;
+  for i = 1 : length (real_vector)
+    y = real_vector(i);
+    x = min (1, (x + y));
+  endfor
+  retval = x;
+endfunction
+

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -20,8 +20,7 @@
 ## @deftypefn {Script File} {} cubic_approx_demo
 ##
 ## Demonstrate the use of the Octave Fuzzy Logic Toolkit to approximate a
-## non-linear function using a Sugeno-type FIS with linear output membership
-## functions.
+## non-linear function using a Sugeno-type FIS with linear output functions.
 ##
 ## The demo:
 ## @itemize @minus
@@ -30,23 +29,26 @@
 ## @item
 ## plots the input membership functions
 ## @item
-## plots the output as a function of the input
+## plots the (linear) output functions
+## @item
+## plots the FIS output as a function of the input
 ## @end itemize
 ##
-## @seealso{heart_demo_1, heart_demo_2, linear_tip_demo, mamdani_tip_demo, sugeno_tip_demo}
+## @seealso{heart_disease_demo_1, heart_disease_demo_2, investment_portfolio_demo, linear_tip_demo, mamdani_tip_demo, sugeno_tip_demo}
 ## @end deftypefn
 
 ## Author:        L. Markowsky
 ## Keywords:      fuzzy-logic-toolkit fuzzy tests demos
 ## Directory:     fuzzy-logic-toolkit/inst
 ## Filename:      cubic_approx_demo.m
-## Last-Modified: 27 Aug 2011
+## Last-Modified: 12 Nov 2011
 
 ## Read the FIS structure from a file.
 fis = readfis ('cubic_approximator.fis');
 
-## Plot the input membership functions.
+## Plot the input membership functions and linear output functions.
 plotmf (fis, 'input', 1);
+plotmf (fis, 'output', 1, -150, 150);
 
-## Plot the output y as a function of the input x.
+## Plot the FIS output y as a function of the input x.
 gensurf (fis);

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approximator.fis
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approximator.fis	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approximator.fis	2011-11-13 18:37:05 UTC (rev 9082)
@@ -29,7 +29,7 @@
 
 [Output1]
 Name='Approx-X-Cubed'
-Range=[-130 130]
+Range=[-5 5]
 NumMFs=11
 MF1 = 'Tangent-at-Neg-Five':'linear', [75 250]
 MF2 = 'Tangent-at-Neg-Four':'linear', [48 128]

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,107 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} drastic_product (@var{x})
+## @deftypefnx {Function File} {@var{retval} =} drastic_product (@var{x}, @var{y})
+##
+## Return the drastic product of the input.
+## The drastic product of two real scalars x and y is:
+## @example
+## @group
+## min (x, y)     if max (x, y) == 1
+## 0              otherwise
+## @end group
+## @end example
+##
+## For one vector argument, apply the drastic product to all of the elements
+## of the vector. (The drastic product is associative.) For one
+## two-dimensional matrix argument, return a vector of the drastic product
+## of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise drastic product.
+##
+## @seealso{algebraic_product, algebraic_sum, bounded_difference, bounded_sum, drastic_sum, einstein_product, einstein_sum, hamacher_product, hamacher_sum}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy drastic_product
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      drastic_product.m
+## Last-Modified: 12 Nov 2011
+
+function retval = drastic_product (x, y = 0)
+  if (nargin == 0 || nargin > 2 ||
+      !is_real_matrix (x) || !is_real_matrix (y))
+    argument_error
+
+  elseif (nargin == 1)
+    if (isvector (x))
+      retval = vector_arg (x);
+    elseif (ndims (x) == 2)
+      retval = matrix_arg (x);
+    else
+      argument_error;
+    endif
+
+  elseif (nargin == 2)
+    if (isequal (size (x), size (y)))
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (isscalar (x) && ismatrix (y))
+      x = x * ones (size (y));
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (ismatrix (x) && isscalar (y))
+      y = y * ones (size (x));
+      retval = arrayfun (@scalar_args, x, y);
+    else
+      argument_error;
+    endif
+  endif
+endfunction
+
+function retval = scalar_args (x, y)
+  if (max (x, y) == 1)
+    retval = min (x, y);
+  else
+    retval = 0;
+  endif
+endfunction
+
+function retval = vector_arg (x)
+  if (isempty (x))
+    retval = 1;
+  elseif (max (x) == 1)
+    retval = min (x);
+  else
+    retval = 0;
+  endif
+endfunction
+
+function retval = matrix_arg (x)
+  num_cols = columns (x);
+  retval = zeros (1, num_cols);
+  for i = 1 : num_cols
+    retval(i) = vector_arg (x(:, i));
+  endfor
+endfunction
+
+function argument_error
+  puts ("Type 'help drastic_product' for more information.\n");
+  error ("invalid arguments to function drastic_product\n");
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,107 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} drastic_sum (@var{x})
+## @deftypefnx {Function File} {@var{retval} =} drastic_sum (@var{x}, @var{y})
+##
+## Return the drastic sum of the input.
+## The drastic sum of two real scalars x and y is:
+## @example
+## @group
+## max (x, y)     if min (x, y) == 0
+## 1              otherwise
+## @end group
+## @end example
+##
+## For one vector argument, apply the drastic sum to all of the elements
+## of the vector. (The drastic sum is associative.) For one
+## two-dimensional matrix argument, return a vector of the drastic sum
+## of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise drastic sum.
+##
+## @seealso{algebraic_product, algebraic_sum, bounded_difference, bounded_sum, drastic_product, einstein_product, einstein_sum, hamacher_product, hamacher_sum}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy drastic_sum
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      drastic_sum.m
+## Last-Modified: 12 Nov 2011
+
+function retval = drastic_sum  (x, y = 0)
+  if (nargin == 0 || nargin > 2 ||
+      !is_real_matrix (x) || !is_real_matrix (y))
+    argument_error
+
+  elseif (nargin == 1)
+    if (isvector (x))
+      retval = vector_arg (x);
+    elseif (ndims (x) == 2)
+      retval = matrix_arg (x);
+    else
+      argument_error;
+    endif
+
+  elseif (nargin == 2)
+    if (isequal (size (x), size (y)))
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (isscalar (x) && ismatrix (y))
+      x = x * ones (size (y));
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (ismatrix (x) && isscalar (y))
+      y = y * ones (size (x));
+      retval = arrayfun (@scalar_args, x, y);
+    else
+      argument_error;
+    endif
+  endif
+endfunction
+
+function retval = scalar_args (x, y)
+  if (min (x, y) == 0)
+    retval = max (x, y);
+  else
+    retval = 1;
+  endif
+endfunction
+
+function retval = vector_arg (x)
+  if (isempty (x))
+    retval = 0;
+  elseif (min (x) == 0)
+    retval = max (x);
+  else
+    retval = 1;
+  endif
+endfunction
+
+function retval = matrix_arg (x)
+  num_cols = columns (x);
+  retval = zeros (1, num_cols);
+  for i = 1 : num_cols
+    retval(i) = vector_arg (x(:, i));
+  endfor
+endfunction
+
+function argument_error
+  puts ("Type 'help drastic_sum' for more information.\n");
+  error ("invalid arguments to function drastic_sum\n");
+endfunction

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/dsigmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/dsigmf.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/dsigmf.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -59,8 +59,7 @@
 ## Here, the symbol ~ means "approximately equal".
 ##
 ## @noindent
-## To run the demonstration code below, type @t{demo('dsigmf')} at the
-## Octave prompt.
+## To run the demonstration code, type @t{demo('dsigmf')} at the Octave prompt.
 ##
 ## @seealso{gauss2mf, gaussmf, gbellmf, pimf, psigmf, sigmf, smf, trapmf, trimf, zmf}
 ## @end deftypefn
@@ -69,7 +68,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy membership-function sigmoidal
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      dsigmf.m
-## Last-Modified: 7 Jun 2011
+## Last-Modified: 28 Oct 2011
 
 function y = dsigmf (x, params)
 

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,97 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} einstein_product (@var{x})
+## @deftypefnx {Function File} {@var{retval} =} einstein_product (@var{x}, @var{y})
+##
+## Return the Einstein product of the input.
+## The Einstein product of two real scalars x and y is:
+## (x * y) / (2 - (x + y - x * y))
+##
+## For one vector argument, apply the Einstein product to all of the elements
+## of the vector. (The Einstein product is associative.) For one
+## two-dimensional matrix argument, return a vector of the Einstein product
+## of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise Einstein product.
+##
+## @seealso{algebraic_product, algebraic_sum, bounded_difference, bounded_sum, drastic_product, drastic_sum, einstein_sum, hamacher_product, hamacher_sum}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy einstein_product
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      einstein_product.m
+## Last-Modified: 12 Nov 2011
+
+function retval = einstein_product (x, y = 0)
+  if (nargin == 0 || nargin > 2 ||
+      !is_real_matrix (x) || !is_real_matrix (y))
+    argument_error
+
+  elseif (nargin == 1)
+    if (isvector (x))
+      retval = vector_arg (x);
+    elseif (ndims (x) == 2)
+      retval = matrix_arg (x);
+    else
+      argument_error;
+    endif
+
+  elseif (nargin == 2)
+    if (isequal (size (x), size (y)))
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (isscalar (x) && ismatrix (y))
+      x = x * ones (size (y));
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (ismatrix (x) && isscalar (y))
+      y = y * ones (size (x));
+      retval = arrayfun (@scalar_args, x, y);
+    else
+      argument_error;
+    endif
+  endif
+endfunction
+
+function retval = scalar_args (x, y)
+  retval = (x * y) / (2 - (x + y - x * y));
+endfunction
+
+function retval = vector_arg (real_vector)
+  x = 1;
+  for i = 1 : length (real_vector)
+    y = real_vector(i);
+    x = (x * y) / (2 - (x + y - x * y));
+  endfor
+  retval = x;
+endfunction
+
+function retval = matrix_arg (x)
+  num_cols = columns (x);
+  retval = zeros (1, num_cols);
+  for i = 1 : num_cols
+    retval(i) = vector_arg (x(:, i));
+  endfor
+endfunction
+
+function argument_error
+  puts ("Type 'help einstein_product' for more information.\n");
+  error ("invalid arguments to function einstein_product\n");
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,96 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} einstein_sum (@var{x})
+## @deftypefnx {Function File} {@var{retval} =} einstein_sum (@var{x}, @var{y})
+##
+## Return the Einstein sum of the input.
+## The Einstein sum of two real scalars x and y is: (x + y) / (1 + x * y)
+##
+## For one vector argument, apply the Einstein sum to all of the elements
+## of the vector. (The Einstein sum is associative.) For one
+## two-dimensional matrix argument, return a vector of the Einstein sum
+## of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise Einstein sum.
+##
+## @seealso{algebraic_product, algebraic_sum, bounded_difference, bounded_sum, drastic_product, drastic_sum, einstein_product, hamacher_product, hamacher_sum}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy einstein_sum
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      einstein_sum.m
+## Last-Modified: 12 Nov 2011
+
+function retval = einstein_sum (x, y = 0)
+  if (nargin == 0 || nargin > 2 ||
+      !is_real_matrix (x) || !is_real_matrix (y))
+    argument_error
+
+  elseif (nargin == 1)
+    if (isvector (x))
+      retval = vector_arg (x);
+    elseif (ndims (x) == 2)
+      retval = matrix_arg (x);
+    else
+      argument_error;
+    endif
+
+  elseif (nargin == 2)
+    if (isequal (size (x), size (y)))
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (isscalar (x) && ismatrix (y))
+      x = x * ones (size (y));
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (ismatrix (x) && isscalar (y))
+      y = y * ones (size (x));
+      retval = arrayfun (@scalar_args, x, y);
+    else
+      argument_error;
+    endif
+  endif
+endfunction
+
+function retval = scalar_args (x, y)
+  retval = (x + y) / (1 + x * y);
+endfunction
+
+function retval = vector_arg (real_vector)
+  x = 0;
+  for i = 1 : length (real_vector)
+    y = real_vector(i);
+    x = (x + y) / (1 + x * y);
+  endfor
+  retval = x;
+endfunction
+
+function retval = matrix_arg (x)
+  num_cols = columns (x);
+  retval = zeros (1, num_cols);
+  for i = 1 : num_cols
+    retval(i) = vector_arg (x(:, i));
+  endfor
+endfunction
+
+function argument_error
+  puts ("Type 'help einstein_sum' for more information.\n");
+  error ("invalid arguments to function einstein_sum\n");
+endfunction

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalfis.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalfis.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalfis.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -90,7 +90,45 @@
 ## @end example
 ##
 ## @noindent
+## Evaluation of hedges and "not":
 ##
+## Each element of each FIS rule antecedent and consequent indicates the
+## corresponding membership function, hedge, and whether or not "not" should
+## be applied to the result. The index of the membership function to be used is
+## given by the positive whole number portion of the antecedent/consequent
+## vector entry, the hedge is given by the fractional portion (if any), and
+## "not" is indicated by a minus sign. A "0" as the integer portion in any
+## position in the rule indicates that the corresponding FIS input or output
+## variable is omitted from the rule.
+##
+## For custom hedges and the four built-in hedges "somewhat," "very,"
+## "extremely," and "very very," the membership function value (without the
+## hedge or "not") is raised to the power corresponding to the hedge. All
+## hedges are rounded to 2 digits.
+##
+## For example, if "mu(x)" denotes the matching degree of the input to the
+## corresponding membership function without a hedge or "not," then the final
+## matching degree recorded in @var{rule_input} will be computed by applying
+## the hedge and "not" in two steps. First, the hedge is applied:
+##
+## @example
+## @group
+## (fraction == .05) <=>  somewhat x       <=>  mu(x)^0.5  <=>  sqrt(mu(x))
+## (fraction == .20) <=>  very x           <=>  mu(x)^2    <=>  sqr(mu(x))
+## (fraction == .30) <=>  extremely x      <=>  mu(x)^3    <=>  cube(mu(x))
+## (fraction == .40) <=>  very very x      <=>  mu(x)^4
+## (fraction == .dd) <=>  <custom hedge> x <=>  mu(x)^(dd/10)
+## @end group
+## @end example
+##
+## After applying the appropriate hedge, "not" is calculated by:
+## @example
+## minus sign present           <=> not x         <=> 1 - mu(x)
+## minus sign and hedge present <=> not <hedge> x <=> 1 - mu(x)^(dd/10)
+## @end example
+##
+## Hedges and "not" in the consequent are handled similarly.
+##
 ## @noindent
 ## The intermediate result @var{rule_output}:
 ##
@@ -172,15 +210,17 @@
 ## @noindent
 ## Examples:
 ##
-## Six examples of using evalfis are shown in:
+## Seven examples of using evalfis are shown in:
 ## @itemize @bullet
 ## @item
 ## cubic_approx_demo.m
 ## @item
-## heart_demo_1.m
+## heart_disease_demo_1.m
 ## @item
-## heart_demo_2.m
+## heart_disease_demo_2.m
 ## @item
+## investment_portfolio_demo.m
+## @item
 ## linear_tip_demo.m
 ## @item
 ## mamdani_tip_demo.m
@@ -188,17 +228,17 @@
 ## sugeno_tip_demo.m
 ## @end itemize
 ##
-## @seealso{cubic_approx_demo, heart_demo_1, heart_demo_2, linear_tip_demo, mamdani_tip_demo, sugeno_tip_demo}
+## @seealso{cubic_approx_demo, heart_disease_demo_1, heart_disease_demo_2, investment_portfolio_demo, linear_tip_demo, mamdani_tip_demo, sugeno_tip_demo}
 ## @end deftypefn
 
 ## Author:        L. Markowsky
 ## Keywords:      fuzzy-logic-toolkit fuzzy fuzzy-inference-system fis
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      evalfis.m
-## Last-Modified: 16 Jul 2011
+## Last-Modified: 12 Nov 2011
 
 function [output, rule_input, rule_output, fuzzy_output] = ...
-           evalfis (user_input, fis, num_points=101)
+           evalfis (user_input, fis, num_points = 101)
 
   ## If evalfis was called with an incorrect number of arguments, or the
   ## arguments do not have the correct type, print an error message and halt.

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalmf.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalmf.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -18,10 +18,15 @@
 
 ## -*- texinfo -*-
 ## @deftypefn {Function File} {@var{y} =} evalmf (@var{x}, @var{param}, @var{mf_type})
+## @deftypefnx {Function File} {@var{y} =} evalmf (@var{x}, @var{param}, @var{mf_type}, @var{hedge})
+## @deftypefnx {Function File} {@var{y} =} evalmf (@var{x}, @var{param}, @var{mf_type}, @var{hedge}, @var{not_flag})
 ## @deftypefnx {Function File} {@var{y} =} evalmf (@var{[x1 x2 ... xn]}, @var{[param1 ... ]}, @var{mf_type})
+## @deftypefnx {Function File} {@var{y} =} evalmf (@var{[x1 x2 ... xn]}, @var{[param1 ... ]}, @var{mf_type}, @var{hedge})
+## @deftypefnx {Function File} {@var{y} =} evalmf (@var{[x1 x2 ... xn]}, @var{[param1 ... ]}, @var{mf_type}, @var{hedge}, @var{not_flag})
 ##
-## For a given domain, set of parameters, and membership function type,
-## return the corresponding y-values for the membership function.
+## For a given domain, set of parameters, membership function type, and
+## optional hedge and not_flag, return the corresponding y-values for the
+## membership function.
 ##
 ## The argument @var{x} must be a real number or a non-empty list of strictly
 ## increasing real numbers, @var{param} must be a valid parameter or a vector
@@ -29,38 +34,61 @@
 ## corresponding to a membership function type. Evalmf handles both built-in and
 ## custom membership functions.
 ##
+## For custom hedges and the four built-in hedges "somewhat", "very",
+## "extremely", and "very very", raise the membership function values to
+## the power corresponding to the hedge.
+##
+## @example
+## @group
+## (fraction == .05) <=>  somewhat x       <=>  mu(x)^0.5  <=>  sqrt(mu(x))
+## (fraction == .20) <=>  very x           <=>  mu(x)^2    <=>  sqr(mu(x))
+## (fraction == .30) <=>  extremely x      <=>  mu(x)^3    <=>  cube(mu(x))
+## (fraction == .40) <=>  very very x      <=>  mu(x)^4
+## (fraction == .dd) <=>  <custom hedge> x <=>  mu(x)^(dd/10)
+## @end group
+## @end example
+##
+## The @var{not_flag} negates the membership function using:
+## @example
+## mu(not(x)) = 1 - mu(x)
+## @end example
+##
 ## @noindent
-## To run the demonstration below, type @t{demo('evalmf')} at the Octave
-## prompt.
-##
+## To run the demonstration code, type @t{demo('evalmf')} at the Octave prompt.
 ## @end deftypefn
 
 ## Author:        L. Markowsky
 ## Keywords:      fuzzy-logic-toolkit fuzzy membership-function evaluate
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      evalmf.m
-## Last-Modified: 16 Jul 2011
+## Last-Modified: 13 Nov 2011
 
-function y = evalmf (x, params, mf_type)
+function y = evalmf (x, params, mf_type, hedge = 0, not_flag = false)
 
-  ## If the caller did not supply 3 argument values with the correct types,
+  ## If the caller did not supply 3 - 5 argument values with the correct types,
   ## print an error message and halt.
 
-  if (nargin != 3)
+  if ((nargin < 3) || (nargin > 5))
     puts ("Type 'help evalmf' for more information.\n");
-    error ("evalmf requires 3 arguments\n");
+    error ("evalmf requires between 3 and 5 arguments\n");
   elseif (!is_domain (x))
     puts ("Type 'help evalmf' for more information.\n");
     error ("evalmf's first argument must be a valid domain\n");
   elseif (!is_string (mf_type))
     puts ("Type 'help evalmf' for more information.\n");
-    error ("evalmf's third argument to evalmf must be a string\n");
+    error ("evalmf's third argument must be a string\n");
+  elseif (!is_real (hedge))
+    puts ("Type 'help evalmf' for more information.\n");
+    error ("evalmf's fourth argument must be a real number\n");
+  elseif (!isbool (not_flag))
+    puts ("Type 'help evalmf' for more information.\n");
+    error ("evalmf's fifth argument must be a Boolean\n");
   endif
 
   ## Calculate and return the y values of the membership function on the
   ## domain x.
 
-  y = evalmf_private (x, params, mf_type);
+  y = evalmf_private (x, params, mf_type, hedge, not_flag);
 
 endfunction
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gauss2mf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gauss2mf.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gauss2mf.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -58,8 +58,7 @@
 ## than 1).
 ##
 ## @noindent
-## To run the demonstration code below, type @t{demo('gauss2mf')} at the
-## Octave prompt.
+## To run the demonstration code, type @t{demo('gauss2mf')} at the Octave prompt.
 ##
 ## @seealso{dsigmf, gaussmf, gbellmf, pimf, psigmf, sigmf, smf, trapmf, trimf, zmf}
 ## @end deftypefn
@@ -68,7 +67,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy membership-function gaussian
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gauss2mf.m
-## Last-Modified: 7 Jun 2011
+## Last-Modified: 28 Oct 2011
 
 function y = gauss2mf (x, params)
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -54,8 +54,7 @@
 ## @end itemize
 ##
 ## @noindent
-## To run the demonstration code below, type @t{demo('gaussmf')} at the
-## Octave prompt.
+## To run the demonstration code, type @t{demo('gaussmf')} at the Octave prompt.
 ##
 ## @seealso{dsigmf, gauss2mf, gbellmf, pimf, psigmf, sigmf, smf, trapmf, trimf, zmf}
 ## @end deftypefn
@@ -64,7 +63,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy membership-function gaussian
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gaussmf.m
-## Last-Modified: 20 Jun 2011
+## Last-Modified: 28 Oct 2011
 
 function y = gaussmf (x, params)
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gbellmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gbellmf.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gbellmf.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -58,8 +58,7 @@
 ## differentiable and is symmetric about the line x = c.
 ##
 ## @noindent
-## To run the demonstration code below, type @t{demo('gbellmf')} at the
-## Octave prompt.
+## To run the demonstration code, type @t{demo('gbellmf')} at the Octave prompt.
 ##
 ## @seealso{dsigmf, gauss2mf, gaussmf, pimf, psigmf, sigmf, smf, trapmf, trimf, zmf}
 ## @end deftypefn
@@ -68,7 +67,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy membership-function bell-shaped bell
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gbellmf.m
-## Last-Modified: 7 Jun 2011
+## Last-Modified: 28 Oct 2011
 
 function y = gbellmf (x, params)
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gensurf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gensurf.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gensurf.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -57,10 +57,12 @@
 ## @item
 ## cubic_approx_demo.m
 ## @item
-## heart_demo_1.m
+## heart_disease_demo_1.m
 ## @item
-## heart_demo_2.m
+## heart_disease_demo_2.m
 ## @item
+## investment_portfolio_demo.m
+## @item
 ## linear_tip_demo.m
 ## @item
 ## mamdani_tip_demo.m
@@ -72,17 +74,17 @@
 ## The form of gensurf that suppresses plotting (the final form above) is not yet
 ## implemented.
 ##
-## @seealso{cubic_approx_demo, heart_demo_1, heart_demo_2, linear_tip_demo, mamdani_tip_demo, sugeno_tip_demo, plotmf}
+## @seealso{cubic_approx_demo, heart_disease_demo_1, heart_disease_demo_2, investment_portfolio_demo, linear_tip_demo, mamdani_tip_demo, sugeno_tip_demo, plotmf}
 ## @end deftypefn
 
 ## Author:        L. Markowsky
 ## Keywords:      fuzzy-logic-toolkit fuzzy fuzzy-inference-system fis plot
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gensurf.m
-## Last-Modified: 30 Aug 2011
+## Last-Modified: 11 Nov 2011
 
-function [x, y, z] = gensurf (fis, input_axes=[1 2], output_axis=1, ...
-                              grids=[15 15], ref_input=[], num_points=101)
+function [x, y, z] = gensurf (fis, input_axes = [1 2], output_axis = 1, ...
+                              grids = [15 15], ref_input = [], num_points = 101)
 
   ## If gensurf was called with an incorrect number of arguments, or the
   ## arguments do not have the correct type, print an error message and halt.

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m	2011-11-13 18:30:38 UTC (rev 9081)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -93,12 +93,12 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy fuzzy-inference-system fis
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      getfis.m
-## Last-Modified: 31 Aug 2011
+## Last-Modified: 31 Oct 2011
 
 ##------------------------------------------------------------------------------
 
-function retval = getfis (fis, arg2='dummy', arg3='dummy', arg4='dummy', ...
-                          arg5='dummy', arg6='dummy')
+function retval = getfis (fis, arg2 = 'dummy', arg3 = 'dummy', ...
+                         arg4 = 'dummy', arg5 = 'dummy', arg6 = 'dummy')
 
   switch (nargin)
     case 1  retval = getfis_one_arg (fis);

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_product.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_product.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,101 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} hamacher_product (@var{x})
+## @deftypefnx {Function File} {@var{retval} =} hamacher_product (@var{x}, @var{y})
+##
+## Return the Hamacher product of the input.
+## The Hamacher product of two real scalars x and y is:
+## (x * y) / (x + y - x * y)
+##
+## For one vector argument, apply the Hamacher product to all of the elements
+## of the vector. (The Hamacher product is associative.) For one
+## two-dimensional matrix argument, return a vector of the Hamacher product
+## of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise Hamacher product.
+##
+## @seealso{algebraic_product, algebraic_sum, bounded_difference, bounded_sum, drastic_product, drastic_sum, einstein_product, einstein_sum, hamacher_sum}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy hamacher_product
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      hamacher_product.m
+## Last-Modified: 12 Nov 2011
+
+function retval = hamacher_product (x, y = 0)
+  if (nargin == 0 || nargin > 2 ||
+      !is_real_matrix (x) || !is_real_matrix (y))
+    argument_error
+
+  elseif (nargin == 1)
+    if (isvector (x))
+      retval = vector_arg (x);
+    elseif (ndims (x) == 2)
+      retval = matrix_arg (x);
+    else
+      argument_error;
+    endif
+
+  elseif (nargin == 2)
+    if (isequal (size (x), size (y)))
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (isscalar (x) && ismatrix (y))
+      x = x * ones (size (y));
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (ismatrix (x) && isscalar (y))
+      y = y * ones (size (x));
+      retval = arrayfun (@scalar_args, x, y);
+    else
+      argument_error;
+    endif
+  endif
+endfunction
+
+function retval = scalar_args (x, y)
+  retval = (x * y) / (x + y - x * y);
+endfunction
+
+function retval = vector_arg (real_vector)
+  x = 1;
+  for i = 1 : length (real_vector)
+    y = real_vector(i);
+    if (x == 0 && y == 0)
+      x = 0;
+    else
+      x = (x * y) / (x + y - x * y);
+    endif
+  endfor
+  retval = x;
+endfunction
+
+function retval = matrix_arg (x)
+  num_cols = columns (x);
+  retval = zeros (1, num_cols);
+  for i = 1 : num_cols
+    retval(i) = vector_arg (x(:, i));
+  endfor
+endfunction
+
+function argument_error
+  puts ("Type 'help hamacher_product' for more information.\n");
+  error ("invalid arguments to function hamacher_product\n");
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_sum.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_sum.m	2011-11-13 18:37:05 UTC (rev 9082)
@@ -0,0 +1,101 @@
+## Copyright (C) 2011 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{retval} =} hamacher_sum (@var{x})
+## @deftypefnx {Function File} {@var{retval} =} hamacher_sum (@var{x}, @var{y})
+##
+## Return the Hamacher sum of the input.
+## The Hamacher sum of two real scalars x and y is:
+## (x + y - 2 * x * y) / (1 - x * y)
+##
+## For one vector argument, apply the Hamacher sum to all of the elements
+## of the vector. (The Hamacher sum is associative.) For one
+## two-dimensional matrix argument, return a vector of the Hamacher sum
+## of each column.
+##
+## For two vectors or matrices of identical dimensions, or for one scalar and
+## one vector or matrix argument, return the pair-wise Hamacher sum.
+##
+## @seealso{algebraic_product, algebraic_sum, bounded_difference, bounded_sum, drastic_product, drastic_sum, einstein_product, einstein_sum, hamacher_product}
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy hamacher_sum
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      hamacher_sum.m
+## Last-Modified: 12 Nov 2011
+
+function retval = hamacher_sum (x, y = 0)
+  if (nargin == 0 || nargin > 2 ||
+      !is_real_matrix (x) || !is_real_matrix (y))
+    argument_error
+
+  elseif (nargin == 1)
+    if (isvector (x))
+      retval = vector_arg (x);
+    elseif (ndims (x) == 2)
+      retval = matrix_arg (x);
+    else
+      argument_error;
+    endif
+
+  elseif (nargin == 2)
+    if (isequal (size (x), size (y)))
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (isscalar (x) && ismatrix (y))
+      x = x * ones (size (y));
+      retval = arrayfun (@scalar_args, x, y);
+    elseif (ismatrix (x) && isscalar (y))
+      y = y * ones (size (x));
+      retval = arrayfun (@scalar_args, x, y);
+    else
+      argument_error;
+    endif
+  endif
+endfunction
+
+function retval = scalar_args (x, y)
+  retval = (x + y - 2 * x * y) / (1 - x * y);
+endfunction
+
+function retval = vector_arg (real_vector)
+  x = 0;
+  fo...
 
[truncated message content]

[Octave-cvsupdate] SF.net SVN: octave:[10740] trunk/octave-forge/main/fuzzy-logic-toolkit/inst

[<lm...@us...>]

Revision: 10740
          http://octave.svn.sourceforge.net/octave/?rev=10740&view=rev
Author:   lmarkov
Date:     2012-07-10 14:20:04 +0000 (Tue, 10 Jul 2012)
Log Message:
-----------
M    inst/gustafson_kessel_demo_1.m
M    inst/gustafson_kessel_demo_2.m
M    inst/xie_beni_index.m
M    inst/gustafson_kessel.m
M    inst/fcm_demo_1.m
M    inst/fcm_demo_2.m
M    inst/fcm.m

Modified Paths:
--------------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	2012-07-09 13:17:11 UTC (rev 10739)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	2012-07-10 14:20:04 UTC (rev 10740)
@@ -24,7 +24,9 @@
 ## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} fcm (@var{input_data}, @var{num_clusters}, @var{options})
 ## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} fcm (@var{input_data}, @var{num_clusters}, [@var{m}, @var{max_iterations}, @var{epsilon}, @var{display_intermediate_results}])
 ##
-## Return the soft partition of a set of unlabeled data points. 
+## Using the Fuzzy C-Means algorithm, calculate and return the soft partition
+## of a set of unlabeled data points. 
+##
 ## Also, if @var{display_intermediate_results} is true, display intermediate 
 ## results after each iteration.
 ##
@@ -112,7 +114,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      fcm.m
-## Last-Modified: 8 July 2012
+## Last-Modified: 10 July 2012
 
 function [cluster_centers, soft_partition, obj_fcn_history] = ...
            fcm (input_data, num_clusters, options = [2.0, 100, 1e-5, 1])

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m	2012-07-09 13:17:11 UTC (rev 10739)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m	2012-07-10 14:20:04 UTC (rev 10740)
@@ -18,8 +18,8 @@
 
 ## -*- texinfo -*-
 ## @deftypefn {Script File} {} fcm_demo_1
-## Use the Fuzzy C-Means algorithm to classify unlabeled data points and
-## evaluate the quality of the resulting clusters.
+## Use the Fuzzy C-Means algorithm to classify a small set of unlabeled
+## data points and evaluate the quality of the resulting clusters.
 ##
 ## This demo:
 ## @itemize @minus
@@ -45,7 +45,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm demo
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      fcm_demo_1.m
-## Last-Modified: 8 July 2012
+## Last-Modified: 10 July 2012
 
 ##------------------------------------------------------------------------------
 ## Note: The input_data is taken from Chapter 13, Example 17 in

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m	2012-07-09 13:17:11 UTC (rev 10739)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m	2012-07-10 14:20:04 UTC (rev 10740)
@@ -18,8 +18,8 @@
 
 ## -*- texinfo -*-
 ## @deftypefn {Script File} {} fcm_demo_2
-## Use the Fuzzy C-Means algorithm to classify unlabeled data points and
-## evaluate the quality of the resulting clusters.
+## Use the Fuzzy C-Means algorithm to classify three-dimensional unlabeled
+## data points and evaluate the quality of the resulting clusters.
 ##
 ## The demo:
 ## @itemize @minus
@@ -45,7 +45,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm demo
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      fcm_demo_2.m
-## Last-Modified: 8 July 2012
+## Last-Modified: 10 July 2012
 
 ##------------------------------------------------------------------------------
 ## Note: The input_data was selected to form three areas of different shapes.

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m	2012-07-09 13:17:11 UTC (rev 10739)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m	2012-07-10 14:20:04 UTC (rev 10740)
@@ -26,7 +26,9 @@
 ## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} gustafson_kessel (@var{input_data}, @var{num_clusters}, @var{cluster_volume}, @var{options})
 ## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} gustafson_kessel (@var{input_data}, @var{num_clusters}, @var{cluster_volume}, [@var{m}, @var{max_iterations}, @var{epsilon}, @var{display_intermediate_results}])
 ##
-## Return the soft partition of a set of unlabeled data points. 
+## Using the Gustafson-Kessel algorithm, calculate and return the soft partition
+## of a set of unlabeled data points. 
+##
 ## Also, if @var{display_intermediate_results} is true, display intermediate 
 ## results after each iteration.
 ##
@@ -117,7 +119,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering gustafson_kessel
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gustafson_kessel.m
-## Last-Modified: 8 July 2012
+## Last-Modified: 10 July 2012
 
 function [cluster_centers, soft_partition, obj_fcn_history] = ...
            gustafson_kessel (input_data, num_clusters, cluster_volume = [], options = [2.0, 100, 1e-5, 1])

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m	2012-07-09 13:17:11 UTC (rev 10739)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m	2012-07-10 14:20:04 UTC (rev 10740)
@@ -18,8 +18,8 @@
 
 ## -*- texinfo -*-
 ## @deftypefn {Script File} {} gustafson_kessel_demo_1
-## Use the Gustafson-Kessel algorithm to classify unlabeled data points and
-## evaluate the quality of the resulting clusters.
+## Use the Gustafson-Kessel algorithm to classify a small set of unlabeled
+## data points and evaluate the quality of the resulting clusters.
 ##
 ## The demo:
 ## @itemize @minus
@@ -45,7 +45,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering gustafson_kessel demo
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gustafson_kessel_demo_1.m
-## Last-Modified: 8 July 2012
+## Last-Modified: 10 July 2012
 
 ##------------------------------------------------------------------------------
 ## Note: The input_data is taken from Chapter 13, Example 17 in

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m	2012-07-09 13:17:11 UTC (rev 10739)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m	2012-07-10 14:20:04 UTC (rev 10740)
@@ -18,8 +18,8 @@
 
 ## -*- texinfo -*-
 ## @deftypefn {Script File} {} gustafson_kessel_demo_2
-## Use the Gustafson-Kessel algorithm to classify unlabeled data points and
-## evaluate the quality of the resulting clusters.
+## Use the Gustafson-Kessel algorithm to classify three-dimensional unlabeled
+## data points and evaluate the quality of the resulting clusters.
 ##
 ## The demo:
 ## @itemize @minus
@@ -45,7 +45,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm demo
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gustafson_kessel_demo_2.m
-## Last-Modified: 8 July 2012
+## Last-Modified: 10 July 2012
 
 ##------------------------------------------------------------------------------
 ## Note: The input_data was selected to form three areas of different shapes.

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m	2012-07-09 13:17:11 UTC (rev 10739)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m	2012-07-10 14:20:04 UTC (rev 10740)
@@ -19,7 +19,7 @@
 ## -*- texinfo -*-
 ## @deftypefn {Function File} {@var{vxb} =} xie_beni_index (@var{input_data}, @var{cluster_centers}, @var{soft_partition})
 ##
-## Return the partition coefficient for a given soft partition.
+## Return the Xie-Beni validity index for a given soft partition.
 ##
 ## The arguments to xie_beni_index are:
 ## @itemize @w
@@ -49,7 +49,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy xie beni index cluster validity
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      xie_beni_index.m
-## Last-Modified: 8 July 2012
+## Last-Modified: 10 July 2012
 
 function vxb = xie_beni_index (input_data, cluster_centers, soft_partition)
 

This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

[Octave-cvsupdate] SF.net SVN: octave:[10915] trunk/octave-forge/main/fuzzy-logic-toolkit/inst

[<lm...@us...>]

Revision: 10915
          http://octave.svn.sourceforge.net/octave/?rev=10915&view=rev
Author:   lmarkov
Date:     2012-08-26 14:54:12 +0000 (Sun, 26 Aug 2012)
Log Message:
-----------
M    inst/fcm.m
M    inst/xie_beni_index.m
M    inst/gustafson_kessel.m
D    inst/fcm_demo_1.m
M    inst/partition_entropy.m
D    inst/fcm_demo_2.m
D    inst/gustafson_kessel_demo_1.m
D    inst/gustafson_kessel_demo_2.m
M    inst/partition_coeff.m

Modified Paths:
--------------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m

Removed Paths:
-------------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	2012-08-25 08:27:39 UTC (rev 10914)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	2012-08-26 14:54:12 UTC (rev 10915)
@@ -106,7 +106,7 @@
 ## @end group
 ## @end example
 ##
-## @seealso{fcm_demo_1, fcm_demo_2, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2, partition_coeff, partition_entropy, xie_beni_index}
+## @seealso{gustafson_kessel, partition_coeff, partition_entropy, xie_beni_index}
 ##
 ## @end deftypefn
 
@@ -114,7 +114,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      fcm.m
-## Last-Modified: 19 Aug 2012
+## Last-Modified: 26 Aug 2012
 
 function [cluster_centers, soft_partition, obj_fcn_history] = ...
            fcm (input_data, num_clusters, options = [2.0, 100, 1e-5, 1])
@@ -212,3 +212,126 @@
   endif
 
 endfunction
+
+##----------------------------------------------------------------------
+## FCM Demo #1
+##----------------------------------------------------------------------
+
+%!demo
+%! ## This demo:
+%! ##    - classifies a small set of unlabeled data points using the
+%! ##      Fuzzy C-Means algorithm into two fuzzy clusters
+%! ##    - plots the input points together with the cluster centers
+%! ##
+%! ## Note: The input_data is taken from Chapter 13, Example 17 in
+%! ##       Fuzzy Logic: Intelligence, Control and Information, by
+%! ##       J. Yen and R. Langari, Prentice Hall, 1999, page 381
+%! ##       (International Edition). 
+%! 
+%! ## Use fcm to classify the input_data.
+%! input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4];
+%! number_of_clusters = 2;
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   fcm (input_data, number_of_clusters)
+%! 
+%! ## Plot the data points as small blue x's.
+%! figure ('NumberTitle', 'off', 'Name', 'FCM Demo 1');
+%! for i = 1 : rows (input_data)
+%!   plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
+%!         'marker', 'x', 'color', 'b');
+%!   hold on;
+%! endfor
+%! 
+%! ## Plot the cluster centers as larger red *'s.
+%! for i = 1 : number_of_clusters
+%!   plot (cluster_centers(i, 1), cluster_centers(i, 2), ...
+%!         'LineWidth', 4, 'marker', '*', 'color', 'r');
+%!   hold on;
+%! endfor
+%! 
+%! ## Make the figure look a little better:
+%! ##    - scale and label the axes
+%! ##    - show gridlines
+%! xlim ([0 15]);
+%! ylim ([0 15]);
+%! xlabel ('Feature 1');
+%! ylabel ('Feature 2');
+%! grid
+%! hold
+
+##----------------------------------------------------------------------
+## FCM Demo #2
+##----------------------------------------------------------------------
+
+%!demo
+%! ## This demo:
+%! ##    - classifies three-dimensional unlabeled data points using the
+%! ##      Fuzzy C-Means algorithm into three fuzzy clusters
+%! ##    - plots the input points together with the cluster centers
+%! ##
+%! ## Note: The input_data was selected to form three areas of
+%! ##       different shapes.
+%! 
+%! ## Use fcm to classify the input_data.
+%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
+%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
+%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
+%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
+%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13];
+%! number_of_clusters = 3;
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0])
+%! 
+%! ## Plot the data points in two dimensions (using features 1 & 2)
+%! ## as small blue x's.
+%! figure ('NumberTitle', 'off', 'Name', 'FCM Demo 2');
+%! for i = 1 : rows (input_data)
+%!   plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
+%!         'marker', 'x', 'color', 'b');
+%!   hold on;
+%! endfor
+%! 
+%! ## Plot the cluster centers in two dimensions (using features 1 & 2)
+%! ## as larger red *'s.
+%! for i = 1 : number_of_clusters
+%!   plot (cluster_centers(i, 1), cluster_centers(i, 2), ...
+%!         'LineWidth', 4, 'marker', '*', 'color', 'r');
+%!   hold on;
+%! endfor
+%! 
+%! ## Make the figure look a little better:
+%! ##    - scale and label the axes
+%! ##    - show gridlines
+%! xlim ([0 15]);
+%! ylim ([0 15]);
+%! xlabel ('Feature 1');
+%! ylabel ('Feature 2');
+%! grid
+%! hold
+%! 
+%! ## Plot the data points in two dimensions (using features 1 & 3)
+%! ## as small blue x's.
+%! figure ('NumberTitle', 'off', 'Name', 'FCM Demo 2');
+%! for i = 1 : rows (input_data)
+%!   plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, ...
+%!         'marker', 'x', 'color', 'b');
+%!   hold on;
+%! endfor
+%! 
+%! ## Plot the cluster centers in two dimensions (using features 1 & 3)
+%! ## as larger red *'s.
+%! for i = 1 : number_of_clusters
+%!   plot (cluster_centers(i, 1), cluster_centers(i, 3), ...
+%!         'LineWidth', 4, 'marker', '*', 'color', 'r');
+%!   hold on;
+%! endfor
+%! 
+%! ## Make the figure look a little better:
+%! ##    - scale and label the axes
+%! ##    - show gridlines
+%! xlim ([0 15]);
+%! ylim ([0 15]);
+%! xlabel ('Feature 1');
+%! ylabel ('Feature 3');
+%! grid
+%! hold

Deleted: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m	2012-08-25 08:27:39 UTC (rev 10914)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m	2012-08-26 14:54:12 UTC (rev 10915)
@@ -1,94 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
-##
-## This file is part of the fuzzy-logic-toolkit.
-##
-## The fuzzy-logic-toolkit is free software; you can redistribute it
-## and/or modify it under the terms of the GNU General Public License
-## as published by the Free Software Foundation; either version 3 of
-## the License, or (at your option) any later version.
-##
-## The fuzzy-logic-toolkit is distributed in the hope that it will be
-## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
-## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
-## General Public License for more details.
-##
-## You should have received a copy of the GNU General Public License
-## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
-## see <http://www.gnu.org/licenses/>.
-
-## -*- texinfo -*-
-## @deftypefn {Script File} {} fcm_demo_1
-## Use the Fuzzy C-Means algorithm to classify a small set of unlabeled
-## data points and evaluate the quality of the resulting clusters.
-##
-## This demo:
-## @itemize @minus
-## @item
-## classifies a small set of unlabeled data points using the Fuzzy C-Means
-## algorithm into two fuzzy clusters
-## @item
-## calculates and prints (on standard output) three validity measures:
-## the partition coefficient, the partition entropy, and the Xie-Beni
-## validity index
-## @item
-## plots the input points together with the cluster centers
-## @end itemize
-##
-## For a description of the data structures used in the script, see the
-## documentation for fcm.
-##
-## @seealso{fcm, fcm_demo_2, partition_coeff, partition_entropy, xie_beni_index, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2}
-##
-## @end deftypefn
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      fcm_demo_1.m
-## Last-Modified: 19 Aug 2012
-
-##----------------------------------------------------------------------
-## Note: The input_data is taken from Chapter 13, Example 17 in
-##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen
-##       and R. Langari, Prentice Hall, 1999, page 381 (International
-##       Edition). 
-##----------------------------------------------------------------------
-
-## Use fcm to classify the data in matrix x.
-input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
-number_of_clusters = 2
-[cluster_centers, soft_partition, obj_fcn_history] = ...
-  fcm (input_data, number_of_clusters)
-
-## Calculate and print the three validity measures.
-printf ("Partition Coefficient: %f\n", ...
-        partition_coeff (soft_partition));
-printf ("Partition Entropy (with a = 2): %f\n", ...
-        partition_entropy (soft_partition, 2));
-printf ("Xie-Beni Index: %f\n\n", ...
-        xie_beni_index (input_data, cluster_centers, soft_partition));
- 
-## Plot the data points as small blue x's.
-figure ('NumberTitle', 'off', 'Name', 'FCM Demo 1');
-for i = 1 : rows (input_data)
-  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
-        'marker', 'x', 'color', 'b');
-  hold on;
-endfor
-
-## Plot the cluster centers as larger red *'s.
-for i = 1 : number_of_clusters
-  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
-        4, 'marker', '*', 'color', 'r');
-  hold on;
-endfor
-
-## Make the figure look a little better:
-##   -- scale and label the axes
-##   -- show gridlines
-xlim ([0 15]);
-ylim ([0 15]);
-xlabel ('Feature 1');
-ylabel ('Feature 2');
-grid
-hold

Deleted: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m	2012-08-25 08:27:39 UTC (rev 10914)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m	2012-08-26 14:54:12 UTC (rev 10915)
@@ -1,125 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
-##
-## This file is part of the fuzzy-logic-toolkit.
-##
-## The fuzzy-logic-toolkit is free software; you can redistribute it
-## and/or modify it under the terms of the GNU General Public License
-## as published by the Free Software Foundation; either version 3 of
-## the License, or (at your option) any later version.
-##
-## The fuzzy-logic-toolkit is distributed in the hope that it will be
-## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
-## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
-## General Public License for more details.
-##
-## You should have received a copy of the GNU General Public License
-## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
-## see <http://www.gnu.org/licenses/>.
-
-## -*- texinfo -*-
-## @deftypefn {Script File} {} fcm_demo_2
-## Use the Fuzzy C-Means algorithm to classify three-dimensional unlabeled
-## data points and evaluate the quality of the resulting clusters.
-##
-## The demo:
-## @itemize @minus
-## @item
-## classifies three-dimensional unlabeled data points using the Fuzzy
-## C-Means algorithm into three fuzzy clusters
-## @item
-## calculates and prints (on standard output) three validity measures:
-## the partition coefficient, the partition entropy, and the Xie-Beni
-## validity index
-## @item
-## plots the input points together with the cluster centers
-## @end itemize
-##
-## For a description of the data structures used in the script, see the
-## documentation for fcm.
-##
-## @seealso{fcm, fcm_demo_1, partition_coeff, partition_entropy, xie_beni_index, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2}
-##
-## @end deftypefn
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      fcm_demo_2.m
-## Last-Modified: 19 Aug 2012
-
-##----------------------------------------------------------------------
-## Note: The input_data was selected to form three areas of different
-##       shapes.
-##----------------------------------------------------------------------
-
-## Use fcm to classify the data in matrix x.
-input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
-              3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
-              3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
-              9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14; 11 12 13;
-              12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13]
-number_of_clusters = 3
-[cluster_centers, soft_partition, obj_fcn_history] = ...
-  fcm (input_data, number_of_clusters, [NaN NaN NaN 0])
-
-## Calculate and print the three validity measures.
-printf ("Partition Coefficient: %f\n", ...
-        partition_coeff (soft_partition));
-printf ("Partition Entropy (with a = 2): %f\n", ...
-        partition_entropy (soft_partition, 2));
-printf ("Xie-Beni Index: %f\n\n", ...
-        xie_beni_index (input_data, cluster_centers, soft_partition));
- 
-## Plot the data points in two dimensions (using features 1 and 2)
-## as small blue x's.
-figure ('NumberTitle', 'off', 'Name', 'FCM Demo 2');
-for i = 1 : rows (input_data)
-  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
-        'marker', 'x', 'color', 'b');
-  hold on;
-endfor
-
-## Plot the cluster centers in two dimensions (using features 1 and 2)
-## as larger red *'s.
-for i = 1 : number_of_clusters
-  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
-        4, 'marker', '*', 'color', 'r');
-  hold on;
-endfor
-
-## Make the figure look a little better:
-##   -- scale and label the axes
-##   -- show gridlines
-xlim ([0 15]);
-ylim ([0 15]);
-xlabel ('Feature 1');
-ylabel ('Feature 2');
-grid
-hold
-
-## Plot the data points in two dimensions (using features 1 and 3)
-## as small blue x's.
-figure ('NumberTitle', 'off', 'Name', 'FCM Demo 2');
-for i = 1 : rows (input_data)
-  plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, ...
-        'marker', 'x', 'color', 'b');
-  hold on;
-endfor
-
-## Plot the cluster centers in two dimensions (using features 1 and 3)
-## as larger red *'s.
-for i = 1 : number_of_clusters
-  plot (cluster_centers(i, 1), cluster_centers(i, 3), 'LineWidth', ...
-        4, 'marker', '*', 'color', 'r');
-  hold on;
-endfor
-
-## Make the figure look a little better:
-##   -- scale and label the axes
-##   -- show gridlines
-xlim ([0 15]);
-ylim ([0 15]);
-xlabel ('Feature 1');
-ylabel ('Feature 3');
-grid
-hold

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m	2012-08-25 08:27:39 UTC (rev 10914)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m	2012-08-26 14:54:12 UTC (rev 10915)
@@ -111,7 +111,7 @@
 ## @end group
 ## @end example
 ##
-## @seealso{fcm, fcm_demo_1, fcm_demo_2, gustafson_kessel_demo_1, gustafson_kessel_demo_2, partition_coeff, partition_entropy, xie_beni_index}
+## @seealso{fcm, partition_coeff, partition_entropy, xie_beni_index}
 ##
 ## @end deftypefn
 
@@ -119,7 +119,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gustafson_kessel.m
-## Last-Modified: 20 Aug 2012
+## Last-Modified: 26 Aug 2012
 
 function [cluster_centers, soft_partition, obj_fcn_history] = ...
            gustafson_kessel (input_data, num_clusters, ...
@@ -283,3 +283,125 @@
 
 endfunction
 
+##----------------------------------------------------------------------
+## Gustafson-Kessel Demo #1
+##----------------------------------------------------------------------
+
+%!demo
+%! ## This demo:
+%! ##    - classifies a small set of unlabeled data points using the
+%! ##      Gustafson-Kessel algorithm into two fuzzy clusters
+%! ##    - plots the input points together with the cluster centers
+%! ##
+%! ## Note: The input_data is taken from Chapter 13, Example 17 in
+%! ##       Fuzzy Logic: Intelligence, Control and Information, by
+%! ##       J. Yen and R. Langari, Prentice Hall, 1999, page 381
+%! ##       (International Edition). 
+%! 
+%! ## Use gustafson_kessel to classify the input_data.
+%! input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4];
+%! number_of_clusters = 2;
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   gustafson_kessel (input_data, number_of_clusters)
+%! 
+%! ## Plot the data points as small blue x's.
+%! figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 1');
+%! for i = 1 : rows (input_data)
+%!   plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
+%!         'marker', 'x', 'color', 'b');
+%!   hold on;
+%! endfor
+%! 
+%! ## Plot the cluster centers as larger red *'s.
+%! for i = 1 : number_of_clusters
+%!   plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
+%!         4, 'marker', '*', 'color', 'r');
+%!   hold on;
+%! endfor
+%! 
+%! ## Make the figure look a little better:
+%! ##    - scale and label the axes
+%! ##    - show gridlines
+%! xlim ([0 15]);
+%! ylim ([0 15]);
+%! xlabel ('Feature 1');
+%! ylabel ('Feature 2');
+%! grid
+%! hold
+
+##----------------------------------------------------------------------
+## Gustafson-Kessel Demo #2
+##----------------------------------------------------------------------
+
+%!demo
+%! ## This demo:
+%! ##    - classifies three-dimensional unlabeled data points using the
+%! ##      Gustafson-Kessel algorithm into three fuzzy clusters
+%! ##    - plots the input points together with the cluster centers
+%! ##
+%! ## Note: The input_data was selected to form three areas of
+%! ##       different shapes.
+%! 
+%! ## Use gustafson_kessel to classify the input_data.
+%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
+%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
+%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
+%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
+%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13];
+%! number_of_clusters = 3;
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
+%!                     [NaN NaN NaN 0])
+%! 
+%! ## Plot the data points in two dimensions (using features 1 & 2)
+%! ## as small blue x's.
+%! figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 2');
+%! for i = 1 : rows (input_data)
+%!   plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
+%!         'marker', 'x', 'color', 'b');
+%!   hold on;
+%! endfor
+%! 
+%! ## Plot the cluster centers in two dimensions (using features 1 & 2)
+%! ## as larger red *'s.
+%! for i = 1 : number_of_clusters
+%!   plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
+%!         4, 'marker', '*', 'color', 'r');
+%!   hold on;
+%! endfor
+%! 
+%! ## Make the figure look a little better:
+%! ##    - scale and label the axes
+%! ##    - show gridlines
+%! xlim ([0 15]);
+%! ylim ([0 15]);
+%! xlabel ('Feature 1');
+%! ylabel ('Feature 2');
+%! grid
+%!  
+%! ## Plot the data points in two dimensions (using features 1 & 3)
+%! ## as small blue x's.
+%! figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 2');
+%! for i = 1 : rows (input_data)
+%!   plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, ...
+%!         'marker', 'x', 'color', 'b');
+%!   hold on;
+%! endfor
+%! 
+%! ## Plot the cluster centers in two dimensions (using features 1 & 3)
+%! ## as larger red *'s.
+%! for i = 1 : number_of_clusters
+%!   plot (cluster_centers(i, 1), cluster_centers(i, 3), 'LineWidth', ...
+%!         4, 'marker', '*', 'color', 'r');
+%!   hold on;
+%! endfor
+%! 
+%! ## Make the figure look a little better:
+%! ##    - scale and label the axes
+%! ##    - show gridlines
+%! xlim ([0 15]);
+%! ylim ([0 15]);
+%! xlabel ('Feature 1');
+%! ylabel ('Feature 3');
+%! grid
+%! hold

Deleted: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m	2012-08-25 08:27:39 UTC (rev 10914)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m	2012-08-26 14:54:12 UTC (rev 10915)
@@ -1,94 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
-##
-## This file is part of the fuzzy-logic-toolkit.
-##
-## The fuzzy-logic-toolkit is free software; you can redistribute it
-## and/or modify it under the terms of the GNU General Public License
-## as published by the Free Software Foundation; either version 3 of
-## the License, or (at your option) any later version.
-##
-## The fuzzy-logic-toolkit is distributed in the hope that it will be
-## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
-## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
-## General Public License for more details.
-##
-## You should have received a copy of the GNU General Public License
-## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
-## see <http://www.gnu.org/licenses/>.
-
-## -*- texinfo -*-
-## @deftypefn {Script File} {} gustafson_kessel_demo_1
-## Use the Gustafson-Kessel algorithm to classify a small set of unlabeled
-## data points and evaluate the quality of the resulting clusters.
-##
-## The demo:
-## @itemize @minus
-## @item
-## classifies a small set of unlabeled data points using the Gustafson-Kessel
-## algorithm into two fuzzy clusters
-## @item
-## calculates and prints (on standard output) three validity measures:
-## the partition coefficient, the partition entropy, and the Xie-Beni
-## validity index
-## @item
-## plots the input points together with the cluster centers
-## @end itemize
-##
-## For a description of the data structures used in the script, see the
-## documentation for gustafson_kessel.
-##
-## @seealso{gustafson_kessel, gustafson_kessel_demo_2, partition_coeff, partition_entropy, xie_beni_index, fcm, fcm_demo_1, fcm_demo_2}
-##
-## @end deftypefn
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      gustafson_kessel_demo_1.m
-## Last-Modified: 20 Aug 2012
-
-##----------------------------------------------------------------------
-## Note: The input_data is taken from Chapter 13, Example 17 in
-##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen
-##       and R. Langari, Prentice Hall, 1999, page 381 (International
-##       Edition). 
-##----------------------------------------------------------------------
-
-## Use gustafson_kessel to classify the data in matrix x.
-input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
-number_of_clusters = 2
-[cluster_centers, soft_partition, obj_fcn_history] = ...
-  gustafson_kessel (input_data, number_of_clusters)
-
-## Calculate and print the three validity measures.
-printf ("Partition Coefficient: %f\n", ...
-        partition_coeff (soft_partition));
-printf ("Partition Entropy (with a = 2): %f\n", ...
-        partition_entropy (soft_partition, 2));
-printf ("Xie-Beni Index: %f\n\n", ...
-        xie_beni_index (input_data, cluster_centers, soft_partition));
- 
-## Plot the data points as small blue x's.
-figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 1');
-for i = 1 : rows (input_data)
-  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
-        'marker', 'x', 'color', 'b');
-  hold on;
-endfor
-
-## Plot the cluster centers as larger red *'s.
-for i = 1 : number_of_clusters
-  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
-        4, 'marker', '*', 'color', 'r');
-  hold on;
-endfor
-
-## Make the figure look a little better:
-##   -- scale and label the axes
-##   -- show gridlines
-xlim ([0 15]);
-ylim ([0 15]);
-xlabel ('Feature 1');
-ylabel ('Feature 2');
-grid
-hold

Deleted: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m	2012-08-25 08:27:39 UTC (rev 10914)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m	2012-08-26 14:54:12 UTC (rev 10915)
@@ -1,125 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
-##
-## This file is part of the fuzzy-logic-toolkit.
-##
-## The fuzzy-logic-toolkit is free software; you can redistribute it
-## and/or modify it under the terms of the GNU General Public License
-## as published by the Free Software Foundation; either version 3 of
-## the License, or (at your option) any later version.
-##
-## The fuzzy-logic-toolkit is distributed in the hope that it will be
-## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
-## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
-## General Public License for more details.
-##
-## You should have received a copy of the GNU General Public License
-## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
-## see <http://www.gnu.org/licenses/>.
-
-## -*- texinfo -*-
-## @deftypefn {Script File} {} gustafson_kessel_demo_2
-## Use the Gustafson-Kessel algorithm to classify three-dimensional unlabeled
-## data points and evaluate the quality of the resulting clusters.
-##
-## The demo:
-## @itemize @minus
-## @item
-## classifies three-dimensional unlabeled data points using the
-## Gustafson-Kessel algorithm into three fuzzy clusters
-## @item
-## calculates and prints (on standard output) three validity measures:
-## the partition coefficient, the partition entropy, and the Xie-Beni
-## validity index
-## @item
-## plots the input points together with the cluster centers
-## @end itemize
-##
-## For a description of the data structures used in the script, see the
-## documentation for gustafson_kessel.
-##
-## @seealso{gustafson_kessel, gustafson_kessel_demo_1, partition_coeff, partition_entropy, xie_beni_index, fcm, fcm_demo_1, fcm_demo_2}
-##
-## @end deftypefn
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      gustafson_kessel_demo_2.m
-## Last-Modified: 20 Aug 2012
-
-##----------------------------------------------------------------------
-## Note: The input_data was selected to form three areas of
-##       different shapes.
-##----------------------------------------------------------------------
-
-## Use gustafson_kessel to classify the data in matrix x.
-input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
-              3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
-              3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
-              9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14; 11 12 13;
-              12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13]
-number_of_clusters = 3
-[cluster_centers, soft_partition, obj_fcn_history] = ...
-  gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
-                    [NaN NaN NaN 0])
-
-## Calculate and print the three validity measures.
-printf ("Partition Coefficient: %f\n", ...
-        partition_coeff (soft_partition));
-printf ("Partition Entropy (with a = 2): %f\n", ...
-        partition_entropy (soft_partition, 2));
-printf ("Xie-Beni Index: %f\n\n", ...
-        xie_beni_index (input_data, cluster_centers, soft_partition));
- 
-## Plot the data points in two dimensions (using features 1 and 2)
-## as small blue x's.
-figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 2');
-for i = 1 : rows (input_data)
-  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
-        'marker', 'x', 'color', 'b');
-  hold on;
-endfor
-
-## Plot the cluster centers in two dimensions (using features 1 and 2)
-## as larger red *'s.
-for i = 1 : number_of_clusters
-  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
-        4, 'marker', '*', 'color', 'r');
-  hold on;
-endfor
-
-## Make the figure look a little better:
-##   -- scale and label the axes
-##   -- show gridlines
-xlim ([0 15]);
-ylim ([0 15]);
-xlabel ('Feature 1');
-ylabel ('Feature 2');
-grid
- 
-## Plot the data points in two dimensions (using features 1 and 3)
-## as small blue x's.
-figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 2');
-for i = 1 : rows (input_data)
-  plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, ...
-        'marker', 'x', 'color', 'b');
-  hold on;
-endfor
-
-## Plot the cluster centers in two dimensions (using features 1 and 3)
-## as larger red *'s.
-for i = 1 : number_of_clusters
-  plot (cluster_centers(i, 1), cluster_centers(i, 3), 'LineWidth', ...
-        4, 'marker', '*', 'color', 'r');
-  hold on;
-endfor
-
-## Make the figure look a little better:
-##   -- scale and label the axes
-##   -- show gridlines
-xlim ([0 15]);
-ylim ([0 15]);
-xlabel ('Feature 1');
-ylabel ('Feature 3');
-grid
-hold

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m	2012-08-25 08:27:39 UTC (rev 10914)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m	2012-08-26 14:54:12 UTC (rev 10915)
@@ -36,7 +36,7 @@
 ## For more information about the @var{soft_partition} matrix, please see the
 ## documentation for function fcm.
 ##
-## @seealso{fcm, fcm_demo_1, fcm_demo_2, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2, partition_entropy, xie_beni_index}
+## @seealso{fcm, gustafson_kessel, partition_entropy, xie_beni_index}
 ##
 ## @end deftypefn
 
@@ -44,7 +44,7 @@
 ## Keywords:      fuzzy-logic-toolkit partition coefficient cluster
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      partition_coeff.m
-## Last-Modified: 19 Aug 2012
+## Last-Modified: 26 Aug 2012
 
 ##----------------------------------------------------------------------
 ## Note: This function is an implementation of Equation 13.9 (corrected
@@ -78,3 +78,77 @@
   vpc = (sum (sum (soft_part_sqr))) / columns (soft_partition);
 
 endfunction
+
+##----------------------------------------------------------------------
+## Partition Coefficient Demo #1
+##----------------------------------------------------------------------
+
+%!demo
+%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
+%! ## a small set of unlabeled data points and evaluate the quality
+%! ## of the resulting clusters.
+%!
+%! ## Note: The input_data is taken from Chapter 13, Example 17 in
+%! ##       Fuzzy Logic: Intelligence, Control and Information, by
+%! ##       J. Yen and R. Langari, Prentice Hall, 1999, page 381
+%! ##       (International Edition). 
+%! 
+%! input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
+%! number_of_clusters = 2
+%! 
+%! ## Using fcm, classify the input data, print the cluster centers,
+%! ## and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
+%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
+%! cluster_centers
+%! printf ("partition coefficient: %f\n", ...
+%!         partition_coeff (soft_partition));
+%! 
+%! ## Using gustafson_kessel, classify the input data, print the cluster
+%! ## centers, and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
+%!                     [NaN NaN NaN 0]);
+%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
+%! cluster_centers
+%! printf ("partition coefficient: %f\n\n", ...
+%!         partition_coeff (soft_partition));
+
+##----------------------------------------------------------------------
+## Partition Coefficient Demo #2
+##----------------------------------------------------------------------
+
+%!demo
+%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
+%! ## three-dimensional unlabeled data points and evaluate the quality
+%! ## of the resulting clusters.
+%!
+%! ## Note: The input_data was selected to form three areas of
+%! ##       different shapes.
+%!
+%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
+%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
+%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
+%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
+%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13]
+%! number_of_clusters = 3
+%!
+%! ## Using fcm, classify the input data, print the cluster centers,
+%! ## and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
+%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
+%! cluster_centers
+%! printf ("partition coefficient: %f\n", ...
+%!         partition_coeff (soft_partition));
+%! 
+%! ## Using gustafson_kessel, classify the input data, print the cluster
+%! ## centers, and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
+%!                     [NaN NaN NaN 0]);
+%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
+%! cluster_centers
+%! printf ("partition coefficient: %f\n\n", ...
+%!         partition_coeff (soft_partition));

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m	2012-08-25 08:27:39 UTC (rev 10914)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m	2012-08-26 14:54:12 UTC (rev 10915)
@@ -38,7 +38,7 @@
 ## For more information about the @var{soft_partition} matrix, please see the
 ## documentation for function fcm.
 ##
-## @seealso{fcm, fcm_demo_1, fcm_demo_2, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2, partition_coeff, xie_beni_index}
+## @seealso{fcm, gustafson_kessel, partition_coeff, xie_beni_index}
 ##
 ## @end deftypefn
 
@@ -46,7 +46,7 @@
 ## Keywords:      fuzzy-logic-toolkit partition entropy cluster
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      partition_entropy.m
-## Last-Modified: 19 Aug 2012
+## Last-Modified: 26 Aug 2012
 
 ##----------------------------------------------------------------------
 ## Note: This function is an implementation of Equation 13.10 in
@@ -86,3 +86,77 @@
   vpe = -(sum (sum (Mu .* log_a_Mu))) / n;
 
 endfunction
+
+##----------------------------------------------------------------------
+## Partition Entropy Demo #1
+##----------------------------------------------------------------------
+
+%!demo
+%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
+%! ## a small set of unlabeled data points and evaluate the quality
+%! ## of the resulting clusters.
+%!
+%! ## Note: The input_data is taken from Chapter 13, Example 17 in
+%! ##       Fuzzy Logic: Intelligence, Control and Information, by
+%! ##       J. Yen and R. Langari, Prentice Hall, 1999, page 381
+%! ##       (International Edition). 
+%! 
+%! input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
+%! number_of_clusters = 2
+%! 
+%! ## Using fcm, classify the input data, print the cluster centers,
+%! ## and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
+%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
+%! cluster_centers
+%! printf ("partition entropy (with a = 2): %f\n", ...
+%!         partition_entropy (soft_partition, 2));
+%! 
+%! ## Using gustafson_kessel, classify the input data, print the cluster
+%! ## centers, and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
+%!                     [NaN NaN NaN 0]);
+%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
+%! cluster_centers
+%! printf ("partition entropy (with a = 2): %f\n\n", ...
+%!         partition_entropy (soft_partition, 2));
+
+##----------------------------------------------------------------------
+## Partition Entropy Demo #2
+##----------------------------------------------------------------------
+
+%!demo
+%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
+%! ## three-dimensional unlabeled data points and evaluate the quality
+%! ## of the resulting clusters.
+%!
+%! ## Note: The input_data was selected to form three areas of
+%! ##       different shapes.
+%!
+%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
+%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
+%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
+%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
+%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13]
+%! number_of_clusters = 3
+%!
+%! ## Using fcm, classify the input data, print the cluster centers,
+%! ## and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
+%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
+%! cluster_centers
+%! printf ("partition entropy (with a = 2): %f\n", ...
+%!         partition_entropy (soft_partition, 2));
+%! 
+%! ## Using gustafson_kessel, classify the input data, print the cluster
+%! ## centers, and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
+%!                     [NaN NaN NaN 0]);
+%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
+%! cluster_centers
+%! printf ("partition entropy (with a = 2): %f\n\n", ...
+%!         partition_entropy (soft_partition, 2));

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m	2012-08-25 08:27:39 UTC (rev 10914)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m	2012-08-26 14:54:12 UTC (rev 10915)
@@ -41,7 +41,7 @@
 ## and @var{soft_partition} matrices, please see the documentation for function
 ## fcm.
 ##
-## @seealso{fcm, fcm_demo_1, fcm_demo_2, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2, partition_coeff, partition_entropy}
+## @seealso{fcm, gustafson_kessel, partition_coeff, partition_entropy}
 ##
 ## @end deftypefn
 
@@ -49,7 +49,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy xie beni cluster validity
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      xie_beni_index.m
-## Last-Modified: 19 Aug 2012
+## Last-Modified: 26 Aug 2012
 
 function vxb = xie_beni_index (input_data, cluster_centers, ...
                                soft_partition)
@@ -126,3 +126,77 @@
   d_sqr_min = min (min (d_sqr_matrix));
 
 endfunction
+
+##----------------------------------------------------------------------
+## Xie-Beni Index Demo #1
+##----------------------------------------------------------------------
+
+%!demo
+%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
+%! ## a small set of unlabeled data points and evaluate the quality
+%! ## of the resulting clusters.
+%!
+%! ## Note: The input_data is taken from Chapter 13, Example 17 in
+%! ##       Fuzzy Logic: Intelligence, Control and Information, by
+%! ##       J. Yen and R. Langari, Prentice Hall, 1999, page 381
+%! ##       (International Edition). 
+%! 
+%! input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
+%! number_of_clusters = 2
+%! 
+%! ## Using fcm, classify the input data, print the cluster centers,
+%! ## and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
+%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
+%! cluster_centers
+%! printf ("Xie-Beni index: %f\n", ...
+%!        xie_beni_index (input_data, cluster_centers, soft_partition));
+%! 
+%! ## Using gustafson_kessel, classify the input data, print the cluster
+%! ## centers, and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
+%!                     [NaN NaN NaN 0]);
+%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
+%! cluster_centers
+%! printf ("Xie-Beni index: %f\n\n", ...
+%!        xie_beni_index (input_data, cluster_centers, soft_partition));
+
+##----------------------------------------------------------------------
+## Xie-Beni Index Demo #2
+##----------------------------------------------------------------------
+
+%!demo
+%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
+%! ## three-dimensional unlabeled data points and evaluate the quality
+%! ## of the resulting clusters.
+%!
+%! ## Note: The input_data was selected to form three areas of
+%! ##       different shapes.
+%!
+%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
+%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
+%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
+%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
+%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13]
+%! number_of_clusters = 3
+%!
+%! ## Using fcm, classify the input data, print the cluster centers,
+%! ## and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
+%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
+%! cluster_centers
+%! printf ("Xie-Beni index: %f\n", ...
+%!        xie_beni_index (input_data, cluster_centers, soft_partition));
+%! 
+%! ## Using gustafson_kessel, classify the input data, print the cluster
+%! ## centers, and calculate and print the partition coefficient.
+%! [cluster_centers, soft_partition, obj_fcn_history] = ...
+%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
+%!                     [NaN NaN NaN 0]);
+%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
+%! cluster_centers
+%! printf ("Xie-Beni index: %f\n\n", ...
+%!        xie_beni_index (input_data, cluster_centers, soft_partition));

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[Octave-cvsupdate] SF.net SVN: octave:[11097] trunk/octave-forge/main/fuzzy-logic-toolkit/inst

[<lm...@us...>]

Revision: 11097
          http://octave.svn.sourceforge.net/octave/?rev=11097&view=rev
Author:   lmarkov
Date:     2012-10-03 00:38:09 +0000 (Wed, 03 Oct 2012)
Log Message:
-----------
M    inst/hamacher_product.m
M    inst/partition_coeff.m
M    inst/heart_disease_risk.fis
M    inst/einstein_product.m
M    inst/mamdani_tip_calculator.fis
M    inst/sugeno_tip_demo.m
M    inst/cubic_approx_demo.m
M    inst/drastic_product.m
M    inst/linear_tip_demo.m
M    inst/hamacher_sum.m
M    inst/rmmf.m
M    inst/einstein_sum.m
M    inst/fcm.m
M    inst/xie_beni_index.m
M    inst/sugeno_tip_calculator.fis
M    inst/drastic_sum.m
M    inst/investment_portfolio.fis
M    inst/gustafson_kessel.m
M    inst/cubic_approximator.fis
M    inst/linear_tip_calculator.fis
M    inst/heart_disease_demo_1.m
M    inst/heart_disease_demo_2.m
M    inst/partition_entropy.m

Modified Paths:
--------------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approximator.fis
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_risk.fis
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/investment_portfolio.fis
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_calculator.fis
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/mamdani_tip_calculator.fis
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/rmmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_calculator.fis
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -41,7 +41,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy tests demos
 ## Directory:     fuzzy-logic-toolkit/inst
 ## Filename:      cubic_approx_demo.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 ## Read the FIS structure from a file.
 fis = readfis ('cubic_approximator.fis');

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approximator.fis
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approximator.fis	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approximator.fis	2012-10-03 00:38:09 UTC (rev 11097)
@@ -1,3 +1,27 @@
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fis
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      cubic_approximator.fis
+## Last-Modified: 28 Aug 2012
+
 [System]
 Name='Cubic-Approximator'
 Type='sugeno'

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -44,7 +44,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy drastic_product
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      drastic_product.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 function retval = drastic_product (x, y = 0)
   if (nargin == 0 || nargin > 2 ||

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -44,7 +44,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy drastic_sum
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      drastic_sum.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 function retval = drastic_sum  (x, y = 0)
   if (nargin == 0 || nargin > 2 ||

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -39,7 +39,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy einstein_product
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      einstein_product.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 function retval = einstein_product (x, y = 0)
   if (nargin == 0 || nargin > 2 ||

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -38,7 +38,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy einstein_sum
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      einstein_sum.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 function retval = einstein_sum (x, y = 0)
   if (nargin == 0 || nargin > 2 ||

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -25,10 +25,12 @@
 ## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} fcm (@var{input_data}, @var{num_clusters}, [@var{m}, @var{max_iterations}, @var{epsilon}, @var{display_intermediate_results}])
 ##
 ## Using the Fuzzy C-Means algorithm, calculate and return the soft partition
-## of a set of unlabeled data points. 
+## of a set of unlabeled data points.
 ##
 ## Also, if @var{display_intermediate_results} is true, display intermediate 
-## results after each iteration.
+## results after each iteration. Note that because the initial cluster
+## prototypes are randomly selected locations in the ranges determined by the
+## input data, the results of this function are nondeterministic.
 ##
 ## The required arguments to fcm are:
 ## @itemize @w
@@ -111,10 +113,10 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      fcm.m
-## Last-Modified: 26 Aug 2012
+## Last-Modified: 5 Sep 2012
 
 function [cluster_centers, soft_partition, obj_fcn_history] = ...
            fcm (input_data, num_clusters, options = [2.0, 100, 1e-5, 1])
@@ -175,8 +177,8 @@
   fcm_private (X, k, m, max_iterations, epsilon, ...
                display_intermediate_results)
 
-  ## Initialize the prototype and the calculation.
-  V = fcm_init_prototype (X, k);
+  ## Initialize the prototypes and the calculation.
+  V = init_cluster_prototypes (X, k);
   obj_fcn_history = zeros (max_iterations);
   convergence_criterion = epsilon + 1;
   iteration = 0;
@@ -191,18 +193,18 @@
   while (convergence_criterion > epsilon && ...
          ++iteration <= max_iterations)
     V_previous = V;
-    Mu = fcm_update_membership_fcn (V, X, m, k, n, sqr_dist);
+    Mu = update_cluster_membership (V, X, m, k, n, sqr_dist);
     Mu_m = Mu .^ m;
-    V = fcm_update_cluster_centers (Mu_m, X, k);
+    V = update_cluster_prototypes (Mu_m, X, k);
     sqr_dist = square_distance_matrix (X, V);
     obj_fcn_history(iteration) = ...
-      fcm_compute_objective_fcn (Mu_m, sqr_dist);
+      compute_cluster_obj_fcn (Mu_m, sqr_dist);
     if (display_intermediate_results)
       printf ("Iteration count = %d,  Objective fcn = %8.6f\n", ...
                iteration, obj_fcn_history(iteration));
     endif
     convergence_criterion = ...
-      fcm_compute_convergence_criterion (V, V_previous);
+      compute_cluster_convergence (V, V_previous);
   endwhile
 
   ## Remove extraneous entries from the tail of the objective
@@ -219,15 +221,18 @@
 
 %!demo
 %! ## This demo:
-%! ##    - classifies a small set of unlabeled data points using the
-%! ##      Fuzzy C-Means algorithm into two fuzzy clusters
+%! ##    - classifies a small set of unlabeled data points using
+%! ##      the Fuzzy C-Means algorithm into two fuzzy clusters
 %! ##    - plots the input points together with the cluster centers
+%! ##    - evaluates the quality of the resulting clusters using
+%! ##      three validity measures: the partition coefficient, the
+%! ##      partition entropy, and the Xie-Beni validity index
 %! ##
 %! ## Note: The input_data is taken from Chapter 13, Example 17 in
 %! ##       Fuzzy Logic: Intelligence, Control and Information, by
 %! ##       J. Yen and R. Langari, Prentice Hall, 1999, page 381
 %! ##       (International Edition). 
-%! 
+%!
 %! ## Use fcm to classify the input_data.
 %! input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4];
 %! number_of_clusters = 2;
@@ -241,14 +246,14 @@
 %!         'marker', 'x', 'color', 'b');
 %!   hold on;
 %! endfor
-%! 
+%!
 %! ## Plot the cluster centers as larger red *'s.
 %! for i = 1 : number_of_clusters
 %!   plot (cluster_centers(i, 1), cluster_centers(i, 2), ...
 %!         'LineWidth', 4, 'marker', '*', 'color', 'r');
 %!   hold on;
 %! endfor
-%! 
+%!
 %! ## Make the figure look a little better:
 %! ##    - scale and label the axes
 %! ##    - show gridlines
@@ -258,6 +263,15 @@
 %! ylabel ('Feature 2');
 %! grid
 %! hold
+%! 
+%! ## Calculate and print the three validity measures.
+%! printf ("Partition Coefficient: %f\n", ...
+%!         partition_coeff (soft_partition));
+%! printf ("Partition Entropy (with a = 2): %f\n", ...
+%!         partition_entropy (soft_partition, 2));
+%! printf ("Xie-Beni Index: %f\n\n", ...
+%!         xie_beni_index (input_data, cluster_centers, ...
+%!         soft_partition));
 
 ##----------------------------------------------------------------------
 ## FCM Demo #2
@@ -265,19 +279,23 @@
 
 %!demo
 %! ## This demo:
-%! ##    - classifies three-dimensional unlabeled data points using the
-%! ##      Fuzzy C-Means algorithm into three fuzzy clusters
+%! ##    - classifies three-dimensional unlabeled data points using
+%! ##      the Fuzzy C-Means algorithm into three fuzzy clusters
 %! ##    - plots the input points together with the cluster centers
+%! ##    - evaluates the quality of the resulting clusters using
+%! ##      three validity measures: the partition coefficient, the
+%! ##      partition entropy, and the Xie-Beni validity index
 %! ##
 %! ## Note: The input_data was selected to form three areas of
 %! ##       different shapes.
 %! 
 %! ## Use fcm to classify the input_data.
-%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
-%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
-%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
-%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
-%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13];
+%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7;
+%!               3 11 6; 3 12 5; 3 13 7; 1 1 10; 1 3 9; 2 2 11;
+%!               3 1 9; 3 3 10; 3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9;
+%!               6 6 10; 9 10 12; 9 12 13; 9 13 14; 10 9 13; 10 13 12;
+%!               11 10 14; 11 12 13; 12 6 12; 12 7 15; 12 9 15;
+%!               14 6 14; 14 8 13];
 %! number_of_clusters = 3;
 %! [cluster_centers, soft_partition, obj_fcn_history] = ...
 %!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0])
@@ -291,8 +309,8 @@
 %!   hold on;
 %! endfor
 %! 
-%! ## Plot the cluster centers in two dimensions (using features 1 & 2)
-%! ## as larger red *'s.
+%! ## Plot the cluster centers in two dimensions
+%! ## (using features 1 & 2) as larger red *'s.
 %! for i = 1 : number_of_clusters
 %!   plot (cluster_centers(i, 1), cluster_centers(i, 2), ...
 %!         'LineWidth', 4, 'marker', '*', 'color', 'r');
@@ -309,8 +327,8 @@
 %! grid
 %! hold
 %! 
-%! ## Plot the data points in two dimensions (using features 1 & 3)
-%! ## as small blue x's.
+%! ## Plot the data points in two dimensions
+%! ## (using features 1 & 3) as small blue x's.
 %! figure ('NumberTitle', 'off', 'Name', 'FCM Demo 2');
 %! for i = 1 : rows (input_data)
 %!   plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, ...
@@ -318,8 +336,8 @@
 %!   hold on;
 %! endfor
 %! 
-%! ## Plot the cluster centers in two dimensions (using features 1 & 3)
-%! ## as larger red *'s.
+%! ## Plot the cluster centers in two dimensions
+%! ## (using features 1 & 3) as larger red *'s.
 %! for i = 1 : number_of_clusters
 %!   plot (cluster_centers(i, 1), cluster_centers(i, 3), ...
 %!         'LineWidth', 4, 'marker', '*', 'color', 'r');
@@ -335,3 +353,12 @@
 %! ylabel ('Feature 3');
 %! grid
 %! hold
+%! 
+%! ## Calculate and print the three validity measures.
+%! printf ("Partition Coefficient: %f\n", ...
+%!         partition_coeff (soft_partition));
+%! printf ("Partition Entropy (with a = 2): %f\n", ...
+%!         partition_entropy (soft_partition, 2));
+%! printf ("Xie-Beni Index: %f\n\n", ...
+%!         xie_beni_index (input_data, cluster_centers, ...
+%!         soft_partition));

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -27,10 +27,12 @@
 ## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} gustafson_kessel (@var{input_data}, @var{num_clusters}, @var{cluster_volume}, [@var{m}, @var{max_iterations}, @var{epsilon}, @var{display_intermediate_results}])
 ##
 ## Using the Gustafson-Kessel algorithm, calculate and return the soft partition
-## of a set of unlabeled data points. 
+## of a set of unlabeled data points.
 ##
 ## Also, if @var{display_intermediate_results} is true, display intermediate 
-## results after each iteration.
+## results after each iteration. Note that because the initial cluster
+## prototypes are randomly selected locations in the ranges determined by the
+## input data, the results of this function are nondeterministic.
 ##
 ## The required arguments to gustafson_kessel are:
 ## @itemize @w
@@ -119,7 +121,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gustafson_kessel.m
-## Last-Modified: 26 Aug 2012
+## Last-Modified: 5 Sep 2012
 
 function [cluster_centers, soft_partition, obj_fcn_history] = ...
            gustafson_kessel (input_data, num_clusters, ...
@@ -194,8 +196,8 @@
   gustafson_kessel_private (X, k, cluster_volume, m, max_iterations, ...
                             epsilon, display_intermediate_results)
 
-  ## Initialize the prototype and the calculation.
-  V = fcm_init_prototype (X, k);
+  ## Initialize the prototypes and the calculation.
+  V = init_cluster_prototypes (X, k);
   obj_fcn_history = zeros (max_iterations);
   convergence_criterion = epsilon + 1;
   iteration = 0;
@@ -210,18 +212,18 @@
   while (convergence_criterion > epsilon && ...
          ++iteration <= max_iterations)
     V_previous = V;
-    Mu = fcm_update_membership_fcn (V, X, m, k, n, sqr_dist);
+    Mu = update_cluster_membership (V, X, m, k, n, sqr_dist);
     Mu_m = Mu .^ m;
-    V = fcm_update_cluster_centers (Mu_m, X, k);
+    V = update_cluster_prototypes (Mu_m, X, k);
     sqr_dist = gk_square_distance_matrix (X, V, Mu_m, cluster_volume);
     obj_fcn_history(iteration) = ...
-      fcm_compute_objective_fcn (Mu_m, sqr_dist);
+      compute_cluster_obj_fcn (Mu_m, sqr_dist);
     if (display_intermediate_results)
       printf ("Iteration count = %d,  Objective fcn = %8.6f\n", ...
                iteration, obj_fcn_history(iteration));
     endif
     convergence_criterion = ...
-      fcm_compute_convergence_criterion (V, V_previous);
+      compute_cluster_convergence (V, V_previous);
   endwhile
 
   ## Remove extraneous entries from the tail of the objective ...
@@ -289,9 +291,12 @@
 
 %!demo
 %! ## This demo:
-%! ##    - classifies a small set of unlabeled data points using the
-%! ##      Gustafson-Kessel algorithm into two fuzzy clusters
+%! ##    - classifies a small set of unlabeled data points using
+%! ##      the Gustafson-Kessel algorithm into two fuzzy clusters
 %! ##    - plots the input points together with the cluster centers
+%! ##    - evaluates the quality of the resulting clusters using
+%! ##      three validity measures: the partition coefficient, the
+%! ##      partition entropy, and the Xie-Beni validity index
 %! ##
 %! ## Note: The input_data is taken from Chapter 13, Example 17 in
 %! ##       Fuzzy Logic: Intelligence, Control and Information, by
@@ -314,8 +319,8 @@
 %! 
 %! ## Plot the cluster centers as larger red *'s.
 %! for i = 1 : number_of_clusters
-%!   plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
-%!         4, 'marker', '*', 'color', 'r');
+%!   plot (cluster_centers(i, 1), cluster_centers(i, 2), ...
+%!         'LineWidth', 4, 'marker', '*', 'color', 'r');
 %!   hold on;
 %! endfor
 %! 
@@ -328,26 +333,39 @@
 %! ylabel ('Feature 2');
 %! grid
 %! hold
-
+%! 
+%! ## Calculate and print the three validity measures.
+%! printf ("Partition Coefficient: %f\n", ...
+%!         partition_coeff (soft_partition));
+%! printf ("Partition Entropy (with a = 2): %f\n", ...
+%!         partition_entropy (soft_partition, 2));
+%! printf ("Xie-Beni Index: %f\n\n", ...
+%!         xie_beni_index (input_data, cluster_centers, ...
+%!         soft_partition));
+ 
 ##----------------------------------------------------------------------
 ## Gustafson-Kessel Demo #2
 ##----------------------------------------------------------------------
 
 %!demo
 %! ## This demo:
-%! ##    - classifies three-dimensional unlabeled data points using the
-%! ##      Gustafson-Kessel algorithm into three fuzzy clusters
+%! ##    - classifies three-dimensional unlabeled data points using
+%! ##      the Gustafson-Kessel algorithm into three fuzzy clusters
 %! ##    - plots the input points together with the cluster centers
+%! ##    - evaluates the quality of the resulting clusters using
+%! ##      three validity measures: the partition coefficient, the
+%! ##      partition entropy, and the Xie-Beni validity index
 %! ##
 %! ## Note: The input_data was selected to form three areas of
 %! ##       different shapes.
 %! 
 %! ## Use gustafson_kessel to classify the input_data.
-%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
-%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
-%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
-%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
-%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13];
+%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7;
+%!               3 11 6; 3 12 5; 3 13 7; 1 1 10; 1 3 9; 2 2 11;
+%!               3 1 9; 3 3 10; 3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9;
+%!               6 6 10; 9 10 12; 9 12 13; 9 13 14; 10 9 13; 10 13 12;
+%!               11 10 14; 11 12 13; 12 6 12; 12 7 15; 12 9 15;
+%!               14 6 14; 14 8 13];
 %! number_of_clusters = 3;
 %! [cluster_centers, soft_partition, obj_fcn_history] = ...
 %!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
@@ -362,11 +380,11 @@
 %!   hold on;
 %! endfor
 %! 
-%! ## Plot the cluster centers in two dimensions (using features 1 & 2)
-%! ## as larger red *'s.
+%! ## Plot the cluster centers in two dimensions
+%! ## (using features 1 & 2) as larger red *'s.
 %! for i = 1 : number_of_clusters
-%!   plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
-%!         4, 'marker', '*', 'color', 'r');
+%!   plot (cluster_centers(i, 1), cluster_centers(i, 2), ...
+%!         'LineWidth', 4, 'marker', '*', 'color', 'r');
 %!   hold on;
 %! endfor
 %! 
@@ -379,8 +397,8 @@
 %! ylabel ('Feature 2');
 %! grid
 %!  
-%! ## Plot the data points in two dimensions (using features 1 & 3)
-%! ## as small blue x's.
+%! ## Plot the data points in two dimensions
+%! ## (using features 1 & 3) as small blue x's.
 %! figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 2');
 %! for i = 1 : rows (input_data)
 %!   plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, ...
@@ -388,11 +406,11 @@
 %!   hold on;
 %! endfor
 %! 
-%! ## Plot the cluster centers in two dimensions (using features 1 & 3)
-%! ## as larger red *'s.
+%! ## Plot the cluster centers in two dimensions
+%! ## (using features 1 & 3) as larger red *'s.
 %! for i = 1 : number_of_clusters
-%!   plot (cluster_centers(i, 1), cluster_centers(i, 3), 'LineWidth', ...
-%!         4, 'marker', '*', 'color', 'r');
+%!   plot (cluster_centers(i, 1), cluster_centers(i, 3), ...
+%!         'LineWidth', 4, 'marker', '*', 'color', 'r');
 %!   hold on;
 %! endfor
 %! 
@@ -405,3 +423,12 @@
 %! ylabel ('Feature 3');
 %! grid
 %! hold
+%! 
+%! ## Calculate and print the three validity measures.
+%! printf ("Partition Coefficient: %f\n", ...
+%!         partition_coeff (soft_partition));
+%! printf ("Partition Entropy (with a = 2): %f\n", ...
+%!         partition_entropy (soft_partition, 2));
+%! printf ("Xie-Beni Index: %f\n\n", ...
+%!         xie_beni_index (input_data, cluster_centers, ...
+%!         soft_partition));

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_product.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_product.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -39,7 +39,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy hamacher_product
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      hamacher_product.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 function retval = hamacher_product (x, y = 0)
   if (nargin == 0 || nargin > 2 ||

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_sum.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_sum.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -39,7 +39,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy hamacher_sum
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      hamacher_sum.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 function retval = hamacher_sum (x, y = 0)
   if (nargin == 0 || nargin > 2 ||

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_1.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_1.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_1.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -47,7 +47,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy tests demos
 ## Directory:     fuzzy-logic-toolkit/inst
 ## Filename:      heart_disease_demo_1.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 ## Create new FIS.
 a = newfis ('Heart-Disease-Risk', 'sugeno', ...

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_2.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_2.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_2.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -45,7 +45,7 @@
 ##                Dr. Bruce Segee (University of Maine Dept. of ECE).
 ## Directory:     fuzzy-logic-toolkit/inst
 ## Filename:      heart_disease_demo_2.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 ## Read the FIS structure from a file.
 ## (Alternatively, to select heart_disease_risk.fis using the dialog,

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_risk.fis
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_risk.fis	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_risk.fis	2012-10-03 00:38:09 UTC (rev 11097)
@@ -1,5 +1,29 @@
-# Heart Disease Risk FIS
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
 
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fis
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      heart_disease_risk.fis
+## Last-Modified: 28 Aug 2012
+
+## Heart Disease Risk FIS
+
 [System]
 
   Name = 'Heart-Disease-Risk'

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/investment_portfolio.fis
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/investment_portfolio.fis	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/investment_portfolio.fis	2012-10-03 00:38:09 UTC (rev 11097)
@@ -1,3 +1,27 @@
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fis
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      investment_portfolio.fis
+## Last-Modified: 28 Aug 2012
+
 [System]
 Name='Investment-Portfolio'
 Type='mamdani'

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_calculator.fis
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_calculator.fis	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_calculator.fis	2012-10-03 00:38:09 UTC (rev 11097)
@@ -1,3 +1,27 @@
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fis
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      linear_tip_calculator.fis
+## Last-Modified: 28 Aug 2012
+
 [System]
 Name='Linear-Tip-Calculator'
 Type='sugeno'

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_demo.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_demo.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_demo.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -43,7 +43,7 @@
 ##                Dr. Bruce Segee (University of Maine Dept. of ECE).
 ## Directory:     fuzzy-logic-toolkit/inst
 ## Filename:      linear_tip_demo.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 ## Read the FIS structure from a file.
 fis = readfis ('linear_tip_calculator.fis');

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/mamdani_tip_calculator.fis
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/mamdani_tip_calculator.fis	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/mamdani_tip_calculator.fis	2012-10-03 00:38:09 UTC (rev 11097)
@@ -1,3 +1,27 @@
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fis
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      mamdani_tip_calculator.fis
+## Last-Modified: 28 Aug 2012
+
 [System]
 Name='Mamdani-Tip-Calculator'
 Type='mamdani'

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -33,6 +33,12 @@
 ## @var{vpc} - the partition coefficient for the given soft partition
 ## @end itemize
 ##
+## For demos of this function, please type:
+## @example
+## demo 'fcm'
+## demo 'gustafson_kessel'
+## @end example
+##
 ## For more information about the @var{soft_partition} matrix, please see the
 ## documentation for function fcm.
 ##
@@ -44,7 +50,7 @@
 ## Keywords:      fuzzy-logic-toolkit partition coefficient cluster
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      partition_coeff.m
-## Last-Modified: 26 Aug 2012
+## Last-Modified: 4 Sep 2012
 
 ##----------------------------------------------------------------------
 ## Note: This function is an implementation of Equation 13.9 (corrected
@@ -78,77 +84,3 @@
   vpc = (sum (sum (soft_part_sqr))) / columns (soft_partition);
 
 endfunction
-
-##----------------------------------------------------------------------
-## Partition Coefficient Demo #1
-##----------------------------------------------------------------------
-
-%!demo
-%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
-%! ## a small set of unlabeled data points and evaluate the quality
-%! ## of the resulting clusters.
-%!
-%! ## Note: The input_data is taken from Chapter 13, Example 17 in
-%! ##       Fuzzy Logic: Intelligence, Control and Information, by
-%! ##       J. Yen and R. Langari, Prentice Hall, 1999, page 381
-%! ##       (International Edition). 
-%! 
-%! input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
-%! number_of_clusters = 2
-%! 
-%! ## Using fcm, classify the input data, print the cluster centers,
-%! ## and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
-%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
-%! cluster_centers
-%! printf ("partition coefficient: %f\n", ...
-%!         partition_coeff (soft_partition));
-%! 
-%! ## Using gustafson_kessel, classify the input data, print the cluster
-%! ## centers, and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
-%!                     [NaN NaN NaN 0]);
-%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
-%! cluster_centers
-%! printf ("partition coefficient: %f\n\n", ...
-%!         partition_coeff (soft_partition));
-
-##----------------------------------------------------------------------
-## Partition Coefficient Demo #2
-##----------------------------------------------------------------------
-
-%!demo
-%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
-%! ## three-dimensional unlabeled data points and evaluate the quality
-%! ## of the resulting clusters.
-%!
-%! ## Note: The input_data was selected to form three areas of
-%! ##       different shapes.
-%!
-%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
-%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
-%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
-%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
-%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13]
-%! number_of_clusters = 3
-%!
-%! ## Using fcm, classify the input data, print the cluster centers,
-%! ## and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
-%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
-%! cluster_centers
-%! printf ("partition coefficient: %f\n", ...
-%!         partition_coeff (soft_partition));
-%! 
-%! ## Using gustafson_kessel, classify the input data, print the cluster
-%! ## centers, and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
-%!                     [NaN NaN NaN 0]);
-%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
-%! cluster_centers
-%! printf ("partition coefficient: %f\n\n", ...
-%!         partition_coeff (soft_partition));

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -35,6 +35,12 @@
 ## @var{vpe} - the partition entropy for the given soft partition
 ## @end itemize
 ##
+## For demos of this function, please type:
+## @example
+## demo 'fcm'
+## demo 'gustafson_kessel'
+## @end example
+##
 ## For more information about the @var{soft_partition} matrix, please see the
 ## documentation for function fcm.
 ##
@@ -46,7 +52,7 @@
 ## Keywords:      fuzzy-logic-toolkit partition entropy cluster
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      partition_entropy.m
-## Last-Modified: 26 Aug 2012
+## Last-Modified: 4 Sep 2012
 
 ##----------------------------------------------------------------------
 ## Note: This function is an implementation of Equation 13.10 in
@@ -86,77 +92,3 @@
   vpe = -(sum (sum (Mu .* log_a_Mu))) / n;
 
 endfunction
-
-##----------------------------------------------------------------------
-## Partition Entropy Demo #1
-##----------------------------------------------------------------------
-
-%!demo
-%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
-%! ## a small set of unlabeled data points and evaluate the quality
-%! ## of the resulting clusters.
-%!
-%! ## Note: The input_data is taken from Chapter 13, Example 17 in
-%! ##       Fuzzy Logic: Intelligence, Control and Information, by
-%! ##       J. Yen and R. Langari, Prentice Hall, 1999, page 381
-%! ##       (International Edition). 
-%! 
-%! input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
-%! number_of_clusters = 2
-%! 
-%! ## Using fcm, classify the input data, print the cluster centers,
-%! ## and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
-%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
-%! cluster_centers
-%! printf ("partition entropy (with a = 2): %f\n", ...
-%!         partition_entropy (soft_partition, 2));
-%! 
-%! ## Using gustafson_kessel, classify the input data, print the cluster
-%! ## centers, and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
-%!                     [NaN NaN NaN 0]);
-%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
-%! cluster_centers
-%! printf ("partition entropy (with a = 2): %f\n\n", ...
-%!         partition_entropy (soft_partition, 2));
-
-##----------------------------------------------------------------------
-## Partition Entropy Demo #2
-##----------------------------------------------------------------------
-
-%!demo
-%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
-%! ## three-dimensional unlabeled data points and evaluate the quality
-%! ## of the resulting clusters.
-%!
-%! ## Note: The input_data was selected to form three areas of
-%! ##       different shapes.
-%!
-%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
-%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
-%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
-%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
-%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13]
-%! number_of_clusters = 3
-%!
-%! ## Using fcm, classify the input data, print the cluster centers,
-%! ## and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
-%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
-%! cluster_centers
-%! printf ("partition entropy (with a = 2): %f\n", ...
-%!         partition_entropy (soft_partition, 2));
-%! 
-%! ## Using gustafson_kessel, classify the input data, print the cluster
-%! ## centers, and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
-%!                     [NaN NaN NaN 0]);
-%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
-%! cluster_centers
-%! printf ("partition entropy (with a = 2): %f\n\n", ...
-%!         partition_entropy (soft_partition, 2));

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/rmmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/rmmf.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/rmmf.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -46,7 +46,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy membership
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      rmmf.m
-## Last-Modified: 16 Jul 2011
+## Last-Modified: 20 Aug 2012
 
 function fis = rmmf (fis, in_or_out, var_index, mf, mf_index)
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_calculator.fis
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_calculator.fis	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_calculator.fis	2012-10-03 00:38:09 UTC (rev 11097)
@@ -1,3 +1,27 @@
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fis
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      sugeno_tip_calculator.fis
+## Last-Modified: 28 Aug 2012
+
 % Sugeno Tip Calculator
 
 % Computes cheap, average, and generous tips

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_demo.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_demo.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_demo.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -49,7 +49,7 @@
 ##                Dr. Bruce Segee (University of Maine Dept. of ECE).
 ## Directory:     fuzzy-logic-toolkit/inst
 ## Filename:      sugeno_tip_demo.m
-## Last-Modified: 10 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 ## Read the FIS structure from a file.
 fis = readfis ('sugeno_tip_calculator.fis');

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m	2012-10-03 00:37:18 UTC (rev 11096)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m	2012-10-03 00:38:09 UTC (rev 11097)
@@ -37,6 +37,12 @@
 ## @var{vxb} - the Xie-Beni validity index for the given partition
 ## @end itemize
 ##
+## For demos of this function, please type:
+## @example
+## demo 'fcm'
+## demo 'gustafson_kessel'
+## @end example
+##
 ## For more information about the @var{input_data}, @var{cluster_centers},
 ## and @var{soft_partition} matrices, please see the documentation for function
 ## fcm.
@@ -49,7 +55,7 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy xie beni cluster validity
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      xie_beni_index.m
-## Last-Modified: 26 Aug 2012
+## Last-Modified: 4 Sep 2012
 
 function vxb = xie_beni_index (input_data, cluster_centers, ...
                                soft_partition)
@@ -126,77 +132,3 @@
   d_sqr_min = min (min (d_sqr_matrix));
 
 endfunction
-
-##----------------------------------------------------------------------
-## Xie-Beni Index Demo #1
-##----------------------------------------------------------------------
-
-%!demo
-%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
-%! ## a small set of unlabeled data points and evaluate the quality
-%! ## of the resulting clusters.
-%!
-%! ## Note: The input_data is taken from Chapter 13, Example 17 in
-%! ##       Fuzzy Logic: Intelligence, Control and Information, by
-%! ##       J. Yen and R. Langari, Prentice Hall, 1999, page 381
-%! ##       (International Edition). 
-%! 
-%! input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
-%! number_of_clusters = 2
-%! 
-%! ## Using fcm, classify the input data, print the cluster centers,
-%! ## and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
-%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
-%! cluster_centers
-%! printf ("Xie-Beni index: %f\n", ...
-%!        xie_beni_index (input_data, cluster_centers, soft_partition));
-%! 
-%! ## Using gustafson_kessel, classify the input data, print the cluster
-%! ## centers, and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
-%!                     [NaN NaN NaN 0]);
-%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
-%! cluster_centers
-%! printf ("Xie-Beni index: %f\n\n", ...
-%!        xie_beni_index (input_data, cluster_centers, soft_partition));
-
-##----------------------------------------------------------------------
-## Xie-Beni Index Demo #2
-##----------------------------------------------------------------------
-
-%!demo
-%! ## Use the Fuzzy C-Means and Gustafson-Kessel algorithms to classify
-%! ## three-dimensional unlabeled data points and evaluate the quality
-%! ## of the resulting clusters.
-%!
-%! ## Note: The input_data was selected to form three areas of
-%! ##       different shapes.
-%!
-%! input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
-%!               3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
-%!               3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
-%!               9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14;
-%!               11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13]
-%! number_of_clusters = 3
-%!
-%! ## Using fcm, classify the input data, print the cluster centers,
-%! ## and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   fcm (input_data, number_of_clusters, [NaN NaN NaN 0]);
-%! puts ("\nResults using the Fuzzy C-Means algorithm:\n\n");
-%! cluster_centers
-%! printf ("Xie-Beni index: %f\n", ...
-%!        xie_beni_index (input_data, cluster_centers, soft_partition));
-%! 
-%! ## Using gustafson_kessel, classify the input data, print the cluster
-%! ## centers, and calculate and print the partition coefficient.
-%! [cluster_centers, soft_partition, obj_fcn_history] = ...
-%!   gustafson_kessel (input_data, number_of_clusters, [1 1 1], ...
-%!                     [NaN NaN NaN 0]);
-%! puts ("\nResults using the Gustafson-Kessel algorithm:\n\n");
-%! cluster_centers
-%! printf ("Xie-Beni index: %f\n\n", ...
-%!        xie_beni_index (input_data, cluster_centers, soft_partition));

This was sent by the SourceForge.net collaborative development platform, the world's largest Open Source development site.

[Octave-cvsupdate] SF.net SVN: octave:[10739] trunk/octave-forge/main/fuzzy-logic-toolkit/inst

[<lm...@us...>]

Revision: 10739
          http://octave.svn.sourceforge.net/octave/?rev=10739&view=rev
Author:   lmarkov
Date:     2012-07-09 13:17:11 +0000 (Mon, 09 Jul 2012)
Log Message:
-----------
A    inst/gustafson_kessel_demo_1.m
A    inst/gustafson_kessel_demo_2.m
A    inst/partition_coeff.m
A    inst/fcm.m
A    inst/xie_beni_index.m
A    inst/gustafson_kessel.m
A    inst/private/square_distance_matrix.m
A    inst/private/fcm_init_prototype.m
A    inst/private/fcm_update_cluster_centers.m
A    inst/private/fcm_compute_convergence_criterion.m
A    inst/private/fcm_update_membership_fcn.m
A    inst/private/fcm_compute_objective_fcn.m
A    inst/fcm_demo_1.m
A    inst/partition_entropy.m
A    inst/fcm_demo_2.m

Added Paths:
-----------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_compute_convergence_criterion.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_compute_objective_fcn.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_init_prototype.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_update_cluster_centers.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_update_membership_fcn.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/square_distance_matrix.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,204 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{cluster_centers} =} fcm (@var{input_data}, @var{num_clusters})
+## @deftypefnx {Function File} {@var{cluster_centers} =} fcm (@var{input_data}, @var{num_clusters}, @var{options})
+## @deftypefnx {Function File} {@var{cluster_centers} =} fcm (@var{input_data}, @var{num_clusters}, [@var{m}, @var{max_iterations}, @var{epsilon}, @var{display_intermediate_results}])
+## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} fcm (@var{input_data}, @var{num_clusters})
+## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} fcm (@var{input_data}, @var{num_clusters}, @var{options})
+## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} fcm (@var{input_data}, @var{num_clusters}, [@var{m}, @var{max_iterations}, @var{epsilon}, @var{display_intermediate_results}])
+##
+## Return the soft partition of a set of unlabeled data points. 
+## Also, if @var{display_intermediate_results} is true, display intermediate 
+## results after each iteration.
+##
+## The required arguments to fcm are:
+## @itemize @w
+## @item
+## @var{input_data} - a matrix of input data points; each row corresponds to one point
+## @item
+## @var{num_clusters} - the number of clusters to form
+## @end itemize
+##
+## The optional arguments to fcm are:
+## @itemize @w
+## @item
+## @var{m} - the parameter (exponent) in the objective function; default = 2.0
+## @item
+## @var{max_iterations} - the maximum number of iterations before stopping; default = 100
+## @item
+## @var{epsilon} - the stopping criteria; default = 1e-5
+## @item
+## @var{display_intermediate_results} - if 1, display results after each iteration, and if 0, do not; default = 1
+## @end itemize
+##
+## The default values are used if any of the optional arguments are missing or
+## evaluate to NaN.
+##
+## The return values are:
+## @itemize @w
+## @item
+## @var{cluster_centers} - a matrix of the cluster centers; each row corresponds to one point
+## @item
+## @var{soft_partition} - a constrained soft partition matrix
+## @item
+## @var{obj_fcn_history} - the values of the objective function after each iteration
+## @end itemize
+##
+## Three important matrices used in the calculation are X (the input points
+## to be clustered), V (the cluster centers), and Mu (the membership of each
+## data point in each cluster). Each row of X and V denotes a single point,
+## and Mu(i, j) denotes the membership degree of input point X(j, :) in the
+## cluster having center V(i, :).
+##
+## X is identical to the required argument @var{input_data}; V is identical
+## to the output @var{cluster_centers}; and Mu is identical to the output
+## @var{soft_partition}.
+##
+## If n denotes the number of input points and k denotes the number of
+## clusters to be formed, then X, V, and Mu have the dimensions:
+##
+## @example
+## @group
+##                               1    2   ...  #features
+##                          1 [                           ]
+##    X  =  input_data  =   2 [                           ]
+##                        ... [                           ]
+##                          n [                           ]
+## @end group
+## @end example
+##
+## @example
+## @group
+##                                    1    2   ...  #features
+##                               1 [                           ]
+##    V  =  cluster_centers  =   2 [                           ]
+##                             ... [                           ]
+##                               k [                           ]
+## @end group
+## @end example
+##
+## @example
+## @group
+##                                    1    2   ...   n
+##                               1 [                    ]
+##    Mu  =  soft_partition  =   2 [                    ]
+##                             ... [                    ]
+##                               k [                    ]
+## @end group
+## @end example
+##
+## @seealso{fcm_demo_1, fcm_demo_2, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2, partition_coeff, partition_entropy, xie_beni_index}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      fcm.m
+## Last-Modified: 8 July 2012
+
+function [cluster_centers, soft_partition, obj_fcn_history] = ...
+           fcm (input_data, num_clusters, options = [2.0, 100, 1e-5, 1])
+
+  ## If fcm was called with an incorrect number of arguments, or the
+  ## arguments do not have the correct type, print an error message and halt.
+
+  if ((nargin != 2) && (nargin != 3))
+    puts ("Type 'help fcm' for more information.\n");
+    error ("fcm requires 2 or 3 arguments\n");
+  elseif (!is_real_matrix (input_data))
+    puts ("Type 'help fcm' for more information.\n");
+    error ("fcm's first argument must be matrix of real numbers\n");
+  elseif (!(is_int (num_clusters) && (num_clusters > 1)))
+    puts ("Type 'help fcm' for more information.\n");
+    error ("fcm's second argument must be an integer greater than 1\n");
+  elseif (!(isreal (options) && isvector (options)))
+    puts ("Type 'help fcm' for more information.\n");
+    error ("fcm's third (optional) argument must be a vector of real numbers\n");
+  endif
+
+  ## Assign options to the more readable variable names: m, max_iterations,
+  ## epsilon, and display_intermediate_results. If options are missing or
+  ## NaN (not a number), use the default values.
+
+  default_options = [2.0, 100, 1e-5, 1];
+
+  for i = 1 : 4
+    if ((length (options) < i) || isna (options(i)) || isnan (options(i)))
+      options(i) = default_options(i);
+    endif
+  endfor
+
+  m = options(1);
+  max_iterations = options(2);
+  epsilon = options(3);
+  display_intermediate_results = options(4);
+
+  ## Call a private function to compute the output.
+
+  [cluster_centers, soft_partition, obj_fcn_history] = ...
+    fcm_private (input_data, num_clusters, m, max_iterations, epsilon,
+                 display_intermediate_results);
+endfunction
+
+##------------------------------------------------------------------------------
+## Note: This function (fcm_private) is an implementation of Figure 13.4 in
+##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
+##       R. Langari, Prentice Hall, 1999, page 380 (International Edition)
+##       and Algorithm 4.1 in Fuzzy and Neural Control, by Robert Babuska,
+##       November 2009, p. 63.
+##------------------------------------------------------------------------------
+
+function [V, Mu, obj_fcn_history] = ...
+  fcm_private (X, k, m, max_iterations, epsilon, display_intermediate_results)
+
+  ## Initialize the prototype and the calculation.
+  V = fcm_init_prototype (X, k);
+  obj_fcn_history = zeros (max_iterations);
+  convergence_criterion = epsilon + 1;
+  iteration = 0;
+
+  ## Calculate a few numbers here to reduce redundant computation.
+  k = rows (V);
+  n = rows (X);
+  sqr_dist = square_distance_matrix (X, V);
+
+  ## Loop until the objective function is within tolerance or the maximum
+  ## number of iterations has been reached.
+  while (convergence_criterion > epsilon && ++iteration <= max_iterations)
+    V_previous = V;
+    Mu = fcm_update_membership_fcn (V, X, m, k, n, sqr_dist);
+    Mu_m = Mu .^ m;
+    V = fcm_update_cluster_centers (Mu_m, X, k);
+    sqr_dist = square_distance_matrix (X, V);
+    obj_fcn_history(iteration) = fcm_compute_objective_fcn (Mu_m, sqr_dist);
+    if (display_intermediate_results)
+      printf ("Iteration count = %d,  Objective fcn = %8.6f\n", ...
+               iteration, obj_fcn_history(iteration));
+    endif
+    convergence_criterion = fcm_compute_convergence_criterion (V, V_previous);
+  endwhile
+
+  ## Remove extraneous entries from the tail of the objective function history.
+  if (convergence_criterion <= epsilon)
+    obj_fcn_history = obj_fcn_history(1 : iteration);
+  endif
+
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,90 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Script File} {} fcm_demo_1
+## Use the Fuzzy C-Means algorithm to classify unlabeled data points and
+## evaluate the quality of the resulting clusters.
+##
+## This demo:
+## @itemize @minus
+## @item
+## classifies a small set of unlabeled data points using the Fuzzy C-Means
+## algorithm into two fuzzy clusters
+## @item
+## calculates and prints (on standard output) three validity measures:
+## the partition coefficient, the partition entropy, and the Xie-Beni
+## validity index
+## @item
+## plots the input points together with the cluster centers
+## @end itemize
+##
+## For a description of the data structures used in the script, see the
+## documentation for fcm.
+##
+## @seealso{fcm, fcm_demo_2, partition_coeff, partition_entropy, xie_beni_index, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm demo
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      fcm_demo_1.m
+## Last-Modified: 8 July 2012
+
+##------------------------------------------------------------------------------
+## Note: The input_data is taken from Chapter 13, Example 17 in
+##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
+##       R. Langari, Prentice Hall, 1999, page 381 (International Edition). 
+##------------------------------------------------------------------------------
+
+## Use fcm to classify the data in matrix x.
+input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
+number_of_clusters = 2
+[cluster_centers, soft_partition, obj_fcn_history] = ...
+  fcm (input_data, number_of_clusters)
+
+## Calculate and print the three validity measures.
+printf ("Partition Coefficient: %f\n", partition_coeff (soft_partition));
+printf ("Partition Entropy (with a = 2): %f\n", partition_entropy (soft_partition, 2));
+printf ("Xie-Beni Index: %f\n\n", xie_beni_index (input_data, cluster_centers, soft_partition));
+ 
+## Plot the data points as small blue x's.
+figure ('NumberTitle', 'off', 'Name', 'FCM Demo 1');
+for i = 1 : rows (input_data)
+  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, 'marker', 'x', ...
+        'color', 'b');
+  hold on;
+endfor
+
+## Plot the cluster centers as larger red *'s.
+for i = 1 : number_of_clusters
+  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', 4, ...
+        'marker', '*', 'color', 'r');
+  hold on;
+endfor
+
+## Make the figure look a little better:
+##   -- scale and label the axes
+##   -- show gridlines
+xlim ([0 15]);
+ylim ([0 15]);
+xlabel ('Feature 1');
+ylabel ('Feature 2');
+grid
+hold

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,121 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Script File} {} fcm_demo_2
+## Use the Fuzzy C-Means algorithm to classify unlabeled data points and
+## evaluate the quality of the resulting clusters.
+##
+## The demo:
+## @itemize @minus
+## @item
+## classifies three-dimensional unlabeled data points using the Fuzzy
+## C-Means algorithm into three fuzzy clusters
+## @item
+## calculates and prints (on standard output) three validity measures:
+## the partition coefficient, the partition entropy, and the Xie-Beni
+## validity index
+## @item
+## plots the input points together with the cluster centers
+## @end itemize
+##
+## For a description of the data structures used in the script, see the
+## documentation for fcm.
+##
+## @seealso{fcm, fcm_demo_1, partition_coeff, partition_entropy, xie_beni_index, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm demo
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      fcm_demo_2.m
+## Last-Modified: 8 July 2012
+
+##------------------------------------------------------------------------------
+## Note: The input_data was selected to form three areas of different shapes.
+##------------------------------------------------------------------------------
+
+## Use fcm to classify the data in matrix x.
+input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6; 3 12 5;
+              3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10; 3 5 11; 4 4 9;
+              4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12; 9 12 13; 9 13 14; 10 9 13;
+              10 13 12; 11 10 14; 11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14;
+              14 8 13]
+number_of_clusters = 3
+[cluster_centers, soft_partition, obj_fcn_history] = ...
+  fcm (input_data, number_of_clusters, [NaN NaN NaN 0])
+
+## Calculate and print the three validity measures.
+printf ("Partition Coefficient: %f\n", partition_coeff (soft_partition));
+printf ("Partition Entropy (with a = 2): %f\n", partition_entropy (soft_partition, 2));
+printf ("Xie-Beni Index: %f\n\n", xie_beni_index (input_data, cluster_centers, soft_partition));
+ 
+## Plot the data points in two dimensions (using features 1 and 2)
+## as small blue x's.
+figure ('NumberTitle', 'off', 'Name', 'FCM Demo 2');
+for i = 1 : rows (input_data)
+  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, 'marker', 'x', ...
+        'color', 'b');
+  hold on;
+endfor
+
+## Plot the cluster centers in two dimensions (using features 1 and 2)
+## as larger red *'s.
+for i = 1 : number_of_clusters
+  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', 4, ...
+        'marker', '*', 'color', 'r');
+  hold on;
+endfor
+
+## Make the figure look a little better:
+##   -- scale and label the axes
+##   -- show gridlines
+xlim ([0 15]);
+ylim ([0 15]);
+xlabel ('Feature 1');
+ylabel ('Feature 2');
+grid
+hold
+
+## Plot the data points in two dimensions (using features 1 and 3)
+## as small blue x's.
+figure ('NumberTitle', 'off', 'Name', 'FCM Demo 2');
+for i = 1 : rows (input_data)
+  plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, 'marker', 'x', ...
+        'color', 'b');
+  hold on;
+endfor
+
+## Plot the cluster centers in two dimensions (using features 1 and 3)
+## as larger red *'s.
+for i = 1 : number_of_clusters
+  plot (cluster_centers(i, 1), cluster_centers(i, 3), 'LineWidth', 4, ...
+        'marker', '*', 'color', 'r');
+  hold on;
+endfor
+
+## Make the figure look a little better:
+##   -- scale and label the axes
+##   -- show gridlines
+xlim ([0 15]);
+ylim ([0 15]);
+xlabel ('Feature 1');
+ylabel ('Feature 3');
+grid
+hold

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,272 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{cluster_centers} =} gustafson_kessel (@var{input_data}, @var{num_clusters})
+## @deftypefnx {Function File} {@var{cluster_centers} =} gustafson_kessel (@var{input_data}, @var{num_clusters}, @var{cluster_volume})
+## @deftypefnx {Function File} {@var{cluster_centers} =} gustafson_kessel (@var{input_data}, @var{num_clusters}, @var{cluster_volume}, @var{options})
+## @deftypefnx {Function File} {@var{cluster_centers} =} gustafson_kessel (@var{input_data}, @var{num_clusters}, @var{cluster_volume}, [@var{m}, @var{max_iterations}, @var{epsilon}, @var{display_intermediate_results}])
+## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} gustafson_kessel (@var{input_data}, @var{num_clusters})
+## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} gustafson_kessel (@var{input_data}, @var{num_clusters}, @var{cluster_volume})
+## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} gustafson_kessel (@var{input_data}, @var{num_clusters}, @var{cluster_volume}, @var{options})
+## @deftypefnx {Function File} {[@var{cluster_centers}, @var{soft_partition}, @var{obj_fcn_history}] =} gustafson_kessel (@var{input_data}, @var{num_clusters}, @var{cluster_volume}, [@var{m}, @var{max_iterations}, @var{epsilon}, @var{display_intermediate_results}])
+##
+## Return the soft partition of a set of unlabeled data points. 
+## Also, if @var{display_intermediate_results} is true, display intermediate 
+## results after each iteration.
+##
+## The required arguments to gustafson_kessel are:
+## @itemize @w
+## @item
+## @var{input_data} - a matrix of input data points; each row corresponds to one point
+## @item
+## @var{num_clusters} - the number of clusters to form
+## @end itemize
+##
+## The third (optional) argument to gustafson_kessel is a vector of cluster volumes.
+## If omitted, a vector of 1's will be used as the default.
+##
+## The fourth (optional) argument to gustafson_kessel is a vector consisting of:
+## @itemize @w
+## @item
+## @var{m} - the parameter (exponent) in the objective function; default = 2.0
+## @item
+## @var{max_iterations} - the maximum number of iterations before stopping; default = 100
+## @item
+## @var{epsilon} - the stopping criteria; default = 1e-5
+## @item
+## @var{display_intermediate_results} - if 1, display results after each iteration, and if 0, do not; default = 1
+## @end itemize
+##
+## The default values are used if any of the four elements of the vector are missing or
+## evaluate to NaN.
+##
+## The return values are:
+## @itemize @w
+## @item
+## @var{cluster_centers} - a matrix of the cluster centers; each row corresponds to one point
+## @item
+## @var{soft_partition} - a constrained soft partition matrix
+## @item
+## @var{obj_fcn_history} - the values of the objective function after each iteration
+## @end itemize
+##
+## Three important matrices used in the calculation are X (the input points
+## to be clustered), V (the cluster centers), and Mu (the membership of each
+## data point in each cluster). Each row of X and V denotes a single point,
+## and Mu(i, j) denotes the membership degree of input point X(j, :) in the
+## cluster having center V(i, :).
+##
+## X is identical to the required argument @var{input_data}; V is identical
+## to the output @var{cluster_centers}; and Mu is identical to the output
+## @var{soft_partition}.
+##
+## If n denotes the number of input points and k denotes the number of
+## clusters to be formed, then X, V, and Mu have the dimensions:
+##
+## @example
+## @group
+##                               1    2   ...  #features
+##                          1 [                           ]
+##    X  =  input_data  =   2 [                           ]
+##                        ... [                           ]
+##                          n [                           ]
+## @end group
+## @end example
+##
+## @example
+## @group
+##                                    1    2   ...  #features
+##                               1 [                           ]
+##    V  =  cluster_centers  =   2 [                           ]
+##                             ... [                           ]
+##                               k [                           ]
+## @end group
+## @end example
+##
+## @example
+## @group
+##                                    1    2   ...   n
+##                               1 [                    ]
+##    Mu  =  soft_partition  =   2 [                    ]
+##                             ... [                    ]
+##                               k [                    ]
+## @end group
+## @end example
+##
+## @seealso{fcm, fcm_demo_1, fcm_demo_2, gustafson_kessel_demo_1, gustafson_kessel_demo_2, partition_coeff, partition_entropy, xie_beni_index}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering gustafson_kessel
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      gustafson_kessel.m
+## Last-Modified: 8 July 2012
+
+function [cluster_centers, soft_partition, obj_fcn_history] = ...
+           gustafson_kessel (input_data, num_clusters, cluster_volume = [], options = [2.0, 100, 1e-5, 1])
+
+  ## If gustafson_kessel was called with an incorrect number of arguments, or the
+  ## arguments do not have the correct type, print an error message and halt.
+
+  if ((nargin < 2) || (nargin > 4))
+    puts ("Type 'help gustafson_kessel' for more information.\n");
+    error ("gustafson_kessel requires 2, 3, or 4 arguments\n");
+  elseif (!is_real_matrix (input_data))
+    puts ("Type 'help gustafson_kessel' for more information.\n");
+    error ("gustafson_kessel's first argument must be matrix of real numbers\n");
+  elseif (!(is_int (num_clusters) && (num_clusters > 1)))
+    puts ("Type 'help gustafson_kessel' for more information.\n");
+    error ("gustafson_kessel's second argument must be an integer greater than 1\n");
+  elseif (!(isequal (cluster_volume, []) || ...
+           (isreal (cluster_volume) && isvector (cluster_volume))))
+    puts ("Type 'help gustafson_kessel' for more information.\n");
+    error ("gustafson_kessel's third (optional) argument must be a vector of real numbers\n");
+  elseif (!(isreal (options) && isvector (options)))
+    puts ("Type 'help gustafson_kessel' for more information.\n");
+    error ("gustafson_kessel's fourth (optional) argument must be a vector of real numbers\n");
+  endif
+
+  ## If the cluster volume matrix was not entered, create a default value
+  ## (a vector of 1's).
+
+  if (isequal (cluster_volume, []))
+    cluster_volume = ones (1, num_clusters);
+  endif
+
+  ## Assign options to the more readable variable names: m, max_iterations,
+  ## epsilon, and display_intermediate_results. If options are missing or
+  ## NaN (not a number), use the default values.
+
+  default_options = [2.0, 100, 1e-5, 1];
+
+  for i = 1 : 4
+    if ((length (options) < i) || isna (options(i)) || isnan (options(i)))
+      options(i) = default_options(i);
+    endif
+  endfor
+
+  m = options(1);
+  max_iterations = options(2);
+  epsilon = options(3);
+  display_intermediate_results = options(4);
+
+  ## Call a private function to compute the output.
+
+  [cluster_centers, soft_partition, obj_fcn_history] = ...
+    gustafson_kessel_private (input_data, num_clusters, cluster_volume, m, ...
+                              max_iterations, epsilon, display_intermediate_results);
+endfunction
+
+##------------------------------------------------------------------------------
+## Function: gustafson_kessel_private
+## Purpose:  Classify unlabeled data points using the Gustafson-Kessel
+##           algorithm.
+## Note:     This function (gustafson_kessel_private) is an implementation of
+##           Algorithm 4.2 in Fuzzy and Neural Control, by Robert Babuska,
+##           November 2009, p. 69.
+##------------------------------------------------------------------------------
+
+function [V, Mu, obj_fcn_history] = ...
+  gustafson_kessel_private (X, k, cluster_volume, m, max_iterations, epsilon, display_intermediate_results)
+
+  ## Initialize the prototype and the calculation.
+  V = fcm_init_prototype (X, k);
+  obj_fcn_history = zeros (max_iterations);
+  convergence_criterion = epsilon + 1;
+  iteration = 0;
+
+  ## Calculate a few numbers here to reduce redundant computation.
+  k = rows (V);
+  n = rows (X);
+  sqr_dist = square_distance_matrix (X, V);
+
+  ## Loop until the objective function is within tolerance or the maximum
+  ## number of iterations has been reached.
+  while (convergence_criterion > epsilon && ++iteration <= max_iterations)
+    V_previous = V;
+    Mu = fcm_update_membership_fcn (V, X, m, k, n, sqr_dist);
+    Mu_m = Mu .^ m;
+    V = fcm_update_cluster_centers (Mu_m, X, k);
+    sqr_dist = gk_square_distance_matrix (X, V, Mu_m, cluster_volume);
+    obj_fcn_history(iteration) = fcm_compute_objective_fcn (Mu_m, sqr_dist);
+    if (display_intermediate_results)
+      printf ("Iteration count = %d,  Objective fcn = %8.6f\n", ...
+               iteration, obj_fcn_history(iteration));
+    endif
+    convergence_criterion = fcm_compute_convergence_criterion (V, V_previous);
+  endwhile
+
+  ## Remove extraneous entries from the tail of the objective function history.
+  if (convergence_criterion <= epsilon)
+    obj_fcn_history = obj_fcn_history(1 : iteration);
+  endif
+
+endfunction
+
+##------------------------------------------------------------------------------
+## Function: gk_square_distance_matrix
+##------------------------------------------------------------------------------
+
+function sqr_dist = gk_square_distance_matrix (X, V, Mu_m, cluster_volume)
+
+  k = rows (V);
+  n = rows (X);
+  num_features = columns (X);
+  sqr_dist = zeros (k, n);
+
+  for i = 1 : k
+    Vi = V(i, :);
+    covariance_matrix = compute_covariance_matrix (X, V, Mu_m, i);
+
+    for j = 1 : n
+      Vi_to_Xj = X(j, :) - Vi;
+      A = cluster_volume(i) * ...
+          det (covariance_matrix) ^ (1.0 / num_features) * ...
+          inv (covariance_matrix);
+      sqr_dist(i, j) = sum (Vi_to_Xj .* (A * Vi_to_Xj')');
+
+    endfor
+
+  endfor
+
+endfunction
+
+##------------------------------------------------------------------------------
+## Function: compute_covariance_matrix
+##------------------------------------------------------------------------------
+
+function covariance_matrix = compute_covariance_matrix (X, V, Mu_m, i)
+
+  num_features = columns (V);
+  n = rows (X);
+  num = zeros (num_features);
+  denom = 0.0;
+  Vi = V(i, :);
+
+  for j = 1 : n
+    Vi_to_Xj = X(j, :) - Vi;
+    num += Mu_m(i, j) * Vi_to_Xj' * Vi_to_Xj;
+    denom += Mu_m(i, j);
+  endfor
+
+  covariance_matrix = num / denom;
+
+endfunction
+

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,90 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Script File} {} gustafson_kessel_demo_1
+## Use the Gustafson-Kessel algorithm to classify unlabeled data points and
+## evaluate the quality of the resulting clusters.
+##
+## The demo:
+## @itemize @minus
+## @item
+## classifies a small set of unlabeled data points using the Gustafson-Kessel
+## algorithm into two fuzzy clusters
+## @item
+## calculates and prints (on standard output) three validity measures:
+## the partition coefficient, the partition entropy, and the Xie-Beni
+## validity index
+## @item
+## plots the input points together with the cluster centers
+## @end itemize
+##
+## For a description of the data structures used in the script, see the
+## documentation for gustafson_kessel.
+##
+## @seealso{gustafson_kessel, gustafson_kessel_demo_2, partition_coeff, partition_entropy, xie_beni_index, fcm, fcm_demo_1, fcm_demo_2}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering gustafson_kessel demo
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      gustafson_kessel_demo_1.m
+## Last-Modified: 8 July 2012
+
+##------------------------------------------------------------------------------
+## Note: The input_data is taken from Chapter 13, Example 17 in
+##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
+##       R. Langari, Prentice Hall, 1999, page 381 (International Edition). 
+##------------------------------------------------------------------------------
+
+## Use gustafson_kessel to classify the data in matrix x.
+input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
+number_of_clusters = 2
+[cluster_centers, soft_partition, obj_fcn_history] = ...
+  gustafson_kessel (input_data, number_of_clusters)
+
+## Calculate and print the three validity measures.
+printf ("Partition Coefficient: %f\n", partition_coeff (soft_partition));
+printf ("Partition Entropy (with a = 2): %f\n", partition_entropy (soft_partition, 2));
+printf ("Xie-Beni Index: %f\n\n", xie_beni_index (input_data, cluster_centers, soft_partition));
+ 
+## Plot the data points as small blue x's.
+figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 1');
+for i = 1 : rows (input_data)
+  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, 'marker', 'x', ...
+        'color', 'b');
+  hold on;
+endfor
+
+## Plot the cluster centers as larger red *'s.
+for i = 1 : number_of_clusters
+  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', 4, ...
+        'marker', '*', 'color', 'r');
+  hold on;
+endfor
+
+## Make the figure look a little better:
+##   -- scale and label the axes
+##   -- show gridlines
+xlim ([0 15]);
+ylim ([0 15]);
+xlabel ('Feature 1');
+ylabel ('Feature 2');
+grid
+hold

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,120 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Script File} {} gustafson_kessel_demo_2
+## Use the Gustafson-Kessel algorithm to classify unlabeled data points and
+## evaluate the quality of the resulting clusters.
+##
+## The demo:
+## @itemize @minus
+## @item
+## classifies three-dimensional unlabeled data points using the
+## Gustafson-Kessel algorithm into three fuzzy clusters
+## @item
+## calculates and prints (on standard output) three validity measures:
+## the partition coefficient, the partition entropy, and the Xie-Beni
+## validity index
+## @item
+## plots the input points together with the cluster centers
+## @end itemize
+##
+## For a description of the data structures used in the script, see the
+## documentation for gustafson_kessel.
+##
+## @seealso{gustafson_kessel, gustafson_kessel_demo_1, partition_coeff, partition_entropy, xie_beni_index, fcm, fcm_demo_1, fcm_demo_2}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm demo
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      gustafson_kessel_demo_2.m
+## Last-Modified: 8 July 2012
+
+##------------------------------------------------------------------------------
+## Note: The input_data was selected to form three areas of different shapes.
+##------------------------------------------------------------------------------
+
+## Use gustafson_kessel to classify the data in matrix x.
+input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6; 3 12 5;
+              3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10; 3 5 11; 4 4 9;
+              4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12; 9 12 13; 9 13 14; 10 9 13;
+              10 13 12; 11 10 14; 11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14;
+              14 8 13]
+number_of_clusters = 3
+[cluster_centers, soft_partition, obj_fcn_history] = ...
+  gustafson_kessel (input_data, number_of_clusters, [1 1 1], [NaN NaN NaN 0])
+
+## Calculate and print the three validity measures.
+printf ("Partition Coefficient: %f\n", partition_coeff (soft_partition));
+printf ("Partition Entropy (with a = 2): %f\n", partition_entropy (soft_partition, 2));
+printf ("Xie-Beni Index: %f\n\n", xie_beni_index (input_data, cluster_centers, soft_partition));
+ 
+## Plot the data points in two dimensions (using features 1 and 2)
+## as small blue x's.
+figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 2');
+for i = 1 : rows (input_data)
+  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, 'marker', 'x', ...
+        'color', 'b');
+  hold on;
+endfor
+
+## Plot the cluster centers in two dimensions (using features 1 and 2)
+## as larger red *'s.
+for i = 1 : number_of_clusters
+  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', 4, ...
+        'marker', '*', 'color', 'r');
+  hold on;
+endfor
+
+## Make the figure look a little better:
+##   -- scale and label the axes
+##   -- show gridlines
+xlim ([0 15]);
+ylim ([0 15]);
+xlabel ('Feature 1');
+ylabel ('Feature 2');
+grid
+ 
+## Plot the data points in two dimensions (using features 1 and 3)
+## as small blue x's.
+figure ('NumberTitle', 'off', 'Name', 'Gustafson-Kessel Demo 2');
+for i = 1 : rows (input_data)
+  plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, 'marker', 'x', ...
+        'color', 'b');
+  hold on;
+endfor
+
+## Plot the cluster centers in two dimensions (using features 1 and 3)
+## as larger red *'s.
+for i = 1 : number_of_clusters
+  plot (cluster_centers(i, 1), cluster_centers(i, 3), 'LineWidth', 4, ...
+        'marker', '*', 'color', 'r');
+  hold on;
+endfor
+
+## Make the figure look a little better:
+##   -- scale and label the axes
+##   -- show gridlines
+xlim ([0 15]);
+ylim ([0 15]);
+xlabel ('Feature 1');
+ylabel ('Feature 3');
+grid
+hold

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,76 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{vpc} =} partition_coeff (@var{soft_partition})
+##
+## Return the partition coefficient for a given soft partition.
+##
+## The argument to partition_coeff is:
+## @itemize @w
+## @item
+## @var{soft_partition} - the membership degree of each input data point in each cluster
+## @end itemize
+##
+## The return value is:
+## @itemize @w
+## @item
+## @var{vpc} - the partition coefficient for the given soft partition
+## @end itemize
+##
+## For more information about the @var{soft_partition} matrix, please see the
+## documentation for function fcm.
+##
+## @seealso{fcm, fcm_demo_1, fcm_demo_2, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2, partition_entropy, xie_beni_index}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition coefficient cluster validity
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      partition_coeff.m
+## Last-Modified: 8 July 2012
+
+##------------------------------------------------------------------------------
+## Note: This function is an implementation of Equation 13.9 (corrected -- the
+##       equation in the book omits the exponent 2) in
+##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
+##       R. Langari, Prentice Hall, 1999, page 384 (International Edition). 
+##------------------------------------------------------------------------------
+
+function vpc = partition_coeff (soft_partition)
+
+  ## If partition_coeff was called with an incorrect number of arguments, or the
+  ## argument does not have the correct type, print an error message and halt.
+
+  if (nargin != 1)
+    puts ("Type 'help partition_coeff' for more information.\n");
+    error ("partition_coeff requires 1 argument\n");
+  elseif (!(is_real_matrix (soft_partition) &&
+            (min (min (soft_partition)) >= 0) &&
+            (max (max (soft_partition)) <= 1)))
+    puts ("Type 'help partition_coeff' for more information.\n");
+    error ("partition_coeff's argument must be a matrix of real numbers mu, with 0 <= mu <= 1\n");
+  endif
+
+  ## Compute and return the partition coefficient.
+
+  soft_part_sqr = soft_partition .* soft_partition;
+  vpc = (sum (sum (soft_part_sqr))) / columns (soft_partition);
+
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,82 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{vpe} =} partition_entropy (@var{soft_partition}, @var{a})
+##
+## Return the partition entropy for a given soft partition.
+##
+## The arguments to partition_entropy are:
+## @itemize @w
+## @item
+## @var{soft_partition} - the membership degree of each input data point in each cluster
+## @item
+## @var{a} - the log base to use in the calculation; must be a real number a > 1
+## @end itemize
+##
+## The return value is:
+## @itemize @w
+## @item
+## @var{vpe} - the partition entropy for the given soft partition
+## @end itemize
+##
+## For more information about the @var{soft_partition} matrix, please see the
+## documentation for function fcm.
+##
+## @seealso{fcm, fcm_demo_1, fcm_demo_2, gustafson_kessel, gustafson_kessel_demo_1, gustafson_kessel_demo_2, partition_coeff, xie_beni_index}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition entropy cluster validity
+## Directory:     fuzzy-logic-toolkit/inst/
+## Filename:      partition_entropy.m
+## Last-Modified: 8 July 2012
+
+##------------------------------------------------------------------------------
+## Note: This function is an implementation of Equation 13.10 in
+##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
+##       R. Langari, Prentice Hall, 1999, page 384 (International Edition). 
+##------------------------------------------------------------------------------
+
+function vpe = partition_entropy (soft_partition, a)
+
+  ## If partition_entropy was called with an incorrect number of arguments, or the
+  ## argument does not have the correct type, print an error message and halt.
+
+  if (nargin != 2)
+    puts ("Type 'help partition_entropy' for more information.\n");
+    error ("partition_entropy requires 2 arguments\n");
+  elseif (!(is_real_matrix (soft_partition) &&
+            (min (min (soft_partition)) >= 0) &&
+            (max (max (soft_partition)) <= 1)))
+    puts ("Type 'help partition_entropy' for more information.\n");
+    error ("partition_entropy's first argument must be a matrix of real numbers mu, with 0 <= mu <= 1\n");
+  elseif (!(is_real (a) && a > 1))
+    puts ("Type 'help partition_entropy' for more information.\n");
+    error ("partition_entropy's second argument argument must be a real number a > 1\n");
+  endif
+
+  ## Compute and return the partition entropy.
+
+  n = columns (soft_partition);
+  Mu = soft_partition;
+  log_a_Mu = log (Mu) / log (a);
+  vpe = -(sum (sum (Mu .* log_a_Mu))) / n;
+
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_compute_convergence_criterion.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_compute_convergence_criterion.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_compute_convergence_criterion.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,40 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{convergence_criterion} =} fcm_compute_convergence_criterion (@var{V}, @var{V_previous})
+##
+## Compute the sum of the changes in position (using the Euclidean
+## distance) of the cluster centers.
+##
+## @seealso{fcm, fcm_init_prototype, fcm_update_membership_fcn, fcm_update_cluster_centers, fcm_compute_objective_fcn}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm private
+## Directory:     fuzzy-logic-toolkit/inst/private/
+## Filename:      fcm_compute_convergence_criterion.m
+## Last-Modified: 7 July 2012
+
+function convergence_criterion = fcm_compute_convergence_criterion (V, V_previous)
+
+  V_delta = V - V_previous;
+  convergence_criterion = sum (sqrt (sum (V_delta .* V_delta)'));
+
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_compute_objective_fcn.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_compute_objective_fcn.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_compute_objective_fcn.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,44 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{obj_fcn} =} fcm_compute_objective_fcn (@var{Mu_m}, @var{sqr_dist})
+##
+## Compute the objective function for the current iteration.
+##
+## @seealso{fcm, fcm_init_prototype, fcm_update_membership_fcn, fcm_update_cluster_centers, fcm_compute_convergence_criterion}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm private
+## Directory:     fuzzy-logic-toolkit/inst/private/
+## Filename:      fcm_compute_objective_fcn.m
+## Last-Modified: 7 July 2012
+
+##------------------------------------------------------------------------------
+## Note:     This function is an implementation of Equation 13.3 in
+##           Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
+##           R. Langari, Prentice Hall, 1999, page 379 (International Edition). 
+##------------------------------------------------------------------------------
+
+function obj_fcn = fcm_compute_objective_fcn (Mu_m, sqr_dist)
+
+  obj_fcn = sum (sum (Mu_m .* sqr_dist));
+
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_init_prototype.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_init_prototype.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_init_prototype.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,47 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{V} =} fcm_init_prototype (@var{X}, @var{k})
+##
+## Initialize k cluster centers to random locations in the ranges
+## given by the min/max values of each feature of the dataset.
+##
+## @seealso{fcm, fcm_update_membership_fcn, fcm_update_cluster_centers, fcm_compute_objective_fcn, fcm_compute_convergence_criterion}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm private
+## Directory:     fuzzy-logic-toolkit/inst/private/
+## Filename:      fcm_init_prototype.m
+## Last-Modified: 7 July 2012
+
+function V = fcm_init_prototype (X, k)
+
+  num_features = columns (X);
+  min_feature_value = min (X);
+  max_feature_value = max (X);
+  V = rand (k, num_features);
+
+  for i = 1 : num_features
+    V(:, i) = (max_feature_value(i) - min_feature_value(i)) * V(:, i) + ...
+                min_feature_value(i);
+  endfor
+
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_update_cluster_centers.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_update_cluster_centers.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_update_cluster_centers.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,54 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{V} =} fcm_update_cluster_centers (@var{Mu_m}, @var{X}, @var{k})
+##
+## Update the cluster centers to correspond to the given membership
+## function values.
+##
+## @seealso{fcm, fcm_init_prototype, fcm_update_membership_fcn, fcm_compute_objective_fcn, fcm_compute_convergence_criterion}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm private
+## Directory:     fuzzy-logic-toolkit/inst/private/
+## Filename:      fcm_update_cluster_centers.m
+## Last-Modified: 7 July 2012
+
+##------------------------------------------------------------------------------
+## Note:     This function is an implementation of Equation 13.5 in
+##           Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
+##           R. Langari, Prentice Hall, 1999, page 380 (International Edition). 
+##------------------------------------------------------------------------------
+
+function V = fcm_update_cluster_centers (Mu_m, X, k)
+
+  V = Mu_m * X;
+  sum_Mu_m = sum (Mu_m');
+
+  if (prod (sum_Mu_m) == 0)
+    error ("division by 0 in function fcm_update_cluster_centers\n");
+  endif
+
+  for i = 1 : k
+    V(i, :) /= sum_Mu_m(i);
+  endfor
+
+endfunction

Added: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_update_membership_fcn.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_update_membership_fcn.m	                        (rev 0)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/private/fcm_update_membership_fcn.m	2012-07-09 13:17:11 UTC (rev 10739)
@@ -0,0 +1,75 @@
+## Copyright (C) 2012 L. Markowsky <lm...@us...>
+##
+## This file is part of the fuzzy-logic-toolkit.
+##
+## The fuzzy-logic-toolkit is free software; you can redistribute it
+## and/or modify it under the terms of the GNU General Public License
+## as published by the Free Software Foundation; either version 3 of
+## the License, or (at your option) any later version.
+##
+## The fuzzy-logic-toolkit is distributed in the hope that it will be
+## useful, but WITHOUT ANY WARRANTY; without even the implied warranty
+## of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+## General Public License for more details.
+##
+## You should have received a copy of the GNU General Public License
+## along with the fuzzy-logic-toolkit; see the file COPYING.  If not,
+## see <http://www.gnu.org/licenses/>.
+
+## -*- texinfo -*-
+## @deftypefn {Function File} {@var{Mu} =} fcm_update_membership_fcn (@var{V}, @var{X}, @var{m}, @var{k}, @var{n}, @var{sqr_dist})
+##
+## Compute Mu for each (cluster center, input point) pair.
+##
+## @seealso{fcm, fcm_init_prototype, fcm_update_cluster_centers, fcm_compute_objective_fcn, fcm_compute_convergence_criterion}
+##
+## @end deftypefn
+
+## Author:        L. Markowsky
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm private
+## Directory:     fuzzy-logic-toolkit/inst/private/
+## Filename:      fcm_update_membership_fcn.m
+## Last-Modified: 7 July 2012
+
+##------------------------------------------------------------------------------
+## Note:     This function is an implementation of Equation 13.4 in
+##           Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
+##           R. Langari, Prentice Hall, 1999, page 380 (International Edition)
+##           and Step 3 of Algorithm 4.1 in Fuzzy and Neural Control,
+##           by Robert Babuska, November 2009, p. 63.
+##------------------------------------------------------------------------------
+
+function Mu = fcm_update_membership_fcn (V, X, m, k, n, sqr_dist)
+
+  Mu = zeros (k, n);
+
+  if (min (min (sqr_dist)) > 0)
+    exponent = 1.0 / (m - 1);
+    for i = 1 : k
+      for j = 1 : n
+        summation = 0.0;
+        for l = 1 : k
+          summation += (sqr_dist(i, j) / sqr_dist(l, j))^exponent;
+        endfor
+        if (summation != 0)
+          Mu(i, ...
 
[truncated message content]

[Octave-cvsupdate] SF.net SVN: octave:[10909] trunk/octave-forge/main/fuzzy-logic-toolkit/inst

[<lm...@us...>]

Revision: 10909
          http://octave.svn.sourceforge.net/octave/?rev=10909&view=rev
Author:   lmarkov
Date:     2012-08-24 16:13:07 +0000 (Fri, 24 Aug 2012)
Log Message:
-----------
M    inst/getfis.m
M    inst/psigmf.m
M    inst/smf.m
M    inst/rmvar.m
M    inst/partition_entropy.m
M    inst/trapmf.m
M    inst/bounded_difference.m
M    inst/newfis.m
M    inst/pimf.m
M    inst/zmf.m
M    inst/hamacher_sum.m
M    inst/setfis.m
M    inst/plotmf.m
M    inst/rmmf.m
M    inst/einstein_sum.m
M    inst/gustafson_kessel_demo_1.m
M    inst/gustafson_kessel_demo_2.m
M    inst/defuzz.m
M    inst/gbellmf.m
M    inst/gensurf.m
M    inst/algebraic_product.m
M    inst/xie_beni_index.m
M    inst/evalmf.m
M    inst/partition_coeff.m
M    inst/gustafson_kessel.m
M    inst/sugeno_tip_demo.m
M    inst/trimf.m
M    inst/cubic_approx_demo.m
M    inst/showfis.m
M    inst/heart_disease_demo_1.m
M    inst/heart_disease_demo_2.m
M    inst/mamdani_tip_demo.m
M    inst/gauss2mf.m
M    inst/drastic_product.m
M    inst/fcm_demo_1.m
M    inst/evalfis.m
M    inst/fcm_demo_2.m
M    inst/linear_tip_demo.m
M    inst/writefis.m
M    inst/algebraic_sum.m
M    inst/investment_portfolio_demo.m
M    inst/addvar.m
M    inst/bounded_sum.m
M    inst/gaussmf.m
M    inst/fcm.m
M    inst/sigmf.m
M    inst/hamacher_product.m
M    inst/showrule.m
M    inst/dsigmf.m
M    inst/addmf.m
M    inst/drastic_sum.m
M    inst/readfis.m
M    inst/einstein_product.m
M    inst/addrule.m

Modified Paths:
--------------
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_difference.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/defuzz.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/dsigmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gauss2mf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gbellmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gensurf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gustafson_kessel_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_product.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/hamacher_sum.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_1.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/heart_disease_demo_2.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/investment_portfolio_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/linear_tip_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/mamdani_tip_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/newfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_coeff.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/partition_entropy.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/pimf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/plotmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/psigmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/readfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/rmmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/rmvar.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/setfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/showfis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/showrule.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sigmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/smf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/sugeno_tip_demo.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/trapmf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/trimf.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/writefis.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/xie_beni_index.m
    trunk/octave-forge/main/fuzzy-logic-toolkit/inst/zmf.m

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addmf.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -59,17 +59,18 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership-function membership
+## Keywords:      fuzzy-logic-toolkit fuzzy membership
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      addmf.m
 ## Note:          The demo code is based on an assignment written by
 ##                Dr. Bruce Segee (University of Maine Dept. of ECE).
-## Last-Modified: 28 Oct 2011
+## Last-Modified: 18 Aug 2012
 
-function fis = addmf (fis, in_or_out, var_index, mf_name, mf_type, mf_params)
+function fis = addmf (fis, in_or_out, var_index, mf_name, mf_type, ...
+                      mf_params)
 
-  ## If the caller did not supply 6 argument values with the correct types,
-  ## print an error message and halt.
+  ## If the caller did not supply 6 argument values with the correct
+  ## types, print an error message and halt.
 
   if (nargin != 6)
     puts ("Type 'help addmf' for more information.\n");
@@ -92,9 +93,11 @@
     error ("addmf's sixth argument must be a vector of parameters\n");
   endif
 
-  ## Create a new membership function struct and update the FIS structure.
+  ## Create a new membership function struct and update the
+  ## FIS structure.
 
-  new_mf = struct ('name', mf_name, 'type', mf_type, 'params', mf_params);
+  new_mf = struct ('name', mf_name, 'type', mf_type, 'params', ...
+                   mf_params);
   if (strcmp (tolower (in_or_out), 'input'))
     if (length (fis.input(var_index).mf) == 0)
       fis.input(var_index).mf = new_mf;
@@ -119,9 +122,12 @@
 %! ## Add two inputs and their membership functions.
 %! a = addvar (a, 'input', 'LDL-Level', [0 300]);
 %! a = addmf (a, 'input', 1, 'Low', 'trapmf', [-1 0 90 110]);
-%! a = addmf (a, 'input', 1, 'Low-Borderline', 'trapmf', [90 110 120 140]);
-%! a = addmf (a, 'input', 1, 'Borderline', 'trapmf', [120 140 150 170]);
-%! a = addmf (a, 'input', 1, 'High-Borderline', 'trapmf', [150 170 180 200]);
+%! a = addmf (a, 'input', 1, 'Low-Borderline', 'trapmf', ...
+%!            [90 110 120 140]);
+%! a = addmf (a, 'input', 1, 'Borderline', 'trapmf', ...
+%!            [120 140 150 170]);
+%! a = addmf (a, 'input', 1, 'High-Borderline', 'trapmf', ...
+%!            [150 170 180 200]);
 %! a = addmf (a, 'input', 1, 'High', 'trapmf', [180 200 300 301]);
 %! 
 %! a = addvar (a, 'input', 'HDL-Level', [0 100]);

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addrule.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -84,12 +84,12 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy rule
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      addrule.m
-## Last-Modified: 11 Nov 2011
+## Last-Modified: 18 Aug 2012
 
 function fis = addrule (fis, rule_matrix) 
 
-  ## If the caller did not supply 2 argument values with the correct types,
-  ## print an error message and halt.
+  ## If the caller did not supply 2 argument values with the correct
+  ## types, print an error message and halt.
 
   if (nargin != 2)
     puts ("Type 'help addrule' for more information.\n");
@@ -98,19 +98,20 @@
     puts ("Type 'help addrule' for more information.\n");
     error ("addrule's first argument must be an FIS structure\n");
   elseif (!is_real_matrix (rule_matrix))
-    puts ("Type 'help addrule' for more information.\n");
-    error ("addrule's second argument must be a matrix of real numbers\n");
+    puts ("Type 'help addrule' for more information. addrule's \n");
+    error ("second argument must be a matrix of real numbers\n");
   endif
 
-  ## For each row in the rule_matrix, create a new rule struct and update
-  ## the FIS structure.
+  ## For each row in the rule_matrix, create a new rule struct and
+  ## update the FIS structure.
 
   num_inputs = columns (fis.input);
   num_outputs = columns (fis.output);
 
   for i = 1 : rows (rule_matrix)
     antecedent = rule_matrix(i, 1 : num_inputs);
-    consequent = rule_matrix(i, (num_inputs+1) : (num_inputs+num_outputs));
+    consequent = rule_matrix(i, ...
+                             (num_inputs+1) : (num_inputs+num_outputs));
     weight = rule_matrix(i, num_inputs + num_outputs + 1);
     connection = rule_matrix(i, num_inputs + num_outputs + 2);
     new_rules(i) = struct ('antecedent', antecedent, ...

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/addvar.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -46,12 +46,12 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy variable
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      addvar.m
-## Last-Modified: 28 Oct 2011
+## Last-Modified: 18 Aug 2012
 
 function fis = addvar (fis, in_or_out, var_name, var_range)
 
-  ## If the caller did not supply 4 argument values with the correct types,
-  ## print an error message and halt.
+  ## If the caller did not supply 4 argument values with the correct
+  ## types, print an error message and halt.
 
   if (nargin != 4)
     puts ("Type 'help addvar' for more information.\n");
@@ -74,7 +74,8 @@
   ## Create a new variable struct and update the FIS input or output
   ## variable list.
 
-  new_variable = struct ('name', var_name, 'range', var_range, 'mf', []);
+  new_variable = struct ('name', var_name, 'range', var_range, ...
+                         'mf', []);
   if (strcmp (tolower (in_or_out), 'input'))
     if (length (fis.input) == 0)
       fis.input = new_variable;

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_product.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_product.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -37,14 +37,17 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy algebraic_product
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      algebraic_product.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 18 Aug 2012
 
 function retval = algebraic_product (x, y = 0)
   if (!(isreal (x) && isreal (y)))
+    puts ("Arguments to algebraic_product must be real scalars ");
+    puts ("or matrices.\n");
     puts ("Type 'help algebraic_product' for more information.\n");
-    error ("algebraic_product requires real scalar or matrix arguments\n");
+    error ("invalid arguments to function algebraic_product\n");
   elseif (nargin == 2 && ...
-          (isscalar (x) || isscalar (y) || isequal (size (x), size (y))))
+          (isscalar (x) || isscalar (y) || ...
+           isequal (size (x), size (y))))
     retval = x .* y;
   elseif (nargin == 1 && ndims (x) <= 2)
     retval = prod (x);

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_sum.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/algebraic_sum.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -37,14 +37,15 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy algebraic_sum
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      algebraic_sum.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 18 Aug 2012
 
 function retval = algebraic_sum (x, y = 0)
   if (!(isreal (x) && isreal (y)))
     puts ("Type 'help algebraic_sum' for more information.\n");
     error ("algebraic_sum requires real scalar or matrix arguments\n");
   elseif (nargin == 2 && ...
-          (isscalar (x) || isscalar (y) || isequal (size (x), size (y))))
+          (isscalar (x) || isscalar (y) || ...
+           isequal (size (x), size (y))))
     retval = x .+ y .- x .* y;
   elseif (nargin == 1 && isvector (x))
     retval = algebraic_sum_of_vector (x);

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_difference.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_difference.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_difference.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -38,14 +38,17 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy bounded_difference
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      bounded_difference.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 18 Aug 2012
 
 function retval = bounded_difference (x, y = 0)
   if (!(isreal (x) && isreal (y)))
+    puts ("Function 'bounded_difference' requires real scalar ");
+    puts ("or matrix arguments.\n");
     puts ("Type 'help bounded_difference' for more information.\n");
-    error ("bounded_difference requires real scalar or matrix arguments\n");
+    error ("invalid arguments to function bounded_difference\n");
   elseif (nargin == 2 && ...
-          (isscalar (x) || isscalar (y) || isequal (size (x), size (y))))
+          (isscalar (x) || isscalar (y) || ...
+           isequal (size (x), size (y))))
     retval = max (0, (x .+ y - 1));
   elseif (nargin == 1 && isvector (x))
     retval = bounded_difference_of_vector (x);

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_sum.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/bounded_sum.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -37,14 +37,15 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy bounded_sum
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      bounded_sum.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 18 Aug 2012
 
 function retval = bounded_sum (x, y = 0)
   if (!(isreal (x) && isreal (y)))
     puts ("Type 'help bounded_sum' for more information.\n");
     error ("bounded_sum requires real scalar or matrix arguments\n");
   elseif (nargin == 2 && ...
-          (isscalar (x) || isscalar (y) || isequal (size (x), size (y))))
+          (isscalar (x) || isscalar (y) || ...
+           isequal (size (x), size (y))))
     retval = min (1, (x .+ y));
   elseif (nargin == 1 && isvector (x))
     retval = bounded_sum_of_vector (x);

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/defuzz.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/defuzz.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/defuzz.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -53,14 +53,14 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy defuzzification
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      defuzz.m
-## Last-Modified: 16 Jul 2011
+## Last-Modified: 18 Aug 2012
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 
 function crisp_x = defuzz (x, y, defuzz_method)
 
-  ## If the caller did not supply 3 argument values with the correct types,
-  ## print an error message and halt.
+  ## If the caller did not supply 3 argument values with the correct
+  ## types, print an error message and halt.
 
   if (nargin != 3)
     puts ("Type 'help defuzz' for more information.\n");
@@ -70,31 +70,31 @@
     error ("defuzz's first argument must be a valid domain\n");
   elseif (!(isvector (y) && isreal (y) && length (x) == length (y)))
     puts ("Type 'help defuzz' for more information.\n");
-    error ("defuzz's second argument must be a real number or vector\n");
+    error ("defuzz's 2nd argument must be a real number or vector\n");
   elseif (!is_string (defuzz_method))
     puts ("Type 'help defuzz' for more information.\n");
     error ("defuzz's third argument must be a string\n");
   endif
 
-  ## Calculate and return the defuzzified (crisp_x) value using the method
-  ## specified by the argument defuzz_method.
+  ## Calculate and return the defuzzified (crisp_x) value using the
+  ## method specified by the argument defuzz_method.
 
   crisp_x = str2func (defuzz_method) (x, y);
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Usage: crisp_x = centroid (x, y)
 ##        crisp_x = centroid ([x1 x2 ... xn], [y1 y2 ... yn])
 ##
 ## For a given domain (x or [x1 x2 ... xn]) and corresponding y-values
-## (y or [y1 y2 ... yn]), return the x-value of the centroid of the region
-## described by the points (xi, yi).
+## (y or [y1 y2 ... yn]), return the x-value of the centroid of the
+## region described by the points (xi, yi).
 ##
 ## Both arguments are assumed to be reals or non-empty vectors of reals.
-## In addition, x is assumed to be strictly increasing, and x and y are assumed
-## to be of equal length.
-##------------------------------------------------------------------------------
+## In addition, x is assumed to be strictly increasing, and x and y are
+## assumed to be of equal length.
+##----------------------------------------------------------------------
 
 function crisp_x = centroid (x, y)
 
@@ -102,7 +102,7 @@
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Usage: crisp_x = bisector (x, y)
 ##        crisp_x = bisector ([x1 x2 ... xn], [y1 y2 ... yn])
 ##
@@ -111,15 +111,15 @@
 ## described by the points (xi, yi).
 ##
 ## Both arguments are assumed to be reals or non-empty vectors of reals.
-## In addition, x is assumed to be strictly increasing, and x and y are assumed
-## to be of equal length.
-##------------------------------------------------------------------------------
+## In addition, x is assumed to be strictly increasing, and x and y are
+## assumed to be of equal length.
+##----------------------------------------------------------------------
 
 function crisp_x = bisector (x, y)
 
-  ## Find the bisector using a binary search. To ensure that the function
-  ## terminates, add a counter to limit the iterations to the length of the
-  ## vectors x and y.
+  ## Find the bisector using a binary search. To ensure that the
+  ## function terminates, add a counter to limit the iterations to the
+  ## length of the vectors x and y.
 
   half_area = trapz (x, y) / 2;
   x_len = length (x);
@@ -145,18 +145,19 @@
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Usage: crisp_x = mom (x, y)
 ##        crisp_x = mom ([x1 x2 ... xn], [y1 y2 ... yn])
 ##
 ## For a given domain (x or [x1 x2 ... xn]) and corresponding y-values
-## (y or [y1 y2 ... yn]), return the "Mean of Maximum"; that is, return the
-## average of the x-values corresponding to the maximum y-value in y. 
+## (y or [y1 y2 ... yn]), return the "Mean of Maximum"; that is, return
+## the average of the x-values corresponding to the maximum y-value
+## in y. 
 ##
 ## Both arguments are assumed to be reals or non-empty vectors of reals.
-## In addition, x is assumed to be strictly increasing, and x and y are assumed
-## to be of equal length.
-##------------------------------------------------------------------------------
+## In addition, x is assumed to be strictly increasing, and x and y are
+## assumed to be of equal length.
+##----------------------------------------------------------------------
 
 function crisp_x = mom (x, y)
 
@@ -167,18 +168,19 @@
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Usage: crisp_x = som (x, y)
 ##        crisp_x = som ([x1 x2 ... xn], [y1 y2 ... yn])
 ##
 ## For a given domain (x or [x1 x2 ... xn]) and corresponding y-values
-## (y or [y1 y2 ... yn]), return the "Smallest of Maximum"; that is, return the
-## smallest x-value corresponding to the maximum y-value in y. 
+## (y or [y1 y2 ... yn]), return the "Smallest of Maximum"; that is,
+## return the smallest x-value corresponding to the maximum y-value
+## in y. 
 ##
 ## Both arguments are assumed to be reals or non-empty vectors of reals.
-## In addition, x is assumed to be strictly increasing, and x and y are assumed
-## to be of equal length.
-##------------------------------------------------------------------------------
+## In addition, x is assumed to be strictly increasing, and x and y are
+## assumed to be of equal length.
+##----------------------------------------------------------------------
 
 function crisp_x = som (x, y)
 
@@ -189,18 +191,18 @@
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Usage: crisp_x = lom (x, y)
 ##        crisp_x = lom ([x1 x2 ... xn], [y1 y2 ... yn])
 ##
 ## For a given domain (x or [x1 x2 ... xn]) and corresponding y-values
-## (y or [y1 y2 ... yn]), return the "Largest of Maximum"; that is, return the
-## largest x-value corresponding to the maximum y-value in y. 
+## (y or [y1 y2 ... yn]), return the "Largest of Maximum"; that is,
+## return the largest x-value corresponding to the maximum y-value in y.
 ##
 ## Both arguments are assumed to be reals or non-empty vectors of reals.
-## In addition, x is assumed to be strictly increasing, and x and y are assumed
-## to be of equal length.
-##------------------------------------------------------------------------------
+## In addition, x is assumed to be strictly increasing, and x and y are
+## assumed to be of equal length.
+##----------------------------------------------------------------------
 
 function crisp_x = lom (x, y)
 
@@ -211,17 +213,17 @@
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Usage: retval = wtaver (values, weights)
 ##
-## Return the weighted average of the values. The parameters are assumed to be
-## equal-length vectors of real numbers.
+## Return the weighted average of the values. The parameters are assumed
+## to be equal-length vectors of real numbers.
 ##
 ## Examples:
 ##    wtaver ([1 2 3 4], [1 1 1 1])  ==> 2.5
 ##    wtaver ([1 2 3 4], [1 2 3 4])  ==> 3
 ##    wtaver ([1 2 3 4], [0 0 1 1])  ==> 3.5
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 
 function retval = wtaver (values, weights)
 
@@ -229,17 +231,17 @@
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Usage: retval = wtsum (values, weights)
 ##
-## Return the weighted sum of the values. The parameters are assumed to be
-## equal-length vectors of real numbers.
+## Return the weighted sum of the values. The parameters are assumed to
+## be equal-length vectors of real numbers.
 ##
 ## Examples:
 ##    wtsum ([1 2 3 4], [1 1 1 1])  ==> 10
 ##    wtsum ([1 2 3 4], [1 2 3 4])  ==> 30
 ##    wtsum ([1 2 3 4], [0 0 1 1])  ==> 7
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 
 function retval = wtsum (values, weights)
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_product.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/drastic_sum.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/dsigmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/dsigmf.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/dsigmf.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -65,15 +65,15 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership-function sigmoidal
+## Keywords:      fuzzy-logic-toolkit fuzzy membership sigmoidal
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      dsigmf.m
-## Last-Modified: 28 Oct 2011
+## Last-Modified: 20 Aug 2012
 
 function y = dsigmf (x, params)
 
-  ## If the caller did not supply 2 argument values with the correct types,
-  ## print an error message and halt.
+  ## If the caller did not supply 2 argument values with the correct
+  ## types, print an error message and halt.
 
   if (nargin != 2)
     puts ("Type 'help dsigmf' for more information.\n");
@@ -94,8 +94,9 @@
   a2 = params(3);
   c2 = params(4);
 
-  y_val = @(x_val) max (0, min (1, 1 / (1 + exp (-a1 * (x_val - c1))) - ...
-                                   1 / (1 + exp (-a2 * (x_val - c2)))));
+  y_val = @(x_val) max (0, ...
+                        min (1, 1 / (1 + exp (-a1 * (x_val - c1))) - ...
+                                1 / (1 + exp (-a2 * (x_val - c2)))));
   y = arrayfun (y_val, x);
 
 endfunction

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_product.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/einstein_sum.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalfis.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalfis.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalfis.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -232,16 +232,17 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy fuzzy-inference-system fis
+## Keywords:      fuzzy-logic-toolkit fuzzy inference system fis
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      evalfis.m
-## Last-Modified: 12 Nov 2011
+## Last-Modified: 20 Aug 2012
 
 function [output, rule_input, rule_output, fuzzy_output] = ...
            evalfis (user_input, fis, num_points = 101)
 
-  ## If evalfis was called with an incorrect number of arguments, or the
-  ## arguments do not have the correct type, print an error message and halt.
+  ## If evalfis was called with an incorrect number of arguments, or
+  ## the arguments do not have the correct type, print an error message
+  ## and halt.
 
   if ((nargin != 2) && (nargin != 3))
     puts ("Type 'help evalfis' for more information.\n");
@@ -251,7 +252,7 @@
     error ("evalfis's second argument must be an FIS structure\n");
   elseif (!is_input_matrix (user_input, fis))
     puts ("Type 'help evalfis' for more information.\n");
-    error ("evalfis's first argument must be a matrix of input values\n");
+    error ("evalfis's 1st argument must be a matrix of input values\n");
   elseif (!is_pos_int (num_points))
     puts ("Type 'help evalfis' for more information.\n");
     error ("evalfis's third argument must be a positive integer\n");

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalmf.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/evalmf.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -58,15 +58,15 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership-function evaluate
+## Keywords:      fuzzy-logic-toolkit fuzzy membership evaluate
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      evalmf.m
-## Last-Modified: 13 Nov 2011
+## Last-Modified: 19 Aug 2012
 
 function y = evalmf (x, params, mf_type, hedge = 0, not_flag = false)
 
-  ## If the caller did not supply 3 - 5 argument values with the correct types,
-  ## print an error message and halt.
+  ## If the caller did not supply 3 - 5 argument values with the correct
+  ## types, print an error message and halt.
 
   if ((nargin < 3) || (nargin > 5))
     puts ("Type 'help evalmf' for more information.\n");
@@ -85,8 +85,8 @@
     error ("evalmf's fifth argument must be a Boolean\n");
   endif
 
-  ## Calculate and return the y values of the membership function on the
-  ## domain x.
+  ## Calculate and return the y values of the membership function on
+  ## the domain x.
 
   y = evalmf_private (x, params, mf_type, hedge, not_flag);
 
@@ -97,7 +97,8 @@
 %! params = [25 50 75];
 %! mf_type = 'trimf';
 %! y = evalmf(x, params, mf_type);
-%! figure('NumberTitle', 'off', 'Name', "evalmf(0:100, [25 50 75], 'trimf')");
+%! figure('NumberTitle', 'off', 'Name', "evalmf(0:100, [25 50 75], ...
+%!        'trimf')");
 %! plot(x, y, 'LineWidth', 2)
 %! ylim([-0.1 1.1]);
 %! xlabel('Crisp Input Value', 'FontWeight', 'bold');

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2012 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -114,13 +114,14 @@
 ## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      fcm.m
-## Last-Modified: 10 July 2012
+## Last-Modified: 19 Aug 2012
 
 function [cluster_centers, soft_partition, obj_fcn_history] = ...
            fcm (input_data, num_clusters, options = [2.0, 100, 1e-5, 1])
 
   ## If fcm was called with an incorrect number of arguments, or the
-  ## arguments do not have the correct type, print an error message and halt.
+  ## arguments do not have the correct type, print an error message
+  ## and halt.
 
   if ((nargin != 2) && (nargin != 3))
     puts ("Type 'help fcm' for more information.\n");
@@ -133,17 +134,19 @@
     error ("fcm's second argument must be an integer greater than 1\n");
   elseif (!(isreal (options) && isvector (options)))
     puts ("Type 'help fcm' for more information.\n");
-    error ("fcm's third (optional) argument must be a vector of real numbers\n");
+    error ("fcm's third argument must be a vector of real numbers\n");
   endif
 
-  ## Assign options to the more readable variable names: m, max_iterations,
-  ## epsilon, and display_intermediate_results. If options are missing or
-  ## NaN (not a number), use the default values.
+  ## Assign options to the more readable variable names: m,
+  ## max_iterations, epsilon, and display_intermediate_results.
+  ## If options are missing or NaN (not a number), use the default
+  ## values.
 
   default_options = [2.0, 100, 1e-5, 1];
 
   for i = 1 : 4
-    if ((length (options) < i) || isna (options(i)) || isnan (options(i)))
+    if ((length (options) < i) || ...
+        isna (options(i)) || isnan (options(i)))
       options(i) = default_options(i);
     endif
   endfor
@@ -160,16 +163,17 @@
                  display_intermediate_results);
 endfunction
 
-##------------------------------------------------------------------------------
-## Note: This function (fcm_private) is an implementation of Figure 13.4 in
-##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
-##       R. Langari, Prentice Hall, 1999, page 380 (International Edition)
-##       and Algorithm 4.1 in Fuzzy and Neural Control, by Robert Babuska,
-##       November 2009, p. 63.
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
+## Note: This function (fcm_private) is an implementation of Figure 13.4
+##       in Fuzzy Logic: Intelligence, Control and Information, by
+##       J. Yen and R. Langari, Prentice Hall, 1999, page 380
+##       (International Edition) and Algorithm 4.1 in Fuzzy and Neural
+##       Control, by Robert Babuska, November 2009, p. 63.
+##----------------------------------------------------------------------
 
 function [V, Mu, obj_fcn_history] = ...
-  fcm_private (X, k, m, max_iterations, epsilon, display_intermediate_results)
+  fcm_private (X, k, m, max_iterations, epsilon, ...
+               display_intermediate_results)
 
   ## Initialize the prototype and the calculation.
   V = fcm_init_prototype (X, k);
@@ -182,23 +186,27 @@
   n = rows (X);
   sqr_dist = square_distance_matrix (X, V);
 
-  ## Loop until the objective function is within tolerance or the maximum
-  ## number of iterations has been reached.
-  while (convergence_criterion > epsilon && ++iteration <= max_iterations)
+  ## Loop until the objective function is within tolerance or the
+  ## maximum number of iterations has been reached.
+  while (convergence_criterion > epsilon && ...
+         ++iteration <= max_iterations)
     V_previous = V;
     Mu = fcm_update_membership_fcn (V, X, m, k, n, sqr_dist);
     Mu_m = Mu .^ m;
     V = fcm_update_cluster_centers (Mu_m, X, k);
     sqr_dist = square_distance_matrix (X, V);
-    obj_fcn_history(iteration) = fcm_compute_objective_fcn (Mu_m, sqr_dist);
+    obj_fcn_history(iteration) = ...
+      fcm_compute_objective_fcn (Mu_m, sqr_dist);
     if (display_intermediate_results)
       printf ("Iteration count = %d,  Objective fcn = %8.6f\n", ...
                iteration, obj_fcn_history(iteration));
     endif
-    convergence_criterion = fcm_compute_convergence_criterion (V, V_previous);
+    convergence_criterion = ...
+      fcm_compute_convergence_criterion (V, V_previous);
   endwhile
 
-  ## Remove extraneous entries from the tail of the objective function history.
+  ## Remove extraneous entries from the tail of the objective
+  ## function history.
   if (convergence_criterion <= epsilon)
     obj_fcn_history = obj_fcn_history(1 : iteration);
   endif

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_1.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2012 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -42,16 +42,17 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm demo
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      fcm_demo_1.m
-## Last-Modified: 10 July 2012
+## Last-Modified: 19 Aug 2012
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Note: The input_data is taken from Chapter 13, Example 17 in
-##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen and
-##       R. Langari, Prentice Hall, 1999, page 381 (International Edition). 
-##------------------------------------------------------------------------------
+##       Fuzzy Logic: Intelligence, Control and Information, by J. Yen
+##       and R. Langari, Prentice Hall, 1999, page 381 (International
+##       Edition). 
+##----------------------------------------------------------------------
 
 ## Use fcm to classify the data in matrix x.
 input_data = [2 12; 4 9; 7 13; 11 5; 12 7; 14 4]
@@ -60,22 +61,25 @@
   fcm (input_data, number_of_clusters)
 
 ## Calculate and print the three validity measures.
-printf ("Partition Coefficient: %f\n", partition_coeff (soft_partition));
-printf ("Partition Entropy (with a = 2): %f\n", partition_entropy (soft_partition, 2));
-printf ("Xie-Beni Index: %f\n\n", xie_beni_index (input_data, cluster_centers, soft_partition));
+printf ("Partition Coefficient: %f\n", ...
+        partition_coeff (soft_partition));
+printf ("Partition Entropy (with a = 2): %f\n", ...
+        partition_entropy (soft_partition, 2));
+printf ("Xie-Beni Index: %f\n\n", ...
+        xie_beni_index (input_data, cluster_centers, soft_partition));
  
 ## Plot the data points as small blue x's.
 figure ('NumberTitle', 'off', 'Name', 'FCM Demo 1');
 for i = 1 : rows (input_data)
-  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, 'marker', 'x', ...
-        'color', 'b');
+  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
+        'marker', 'x', 'color', 'b');
   hold on;
 endfor
 
 ## Plot the cluster centers as larger red *'s.
 for i = 1 : number_of_clusters
-  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', 4, ...
-        'marker', '*', 'color', 'r');
+  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
+        4, 'marker', '*', 'color', 'r');
   hold on;
 endfor
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/fcm_demo_2.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2012 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -42,44 +42,48 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm demo
+## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering fcm
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      fcm_demo_2.m
-## Last-Modified: 10 July 2012
+## Last-Modified: 19 Aug 2012
 
-##------------------------------------------------------------------------------
-## Note: The input_data was selected to form three areas of different shapes.
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
+## Note: The input_data was selected to form three areas of different
+##       shapes.
+##----------------------------------------------------------------------
 
 ## Use fcm to classify the data in matrix x.
-input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6; 3 12 5;
-              3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10; 3 5 11; 4 4 9;
-              4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12; 9 12 13; 9 13 14; 10 9 13;
-              10 13 12; 11 10 14; 11 12 13; 12 6 12; 12 7 15; 12 9 15; 14 6 14;
-              14 8 13]
+input_data = [1 11 5; 1 12 6; 1 13 5; 2 11 7; 2 12 6; 2 13 7; 3 11 6;
+              3 12 5; 3 13 7;  1 1 10; 1 3 9; 2 2 11; 3 1 9; 3 3 10;
+              3 5 11; 4 4 9; 4 6 8; 5 5 8; 5 7 9; 6 6 10; 9 10 12;
+              9 12 13; 9 13 14; 10 9 13; 10 13 12; 11 10 14; 11 12 13;
+              12 6 12; 12 7 15; 12 9 15; 14 6 14; 14 8 13]
 number_of_clusters = 3
 [cluster_centers, soft_partition, obj_fcn_history] = ...
   fcm (input_data, number_of_clusters, [NaN NaN NaN 0])
 
 ## Calculate and print the three validity measures.
-printf ("Partition Coefficient: %f\n", partition_coeff (soft_partition));
-printf ("Partition Entropy (with a = 2): %f\n", partition_entropy (soft_partition, 2));
-printf ("Xie-Beni Index: %f\n\n", xie_beni_index (input_data, cluster_centers, soft_partition));
+printf ("Partition Coefficient: %f\n", ...
+        partition_coeff (soft_partition));
+printf ("Partition Entropy (with a = 2): %f\n", ...
+        partition_entropy (soft_partition, 2));
+printf ("Xie-Beni Index: %f\n\n", ...
+        xie_beni_index (input_data, cluster_centers, soft_partition));
  
 ## Plot the data points in two dimensions (using features 1 and 2)
 ## as small blue x's.
 figure ('NumberTitle', 'off', 'Name', 'FCM Demo 2');
 for i = 1 : rows (input_data)
-  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, 'marker', 'x', ...
-        'color', 'b');
+  plot (input_data(i, 1), input_data(i, 2), 'LineWidth', 2, ...
+        'marker', 'x', 'color', 'b');
   hold on;
 endfor
 
 ## Plot the cluster centers in two dimensions (using features 1 and 2)
 ## as larger red *'s.
 for i = 1 : number_of_clusters
-  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', 4, ...
-        'marker', '*', 'color', 'r');
+  plot (cluster_centers(i, 1), cluster_centers(i, 2), 'LineWidth', ...
+        4, 'marker', '*', 'color', 'r');
   hold on;
 endfor
 
@@ -97,16 +101,16 @@
 ## as small blue x's.
 figure ('NumberTitle', 'off', 'Name', 'FCM Demo 2');
 for i = 1 : rows (input_data)
-  plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, 'marker', 'x', ...
-        'color', 'b');
+  plot (input_data(i, 1), input_data(i, 3), 'LineWidth', 2, ...
+        'marker', 'x', 'color', 'b');
   hold on;
 endfor
 
 ## Plot the cluster centers in two dimensions (using features 1 and 3)
 ## as larger red *'s.
 for i = 1 : number_of_clusters
-  plot (cluster_centers(i, 1), cluster_centers(i, 3), 'LineWidth', 4, ...
-        'marker', '*', 'color', 'r');
+  plot (cluster_centers(i, 1), cluster_centers(i, 3), 'LineWidth', ...
+        4, 'marker', '*', 'color', 'r');
   hold on;
 endfor
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gauss2mf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gauss2mf.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gauss2mf.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -64,15 +64,15 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership-function gaussian
+## Keywords:      fuzzy-logic-toolkit fuzzy membership gaussian
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gauss2mf.m
-## Last-Modified: 28 Oct 2011
+## Last-Modified: 19 Aug 2012
 
 function y = gauss2mf (x, params)
 
-  ## If the caller did not supply 2 argument values with the correct types,
-  ## print an error message and halt.
+  ## If the caller did not supply 2 argument values with the correct
+  ## types, print an error message and halt.
 
   if (nargin != 2)
     puts ("Type 'help gauss2mf' for more information.\n");
@@ -85,16 +85,17 @@
     error ("gauss2mf's second argument must be a parameter vector\n");
   endif
 
-  ## Calculate and return the y values of the membership function on the
-  ## domain x according to the definition of gauss2mf given in the comment
-  ## above.
+  ## Calculate and return the y values of the membership function on
+  ## the domain x according to the definition of gauss2mf given in the
+  ## comment above.
 
   sig1 = params(1);
   c1 = params(2);
   sig2 = params(3);
   c2 = params(4);
 
-  f1_val = @(x_val) (x_val <= c1) * exp ((-(x_val - c1)^2)/(2 * sig1^2)) + ...
+  f1_val = @(x_val) (x_val <= c1) * ...
+                    exp ((-(x_val - c1)^2)/(2 * sig1^2)) + ...
                     (x_val > c1);
 
   f2_val = @(x_val) (x_val <= c2) + ... 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gaussmf.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -60,15 +60,15 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership-function gaussian
+## Keywords:      fuzzy-logic-toolkit fuzzy membership gaussian
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gaussmf.m
-## Last-Modified: 28 Oct 2011
+## Last-Modified: 19 Aug 2012
 
 function y = gaussmf (x, params)
 
-  ## If the caller did not supply 2 argument values with the correct types,
-  ## print an error message and halt.
+  ## If the caller did not supply 2 argument values with the correct
+  ## types, print an error message and halt.
 
   if (nargin != 2)
     puts ("Type 'help gaussmf' for more information.\n");

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gbellmf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gbellmf.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gbellmf.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -64,15 +64,15 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership-function bell-shaped bell
+## Keywords:      fuzzy-logic-toolkit fuzzy membership bell-shaped bell
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gbellmf.m
-## Last-Modified: 28 Oct 2011
+## Last-Modified: 19 Aug 2012
 
 function y = gbellmf (x, params)
 
-  ## If the caller did not supply 2 argument values with the correct types,
-  ## print an error message and halt.
+  ## If the caller did not supply 2 argument values with the correct
+  ## types, print an error message and halt.
 
   if (nargin != 2)
     puts ("Type 'help gbellmf' for more information.\n");

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gensurf.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gensurf.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/gensurf.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -70,7 +70,7 @@
 ## sugeno_tip_demo.m
 ## @end itemize
 ##
-## CURRENT LIMITATION:
+## Current limitation:
 ## The form of gensurf that suppresses plotting (the final form above) is not yet
 ## implemented.
 ##
@@ -78,16 +78,18 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy fuzzy-inference-system fis plot
+## Keywords:      fuzzy-logic-toolkit fuzzy inference system fis plot
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      gensurf.m
-## Last-Modified: 11 Nov 2011
+## Last-Modified: 19 Aug 2012
 
-function [x, y, z] = gensurf (fis, input_axes = [1 2], output_axis = 1, ...
-                              grids = [15 15], ref_input = [], num_points = 101)
+function [x, y, z] = gensurf (fis, input_axes = [1 2], ...
+                              output_axis = 1, grids = [15 15], ...
+                              ref_input = [], num_points = 101)
 
-  ## If gensurf was called with an incorrect number of arguments, or the
-  ## arguments do not have the correct type, print an error message and halt.
+  ## If gensurf was called with an incorrect number of arguments,
+  ## or the arguments do not have the correct type, print an error
+  ## message and halt.
 
   if ((nargin < 1) || (nargin > 6))
     puts ("Type 'help gensurf' for more information.\n");
@@ -103,32 +105,34 @@
     error ("gensurf's third argument must be a valid output index\n");
   elseif ((nargin >= 4) && !is_grid_spec (grids))
     puts ("Type 'help gensurf' for more information.\n");
-    error ("gensurf's fourth argument must be a valid grid specification\n");
+    error ("gensurf's 4th argument must be a grid specification\n");
   elseif ((nargin >= 5) && !is_ref_input (ref_input, fis, input_axes))
     puts ("Type 'help gensurf' for more information.\n");
-    error ("gensurf's fifth argument must specify reference input values\n");
-  elseif ((nargin == 6) && !(is_pos_int (num_points) && (num_points >= 2)))
+    error ("gensurf's 5th argument must be reference input values\n");
+  elseif ((nargin == 6) && ...
+          !(is_pos_int (num_points) && (num_points >= 2)))
     puts ("Type 'help gensurf' for more information.\n");
-    error ("gensurf's sixth argument to gensurf must be an integer >= 2\n");
+    error ("gensurf's sixth argument must be an integer >= 2\n");
   endif
 
   if (length (input_axes) == 1 || columns (fis.input) == 1)
-    generate_plot (fis, input_axes, output_axis, grids, ref_input, num_points);
+    generate_plot (fis, input_axes, output_axis, grids, ...
+                   ref_input, num_points);
   else
-    generate_surface (fis, input_axes, output_axis, grids, ref_input, ...
-                      num_points);
+    generate_surface (fis, input_axes, output_axis, grids, ...
+                      ref_input, num_points);
   endif
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Function: generate_plot
 ## Purpose:  Generate a plot representing one of the FIS outputs as a
 ##           function of one of the FIS inputs.
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 
-function [x, y, z] = generate_plot (fis, input_axis, output_axis, grids, ...
-                                    ref_input, num_points)
+function [x, y, z] = generate_plot (fis, input_axis, output_axis, ...
+                                    grids, ref_input, num_points)
 
   ## Create input to FIS using grid points and reference values.
 
@@ -163,14 +167,14 @@
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Function: generate_surface
-## Purpose:  Generate a surface representing one of the FIS outputs as a
-##           function of two of the FIS inputs.
-##------------------------------------------------------------------------------
+## Purpose:  Generate a surface representing one of the FIS outputs as
+##           a function of two of the FIS inputs.
+##----------------------------------------------------------------------
 
-function [x, y, z] = generate_surface (fis, input_axes, output_axis, grids, ...
-                                       ref_input, num_points)
+function [x, y, z] = generate_surface (fis, input_axes, output_axis, ...
+                                       grids, ref_input, num_points)
 
   ## Create input to FIS using grid points and reference values.
 
@@ -203,7 +207,8 @@
   ## Compute the output and reshape it to fit the grid.
 
   output = evalfis_private (fis_input, fis, num_points);
-  z_matrix = reshape (output(:, output_axis), length (x_axis), length (y_axis));
+  z_matrix = reshape (output(:, output_axis), length (x_axis), ...
+                      length (y_axis));
 
   ## Plot the surface.
 

Modified: trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m
===================================================================
--- trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m	2012-08-24 16:11:37 UTC (rev 10908)
+++ trunk/octave-forge/main/fuzzy-logic-toolkit/inst/getfis.m	2012-08-24 16:13:07 UTC (rev 10909)
@@ -1,4 +1,4 @@
-## Copyright (C) 2011 L. Markowsky <lm...@us...>
+## Copyright (C) 2011-2012 L. Markowsky <lm...@us...>
 ##
 ## This file is part of the fuzzy-logic-toolkit.
 ##
@@ -90,15 +90,16 @@
 ## @end deftypefn
 
 ## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy fuzzy-inference-system fis
+## Keywords:      fuzzy-logic-toolkit fuzzy inference system fis
 ## Directory:     fuzzy-logic-toolkit/inst/
 ## Filename:      getfis.m
-## Last-Modified: 31 Oct 2011
+## Last-Modified: 20 Aug 2012
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 
 function retval = getfis (fis, arg2 = 'dummy', arg3 = 'dummy', ...
-                         arg4 = 'dummy', arg5 = 'dummy', arg6 = 'dummy')
+                          arg4 = 'dummy', arg5 = 'dummy', ...
+                          arg6 = 'dummy')
 
   switch (nargin)
     case 1  retval = getfis_one_arg (fis);
@@ -106,7 +107,8 @@
     case 3  retval = getfis_three_args (fis, arg2, arg3);
     case 4  retval = getfis_four_args (fis, arg2, arg3, arg4);
     case 5  retval = getfis_five_args (fis, arg2, arg3, arg4, arg5);
-    case 6  retval = getfis_six_args (fis, arg2, arg3, arg4, arg5, arg6);
+    case 6  retval = getfis_six_args (fis, arg2, arg3, arg4, arg5, ...
+                                      arg6);
     otherwise
             puts ("Type 'help getfis' for more information.\n");
             error ("getfis requires 1-6 arguments\n");
@@ -114,11 +116,11 @@
 
 endfunction
 
-##------------------------------------------------------------------------------
+##----------------------------------------------------------------------
 ## Function: getfis_one_arg
-## Purpose:  Handle calls to getfis that have 1 argument.
-##           See the comment at the top of this file for more complete info.
-##------------------------------------------------------------------------------
+## Purpose...
 
[truncated message content]