--- a/main/fuzzy-logic-toolkit/COPYING	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,674 +0,0 @@
-                    GNU GENERAL PUBLIC LICENSE
-                       Version 3, 29 June 2007
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-  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
-WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
-THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
-GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
-USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
-DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
-PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
-EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
-SUCH DAMAGES.
-
-  17. Interpretation of Sections 15 and 16.
-
-  If the disclaimer of warranty and limitation of liability provided
-above cannot be given local legal effect according to their terms,
-reviewing courts shall apply local law that most closely approximates
-an absolute waiver of all civil liability in connection with the
-Program, unless a warranty or assumption of liability accompanies a
-copy of the Program in return for a fee.
-
-                     END OF TERMS AND CONDITIONS
-
-            How to Apply These Terms to Your New Programs
-
-  If you develop a new program, and you want it to be of the greatest
-possible use to the public, the best way to achieve this is to make it
-free software which everyone can redistribute and change under these terms.
-
-  To do so, attach the following notices to the program.  It is safest
-to attach them to the start of each source file to most effectively
-state the exclusion of warranty; and each file should have at least
-the "copyright" line and a pointer to where the full notice is found.
-
-    <one line to give the program's name and a brief idea of what it does.>
-    Copyright (C) <year>  <name of author>
-
-    This program 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.
-
-    This program 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 this program.  If not, see <http://www.gnu.org/licenses/>.
-
-Also add information on how to contact you by electronic and paper mail.
-
-  If the program does terminal interaction, make it output a short
-notice like this when it starts in an interactive mode:
-
-    <program>  Copyright (C) <year>  <name of author>
-    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
-    This is free software, and you are welcome to redistribute it
-    under certain conditions; type `show c' for details.
-
-The hypothetical commands `show w' and `show c' should show the appropriate
-parts of the General Public License.  Of course, your program's commands
-might be different; for a GUI interface, you would use an "about box".
-
-  You should also get your employer (if you work as a programmer) or school,
-if any, to sign a "copyright disclaimer" for the program, if necessary.
-For more information on this, and how to apply and follow the GNU GPL, see
-<http://www.gnu.org/licenses/>.
-
-  The GNU General Public License does not permit incorporating your program
-into proprietary programs.  If your program is a subroutine library, you
-may consider it more useful to permit linking proprietary applications with
-the library.  If this is what you want to do, use the GNU Lesser General
-Public License instead of this License.  But first, please read
-<http://www.gnu.org/philosophy/why-not-lgpl.html>.

--- a/main/fuzzy-logic-toolkit/ChangeLog	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,262 +0,0 @@
-2012-10-02 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.4.2 released.
-  * ChangeLog: Updated file.
-  * DESCRIPTION: Updated file.
-  * NEWS: Updated file.
-  * inst/*.m: Some trivial changes to line length and comments.
-  * inst/fcm.m: Edited to reflect the five renamed private functions.
-      Edited the demos to calculate and print the three cluster validity
-      indices. Edited comment.
-  * inst/gustafson_kessel.m: Edited to reflect the five renamed private
-      functions. Edited the demos to calculate and print the three
-      cluster validity indices. Edited comment.
-  * inst/partition_coeff.m: Demos were merged with the demos in fcm.m
-      and gustafson_kessel.m and then removed. Edited comment.
-  * inst/partition_entropy.m: Demos were merged with the demos in fcm.m
-      and gustafson_kessel.m and then removed. Edited comment.
-  * inst/xie_beni_index.m: Demos were merged with the demos in fcm.m
-      and gustafson_kessel.m and then removed. Edited comment.
-  * inst/private/evalmf_private.m: Edited comment.
-  * inst/private/is_builtin_language.m: Edited comment.
-  * inst/private/fcm_compute_convergence_criterion.m: Edited and renamed
-      compute_cluster_convergence.m.
-  * inst/private/fcm_compute_objective_fcn.m: Edited and renamed
-      compute_cluster_obj_fcn.m.
-  * inst/private/fcm_init_prototype.m: Edited and renamed
-      init_cluster_prototypes.m.
-  * inst/private/fcm_update_cluster_centers.m: Edited and renamed
-      update_cluster_prototypes.m.
-  * inst/private/fcm_update_membership_fcn.m: Edited and renamed
-      update_cluster_membership.m.
-  * inst/private/probor.m: Removed unused private function.
-  * Demos tested under: Fedora 17/Octave 3.6.2
-  * Demos tested under: Fedora 16/Octave 3.4.3
-  * Demos tested under: Windows 7/Octave 3.2.4
-
-2012-08-26 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.4.1 released.
-  * ChangeLog: Updated file.
-  * COPYING: Replaced GPLv2 with GPLv3 (to fix inconsistency with source
-      files).
-  * DESCRIPTION: Updated file.
-  * INDEX: Updated file.
-  * NEWS: Updated file.
-  * inst/fcm.m: Rewrote and embedded the demos previously contained in
-      fcm_demo_1.m and fcm_demo_2.m.
-  * inst/fcm_demo_1.m: Removed script file.
-  * inst/fcm_demo_2.m: Removed script file.
-  * inst/gustafson_kessel.m: Rewrote and embedded the demos previously
-      contained in gustafson_kessel_demo_1.m and
-      gustafson_kessel_demo_2.m.
-  * inst/gustafson_kessel_demo_1.m: Removed script file.
-  * inst/gustafson_kessel_demo_2.m: Removed script file.
-  * inst/*.m: Many trivial changes to line length and copyright notices.
-  * inst/private/*.m: Many trivial changes to line length and copyright
-      notice.
-  * All demos tested under: Fedora 17/Octave 3.6.2
-
-2012-07-10 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.4.0 released.
-  * ChangeLog: Updated file.
-  * DESCRIPTION: Updated file.
-  * INDEX: Updated file.
-  * NEWS: New file.
-  * inst/fcm.m: New file. Addition of the Fuzzy C-Means clustering
-      algorithm to the toolkit.
-  * inst/fcm_demo_1.m: New file. Addition of demo script.
-  * inst/fcm_demo_2.m: New file. Addition of demo script.
-  * inst/gustafson_kessel.m: New file. Addition of the Gustafson-Kessel
-      clustering algorithm to the toolkit.
-  * inst/gustafson_kessel_demo_1.m: New file. Addition of demo script.
-  * inst/gustafson_kessel_demo_2.m: New file. Addition of demo script.
-  * inst/partition_coeff.m: New file. Addition of a measure of cluster
-      validity.
-  * inst/partition_entropy.m: New file. Addition of a measure of cluster
-      validity.
-  * inst/xie_beni_index.m: New file. Addition of a measure of cluster
-      validity.
-  * inst/private/fcm_compute_convergence_criterion.m: New file.
-  * inst/private/fcm_compute_objective_fcn.m: New file.
-  * inst/private/fcm_init_prototype.m: New file.
-  * inst/private/fcm_update_cluster_centers.m: New file.
-  * inst/private/fcm_update_membership_fcn.m: New file.
-  * inst/private/square_dist_matrix.m: New file.
-  * New demos tested under: Fedora 16/Octave 3.4.3
-
-2011-11-12 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.3.0 released.
-  * ChangeLog: Updated file.
-  * DESCRIPTION: Updated file.
-  * inst/*.m: Many trivial changes to comments and spacing in parameter
-      lists.
-  * inst/addrule.m: Edited comment to describe use with hedges.
-  * inst/algebraic_product.m: New file.
-  * inst/algebraic_sum.m: New file.
-  * inst/bounded_difference.m: New file.
-  * inst/bounded_sum.m: New file.
-  * inst/cubic_approx_demo.m: Added plot of output membership functions.
-  * inst/cubic_approximator.fis: Corrected range for FIS output.
-  * inst/drastic_product.m: New file.
-  * inst/drastic_sum.m: New file.
-  * inst/einstein_product.m: New file.
-  * inst/einstein_sum.m: New file.
-  * inst/evalmf.m: Edited to add custom and new built-in hedge support.
-  * inst/hamacher_product.m: New file.
-  * inst/hamacher_sum.m: New file.
-  * inst/heart_disease_demo_1.m : Edited and renamed heart_demo_1.m.
-      Edited script to demonstrate hedges and new T-norm/S-norm pairs.
-  * inst/heart_disease_demo_2.m : Renamed heart_demo_2.m.
-  * inst/investment_portfolio.fis: New file.
-  * inst/investment_portfolio_demo.m: New file.
-  * inst/plotmf.m: Edited to add support for linear output membership
-      functions and to support optional y-limit arguments.
-  * inst/readfis.m: Edited to add custom and built-in hedge support.
-  * inst/showrule.m: Edited to add Chinese, Russian, and Spanish to the
-      built-in languages and to add custom language support. Also edited
-      to add custom hedge support and to implement the hedges
-      "somewhat", "very", "extremely", and "very very".
-  * inst/sugeno_tip_calculator.fis: Edited to demonstrate hedges.
-  * inst/sugeno_tip_demo.m: Edited to demonstrate hedges.
-  * inst/writefis.m: Edited comment to note that zenity is required by
-      the GUI. Code edited to support hedges.
-  * inst/private/*.m: Many trivial changes to spacing in parameter
-      lists.
-  * inst/private/aggregate_output_mamdani.m: Edited to support new
-      built-in T-norm/S-norm pairs when used as the FIS aggregation
-      method.
-  * inst/private/eval_firing_strength.m: Edited to support new built-in
-      T-norm/S-norm pairs when used as the FIS 'and' or 'or' method.
-  * inst/private/evalmf_private.m: Edited to evaluate linear membership
-      functions and to add custom and new built-in hedge support.
-  * inst/private/eval_rules_mamdani.m: Edited to add custom and built-in
-      hedge support.
-  * inst/private/eval_rules_sugeno.m: Edited to add custom and built-in
-      hedge support.
-  * inst/private/fuzzify_input.m: Edited to add custom and built-in
-      hedge support.
-  * inst/private/get_mf_index_and_hedge.m: New file to add hedge
-      support.
-  * inst/private/is_real.m: Improved test.
-  * inst/private/is_real_matrix.m: Improved test.
-  * inst/private/is_builtin_language.m: Renamed is_language.m. Edited
-      test to add 'chinese', 'mandarin', 'pinyin', 'russian', 'pycckii',
-      'russkij', 'spanish', 'french', and 'german' to the strings
-      specifying built-in languages.
-  * Demos tested under: Fedora 15/Octave 3.4.2
-  * Demos tested under: Windows 7/Octave 3.2.4
-
-2011-09-01 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.2.4 released.
-  * ChangeLog: Updated file.
-  * DESCRIPTION: Updated file.
-  * INDEX: Updated file.
-  * inst/*.m: Numerous trivial changes.
-  * inst/addmf_demo.m: Merged into addmf.m as an embedded demo
-      and then removed.
-  * inst/addvar_demo.m: Merged into addvar.m as an embedded demo
-      and then removed.
-  * inst/showrule_demo.m: Merged into showrule.m as four embedded
-      demos and then removed.
-  * inst/gensurf.m: Edited to permit scalar grids argument.
-  * inst/getfis.m: Edited to implement "version" field in the FIS.
-  * inst/newfis.m: Edited to implement "version" field in the FIS.
-  * inst/readfis.m: Edited to implement "version" field in the FIS
-      and to handle comments, whitespace, and variable number of
-      membership function parameters.
-  * inst/setfis.m: Edited to implement "version" field in the FIS.
-      Fixed several bugs.
-  * inst/writefis.m: Edited to implement "version" field in the FIS.
-  * inst/cubic_approximator.fis: Renamed cubic-approximator.fis.
-  * inst/heart_disease_risk.fis: Renamed heart-disease-risk.fis.
-      Added comments and whitespace.
-  * inst/linear_tip_calculator.fis: Renamed linear-tip-calculator.fis.
-  * inst/mamdani_tip_calculator.fis: Renamed mamdani-tip-calculator.fis
-      and edited to have multiple outputs.
-  * inst/mamdani_tip_demo.m: Edited to demonstrate multiple outputs.
-  * inst/sugeno_tip_calculator.fis: Renamed sugeno-tip-calculator.fis
-      and edited to have multiple outputs.
-  * inst/sugeno_tip_demo.m: Edited to demonstrate multiple outputs.
-  * inst/private/defuzzify_output_mamdani.m: Bug fix (to handle an FIS
-      with multiple outputs).
-  * inst/private/defuzzify_output_sugeno.m: Bug fix (to handle an FIS
-      with multiple outputs).
-  * inst/private/eval_firing_strength.m: Bug fix.
-  * inst/private/eval_rules_mamdani.m: Bug fix (to handle an FIS with
-      multiple outputs).
-  * inst/private/eval_rules_sugeno.m: Bug fix (to handle an FIS with
-      multiple outputs).
-  * inst/private/is_grid_spec.m: Edited test to make more efficient.
-  * inst/private/is_real.m: New file.
-  * Demos tested under: Fedora 15/Octave 3.4.2
-  * Demos tested under: Fedora 15/Octave 3.2.4
-  * Demos tested under: Windows 7/Octave 3.2.4
-
-2011-07-19 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.2.3 released.
-  * ChangeLog: Updated file.
-  * DESCRIPTION: Updated file.
-  * INDEX: Updated file.
-  * inst/*.m: Edited numerous comments and texinfo comment blocks.
-  * inst/private/*.m: Edited numerous comments and texinfo comment
-      blocks.
-  * inst/cubic_approx_demo.m: New file.
-  * inst/cubic-approximator.fis: New file.
-  * inst/linear-tip-calculator.fis: New file.
-  * inst/linear_tip_demo.m: New file.
-  * inst/heart_demo_1.m: Renamed commandline_demo.m.
-  * inst/heart_demo_2.m: Renamed heart_demo.m.
-  * inst/mamdani_tip_demo.m: Renamed mamdani_demo.m.
-  * inst/sugeno_tip_demo.m: Renamed tipping_demo.m.
-  * inst/gensurf.m: Edited to handle 2-dimensional plots.
-  * inst/private/eval_rules_sugeno.m: Edited to handle linear output
-      membership functions.
-  * Demos tested under: Fedora 15/Octave 3.4.0
-  * Demos tested under: Fedora 15/Octave 3.2.4
-
-2011-06-21 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.2.2 released.
-  * ChangeLog: New file.
-  * DESCRIPTION: Updated file.
-  * inst/addmf.m: Modified to workaround a bug in Octave 3.4.0.
-  * inst/addrule.m: Modified to workaround a bug in Octave 3.4.0.
-  * inst/addvar.m: Modified to workaround a bug in Octave 3.4.0.
-  * inst/gaussmf.m: Modified demo and texinfo comment string.
-  * inst/getfis.m: Modified to workaround a bug in Octave 3.4.0.
-  * inst/readfis.m: Modified to workaround a bug in Octave 3.4.0.
-  * inst/private/aggregate_output_mamdani.m: Modified to workaround
-      a bug in Octave 3.4.0.
-  * inst/private/evalmf_private.m: Modified to workaround a bug in
-      Octave 3.4.0.
-  * Demos tested under: Fedora 15/Octave 3.4.0
-  * Demos tested under: Fedora 15/Octave 3.2.4
-
-2011-06-08 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.2.1 released.
-  * Initial release on Octave-Forge.
-  * Merged membership function demos into related function files.
-  * Created documentation for Octave-Forge website.
-  * DESCRIPTION: Updated file.
-  * Demos tested under: Fedora 13/Octave 3.2.4
-
-2011-05-25 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.2 released.
-  * Moved tests/demos/* and tests/fis/* to inst/*.
-  * Changed indentation and spacing to conform to Octave style.
-  * Converted comments to texinfo.
-  * DESCRIPTION: Update file.
-  * Demos tested under: Fedora 13/Octave 3.2.4
-
-2011-04-19 L. Markowsky <lmarkov@users.sourceforge.net>
-
-  * Version 0.1 released.
-  * Initial release on SourceForge.
-  * Demos tested under: Fedora 13/Octave 3.2.4

--- a/main/fuzzy-logic-toolkit/DESCRIPTION	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,12 +0,0 @@
-Name: fuzzy-logic-toolkit
-Version: 0.4.2
-Date: 2012-10-02
-Author: L. Markowsky <lmarkov@users.sourceforge.net>
-Maintainer: L. Markowsky <lmarkov@users.sourceforge.net>
-Title: Octave Fuzzy Logic Toolkit
-Description: A mostly MATLAB-compatible fuzzy logic toolkit for Octave.
-Depends: octave (>= 3.2.4)
-Autoload: no
-License: GPLv3+
-Url: http://octave.sf.net
- http://sf.net/projects/octave-fuzzy

--- a/main/fuzzy-logic-toolkit/INDEX	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,69 +0,0 @@
-fuzzy-logic-toolkit >> Octave Fuzzy Logic Toolkit
-
-Evaluation
- defuzz
- evalfis
- evalmf
-
-Plotting
- gensurf
- plotmf
-
-File Input/Output of Fuzzy Inference Systems
- readfis
- writefis
-
-Command-Line Creation and Modification of Fuzzy Inference Systems
- addmf
- addrule
- addvar
- newfis
- rmmf
- rmvar
- setfis
-
-Text Representation of Fuzzy Inference Systems
- getfis
- showfis
- showrule
-
-Membership Functions
- dsigmf
- gauss2mf
- gaussmf
- gbellmf
- pimf
- psigmf
- sigmf
- smf
- trapmf
- trimf
- zmf
-
-T-Norms and S-Norms (in addition to max/min)
- algebraic_product
- algebraic_sum
- bounded_difference
- bounded_sum
- drastic_product
- drastic_sum
- einstein_product
- einstein_sum
- hamacher_product
- hamacher_sum
-
-Complete Fuzzy Inference System Demos
- cubic_approx_demo
- heart_disease_demo_1
- heart_disease_demo_2
- investment_portfolio_demo
- linear_tip_demo
- mamdani_tip_demo
- sugeno_tip_demo
-
-Fuzzy Clustering Functions
- fcm
- gustafson_kessel
- partition_coeff
- partition_entropy
- xie_beni_index

--- a/main/fuzzy-logic-toolkit/NEWS	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,38 +0,0 @@
-Summary of important user-visible changes for fuzzy-logic-toolkit 0.4.2:
-------------------------------------------------------------------------
-
- ** The demos embedded in partition_coeff.m, partition_entropy.m,
-    and xie_beni_index.m were merged with the embedded demos in
-    fcm.m and gustafson_kessel.m.
-
-Summary of important user-visible changes for fuzzy-logic-toolkit 0.4.1:
-------------------------------------------------------------------------
-
- ** The package is no longer automatically loaded.
-
- ** The following demo scripts were rewritten and embedded in fcm.m,
-    gustafson_kessel.m, partition_coeff.m, partition_entropy.m, and
-    xie_beni_index.m:
-
-      fcm_demo_1
-      fcm_demo_2
-      gustafson_kessel_demo_1
-      gustafson_kessel_demo_2
-
-    (The separate demo script files have been removed.)
-
-Summary of important user-visible changes for fuzzy-logic-toolkit 0.4.0:
-------------------------------------------------------------------------
-
- ** The following functions are new:
-      fcm
-      gustafson_kessel
-      partition_coeff
-      partition_entropy
-      xie_beni_index
-
- ** The following demo scripts are new:
-      fcm_demo_1
-      fcm_demo_2
-      gustafson_kessel_demo_1
-      gustafson_kessel_demo_2

--- a/main/fuzzy-logic-toolkit/inst/addmf.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,140 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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{fis} =} addmf (@var{fis}, @var{in_or_out}, @var{var_index}, @var{mf_name}, @var{mf_type}, @var{mf_params})
-##
-## Add a membership function to an existing FIS 
-## structure and return the updated FIS.
-##
-## The types of the arguments are expected to be:
-## @itemize @w
-## @item @var{fis}:
-## an FIS structure
-## @item @var{in_or_out}:
-## 'input' or 'output' (case-insensitive)
-## @item @var{var_index}:
-## valid index of an FIS input/output variable
-## @item @var{mf_name}:
-## a string
-## @item @var{mf_type}:
-## a string
-## @item @var{mf_params}:
-## a vector
-## @end itemize
-##
-## If @var{mf_type} is one of the built-in membership functions, then the
-## number and values of the parameters must satisfy the membership function
-## requirements for the specified @var{mf_type}.
-##
-## Note that addmf will allow the user to add membership functions or 
-## membership function names for a given input or output variable that
-## duplicate mfs or mf names already entered.
-##
-## Also, constant and linear membership functions are not restricted to FIS
-## structure outputs or to Sugeno-type FIS structures, and the result of using
-## them for FIS inputs or Mamdani-type FIS outputs has not yet been tested.
-##
-## @noindent
-## 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
-
-## Author:        L. Markowsky
-## 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: 18 Aug 2012
-
-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 (nargin != 6)
-    puts ("Type 'help addmf' for more information.\n");
-    error ("addmf requires 6 arguments\n");
-  elseif (!is_fis (fis))
-    puts ("Type 'help addmf' for more information.\n");
-    error ("addmf's first argument must be an FIS structure\n");
-  elseif (!(is_string (in_or_out) && ...
-          ismember (tolower (in_or_out), {'input', 'output'})))
-    puts ("Type 'help addmf' for more information.\n");
-    error ("addmf's second argument must be 'input' or 'output'\n");
-  elseif (!is_var_index (fis, in_or_out, var_index))
-    puts ("Type 'help addmf' for more information.\n");
-    error ("addmf's third argument must be a variable index\n");
-  elseif (!(is_string (mf_name) && is_string (mf_type)))
-    puts ("Type 'help addmf' for more information.\n");
-    error ("addmf's fourth and fifth arguments must be strings\n");
-  elseif (!are_mf_params (mf_type, mf_params))
-    puts ("Type 'help addmf' for more information.\n");
-    error ("addmf's sixth argument must be a vector of parameters\n");
-  endif
-
-  ## Create a new membership function struct and update the
-  ## FIS structure.
-
-  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;
-    else
-      fis.input(var_index).mf = [fis.input(var_index).mf, new_mf];
-    endif
-  else
-    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
-
-%!demo
-%! ## Create new FIS.
-%! a = newfis ('Heart-Disease-Risk', 'sugeno', ...
-%!             'min', 'max', 'min', 'max', 'wtaver');
-%! 
-%! ## 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, 'High', 'trapmf', [180 200 300 301]);
-%! 
-%! a = addvar (a, 'input', 'HDL-Level', [0 100]);
-%! a = addmf (a, 'input', 2, 'Low-HDL', 'trapmf', [-1 0 35 45]);
-%! a = addmf (a, 'input', 2, 'Moderate-HDL', 'trapmf', [35 45 55 65]);
-%! a = addmf (a, 'input', 2, 'High-HDL', 'trapmf', [55 65 100 101]);
-%! 
-%! ## Plot the input membership functions.
-%! plotmf (a, 'input', 1);
-%! plotmf (a, 'input', 2);

--- a/main/fuzzy-logic-toolkit/inst/addrule.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,129 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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{fis} =} addrule (@var{fis}, @var{rule_matrix})
-##
-## Add a list of rules to an existing FIS structure and return
-## the updated FIS.
-##
-## Each row of the @var{rule_matrix} represents one rule and has the form:
-## @example
-## [in1_mf ... inM_mf out1_mf ... outN_mf weight connect]
-## @end example
-##
-## @noindent
-## where:
-##
-## @itemize @w
-## @item
-## in<i>_mf == membership function index for input i
-## @item
-## out<j>_mf == membership function index for output j
-## @item
-## weight == relative weight of the rule (0 <= weight <= 1)
-## @item
-## connect == antecedent connective (1 == and; 2 == or)
-## @end itemize
-##
-## 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) 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   4.2   2   1.03   1   2]
-## @end example
-##
-## @noindent
-## For a complete example that uses addrule, see heart_disease_demo_1.m.
-##
-## @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: 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 (nargin != 2)
-    puts ("Type 'help addrule' for more information.\n");
-    error ("addrule requires 2 arguments\n");
-  elseif (!is_fis (fis))
-    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. 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.
-
-  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));
-    weight = rule_matrix(i, num_inputs + num_outputs + 1);
-    connection = rule_matrix(i, num_inputs + num_outputs + 2);
-    new_rules(i) = struct ('antecedent', antecedent, ...
-                           'consequent', consequent, ...
-                           'weight', weight, ...
-                           'connection', connection);
-  endfor
-
-  if (length (fis.rule) == 0)
-    fis.rule = new_rules;
-  else
-    fis.rule = [fis.rule, new_rules];
-  endif
-
-endfunction

--- a/main/fuzzy-logic-toolkit/inst/addvar.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,99 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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{fis} =} addvar (@var{fis}, @var{in_or_out}, @var{var_name}, @var{var_range})
-##
-## Add an input or output variable to an existing FIS
-## structure and return the updated FIS.
-##
-## The types of the arguments are expected to be:
-## @itemize @w
-## @item
-## @var{fis} - an FIS structure
-## @item
-## @var{in_or_out} - either 'input' or 'output' (case-insensitive)
-## @item
-## @var{var_name} - a string
-## @item
-## @var{var_range} - a vector [x1 x2] of two real numbers
-## @end itemize
-##
-## The vector components x1 and x2, which must also satisfy x1 <= x2,
-## specify the lower and upper bounds of the variable's domain.
-##
-## @noindent
-## To run the demonstration code, type @t{demo('addvar')} at the Octave prompt.
-##
-## @end deftypefn
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy variable
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      addvar.m
-## 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 (nargin != 4)
-    puts ("Type 'help addvar' for more information.\n");
-    error ("addvar requires 4 arguments\n");
-  elseif (!is_fis (fis))
-    puts ("Type 'help addvar' for more information.\n");
-    error ("addvar's first argument must be an FIS structure\n");
-  elseif (!(is_string (in_or_out) && ...
-          ismember (tolower (in_or_out), {'input', 'output'})))
-    puts ("Type 'help addvar' for more information.\n");
-    error ("addvar's second argument must be 'input' or 'output'\n");
-  elseif (!is_string (var_name))
-    puts ("Type 'help addvar' for more information.\n");
-    error ("addvar's third argument must be a string\n\n");
-  elseif (!are_bounds (var_range))
-    puts ("Type 'help addvar' for more information.\n");
-    error ("addvar's fourth argument must specify variable bounds\n");
-  endif
-
-  ## Create a new variable struct and update the FIS input or output
-  ## variable list.
-
-  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;
-    else
-      fis.input = [fis.input, new_variable];
-    endif
-  else
-    if (length (fis.output) == 0)
-      fis.output = new_variable;
-    else
-      fis.output = [fis.output, new_variable];
-    endif
-  endif
-
-endfunction
-
-%!demo
-%! a = newfis ('Heart-Disease-Risk', 'sugeno', ...
-%!             'min', 'max', 'min', 'max', 'wtaver');
-%! a = addvar (a, 'input', 'LDL-Level', [0 300]);
-%! getfis (a, 'input', 1);

--- a/main/fuzzy-logic-toolkit/inst/algebraic_product.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,59 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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: 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 ("invalid arguments to function algebraic_product\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
-

--- a/main/fuzzy-logic-toolkit/inst/algebraic_sum.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,72 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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: 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))))
-    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
-

--- a/main/fuzzy-logic-toolkit/inst/bounded_difference.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,75 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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: 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 ("invalid arguments to function bounded_difference\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
-

--- a/main/fuzzy-logic-toolkit/inst/bounded_sum.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,72 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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: 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))))
-    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
-

--- a/main/fuzzy-logic-toolkit/inst/cubic_approx_demo.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,54 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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} {} 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 functions.
-##
-## The demo:
-## @itemize @minus
-## @item
-## reads an FIS structure from a file
-## @item
-## plots the input membership functions
-## @item
-## plots the (linear) output functions
-## @item
-## plots the FIS output as a function of the input
-## @end itemize
-##
-## @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: 20 Aug 2012
-
-## Read the FIS structure from a file.
-fis = readfis ('cubic_approximator.fis');
-
-## Plot the input membership functions and linear output functions.
-plotmf (fis, 'input', 1);
-plotmf (fis, 'output', 1, -150, 150);
-
-## Plot the FIS output y as a function of the input x.
-gensurf (fis);

--- a/main/fuzzy-logic-toolkit/inst/cubic_approximator.fis	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,81 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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'
-Version=2.0
-NumInputs=1
-NumOutputs=1
-NumRules=11
-AndMethod='min'
-OrMethod='max'
-ImpMethod='min'
-AggMethod='max'
-DefuzzMethod='wtaver'
-
-[Input1]
-Name='X'
-Range=[-5 5]
-NumMFs=11
-MF1 = 'About-Neg-Five':'trimf', [-6 -5 -4]
-MF2 = 'About-Neg-Four':'trimf', [-5 -4 -3]
-MF3 = 'About-Neg-Three':'trimf', [-4 -3 -2]
-MF4 = 'About-Neg-Two':'trimf', [-3 -2 -1]
-MF5 = 'About-Neg-One':'trimf', [-2 -1 0]
-MF6 = 'About-Zero':'trimf', [-1 0 1]
-MF7 = 'About-One':'trimf', [0 1 2]
-MF8 = 'About-Two':'trimf', [1 2 3]
-MF9 = 'About-Three':'trimf', [2 3 4]
-MF10 = 'About-Four':'trimf', [3 4 5]
-MF11 = 'About-Five':'trimf', [4 5 6]
-
-[Output1]
-Name='Approx-X-Cubed'
-Range=[-5 5]
-NumMFs=11
-MF1 = 'Tangent-at-Neg-Five':'linear', [75 250]
-MF2 = 'Tangent-at-Neg-Four':'linear', [48 128]
-MF3 = 'Tangent-at-Neg-Three':'linear', [27 54]
-MF4 = 'Tangent-at-Neg-Two':'linear', [12 16]
-MF5 = 'Tangent-at-Neg-One':'linear', [3 2]
-MF6 = 'Tangent-at-Zero':'linear', [0 0]
-MF7 = 'Tangent-at-One':'linear', [3 -2]
-MF8 = 'Tangent-at-Two':'linear', [12 -16]
-MF9 = 'Tangent-at-Three':'linear', [27 -54]
-MF10 = 'Tangent-at-Four':'linear', [48 -128]
-MF11 = 'Tangent-at-Five':'linear', [75 -250]
-
-[Rules]
-1, 1 (1) : 1
-2, 2 (1) : 1
-3, 3 (1) : 1
-4, 4 (1) : 1
-5, 5 (1) : 1
-6, 6 (1) : 1
-7, 7 (1) : 1
-8, 8 (1) : 1
-9, 9 (1) : 1
-10, 10 (1) : 1
-11, 11 (1) : 1

--- a/main/fuzzy-logic-toolkit/inst/defuzz.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,250 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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{crisp_x} =} defuzz (@var{x}, @var{y}, @var{defuzz_method})
-## @deftypefnx {Function File} {@var{crisp_x} =} defuzz (@var{[x1 x2 ... xn]}, @var{[y1 y2 ... yn]}, @var{defuzz_method})
-##
-## For a given domain, set of fuzzy function values, and defuzzification method,
-## return the defuzzified (crisp) value of the fuzzy function.
-##
-## The arguments @var{x} and @var{y} must be either two real numbers or
-## two equal-length, non-empty vectors of reals, with the elements of @var{x}
-## strictly increasing. @var{defuzz_method} must be a (case-sensitive) string
-## corresponding to a defuzzification method. Defuzz handles both built-in
-## and custom defuzzification methods. 
-##
-## The built-in defuzzification methods are:
-## @table @samp
-## @item centroid
-## Return the x-value of the centroid.
-## @item bisector
-## Return the x-value of the vertical bisector of the area.
-## @item mom
-## Return the mean x-value of the points with maximum y-values.
-## @item som
-## Return the smallest (absolute) x-value of the points with maximum y-values.
-## @item lom
-## Return the largest (absolute) x-value of the points with maximum y-values.
-## @item wtaver
-## Return the weighted average of the x-values, with the y-values used as
-## weights.
-## @item wtsum
-## Return the weighted sum of the x-values, with the y-values used as weights.
-## @end table
-## @end deftypefn
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy defuzzification
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      defuzz.m
-## 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 (nargin != 3)
-    puts ("Type 'help defuzz' for more information.\n");
-    error ("defuzz requires 3 arguments\n");
-  elseif (!is_domain (x))
-    puts ("Type 'help defuzz' for more information.\n");
-    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 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.
-
-  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).
-##
-## 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.
-##----------------------------------------------------------------------
-
-function crisp_x = centroid (x, y)
-
-  crisp_x = trapz (x, x.*y) / trapz (x, y);
-
-endfunction
-
-##----------------------------------------------------------------------
-## Usage: crisp_x = bisector (x, y)
-##        crisp_x = bisector ([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 a bisector 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.
-##----------------------------------------------------------------------
-
-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.
-
-  half_area = trapz (x, y) / 2;
-  x_len = length (x);
-  upper = x_len;
-  lower = 1;
-  count = 1;
-
-  while ((lower <= upper) && (count++ < x_len))
-    midpoint = round ((lower + upper)/2);
-    left_domain = [ones(1, midpoint), zeros(1, x_len-midpoint)];
-    left_y_vals = left_domain .* y;
-    left_area = trapz (x, left_y_vals);
-    error = left_area - half_area;
-
-    if (error > 0)
-      upper = midpoint;
-    else
-      lower = midpoint;
-    endif
-  endwhile
-
-  crisp_x = midpoint;
-
-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. 
-##
-## 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.
-##----------------------------------------------------------------------
-
-function crisp_x = mom (x, y)
-
-  max_y = max (y);
-  y_val = @(y_val) if (y_val == max_y) 1 else 0 endif;
-  max_y_locations = arrayfun (y_val, y);
-  crisp_x = sum (x .* max_y_locations) / sum (max_y_locations);
-
-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. 
-##
-## 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.
-##----------------------------------------------------------------------
-
-function crisp_x = som (x, y)
-
-  max_y = max (y);
-  y_val = @(y_val) if (y_val == max_y) 1 else (NaN) endif;
-  max_y_locations = arrayfun (y_val, y);
-  crisp_x = min (x .* max_y_locations);
-
-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.
-##
-## 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.
-##----------------------------------------------------------------------
-
-function crisp_x = lom (x, y)
-
-  max_y = max (y);
-  y_val = @(y_val) if (y_val == max_y) 1 else (NaN) endif;
-  max_y_locations = arrayfun (y_val, y);
-  crisp_x = max (x .* max_y_locations);
-
-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.
-##
-## 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)
-
-  retval = sum (weights .* values) / sum (weights);
-
-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.
-##
-## 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)
-
-  retval = sum (weights .* values);
-
-endfunction

--- a/main/fuzzy-logic-toolkit/inst/drastic_product.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,107 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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: 20 Aug 2012
-
-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

--- a/main/fuzzy-logic-toolkit/inst/drastic_sum.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,107 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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: 20 Aug 2012
-
-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

--- a/main/fuzzy-logic-toolkit/inst/dsigmf.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,121 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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{y} =} dsigmf (@var{x}, @var{params})
-## @deftypefnx {Function File} {@var{y} =} dsigmf (@var{[x1 x2 ... xn]}, @var{[a1 c1 a2 c2]})
-##
-## For a given domain @var{x} and parameters @var{params} (or
-## @var{[a1 c1 a2 c2]}), return the corresponding @var{y} values for the
-## difference between two sigmoidal membership functions.
-##
-## The argument @var{x} must be a real number or a non-empty list of strictly
-## increasing real numbers, and @var{a1}, @var{c1}, @var{a2}, and @var{c2} must
-## be real numbers. This membership function satisfies the equation:
-## @example
-## f(x) = 1/(1 + exp(-a1*(x - c1))) - 1/(1 + exp(-a2*(x - c2)))
-## @end example
-##
-## @noindent
-## and in addition, is bounded above and below by 1 and 0 (regardless of the
-## value given by the formula above).
-##
-## If the parameters @var{a1} and @var{a2} are positive and @var{c1} and
-## @var{c2} are far enough apart with @var{c1} < @var{c2}, then:
-## @itemize @w
-## @item
-## (a1)/4 ~ the rising slope at c1
-## @item
-## c1 ~ the left inflection point
-## @item
-## (-a2)/4 ~ the falling slope at c2
-## @item
-## c2 ~ the right inflection point
-## @end itemize
-##
-## @noindent
-## and at each inflection point, the value of the function is about 0.5:
-## @itemize @w
-## @item
-## f(c1) ~ f(c2) ~ 0.5.
-## @end itemize
-##
-## @noindent
-## Here, the symbol ~ means "approximately equal".
-##
-## @noindent
-## 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
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership sigmoidal
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      dsigmf.m
-## 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 (nargin != 2)
-    puts ("Type 'help dsigmf' for more information.\n");
-    error ("dsigmf requires 2 arguments\n");
-  elseif (!is_domain (x))
-    puts ("Type 'help dsigmf' for more information.\n");
-    error ("dsigmf's first argument must be a valid domain\n");
-  elseif (!are_mf_params ('dsigmf', params))
-    puts ("Type 'help dsigmf' for more information.\n");
-    error ("dsigmf's second argument must be a parameter vector\n");
-  endif
-
-  ## Calculate and return the y values of the membership function on the
-  ## domain x.
-
-  a1 = params(1);
-  c1 = params(2);
-  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 = arrayfun (y_val, x);
-
-endfunction
-
-%!demo
-%! x = 0:100;
-%! params = [0.5 20 0.3 60];
-%! y1 = dsigmf(x, params);
-%! params = [0.3 20 0.2 60];
-%! y2 = dsigmf(x, params);
-%! params = [0.2 20 0.1 60];
-%! y3 = dsigmf(x, params);
-%! figure('NumberTitle', 'off', 'Name', 'dsigmf demo');
-%! plot(x, y1, 'r;params = [0.5 20 0.3 60];', 'LineWidth', 2)
-%! hold on;
-%! plot(x, y2, 'b;params = [0.3 20 0.2 60];', 'LineWidth', 2)
-%! hold on;
-%! plot(x, y3, 'g;params = [0.2 20 0.1 60];', 'LineWidth', 2)
-%! ylim([-0.1 1.1]);
-%! xlabel('Crisp Input Value', 'FontWeight', 'bold');
-%! ylabel('Degree of Membership', 'FontWeight', 'bold');
-%! grid;

--- a/main/fuzzy-logic-toolkit/inst/einstein_product.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,97 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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: 20 Aug 2012
-
-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

--- a/main/fuzzy-logic-toolkit/inst/einstein_sum.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,96 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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: 20 Aug 2012
-
-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

--- a/main/fuzzy-logic-toolkit/inst/evalfis.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,267 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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{output} =} evalfis (@var{user_input}, @var{fis})
-## @deftypefnx {Function File} {@var{output} =} evalfis (@var{user_input}, @var{fis}, @var{num_points})
-## @deftypefnx {Function File} {[@var{output}, @var{rule_input}, @var{rule_output}, @var{fuzzy_output}] =} evalfis (@var{user_input}, @var{fis})
-## @deftypefnx {Function File} {[@var{output}, @var{rule_input}, @var{rule_output}, @var{fuzzy_output}] =} evalfis (@var{user_input}, @var{fis}, @var{num_points})
-##
-## Return the crisp output(s) of an FIS for each row in a matrix of crisp input
-## values.
-## Also, for the last row of @var{user_input}, return the intermediate results:
-##
-## @table @var
-## @item rule_input
-## a matrix of the degree to which
-## each FIS rule matches each FIS input variable
-## @item rule_output
-## a matrix of the fuzzy output for each (rule, FIS output) pair
-## @item fuzzy_output
-## a matrix of the aggregated output for each FIS output variable
-## @end table
-##
-## The optional argument @var{num_points} specifies the number of points over
-## which to evaluate the fuzzy values. The default value of @var{num_points} is
-## 101.
-##
-## @noindent
-## Argument @var{user_input}:
-## 
-## @var{user_input} is a matrix of crisp input values. Each row 
-## represents one set of crisp FIS input values. For an FIS that has N inputs,
-## an input matrix of z sets of input values will have the form:
-##
-## @example
-## @group
-## [input_11 input_12 ... input_1N]  <-- 1st row is 1st set of inputs
-## [input_21 input_22 ... input_2N]  <-- 2nd row is 2nd set of inputs
-## [             ...              ]                 ...
-## [input_z1 input_z2 ... input_zN]  <-- zth row is zth set of inputs
-## @end group
-## @end example
-##
-## @noindent
-## Return value @var{output}:
-##
-## @var{output} is a matrix of crisp output values. Each row represents
-## the set of crisp FIS output values for the corresponding row of
-## @var{user_input}. For an FIS that has M outputs, an @var{output} matrix
-## corresponding to the preceding input matrix will have the form:
-##
-## @example
-## @group
-## [output_11 output_12 ... output_1M]  <-- 1st row is 1st set of outputs
-## [output_21 output_22 ... output_2M]  <-- 2nd row is 2nd set of outputs
-## [               ...               ]                 ...
-## [output_z1 output_z2 ... output_zM]  <-- zth row is zth set of outputs
-## @end group
-## @end example
-##
-## @noindent
-## The intermediate result @var{rule_input}:
-## 
-## The matching degree for each (rule, input value) pair is specified by the
-## @var{rule_input} matrix. For an FIS that has Q rules and N input variables,
-## the matrix will have the form:
-## @example
-## @group
-##          in_1  in_2 ...  in_N
-## rule_1 [mu_11 mu_12 ... mu_1N]
-## rule_2 [mu_21 mu_22 ... mu_2N]
-##        [            ...      ]
-## rule_Q [mu_Q1 mu_Q2 ... mu_QN]
-## @end group
-## @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}:
-##
-## For either a Mamdani-type FIS (that is, an FIS that does not have constant or
-## linear output membership functions) or a Sugeno-type FIS (that is, an FIS
-## that has only constant and linear output membership functions),
-## @var{rule_output} specifies the fuzzy output for each (rule, FIS output) pair.
-## The format of rule_output depends on the FIS type.
-##
-## For a Mamdani-type FIS, @var{rule_output} is a @var{num_points} x (Q * M)
-## matrix, where Q is the number of rules and M is the number of FIS output
-## variables. Each column of this matrix gives the y-values of the fuzzy
-## output for a single (rule, FIS output) pair.
-##
-## @example
-## @group
-##                  Q cols            Q cols              Q cols 
-##             ---------------   ---------------     ---------------
-##             out_1 ... out_1   out_2 ... out_2 ... out_M ... out_M
-##          1 [                                                     ]
-##          2 [                                                     ]
-##        ... [                                                     ]
-## num_points [                                                     ]
-## @end group
-## @end example
-##
-## For a Sugeno-type FIS, @var{rule_output} is a 2 x (Q * M) matrix.
-## Each column of this matrix gives the (location, height) pair of the
-## singleton output for a single (rule, FIS output) pair.
-##
-## @example
-## @group
-##                Q cols            Q cols                  Q cols 
-##           ---------------   ---------------         ---------------
-##           out_1 ... out_1   out_2 ... out_2   ...   out_M ... out_M
-## location [                                                         ]
-##   height [                                                         ]
-## @end group
-## @end example
-##
-## @noindent
-## The intermediate result @var{fuzzy_output}:
-##
-## The format of @var{fuzzy_output} depends on the FIS type ('mamdani' or
-## 'sugeno').
-##
-## For either a Mamdani-type FIS or a Sugeno-type FIS, @var{fuzzy_output}
-## specifies the aggregated fuzzy output for each FIS output.
-##
-## For a Mamdani-type FIS, the aggregated @var{fuzzy_output} is a
-## @var{num_points} x M matrix. Each column of this matrix gives the y-values
-## of the fuzzy output for a single FIS output, aggregated over all rules.
-##
-## @example
-## @group
-##             out_1  out_2  ...  out_M
-##          1 [                        ]
-##          2 [                        ]
-##        ... [                        ]
-## num_points [                        ]
-## @end group
-## @end example
-##
-## For a Sugeno-type FIS, the aggregated output for each FIS output is a 2 x L
-## matrix, where L is the number of distinct singleton locations in the
-## @var{rule_output} for that FIS output:
-##
-## @example
-## @group
-##           singleton_1  singleton_2 ... singleton_L
-## location [                                        ]
-##   height [                                        ]
-## @end group
-## @end example
-##
-## Then @var{fuzzy_output} is a vector of M structures, each of which has an index and
-## one of these matrices.
-##
-## @noindent
-## Examples:
-##
-## Seven examples of using evalfis are shown in:
-## @itemize @bullet
-## @item
-## cubic_approx_demo.m
-## @item
-## heart_disease_demo_1.m
-## @item
-## heart_disease_demo_2.m
-## @item
-## investment_portfolio_demo.m
-## @item
-## linear_tip_demo.m
-## @item
-## mamdani_tip_demo.m
-## @item
-## sugeno_tip_demo.m
-## @end itemize
-##
-## @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 inference system fis
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      evalfis.m
-## 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 ((nargin != 2) && (nargin != 3))
-    puts ("Type 'help evalfis' for more information.\n");
-    error ("evalfis requires 2 or 3 arguments\n");
-  elseif (!is_fis (fis))
-    puts ("Type 'help evalfis' for more information.\n");
-    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 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");
-  endif
-
-  ## Call a private function to compute the output.
-  ## (The private function is also called by gensurf.)
-
-  [output, rule_input, rule_output, fuzzy_output] = ...
-    evalfis_private (user_input, fis, num_points);
-
-endfunction

--- a/main/fuzzy-logic-toolkit/inst/evalmf.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,106 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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{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, 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
-## of valid parameters for @var{mf_type}, and @var{mf_type} must be a string
-## 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 code, type @t{demo('evalmf')} at the Octave prompt.
-## @end deftypefn
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership evaluate
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      evalmf.m
-## 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 ((nargin < 3) || (nargin > 5))
-    puts ("Type 'help evalmf' for more information.\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 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, hedge, not_flag);
-
-endfunction
-
-%!demo
-%! x = 0:100;
-%! params = [25 50 75];
-%! mf_type = 'trimf';
-%! y = evalmf(x, params, mf_type);
-%! 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');
-%! ylabel('Degree of Membership', 'FontWeight', 'bold');
-%! grid;

--- a/main/fuzzy-logic-toolkit/inst/fcm.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,364 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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}])
-##
-## 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. 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
-## @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{gustafson_kessel, partition_coeff, partition_entropy, xie_beni_index}
-##
-## @end deftypefn
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy partition clustering
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      fcm.m
-## 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])
-
-  ## 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 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 prototypes and the calculation.
-  V = init_cluster_prototypes (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 = update_cluster_membership (V, X, m, k, n, sqr_dist);
-    Mu_m = Mu .^ m;
-    V = update_cluster_prototypes (Mu_m, X, k);
-    sqr_dist = square_distance_matrix (X, V);
-    obj_fcn_history(iteration) = ...
-      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 = ...
-      compute_cluster_convergence (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
-
-##----------------------------------------------------------------------
-## 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
-%! ##    - 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;
-%! [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
-%! 
-%! ## 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
-##----------------------------------------------------------------------
-
-%!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
-%! ##    - 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];
-%! 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
-%! 
-%! ## 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));

--- a/main/fuzzy-logic-toolkit/inst/gauss2mf.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,128 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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{y} =} gauss2mf (@var{x}, @var{params})
-## @deftypefnx {Function File} {@var{y} =} gauss2mf (@var{[x1 x2 ... xn]}, @var{[sig1 c1 sig2 c2]})
-##
-## For a given domain @var{x} and parameters @var{params} (or
-## @var{[sig1 c1 sig2 c2]}), return the corresponding @var{y} values for the
-## two-sided Gaussian composite membership function. This membership function is
-## a smooth curve calculated from two Gaussian membership functions as follows:
-##
-## Given parameters @var{sig1}, @var{c1}, @var{sig2}, and @var{c2}, that define
-## two Gaussian membership functions, let:
-##
-## @example
-## @group
-## f1(x) = exp((-(x - c1)^2)/(2 * sig1^2))     if x <= c1
-##         1                                   otherwise
-##
-## f2(x) = 1                                   if x <= c2
-##         exp((-(x - c2)^2)/(2 * sig2^2))     otherwise
-## @end group
-## @end example
-##
-## @noindent
-## Then gauss2mf is given by:
-##
-## @example
-## f(x) = f1(x) * f2(x)
-## @end example
-##
-## The argument @var{x} must be a real number or a non-empty vector of strictly
-## increasing real numbers, and @var{sig1}, @var{c1}, @var{sig2}, and @var{c2}
-## must be real numbers.
-## Gauss2mf always returns a continuously differentiable curve with values in
-## the range [0, 1]. 
-##
-## If @var{c1} < @var{c2}, gauss2mf is a normal membership function (has a
-## maximum value of 1), with the rising curve identical to that of f1(x) and a
-## falling curve identical to that of f2(x), above. If @var{c1} >= @var{c2},
-## gauss2mf returns a subnormal membership function (has a maximum value less
-## than 1).
-##
-## @noindent
-## 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
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership gaussian
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      gauss2mf.m
-## 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 (nargin != 2)
-    puts ("Type 'help gauss2mf' for more information.\n");
-    error ("gauss2mf requires 2 arguments\n");
-  elseif (!is_domain (x))
-    puts ("Type 'help gauss2mf' for more information.\n");
-    error ("gauss2mf's first argument must be a valid domain\n");
-  elseif (!are_mf_params ('gauss2mf', params))
-    puts ("Type 'help gauss2mf' for more information.\n");
-    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.
-
-  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)) + ...
-                    (x_val > c1);
-
-  f2_val = @(x_val) (x_val <= c2) + ... 
-                    (x_val > c2) * exp ((-(x_val - c2)^2)/(2 * sig2^2));
-
-  f1 = arrayfun (f1_val, x);
-  f2 = arrayfun (f2_val, x);
-  y = f1 .* f2;
-
-endfunction
-
-%!demo
-%! x = -10:0.2:10;
-%! params = [3 0 1.5 2];
-%! y1 = gauss2mf(x, params);
-%! params = [1.5 0 3 2];
-%! y2 = gauss2mf(x, params);
-%! params = [1.5 2 3 0];
-%! y3 = gauss2mf(x, params);
-%! figure('NumberTitle', 'off', 'Name', 'gauss2mf demo');
-%! plot(x, y1, 'r;params = [3 0 1.5 2];', 'LineWidth', 2);
-%! hold on ;
-%! plot(x, y2, 'b;params = [1.5 0 3 2];', 'LineWidth', 2);
-%! hold on ;
-%! plot(x, y3, 'g;params = [1.5 2 3 0];', 'LineWidth', 2);
-%! ylim([-0.1 1.1]);
-%! xlabel('Crisp Input Value', 'FontWeight', 'bold');
-%! ylabel('Degree of Membership', 'FontWeight', 'bold');
-%! grid;
-%! hold;

--- a/main/fuzzy-logic-toolkit/inst/gaussmf.m	Wed Jan 08 22:25:55 2014 +0000
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,113 +0,0 @@
-## Copyright (C) 2011-2012 L. Markowsky <lmarkov@users.sourceforge.net>
-##
-## 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{y} =} gaussmf (@var{x}, @var{params})
-## @deftypefnx {Function File} {@var{y} =} gaussmf (@var{[x1 x2 ... xn]}, @var{[sig c]})
-##
-## 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. 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.
-## This membership function satisfies the equation:
-## @example
-## f(x) = exp((-(x - c)^2)/(2 * sig^2))
-## @end example
-##
-## @noindent
-## which always returns values in the range [0, 1].
-##
-## Just as for the Gaussian (normal) distribution, the parameters @var{sig} and
-## @var{c} represent:
-## @itemize @w
-## @item
-## sig^2 == the variance (a measure of the width of the curve)
-## @item
-## c == the center (the mean; the x value of the peak)
-## @end itemize
-##
-## @noindent
-## For larger values of @var{sig}, the curve is flatter, and for smaller values
-## of sig, the curve is narrower. The @var{y} value at the center is always 1:
-## @itemize @w
-## @item
-## f(c) == 1
-## @end itemize
-##
-## @noindent
-## 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
-
-## Author:        L. Markowsky
-## Keywords:      fuzzy-logic-toolkit fuzzy membership gaussian
-## Directory:     fuzzy-logic-toolkit/inst/
-## Filename:      gaussmf.m
-## 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 (nargin != 2)
-    puts ("Type 'help gaussmf' for more information.\n");
-    error ("gaussmf requires 2 arguments\n");
-  elseif (!is_domain (x))
-    puts ("Type 'help gaussmf' for more information.\n");
-    error ("gaussmf's first argument must be a valid domain\n");
-  elseif (!are_mf_params ('gaussmf', params))
-    puts ("Type 'help gaussmf' for more information.\n");
-    error ("gaussmf's second argument must be a parameter vector\n");
-  endif
-
-  ## Calculate and return the y values of the membership function on the
-  ## domain x.
-
-  sig = params(1);
-  c = params(2);
-
-  y_val = @(x_val) exp ((-(x_val - c)^2)/(2 * sig^2));
-  y = arrayfun (y_val, x);
-
-endfunction
-
-%!demo
-%! x = -5:0.1:5;
-%! params = [0.5 0];
-%! y1 = gaussmf(x, params);
-%! params = [1 0];
-%! y2 = gaussmf(x, params);
-%! params = [2 0];
-%! y3 = gaussmf(x, params);
-%! figure('NumberTitle', 'off', 'Name', 'gaussmf demo');
-%! plot(x, y1, 'r;params = [0.5 0];', 'LineWidth', 2);
-%! hold on ;
-%! plot(x, y2, 'b;params = [1 0];', 'LineWidth', 2);
-%! hold on ;
-%! plot(x, y3, 'g;params = [2 0];', 'LineWidth', 2);
-%! ylim([-0.1 1.1]);
-%! xlabel('Crisp Input Value');
-%! ylabel('Degree of Membership');
-%! grid;
-%! hold;