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## Copyright (C) 2011-2025 L. Markowsky <lmarkowsky@gmail.com>
##
## 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:
##
## @verbatim
## [in1_mf ... inM_mf out1_mf ... outN_mf weight connect]
## @end verbatim
##
## where:
##
## @multitable @columnfractions .25 .70
## @headitem Element in Rule Vector @tab Expected Type or Value
## @item in<i>_mf
## @tab membership function index for input i
## @item out<j>_mf
## @tab membership function index for output j
## @item weight
## @tab relative weight of the rule (0 <= weight <= 1)
## @item connect
## @tab antecedent connective (1 == and; 2 == or)
## @item @ @
## @tab @ @
## @headitem Hedge String @tab Effect of Applying Hedge
## @item "not"
## @tab prepend a minus sign to the membership function index
## @item "somewhat"
## @tab append ".05" to the membership function index
## @item "very"
## @tab append ".20" to the membership function index
## @item "extremely"
## @tab append ".30" to the membership function index
## @item "very very"
## @tab append ".40" to the membership function index
## @item custom hedge
## @tab append .xy, where x.y is the degree to which the membership
## value should be raised, to the membership function index
## @end multitable
## @sp 1
## To omit an input or output, use 0 for the membership function index.
## The consequent connective is always "and".
##
## For example, to express:
##
## @verbatim
## "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 verbatim
##
## with weight 1, the corresponding row of @var{rule_matrix} would be:
##
## @verbatim
## [2 0 -1 4.2 2 1.03 1 2]
## @end verbatim
##
## 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: 13 Jun 2024
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)
error ("addrule requires 2 arguments\n");
elseif (!is_fis (fis))
error ("addrule's first argument must be an FIS structure\n");
elseif (!is_real_matrix (rule_matrix))
error ("addrule's 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
%!shared fis
%! fis = readfis ('mamdani_tip_calculator.fis');
%!test
%! fis = addrule(fis, [1 2 2 1 1 1]);
%! assert(fis.rule(5).antecedent, [1 2]);
## Test input validation
%!error <addrule requires 2 arguments>
%! addrule()
%!error <addrule requires 2 arguments>
%! addrule(1)
%!error <addrule: function called with too many inputs>
%! addrule(1, 2, 3)
%!error <addrule's first argument must be an FIS structure>
%! addrule(1, 2)
%!error <addrule's second argument must be a matrix of real numbers>
%! addrule(fis, 2j)
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