% MINCALC file mincalc.m Determines minterm probabilities
% Version of 1/22/94 Updated for version 5.1 on  6/6/97
% Assumes a data file which includes
%  1. Call for minvecq to set q basic minterm vectors, each (1 x 2^q)
%  2. Data vectors DV = matrix of md data Boolean combinations of basic sets--
%     Matlab produces md minterm vectors-- one on each row.
%     The first combination is always A|Ac (the whole space)
%  3. DP = row matrix of md data probabilities.
%     The first probability is always 1.
%  4. Target vectors TV = matrix of mt target Boolean combinations.
%     Matlab produces a row minterm vector for each target combination.
%     If there are no target combinations, set TV = [];
[md,nd] = size(DV);
ND = 0:nd-1;
ID = eye(nd);                 % Row i is minterm vector i-1
[mt,nt] = size(TV);
MT = 1:mt;
rd = rank(DV);
if rd < md                    
   disp('Data vectors are NOT linearly independent')
  else
   disp('Data vectors are linearly independent')
end
% Identification of which minterm probabilities can be determined from the data
% (i.e., which minterm vectors are not linearly independent of data vectors)
AM = zeros(1,nd);
for i = 1:nd
  AM(i) = rd == rank([DV;ID(i,:)]);  % Checks for linear dependence of each
  end   
am = find(AM);                             % minterm vector
CAM = ID(am,:)/DV;     % Determination of coefficients for the available minterms
pma = DP*CAM';                % Calculation of probabilities of available minterms
PMA = [ND(am);pma]';
if sum(pma < -0.001) > 0      % Check for data consistency
   disp('Data probabilities are INCONSISTENT')
else
% Identification of which target probabilities are computable from the data
CT = zeros(1,mt);
for j = 1:mt
  CT(j) = rd == rank([DV;TV(j,:)]);
  end
ct  = find(CT);
CCT = TV(ct,:)/DV;            % Determination of coefficients for computable targets
ctp = DP*CCT';                % Determination of probabilities
disp(' Computable target probabilities')
disp([MT(ct); ctp]')
end                           % end for "if sum(pma < -0.001) > 0"
disp(['The number of minterms is ',num2str(nd),])
disp(['The number of available minterms is ',num2str(length(pma)),])
disp('Available minterm probabilities are in vector pma')
disp('To view available minterm probabilities, call for PMA')