1 files changed, 123 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/SLP/examples/test_gener.m b/sourcecodes/bnt-master/SLP/examples/test_gener.m
new file mode 100644
index 00000000..d8d5ebb2
--- /dev/null
+++ b/sourcecodes/bnt-master/SLP/examples/test_gener.m
@@ -0,0 +1,123 @@
+%  data generation
+clear all
+close all
+
+ddd = datestr(now);
+ddd([12 15 18])='-' ;
+fnd=[ddd '.txt'];
+diary(fnd)
+
+% Metaparams
+hyp = 'mar';
+ntests = 2;   % change it !
+nessais = 2;  % change it !
+m = 1000;     % change it !
+
+% INIT
+missing = 2;
+misv = -9999;
+%test = zeros(nessais,6);
+test = zeros(nessais,ntests);
+taille = zeros(nessais,ntests);
+kiki = zeros(nessais,1);
+
+%%%%%%%%%% TESTS %%%%%%%%%%%
+for essai=1:nessais
+
+  N = ceil(rand*11) + 2
+  base_proba = .15 + rand/4;
+
+  fan_in = ceil(rand*4)
+  dag=mk_rnd_dag(N,fan_in)
+  discrete=1:N;
+  for i=1:N, node_sizes(i) = ceil(rand*4)+1; end
+  bnet = mk_bnet(dag, node_sizes, discrete);
+  node_sizes
+  for i=1:N, bnet.CPD{i} = tabular_CPD(bnet, i); end
+
+  if prod([hyp(1:3) == 'mca']+0),
+    bnet_miss = gener_MCAR_net(bnet, base_proba);
+    disp(' - MCAR net generated');
+  elseif prod([hyp(1:3) == 'mar']+0),
+    bnet_miss = gener_MAR_net(bnet, base_proba);
+    disp(' - MAR net generated');
+  end
+
+  [data, comp_data, bnet_miss, taux, bnet_orig, notok, dT] = gener_data_from_bnet_miss(bnet_miss, m, base_proba ,1);
+  base_proba
+
+  kiki(essai) = 1-chi2cdf(dT,1);
+
+  %test(essai,1)=1-chi2cdf(d,df);
+  node0=[]; param0=[];
+  for i=1:ntests
+    % choose a node
+    node=ceil(rand*N);
+    while ~isempty(myintersect(node,node0)) & i<N-2,
+      node = ceil(rand*N);
+    end
+    node0 = myunion(node0,node);
+
+    % choose a param
+    par = parents(bnet_miss.dag, node+N);
+    sorted=[]; ord=[];
+    for par1=1:length(par)
+      ord(par1)=find(par(par1)==bnet_miss.order);
+    end
+    [tmp, sorted] = sort(ord);
+    family = par(sorted);
+
+    state = []; stateM = [];
+    for par1=1:length(family)
+      state(par1) = ceil(rand*bnet_miss.node_sizes(family(par1)));
+      if state(par1) == bnet_miss.node_sizes(family(par1)), stateM(par1) = misv; else, stateM(par1) = state(par1); end
+    end
+
+    if prod([hyp(1:3) == 'mca']+0),
+      family = family-N;
+    elseif prod([hyp(1:3) == 'mar']+0),
+      family = family-2*N;
+    end
+    family(end+1)=node;
+    state(end+1) = missing; stateM(end+1)=misv;
+
+    CPT = CPT_from_bnet(bnet_miss);
+    value = CPT{node+N}(subv2ind(bnet_miss.node_sizes(family), state))
+
+    % test this param "value"
+    datamat = bnt_to_mat(data(family,:), misv);
+    indj=1:m;
+    for par1 = 1:(length(family)-1)
+      [tmp, indj] = find(datamat(par1,indj)==stateM(par1));
+    end
+    mtest = length(indj);
+    [tmp, indj] = find(datamat(length(family),indj)==stateM(length(family)));
+
+    toto=mtest; nbr_miss=length(indj);
+d = ((nbr_miss-value*toto)^2)/(value*toto)...
+  + (((toto-nbr_miss)-(1-value)*toto)^2)/((1-value)*toto)
+
+    family
+    %df = prod(bnet_miss.node_sizes(family)-1);
+    df = 1; % present or missing
+    %for chiv=1:nchi,
+    %  if d>chi2_table(chi2(chiv),df), test(essai,i,chiv) = 1; end
+    %end
+    cumchi=chi2cdf(d,df)
+    test(essai,i) = 1-cumchi;
+    taille(essai,i) = toto;
+
+    %fprintf('%2.1f%% OF MISSING DATA (%2.1f%%, Khi2 : %2.1f > %2.1f)\n', round(base_proba*10000)/100, round(taux*10000)/100, d, chi2(nchi));
+
+  end
+  clear bnet_miss bnet datamat data node0 family node_sizes CPT indj tmp
+end
+
+kiki
+taille
+test
+
+%eval(['save resgener' ddd 'kiki taille test hyp ntests nessais = 50 m'])
+
+diary off
+