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Diffstat (limited to 'sourcecodes/bnt-master/SLP/misc/gener_NMAR_data.m')
| -rw-r--r-- | sourcecodes/bnt-master/SLP/misc/gener_NMAR_data.m | 290 |
1 files changed, 290 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/SLP/misc/gener_NMAR_data.m b/sourcecodes/bnt-master/SLP/misc/gener_NMAR_data.m new file mode 100644 index 00000000..4cff44d6 --- /dev/null +++ b/sourcecodes/bnt-master/SLP/misc/gener_NMAR_data.m @@ -0,0 +1,290 @@ +function [data, comp_data, bnet_miss] = gener_NMAR_dataset(bnet_orig, m, bnet_miss, upd) +% [NMAR_data] = gener_NMAR_data(bnet_miss, length_of_dataset) +% +% this function takes in input a bnet that can be used to generate NMAR data. +% this bnet bnet_miss can be creating by the function gener_NMAR_bnet. +% +% - comp_data (array) is a dataset that was generate by the bnet_orig that you enter in gener_NMAR_bnet +% - NMAR_data (cell array) is the dataset compdata that was emptyied by the NMAR process encodes in bnet_miss +% +% optional : +% - bnet_miss : an old bnet_miss built by this function +% - upd==1 if you want to update the bnet_miss +% +% [data, comp_data, bnet_miss] = gener_NMAR_dataset(bnet_orig, m, bnet_miss, upd); +% +% version 0.5 : june 8th 2005, olivier.francois@insa-rouen.fr +% +% TO DO : +% - allow the combinaison of a missing state of one variable and another state of another variable to have influence +% - allow the introduction of new nodes and specify which nodes it influence and which nodes has influence on it (it will also satisfy the first task then) +% + + +% INIT +N = size(bnet_orig.dag,2); +if mod(N,2)~=0, error('The number of nodes must be even'); end +if nargin<4, upd =0; end + +% fisrt rules +if nargin<3, + l1=[]; l2=[]; lp=[]; b=-1; + while ~(b==0 | b==1), b = input('Would you like to make a node missing when another one is missing (1 for yes, 0 for no) ? '); end +else + b=-1; + if upd, while ~(b==0 | b==1), b = input('Would you like to add rules (1 for yes, 0 for no) ? '); end + l1=bnet_miss.list{1}; + l2=bnet_miss.list{2}; + lp=bnet_miss.list{3}; + else + l1=[]; l2=[]; lp=[]; b=-1; + end +end + +while b==1, + n = input('The firts node ? '); + s = input('The node that have to be missing when this one is missing ? '); + p = input('The probability of the second node to be missing ? '); + l1 = [l1, n]; l2 = [l2, s]; lp=[lp, p]; + b=-1; + while ~(b==0 | b==1), b = input('Another one (1 for yes, 0 for no) ? '); end +end +bb = length(l1); + + +if nargin>=3, + bnet_miss = gener_NMAR_bnet(upd, bnet_orig, bnet_miss); +else + bnet_miss = gener_NMAR_bnet(1, bnet_orig); + bnet_miss.list={l1; l2; lp}; +%%%%%%%%%%% SAVING FILE + ss = 1; + if nargin == 2 | upd==1, ss = input('Would you like to save the bnet of the NMAR process you have made (1 for yes) ? '); end + if ss == 1, + ddd = datestr(now); + ddd([12 15 18])='-' ; + fnout=['NMAR-bnet-' ddd '.mat']; + eval(['save ' fnout ' bnet_miss']); + fprintf(' The bnet for NMAR process was saved as : %s\n',fnout); + end +end %if nargin + +% Generation of a complete dataset +if N>9 & m>2000, disp(' ! It could take a long time...'); end +data = cell(N,m); +for l = 1:m, data(:,l) = sample_bnet(bnet_orig); end +disp('Complete data have been creating.'); + +% Generation of a NMAR dataset +miss_array = cell(2*N,m); +vide = cell(1,N); l= 1; +while l <= m, + ev(1:N) = data(:,l); ev(N+1:2*N) = vide; + miss_array(:,l) = sample_bnet(bnet_miss, 'evidence', ev); + % apply simple rule of missingness + ev2 = cell2mat(miss_array(N+1:2*N, l)); + if bb, + missl1 = myintersect(find(ev2==2), l1); + if ~isempty(missl1), + for i=1:length(l1), + if ev2(l1(i))==2, if rand<lp(i), ev2(l2(i))=2; miss_array{N+l2(i),l}=[2]; end, end + end, end, end + % verification that we have not a completly missing sample + ev2 = 3-ev2; + if prod(ev2)==1, fprintf(' - %d, one completly missing sample removed', l); else l=l+1; end + if mod(l,100)==0, fprintf('\n - %d',l); end +end +fprintf('\n'); +data = bnt_to_mat(data); comp_data = data; +miss_array = bnt_to_mat(miss_array(N+1:2*N, :)); +miss_array = 2-miss_array; +data = data.*miss_array; +data = mat_to_bnt(data, 0); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function bnet_miss = gener_NMAR_bnet(upd, bnet_orig, bnet_miss) + +%%%%%%%%%%%% INIT +dag = bnet_orig.dag; +N = size(dag,2); +ns = bnet_orig.node_sizes; +NN = 0; +ns_miss = zeros(1,2*N+NN); +ns_miss(1:N) = ns; +ns_miss(N+1:2*N) = 2*ones(1,N); % 1= node i-N present, 2= node i-N missing + dagm = zeros(2*N,2*N); + dagm(1:N,1:N) = dag; + dagm(N+1:2*N, N+1:2*N) = dag; + dagm(1:N, N+1:2*N) = dag; + for i=1:N, dagm(i, i+N)=1; end + +%%%%%%%%%%%% NEW NODES +% b=-1; +% while ~(b==0 | b==1), b = input('Would you like to add new nodes ? '); end +% +% if b==1, +% NN = -1; +% while (NN<0 | round(NN)~=NN), NN = input('How Many ? '); end +% if NN==1, fprintf('New node will be called %d\n',(2*N+1)); +% else fprintf('New node will be called %d and following numbers\n',(2*N+1)); end +% +% disp(' !!! Make sur that the dependence you will create will not create cycle in the Bnet used to create NMAR data !!! here is the current DAG'); +% dagm2 = zeros(2*N+NN, 2*N+NN); + dagm2(1:2*N, 1:2*N) = dagm; +% draw_graph(dagm2); drawnow; +% clear dagm +% +% L1={};L2={}; +% for i=1:NN +% fprintf('For the node %d, ',(2*N+i)); +% L1{i} = input('FROM which nodes will it have influence (sample [3 2]) ? '); +% L2{i} = input('ON which nodes will it have influence (sample [1 4 3]) ? '); +% ns_miss(2*N+i) = input('What is its size ? '); +% end +% +% end + +%%%%%%%%%%%% BNET CREATION +if nargin==2, + dag_miss = dagm2; + for i=1:NN, dag_miss(L1{i},2*N+i)=1; dag_miss(2*N+i, L2{i})=1; end + + bnet_miss = mk_bnet(dag_miss, ns_miss); + CPT = CPT_from_bnet(bnet_orig); + for i=1:N + bnet_miss.CPD{i} = tabular_CPD (bnet_miss, i, CPT{i}); % error with new nodes + end +elseif nargin==3, + ns_miss = bnet_miss.node_sizes; + dag_miss = bnet_miss.dag; +end +clear dagm2 +order = 1:(2*N+NN); + +%%%%%%%%%%%% Base probability of missing value +if nargin==2, b=1; else b=0; end +if b==1, +disp('Probability MUST be between 0 and 1.'); + +if nargin==2, + p=-1; + while p<0 | p>1, p = input('Base probability of a value to be missing ? '); end + for i=1:N + fam = find(dag_miss(:,N+i)==1)'; + semisize = prod(ns_miss(fam)); % as node N+i is binary to say i is present or missing + CPT = zeros(1,2*semisize); + CPT(1:semisize) = 1-p; + CPT(semisize+1:2*semisize) = p; + bnet_miss.CPD{N+i} = tabular_CPD (bnet_miss, N+i, CPT); + end +end +end + +b=-1; +while ~(b==0 | b==1), b = input('Would you like to change a probability of a node to be missing (1 for yes, 0 for no) ? '); end +if b, disp(' BE CAREFULL !! New rules can overwrite old ones partialy or fully !! So the order of entries is important'); end + +%%%%%%%%%%%% Update CPT with NMAR process +while b + fprintf('Nodes are from 1 to %d. ',N); + i=0; + while i<1 | i>N | round(i)~=i, i = input('Which node ? '); end + fam = find(dag(:,i)==1)'; + fam_miss = find(dag_miss(:,N+i)==1)'; + cas = -ones(1, length(fam_miss)+1); + familly = [fam_miss, N+i]; + fprintf('States are from 1 to %d (-1 for any states, -2 to cancel). For which state of the variable %d ?', ns(i), i); + state=-3; + while state<-2 | state>ns(i) | round(state)~=state | state==0, state = input(' ');end + if isempty(fam), + if state==-1, + p=-1; + while p<0 | p>1, p = input(' - A priori probability for this node to be missing ? ');end + semisize = prod(ns_miss(fam_miss)); + CPT = zeros(1,2*semisize); + CPT(1:semisize) = 1-p; + CPT(semisize+1:2*semisize) = p; + bnet_miss.CPD{N+i} = tabular_CPD (bnet_miss, N+i, CPT); + elseif state~=-2 + cas = state; + CPT = CPT_from_bnet(bnet_miss); + CPT = CPT{N+i}; + p=-1; + while p<0 | p>1, p = input(' - A priori probability for this node to be missing in this state ? ');end + ind = subv2ind(ns_miss(familly),[cas, 1]); + CPT(ind)=1-p; + ind = subv2ind(ns_miss(familly),[cas, 2]); + CPT(ind)=p; + bnet_miss.CPD{N+i} = tabular_CPD (bnet_miss, N+i, CPT); + end + else + if state>-2, + siz=length(cas); + place = find(fam_miss==i); + cas(place) = state; + + for k = fam, + state=-3; + fprintf(' - For the parent named %d, states are from 1 to %d (-1 for any states of this parent). ',k, ns(k)); + while state<0 | state>ns(k) | round(state)~=state, state = input('Which state ? ');end + %if state==0, + % place = find(fam_miss==(fam_miss(k)+N)); + % cas(place) = 2; % Missing + %elseif state==-2, % a changer ??? + % disp(' This case is buggy, taking missing state instand to minimise influence.'); + % place = find(fam_miss==(fam_miss(k)+N)); + % cas(place) = 2; + %elseif state~=0 & state~=-2, + place = find(fam_miss==(fam_miss(k))); + cas(place) = state; % Present + if state~=-1; place = find(fam_miss==(fam_miss(k)+N)); cas(place) = 1; end + %end + end + + p=-1; + while p<0 | p>1, p = input('Probability in this case of the value to be missing ? ');end + CPT = CPT_from_bnet(bnet_miss); + CPT = CPT{N+i}; + + cas(end) = 1; % i is present + subcas_names = find(cas==-1); + if isempty(subcas_names), + ind = subv2ind(ns_miss(familly),cas); + CPT(ind) = 1-p; + else + subcas = ones(1, length(subcas_names)); + continu = 1; + while continu + cas(subcas_names) = subcas; + ind = subv2ind(ns_miss(familly),cas); + CPT(ind) = 1-p; + [subcas, continu] = next_case(subcas, ns_miss(familly(subcas_names))); + end + end + + cas(end)=2; % i is missing + if isempty(subcas_names), + ind = subv2ind(ns_miss(familly),cas); + CPT(ind) = p; + else + subcas = ones(1, length(subcas_names)); + continu = 1; + while continu + cas(subcas_names) = subcas; + ind = subv2ind(ns_miss(familly),cas); + CPT(ind) = p; + [subcas, continu] = next_case(subcas, ns_miss(familly(subcas_names))); + end + end + mass = sum(CPT, length(size(CPT))); + while length(size(mass))>2, mass = prod(mass, length(size(mass))); end + mass = prod(prod(mass)); + if mass~=1, disp('not a proba...'); end + bnet_miss.CPD{N+i} = tabular_CPD (bnet_miss, N+i, CPT); + end %if state~=-2 for the node + end %if isempty(fam), + b=-1; + while ~(b==0 | b==1), b = input('Would you like to change a probability of a node to be missing (1 for yes, 0 for no) ? ');end +end + |