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total_likeli_sample_point_global_tao_x_end_fine.m
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total_likeli_sample_point_global_tao_x_end_fine.m
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%calculate the total likelihood of the samples to maximize the expectation
%in EM
function total_likeli_prob = total_likeli_sample_point_global_tao_x_end_fine(sample_seq,pi_0,log_pi_begin,log_tao_x_begin,log_tao_y_begin,log_tao_y_end,log_delta_r,log_grid,ratio_track,dis_bin_input_new,log_input_gap_raw,aaa,transition_prob_track, ratio_track_new,group_transition)
log_tao_x_end = [log(aaa) log(1-aaa)];
%log_A = log(A_enlarge);
likeli_sample = zeros(size(sample_seq,2),1);
for s=1:size(sample_seq,2)
ali_seq = sample_seq(:,s);
have_align = find(ali_seq~=0);
align_start = have_align(1);
align_end = have_align(end);
i = align_start+1;
tmp = ali_seq(i)-ali_seq(i-1)+1;
pre_index = ratio_track(dis_bin_input_new(i),tmp);
pre_rr = ratio_track_new(i,tmp);
% if dis_bin_input_new(i)~=0 && tmp~=0
% pre_index = ratio_track(dis_bin_input_new(i),tmp);
% %elseif tmp~=0
% % pre_index = ratio_track_0(tmp);
% elseif dis_bin_input_new(i)~=0
% pre_index = ratio_track_1(dis_bin_input_new(i));
% else
% pre_index=9;
%
% end
%
% if ali_seq(i)-ali_seq(i-1)~=0
% pre_rr = dis_bin_input_new(i)/(ali_seq(i)-ali_seq(i-1));
% else
% pre_rr = dis_bin_input_new(i)/0.5;
% end
%pre_index = ratio_track(dis_bin_input(i),ali_seq(i)-ali_seq(i-1)+1);
log_prob = log_grid(align_start,ali_seq(align_start)) + log(pi_0(pre_index))+log_grid(i,ali_seq(i));
for i=align_start+2:align_end
% tmp = ali_seq(i)-ali_seq(i-1)+1;
% if dis_bin_input(i)~=0 && tmp~=0
% curr_index = ratio_track(dis_bin_input(i),tmp);
% elseif tmp~=0
% curr_index=ratio_track_0(tmp);
% elseif dis_bin_input(i)~=0
% curr_index=ratio_track_1(dis_bin_input(i));
% else
% curr_index=9;
%
% end
%curr_index = ratio_track(dis_bin_input(i),ali_seq(i)-ali_seq(i-1)+1);
% if ali_seq(i)-ali_seq(i-1)~=0
% curr_rr = dis_bin_input_new(i)/(ali_seq(i)-ali_seq(i-1));
% else
% curr_rr=dis_bin_input_new(i)/0.5;
% end
curr_rr = ratio_track_new(i,ali_seq(i)-ali_seq(i-1)+1);
if pre_rr<0.9220
pre_qq=1;
elseif pre_rr>1.085
pre_qq=3;
else
pre_qq=2;
end
if curr_rr<0.9220
curr_qq=1;
elseif curr_rr>1.085
curr_qq=3;
else
curr_qq=2;
end
density_rr = transition_prob_track(i,ali_seq(i)-ali_seq(i-1)+1);
% density_rr = density_mixture_gaussian(log(curr_rr),mix_mu1,mix_std1,mix_mu2,mix_std2,mix_p1,mix_p2);
%ssum= group_transition(qq1,qq2)*density_rr;
log_prob = log_prob + log(group_transition(pre_qq,curr_qq)*density_rr)+log_grid(i,ali_seq(i))+log_delta_r(1);
pre_rr = curr_rr;
end
if align_start==1 && ali_seq(1)==1
log_prob = log_prob+log_pi_begin(2);
elseif align_start~=1
log_prob = log_prob + log_pi_begin(1)+log_tao_x_begin(1)*(align_start-2)+log_tao_x_begin(2);
for j=1:align_start-1
log_prob = log_prob +log_input_gap_raw(j);
end
else
log_prob = log_prob + log_pi_begin(3)+log_tao_y_begin(1)*(ali_seq(1)-2)+log_tao_y_begin(2);
end
if align_end==size(sample_seq,1) && ali_seq(size(sample_seq,1))==size(log_grid,2)
log_prob = log_prob + log_delta_r(3);
elseif align_end==size(sample_seq,1);
log_prob = log_prob + log_delta_r(3)+log_tao_y_end(1)*(size(log_grid,2)-ali_seq(end)...
-1)+log_tao_y_end(2);
else
log_prob = log_prob + log_delta_r(2)+log_tao_x_end(1)*(size(log_grid,1)-align_end-1)...
+log_tao_x_end(2);
for j=align_end+1:length(log_input_gap_raw)
log_prob = log_prob +log_input_gap_raw(j);
end
end
likeli_sample(s)=log_prob;
end
total_likeli_prob = -sum(likeli_sample);