How to save multiple samples from the same or different chains in the LDACOL model

Load a dataset

dataset = 1; % 1 = psych review; 2 = nips if (dataset == 1) fprintf( 'Loading Psych Review Abstracts - Collocation Data\n' ); load 'psychreviewcollocation'; % load in variables: WW WO DS WS SI elseif (dataset == 2 ) fprintf( 'Loading NIPS papers - Collocation Data\n' ); load 'nipscollocation'; % load in variables: WW WO DS WS SI end

Loading Psych Review Abstracts - Collocation Data

The number of topics

T = 50;

What output to show (0=no output; 1=iterations; 2=all output)

OUTPUT = 1;

Set the hyperparameters of the model

BETA = 0.01; ALPHA = 50/T; GAMMA0 = 0.1; GAMMA1 = 0.1; DELTA = 0.1;

The number of iterations

BURNIN = 100; % the number of iterations before taking samples LAG = 10; % the lag between samples NSAMPLES = 2; % the number of samples for each chain NCHAINS = 2; % the number of chains to run

The starting seed number

SEED = 1; for c=1:NCHAINS SEED = SEED + 1; N = BURNIN; fprintf( 'Running Gibbs sampler for burnin\n' ); [ WP,DP,WC,C,Z ] = GibbsSamplerLDACOL( WS , DS , SI , WW , T , N , ALPHA , BETA , GAMMA0, GAMMA1 , DELTA , SEED , OUTPUT ); fprintf( 'Continue to run sampler to collect samples\n' ); for s=1:NSAMPLES filename = sprintf( 'ldacol_chain%d_sample%d' , c , s ); fprintf( 'Saving sample #%d from chain #%d: filename=%s\n' , s , c , filename ); comm = sprintf( 'save ''%s'' WP DP WC C ALPHA BETA GAMMA0 GAMMA1 DELTA SEED N Z T s c' , filename ); eval( comm ); if (s < NSAMPLES) N = LAG; SEED = SEED + 1; % important -- change the seed between samples !! [ WP,DP,WC,C,Z ] = GibbsSamplerLDACOL( WS , DS , SI , WW , T , N , ALPHA , BETA , GAMMA0, GAMMA1 , DELTA , SEED , OUTPUT , C , Z ); end end end

Running Gibbs sampler for burnin Iteration 0 of 100; Number of tokens in collocation = 0 Iteration 10 of 100; Number of tokens in collocation = 5476 Iteration 20 of 100; Number of tokens in collocation = 6720 Iteration 30 of 100; Number of tokens in collocation = 7204 Iteration 40 of 100; Number of tokens in collocation = 7502 Iteration 50 of 100; Number of tokens in collocation = 7457 Iteration 60 of 100; Number of tokens in collocation = 7508 Iteration 70 of 100; Number of tokens in collocation = 7511 Iteration 80 of 100; Number of tokens in collocation = 7453 Iteration 90 of 100; Number of tokens in collocation = 7474 Continue to run sampler to collect samples Saving sample #1 from chain #1: filename=ldacol_chain1_sample1 Iteration 0 of 10; Number of tokens in collocation = 7602 Saving sample #2 from chain #1: filename=ldacol_chain1_sample2 Running Gibbs sampler for burnin Iteration 0 of 100; Number of tokens in collocation = 0 Iteration 10 of 100; Number of tokens in collocation = 5155 Iteration 20 of 100; Number of tokens in collocation = 6561 Iteration 30 of 100; Number of tokens in collocation = 7082 Iteration 40 of 100; Number of tokens in collocation = 7400 Iteration 50 of 100; Number of tokens in collocation = 7595 Iteration 60 of 100; Number of tokens in collocation = 7491 Iteration 70 of 100; Number of tokens in collocation = 7492 Iteration 80 of 100; Number of tokens in collocation = 7516 Iteration 90 of 100; Number of tokens in collocation = 7543 Continue to run sampler to collect samples Saving sample #1 from chain #2: filename=ldacol_chain2_sample1 Iteration 0 of 10; Number of tokens in collocation = 7641 Saving sample #2 from chain #2: filename=ldacol_chain2_sample2