From 226f6c525074fdde3415d86d1cf9b82fb70ae18c Mon Sep 17 00:00:00 2001 From: Kevin Shan Date: Mon, 24 Apr 2017 11:42:25 -0700 Subject: [PATCH] Bugfix demo_benchmarking (missing spike weights) This demo script was missing the spike weights. This does not significantly affect the runtimes, but it does have a large impact on the quality of fit on the subsetted data. --- demo_benchmarking.m | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/demo_benchmarking.m b/demo_benchmarking.m index 87a700a..9bd3978 100644 --- a/demo_benchmarking.m +++ b/demo_benchmarking.m @@ -114,14 +114,14 @@ end % Try a dry run first modt.setParams(starting_params); - modt.attachData(spk_Y, spk_t); + modt.attachData(spk_Y, spk_t, spk_w); modt.EM('maxIter',3); modt.detachData(); % Do it for real fprintf('Running %s\n', modt_desc{ii}); t_start = tic(); modt.setParams(starting_params); - modt.attachData(spk_Y, spk_t); + modt.attachData(spk_Y, spk_t, spk_w); modt.EM('minIter',nIter, 'maxIter',nIter); t_elapsed = toc(t_start); % If this was a subset, then measure the log-likelihood on the full dataset