Thank you. Easily setting up "tunable" parameters (e.g., sliders) in a computation was a key requirement for Blabr.
For example, it is very instructive/insightful to adjust the variable k in this compressive sensing blab to see the abrupt transition between sparsity and non-sparsity: http://blabr.io/?e8a066234715f21c21fd
Regarding packaging a blab: yes, it's very simple to share a blab on the web. After editing the blab, just click "Save" at the top right. This will save the blab to a Github Gist. You'll then get a link to the blab, like the one above (for the compressive sensing blab). Share the link with anyone. There are two ways to save a blab:
1. Anonymous Gist - easiest way, no need for GitHub account, but no revision control (new gist for each save).
2. Gist under your GitHub username - full revision control (gist revision each time you edit and save your blab); can make gist public or private.
For example, it is very instructive/insightful to adjust the variable k in this compressive sensing blab to see the abrupt transition between sparsity and non-sparsity: http://blabr.io/?e8a066234715f21c21fd
Regarding packaging a blab: yes, it's very simple to share a blab on the web. After editing the blab, just click "Save" at the top right. This will save the blab to a Github Gist. You'll then get a link to the blab, like the one above (for the compressive sensing blab). Share the link with anyone. There are two ways to save a blab:
1. Anonymous Gist - easiest way, no need for GitHub account, but no revision control (new gist for each save).
2. Gist under your GitHub username - full revision control (gist revision each time you edit and save your blab); can make gist public or private.