Student: Punit Batra
Mentors: Paula Popa, Lia Domide [Codemart,Romania]
Project: TVB: Web GUI for reconstruction pipeline
Description: The project will focus on constructing a Web GUI for Reconstruction pipeline. The reconstruction pipeline takes RMN images as input and processes them, then produces files that are compatible with TVB. We Integrated the Web GUI with workflow engine (Pegasus) in order to provide job status and job execution statistics. GUI for such a pipeline would greatly improve our user experience. So, in this project our goal is to make the GUI more interactive and user-friendly.
What work was done
Implemented the Home Page component with description and carousel of flow of the workflow.
Implemented the Input Page component for uploading the specific extension files in the specific folder structure dynamically.
Added the configuration component for editing and choosing configuration properties and save then in .properties file dynamically.
Changes in run_sequentially.py file such that it doesn't generate the .properties file.
Modified the dockerfile for tvb-recon and tvb-recon software using Andypohl/htcondor image and change all the commands according to centos7.
Integrated the web gui with pegasus WMS by using the monitoring API.
Implemented the workflow list component for showing all the details of the workflow along with states in their respective color scheme.
Completed the job list component showing details for all the jobs with tables for successful/running/failed/failing jobs.
Completed the initial work for the DAX graph.
Added the detailed readme for TVB-recon web GUI.
Modified docker images can be found using the tag GSOC.
These are some of the improvements which can be done in future for making the Web GUI more user interactive.
Automate the docker part by starting condor automatically inside docker too. It require some more changes in the modified docker images as above.
Testing can be done for the components and API part.
Some code snippets can also be make more generalised in server file.
Many more new features can be added.
I gratefully acknowledge the assistance of my mentors Paula and Lia. They helped me a lot in learning some new things and helped at every stage whenever i got stuck. We solved many issues by discussing together and found out the best solutions which we can do. The experiences and challenges which I have been given in the project are profound for my growth and future development. I will keep contributing to this project in future also because this project domain matches exactly with my field of interest. Thanks a lot Paula and Lia for making me a better developer as well as a better person.
Thanks to the awesome INCF community behind this project because they helped me to decide which project to choose.