Since the computer our clients use to run the Wave Maker is not connected to the internet, we made most of our code changes onto the lab computer that stored the wave maker new GUI code. One of the problems that we and our clients faced was not knowing which folder on their system contained the most accurate and up-to-date code for the machine. To resolve this issue, we named this folder in the lab computer new_gui and uploaded all these files into a GitHub repository. In addition, we will provide the clients with a link to our repository in case they want to view it and share it with future teams. This will help future teams know which folder to revise and improve when working on the lab computer as well as have a reference through the repository to the changes we implemented.
The computer is located in the Fluids Lab in Chapman Hall where our client works. Therefore, they will be able to access it any time once the repository is uploaded. The computer is connected to the Wave Maker hardware, and once they run the code, the clients can access the GUI and Studio 5000, allowing them to select the motors and run them. All of the applications the clients need are downloaded on their computer, including MongoDB which will be used to collect data for each run, so our client will not incur any costs.
In the past, the clients were only able to test if motors have been activated or not by having turn on Studio 5000 and the hardware. Another issue was that in order to run the motors, the tank had to be filled with a certain amount of water. To make it more convenient for our clients and future teams, they can follow the testing examples we included in the motor, model, preset, and control home classes to see if Wave Maker is activating the selected motors and loading in the presets. They can run these tests by going into new_GUI > testing> python -m pytest <filename.py>. There are some final changes that are wip, and once finished, we will create a video that showcases how to run the tests and database to our clients.
For the database, the client can access the files on the WaveMaker lab computer, by going to the folder new_GUI > pymongo_test > database.py and running the functions in the terminal, such as building and querying particular collections. The client can refer to the user manual for specific instructions and descriptions of features. The current purpose the database serves is to assist future researchers in data collection to create training sets for AI/ML research. We also encourage future 523 teams (or other developers) to build on this feature as they see fit.
In terms on licensing/ownership of software, our team installed free, open-source versions of pytest and pymongo/MongoDB and they currently run locally on the computer (without connecting to the internet). There are no api calls being made or other functionality that would incur extra costs. The client will not need to worry about additional fees and can run our code as many times as needed.
Client Handoff Video
https://drive.google.com/file/d/1PYeK16k0xbrsP9fzNph7AQNlOMPyftGS/view?usp=drive_link