If you want to get started with GitHub there are a few introductional videos I randomly found on YouTube: https://www.youtube.com/watch?v=O72FWNeO-xY&list=PL5-da3qGB5IBLMp7LtN8Nc3Efd4hJq0kD&index=1
First of all I would recommend to create and use your own GitHub account rather than the general account (stanfordbeads). The general procedere can be summarized as following:
1a. Clone the repository on your account at the beads-dataserver2
1b. Clone the repository to your own computer [You will see, this will not be necessary as you should be able to access the jupyterhub at any time from everywhere]
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Writing code? Good! But check first if already exists (Chas and AlexR have written a lot of stuff). If you are not sure, better ask to not do a job twice.
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You wrote new code? Add it to the git repository by pushing it.
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You improved existing code? Why not going for a pull request in order to get it cross checked.
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In all cases, comment(!) your code as well as your changes. Write more than less of descriptive text. Always a good idea. Always.
Accessing the JupyterHub
Using the JupyterHub Terminal
Data saving In our meeting on 05/08/2019 we decided to do the following steps:
Save data in the same way as in the old trap. This includes two files - one for the data stream from the FPGA and one from the DAQ(mainly the electrode data). The data should be saved according to its date to a folder. Within the date folder a substrcture will be created automatically given on what ever measurment was taken. The list includes: Data
- without radial feedback at different heights
- with radial feedback
- after pump down
- coarse charging data
- diagonalization data
- mass measurement
- fine discharging data
- height finding data
- measurement of interest (add further like spinning is of course done as required)
Database Given the .XML output we will implement a search and selectable data base in order to do systematic research through data.
Data processor We will investigate the old data processor and use it. However, a parallelization should be added.
High-level analysis
Storing LabView code
Use the wiki pages