Direct link to github repository containing DEMO_Getdata_SciServer.ipynb and DEMO_Getcutout_SciServer.ipynb files, as well as other codes being run on the JHTDB backend.
Overview: The DEMO Python code illustrates sampling velocities on arrays of points (a 2D plane, a 3D volume, random sets of points, and a time-history at a single point). Users can execute the Python code on Sciserver and it will query the database during execution.
The SciServer is a cloud-based data-driven cluster, of The Institute for Data Intensive Engineering and Science (IDIES) at Johns Hopkins University. Users get the advantages of more reliable and faster data access since the SciServer is directly connected to JHTDB through a 10 Gigabit ethernet connection. SciServer provides containers with the "giverny" library pre-installed.
1. Login to SciServer (may need to create a new account first).
2. Click on *Compute* and then *Create container* (You could also run jobs in batch mode, by selecting Compute Jobs).
3. Type in *Container name*, select *SciServer Essentials (Test)* in*Compute Image*, mark *Turbulence (filedb)* in *Data volumes*, and then click on *Create*.
4. Click on the container you just created, then you could start using giverny with IPython Notebook.