Thanks. We have found a problem with our database that might be the cause of the slow execution so we are running that down. If that doesn’t fix the problem we’ll dig into the Jupyter code and that’s where we will need some help.
Initially I’m interested in knowing whether others are experiencing performance problems that are related to browser security or other technology changes to the Internet in recent years. This is because I am weighing whether we should attempt an upgrade. Please let me know if others have reported problems of this nature.
A little bit about us
Our segment of the Insight mission is called the Mars Weather Service (MWS) and we collect an analyze data such as wind speed and direction, atmospheric pressure and the intensity of light received at the surface. There are many scientists who use our software but there are only two developers. I can say without a doubt that if we had not based the application on Jupyter Notebook and JupyterHub the job would have been impossible for such a small group.
My initial interest in Jupyter was to fulfill a requirement to allow users to specify methods to filter data, including transforming and combining streams of data. There was also an implicit requirement that the user be able to accomplish this without doing any programming. I thought I would be able to use the kernel communication protocol to accomplish this and expected to write a front end from scratch, but I discovered there were many features of Notebook that I could leverage to make my task easier. As it turns out nobody used the filtering functionality but none-the-less the project benefited greatly by using Jupyter.
Screenshot of GUI
The top pane with the green “Load” button shows data for 10 Sols (Martian days) beginning with Sol 700 (the seven hundredth day after landing). Note the periodic nature of the data which shows diurnal variations. Toward the center of the pane is a brush widget (just above the 7 on 700) this is used to select a subset of the data. Below that is another pane that shows the data that was selected from the top pane. This pane contains another brush used to select the data shown in the lower panes. Data selection was done this way to allow the user to maintain a sense of the data in its entirety while zooming in on the finest detail. There are many other functions which are hidden under the venetian blind widget such as “Filter Controls”, “Log Viewer”,…, etc.