Hi all,
Attached is a gif illustrating the problem I’m facing when I set ‘x_axis_type’ to ‘datetime’.
This is observed if and only if I’m “remotely” connected to the Jupyter session (i.e. if the web browser is running on a machine which is not the one hosting the Jupyter session).
Everything works smoothly if run the web browser locally (on the Jupyter host).
That’s weird, isn’t? Any idea about the nature of the problem?
Hi all,
Attached is a gif illustrating the problem I'm facing when I set 'x_axis_type' to 'datetime'.
This is observed if and only if I'm "remotely" connected to the Jupyter session (i.e. if the web browser is running on a machine which is not the one hosting the Jupyter session).
Everything works smoothly if run the web browser locally (on the Jupyter host).
That's weird, isn't? Any idea about the nature of the problem?
Thanks for your help.
Nicolas.
Here is the some code allowing to reproduce the problem I have with the ‘datetime’ axis. Just make sure you can import dim.py from your notebook session then execute the cellsDateTimeScaleProblem.ipyn.You should some live data updated @ 4 Hz.
The problem seems to be due to a random shifting of the data along the time axis. This shift is sometimes so huge that the data is out of the time range and disappears from the plot. This could obviously come from my code but I really don’t see where. In term of implementation, everything is located into the ScalarChannel class (see dim.py file).
I'm sorry this fell off my radar. It's getting (gotten) difficult to keep up with this list as much as I would like. Im glad the fixes in the latest release got things working for you, though!