chuaxr

I often restart the kernel and run all cells. Currently, I do so by mapping a shortcut in jupyter mode (Shift-R), and so have to press the somewhat awkward combination...

Re your first comment: the pre-existing shortcut doesn't restart the kernel. Re your second comment: I was able to add a mapping to $(jupyter --data-dir)/nbextensions/vim_binding/lib/jupyter/shortcuts.js and it works, thanks!

I was using Ubuntu installed on windows and also needed to install gcc (via sudo apt install gcc) before the pip install git+.

It certainly would, especially together with a more meaningful option for output_time_intervals (perhaps 'all'). Thanks!

It's likely that I'll only be able to update aospy after #208 is resolved, so that would be highest on my wish list. Or perhaps the two issues could be...

This is the function I use for selecting variables corresponding to specified percentiles of precipitation: ```python def cond_pct_prcp(prcp_nc,prcp_c,var2cond): """Condition on precip percentile Parameters ---------- prcp_nc: precipitation """ prcp_tot=total_precip(prcp_nc,prcp_c) prcp_pct=pct_prcp(prcp_nc,prcp_c) #percentiles...

Well, more accurately, it's @spencerkclark's workaround, so I assume he wouldn't object to sharing it. It's in /nbhome/xrc/anaconda2/envs/py361/lib/python3.6/site-packages/aospy/calc.py, which you should both have read access to.

The assumption seems to be that reduction operations will be performed on a time dimension of the data. At least for my use case, I often wish to simultaneously reduce...

I think we're on the same page, here's a more precise example: Let's say I have a 10 by 10 (x,t) grid with the numbers 1 to 100. The 90th...

@spencerahill yes, I mean (1) :)