issue_comments: 195499002

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https://github.com/pydata/xarray/issues/788#issuecomment-195499002 https://api.github.com/repos/pydata/xarray/issues/788 195499002 MDEyOklzc3VlQ29tbWVudDE5NTQ5OTAwMg== 22805 2016-03-11T19:00:27Z 2016-03-11T19:00:27Z NONE

I think the axes on the pdf are wrong as I used integers in the coordinate definition and Python 2 to generate the example. Redefining time as [1.0, 2,0, 3.0] gives a better plot. I should have done this in my example, sorry about that.

I can do this in matplotlib and will do so, I guess I was little surprised that (a) it worked at all, and (b) it only worked in one orientation.

I would expect the plots to look exactly like time vs. x, except the time axis is normalised by 'r'.

My hope was that this would work, so I could do something like:

temp.plot(x='rtime', y='x', col='r')

and get an array of plots, each with their own timescales along the x-axis. For my analysis, time is seconds is not really that interesting, it's how it maps to the rotation timescale that matters.

I realise this is probably not a normal use case, so thanks to both of you for taking the time to reply to my question!

On 11 Mar 2016, at 16:58, Stephan Hoyer notifications@github.com wrote:

Honestly I'm a little surprised this doesn't error: dat.temperature.sel(r=2).mean(’y’).plot(x=’x’, y=’rtime’). The plot from your PDF doesn't seem to have the right y labels (rtime ranges from 0 to 2, but the highest label on the plot is 1).

What would you expect these plots to look like? Can you do this in pure matplotlib instead of xarray plotting? I would guess the result you're looking for may be possible but it's not immediately obvious to me what plot should result from this code.

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