From: Nic E. <ns...@co...> - 2012-08-24 14:37:32
|
Stacked type histograms have this problem as well. The solution I've found is to do fig.set_yscale('log', nonposy='clip'). On Fri, Aug 24, 2012 at 8:43 AM, Benjamin Root <ben...@ou...> wrote: > > > On Fri, Aug 24, 2012 at 1:44 AM, Eric Firing <ef...@ha...> wrote: >> >> On 2012/08/23 6:41 PM, Fernando Perez wrote: >> > Hi Eric, >> > >> > On Thu, Aug 23, 2012 at 7:56 PM, Eric Firing <ef...@ha...> wrote: >> >> I'm not sure I understand what you are getting at, but I don't think >> >> there >> >> should be any interface changes for plot or for their log variants. >> > >> > I probably phrased my question poorly. I'm just wondering, how would >> > one use the proposed stackplot function to obtain a stacked plot but >> > that used log axes (x, y or both)? >> >> One would follow the stackplot call with calls to xscale('log') and/or >> yscale('log'). This works fine for the x-axis (if x values are >> positive), but when the y-axis is log, the bottom region is not filled, >> presumably because it is trying to fill down to zero. I haven't looked >> at the code, so I don't know whether there is some way of improving this >> behavior without the stackplot call knowing beforehand that it will be >> dealing with a log axis. >> >> Eric >> > > This is a similar problem that we face with bar() and hist()... > > Ben Root > > > ------------------------------------------------------------------------------ > Live Security Virtual Conference > Exclusive live event will cover all the ways today's security and > threat landscape has changed and how IT managers can respond. Discussions > will include endpoint security, mobile security and the latest in malware > threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ > _______________________________________________ > Matplotlib-devel mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-devel > |