[Matplotlib-users] 'save file' GUI dialog
Hi everyone, I'm developing a simple GUI tool in Matplotlib that relies on the event framework to handle buttons/sliders. I am trying to avoid using a GUI toolkit directly to ensure maximum compatibility for users. One thing I would like is to be able to have a 'save' button that will open up a standard 'save file' dialog window (but not necessarily the plot itself). Matplotlib already has 'save file' GUI dialogs for the different backends, so I was wondering whether there is an easy and abstract way of asking matplotlib to open a 'save file' dialog and capturing the output? Or is this all handled separately in the different backends? Thanks! Tom -- HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions Find What Matters Most in Your Big Data with HPCC Systems Open Source. Fast. Scalable. Simple. Ideal for Dirty Data. Leverages Graph Analysis for Fast Processing Easy Data Exploration http://p.sf.net/sfu/hpccsystems ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] 'save file' GUI dialog
Hey Tom, It looks like the only backend-agnostic file save function is save_figure() (a toolbar method), which conflates choosing a filename and doing the actual saving. The backend-specific code to choose a filename via a dialog isn't uniform: Qt4: matplotlib.backends.backend_qt4._getSaveFileName MacOS matplotlib.backends.backend_osx._macosx.choose_save_file Wx: A bunch of code in matplotlib.backends.backend_wx.save_figure TkAgg: Tkinter.FileDialog GtkAgg: get_filechooser().get_filename_from_user() It looks like, at a minimum, you would have to write your own wrapper code to make a backend-agnostic interface for choosing a filename. Of course, if you did that, it would also be nice to refactor that into MPL itself... :) chris On Fri, Jun 20, 2014 at 8:22 AM, Thomas Robitaille thomas.robitai...@gmail.com wrote: Hi everyone, I'm developing a simple GUI tool in Matplotlib that relies on the event framework to handle buttons/sliders. I am trying to avoid using a GUI toolkit directly to ensure maximum compatibility for users. One thing I would like is to be able to have a 'save' button that will open up a standard 'save file' dialog window (but not necessarily the plot itself). Matplotlib already has 'save file' GUI dialogs for the different backends, so I was wondering whether there is an easy and abstract way of asking matplotlib to open a 'save file' dialog and capturing the output? Or is this all handled separately in the different backends? Thanks! Tom -- HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions Find What Matters Most in Your Big Data with HPCC Systems Open Source. Fast. Scalable. Simple. Ideal for Dirty Data. Leverages Graph Analysis for Fast Processing Easy Data Exploration http://p.sf.net/sfu/hpccsystems ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users -- * Chris Beaumont Senior Software Engineer Harvard Center for Astrophysics 60 Garden Street, MS 42 Cambridge, MA 02138 chrisbeaumont.org * -- HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions Find What Matters Most in Your Big Data with HPCC Systems Open Source. Fast. Scalable. Simple. Ideal for Dirty Data. Leverages Graph Analysis for Fast Processing Easy Data Exploration http://p.sf.net/sfu/hpccsystems___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
Re: [Matplotlib-users] colors
Ok! I'm getting there! I've been trying to figure out, though, how to set black - for example - for the zero values BUT interpolate also the colors linearly from black to blue in the linear region (from zero to the linear threshold). Is there a way to change the colormap like that? Thanks a lot! On 2014/06/18, 5:23 AM, Bruno Pace wrote: Ok, so using the norm=SymLogNorm I cannot distinguish the values that are exactly 0.0 from the really small ones, right? Would it be possible Correct, the scale is linear for small values. to make use of the set_bad method without having to use masked arrays, just combining the SymLogNorm and the set_bad? No, the mask is what identifies a point as bad. If you want to distinguish zero from non-zero, no matter how small, then this is the way to do it. zm = np.ma.masked_equal(z, 0, copy=False) Now you have a masked array where the points that are exactly zero are masked. The bad color won't show up on the colorbar, however. There is no suitable place for it. It can show only the range from vmin to vmax, and a set_over color for values greater than vmax, and a set_under color for values less than vmin. Eric -- HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions Find What Matters Most in Your Big Data with HPCC Systems Open Source. Fast. Scalable. Simple. Ideal for Dirty Data. Leverages Graph Analysis for Fast Processing Easy Data Exploration http://p.sf.net/sfu/hpccsystems___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
[Matplotlib-users] poor performance scaling in number of tick marks
I have observed that the amount of time to draw a figure with a plot depends heavily on the number of tick marks on the axes. This appears to be a major driver of perceived refresh performance on interactive graphics in PySide (for example). Somewhat tangentially this makes log axes appear to perform slowly, but I think that is merely a side-effect of the fact that log axes come with minor tick marks by default. I'm working with built-from-source matplotlib as of Apr 17, 2014; I think the observations here apply to any recent matplotlib. I've published a full illustration at https://gist.github.com/jbmohler/7c5c8cca39826ea8ede7 . This small PySide application lets you enter the number of points in a scatter plot and the number of minor tick marks. You can see for yourself that increasing the number of points in the scatter plot has little impact on performance, but increasing the number of tick marks has a noticeable effect with only moderate increase. Why does this matter if you have a sane number of tick marks? It points to tick marks being simply very expensive -- on my 2 year old quad core, entirely removing tick marks results in 117 frames per second, but with 7 (major) tick marks on x y that drops to 38 frames per second. I think 100 tick marks falls with-in sane (in some cases) and a graph with 100 tick marks has decidedly more lag in a gui than 10 tick marks. As mentioned above, log axes are particularly likely place to have lots of tick marks. How can I fix this? I'm not sure, but I think there are reasonable special cases that could be highly optimized. The problem seems to me to be that each tick mark is a Line2D artist and that has a marker type (in fact, I think there is no line shown, the tick mark is the single marker of the Line2D). In the case of uniform sized tick marks, I believe the tick marks for an axis could be all in one Line2D with each tick mark being a marker in the single Line2D. This is a huge reduction of artists which seems likely to yield a speed up in quite few places. I'd love to hear your thoughts and/or fix suggestions on this topic. Joel -- HPCC Systems Open Source Big Data Platform from LexisNexis Risk Solutions Find What Matters Most in Your Big Data with HPCC Systems Open Source. Fast. Scalable. Simple. Ideal for Dirty Data. Leverages Graph Analysis for Fast Processing Easy Data Exploration http://p.sf.net/sfu/hpccsystems ___ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
