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>>>>> "Abraham" == Abraham Schneider <ab...@cn...> writes: Abraham> Hi. Well, not sure anyone is interested in following up Abraham> on the config file issue, but if so, attached is a Abraham> complete version (sorry for the big size!). One class and Abraham> two functions were moved from __init__.py, but besides Abraham> that it's all new (and thus the non-patch). But at least Abraham> my quick tests shows it to be backwards compatible Abraham> (i.e. it can read the .matplotlibrc files, and rc(...) Abraham> was rewritten to work with the new system). Abraham> A very quick synopsis: config['text']['color'] = 'r' Abraham> config['text.color'] = 'g' config['text.c'] = 'b' Abraham> rc('text', color=(100, 100, 100)) I'm interested. I haven't had time to follow it closely yet, but I do plan on taking a close look soon. One thing I would like to see is a syntax like rc.text.color = 'red' I think by creating a proper class for the rc instance and text attribute and overriding setattr and getattr appropriately, you can achieve this. FYI, I'll include some code I worked on over holiday investigating using enthought traits for rc files which does support a syntax like this. Note the usage of rc.lines.color = 'r' Thanks for chugging along on this. When time permits, I know Fernando is interested in joining in this discussion because we previously discussed adopting a python based config file that allowed recursive includes that might be usable both for ipython and matplotlib, JDH import sys, os, re from traits import * from matplotlib.cbook import is_string_like from matplotlib.artist import Artist doprint = True flexible_true_trait = Trait( True, { 'true': True, 't': True, 'yes': True, 'y': True, 'on': True, True: True, 'false': False, 'f': False, 'no': False, 'n': False, 'off': False, False: False } ) flexible_false_trait = Trait( False, flexible_true_trait ) colors = { 'c' : '#00bfbf', 'b' : '#0000ff', 'g' : '#008000', 'k' : '#000000', 'm' : '#bf00bf', 'r' : '#ff0000', 'w' : '#ffffff', 'y' : '#bfbf00', 'gold' : '#FFD700', 'peachpuff' : '#FFDAB9', 'navajowhite' : '#FFDEAD', } def hex2color(s): "Convert hex string (like html uses, eg, #efefef) to a r,g,b tuple" return tuple([int(n, 16)/255.0 for n in (s[1:3], s[3:5], s[5:7])]) class RGBA(HasTraits): # r,g,b,a in the range 0-1 with default color 0,0,0,1 (black) r = Range(0., 1., 0.) g = Range(0., 1., 0.) b = Range(0., 1., 0.) a = Range(0., 1., 1.) def __init__(self, r=0., g=0., b=0., a=1.): self.r = r self.g = g self.b = b self.a = a def __repr__(self): return 'r,g,b,a = (%1.2f, %1.2f, %1.2f, %1.2f)'%\ (self.r, self.g, self.b, self.a) def tuple_to_rgba(ob, name, val): tup = [float(x) for x in val] if len(tup)==3: r,g,b = tup return RGBA(r,g,b) elif len(tup)==4: r,g,b,a = tup return RGBA(r,g,b,a) else: raise ValueError tuple_to_rgba.info = 'a RGB or RGBA tuple of floats' def hex_to_rgba(ob, name, val): rgx = re.compile('^#[0-9A-Fa-f]{6}$') if not is_string_like(val): raise TypeError if rgx.match(val) is None: raise ValueError r,g,b = hex2color(val) return RGBA(r,g,b,1.0) hex_to_rgba.info = 'a hex color string' def colorname_to_rgba(ob, name, val): hex = colors[val.lower()] r,g,b = hex2color(hex) return RGBA(r,g,b,1.0) colorname_to_rgba.info = 'a named color' def float_to_rgba(ob, name, val): val = float(val) return RGBA(val, val, val, 1.) float_to_rgba.info = 'a grayscale intensity' Color = Trait(RGBA(), float_to_rgba, colorname_to_rgba, RGBA, hex_to_rgba, tuple_to_rgba) def file_exists(ob, name, val): fh = file(val, 'r') return val def path_exists(ob, name, val): os.path.exists(val) linestyles = ('-', '--', '-.', ':', 'steps', 'None') TICKLEFT, TICKRIGHT, TICKUP, TICKDOWN = range(4) linemarkers = (None, '.', ',', 'o', '^', 'v', '<', '>', 's', '+', 'x', 'd', 'D', '|', '_', 'h', 'H', 'p', '1', '2', '3', '4', TICKLEFT, TICKRIGHT, TICKUP, TICKDOWN, 'None' ) class LineRC(HasTraits): linewidth = Float(0.5) linestyle = Trait(*linestyles) color = Color marker = Trait(*linemarkers) markerfacecolor = Color markeredgecolor = Color markeredgewidth = Float(0.5) markersize = Float(6) antialiased = flexible_true_trait data_clipping = flexible_false_trait class PatchRC(HasTraits): linewidth = Float(1.0) facecolor = Color edgecolor = Color antialiased = flexible_true_trait timezones = 'UTC', 'US/Central', 'ES/Eastern' # fixme: and many more backends = ('GTKAgg', 'Cairo', 'FltkAgg', 'GD', 'GDK', 'GTK', 'Agg', 'GTKCairo', 'Paint', 'PS', 'SVG', 'Template', 'TkAgg', 'WX') class RC(HasTraits): backend = Trait(*backends) numerix = Trait('Numeric', 'numarray') interactive = flexible_false_trait toolbar = Trait('toolbar2', 'classic', None) timezone = Trait(*timezones) lines = Trait(LineRC()) patch = Trait(PatchRC()) rc = RC() rc.lines.color = 'r' if doprint: print 'RC' rc.print_traits() print 'RC lines' rc.lines.print_traits() print 'RC patches' rc.patch.print_traits() class Patch(Artist, HasTraits): linewidth = Float(0.5) facecolor = Color fc = facecolor edgecolor = Color fill = flexible_true_trait def __init__(self, edgecolor=None, facecolor=None, linewidth=None, antialiased = None, fill=1, **kwargs ): Artist.__init__(self) if edgecolor is None: edgecolor = rc.patch.edgecolor if facecolor is None: facecolor = rc.patch.facecolor if linewidth is None: linewidth = rc.patch.linewidth if antialiased is None: antialiased = rc.patch.antialiased self.edgecolor = edgecolor self.facecolor = facecolor self.linewidth = linewidth self.antialiased = antialiased self.fill = fill p = Patch() p.facecolor = '#bfbf00' p.edgecolor = 'gold' p.facecolor = (1,.5,.5,.25) p.facecolor = 0.25 p.fill = 'f' print 'p.facecolor', type(p.facecolor), p.facecolor print 'p.fill', type(p.fill), p.fill if p.fill_: print 'fill' else: print 'no fill' if doprint: print print 'Patch' print_traits()
Hi. Well, not sure anyone is interested in following up on the config file issue, but if so, attached is a complete version (sorry for the big size!). One class and two functions were moved from __init__.py, but besides that it's all new (and thus the non-patch). But at least my quick tests shows it to be backwards compatible (i.e. it can read the .matplotlibrc files, and rc(...) was rewritten to work with the new system). A very quick synopsis: config['text']['color'] = 'r' config['text.color'] = 'g' config['text.c'] = 'b' rc('text', color=(100, 100, 100)) I believe the new syntax allows for easy addition of plugins. Several possible methods exist to handle this: (1) allow a new file '.pylabrc' which will automatically be parsed as a python file. The function 'read_rc_file(...)' still allows old-style config files to be used inside the new method, but then we don't need to introduce new syntax for setting up plugins. If no '.pylabrc' file, process '.matplotlibrc' file old style. (2) if '.matplotlibrc' is a directory, then assume new style. Each file in this directory will automatically be processed as a python file. If not a directory, process same as old method. (3) Allow python code to be included in the .matplotlibrc file as: #include <python-script> Thus, instead of requiring new config-file syntax for configuration of the plugins, they can simply be put in python files. Abe
John Hunter wrote: > I just committed some changes to CVS for auto-log scaling of line > plots - you pay a performance hit for log plots but it appears to > work. Eg, you can do > > x = arange(-2.002, 10, 0.01) > y = sin(2*pi*x) > plot(x,y) > set(gca(), xscale='log') > > and only the positive data are plotted. OK, with ssh CVS this works quite well. If you try the same with set(gca(), yscale='log') you'll see a funky junction. I think here gnuplot can again give us some guidance for good bailout behaviour: http://amath.colorado.edu/faculty/fperez/tmp/log-sin.ps I think this is a reasonable approach. Now, there is something funky though in semilogy: In [13]: plot(frange(.1,1,npts=20),frange(0.1,1,npts=20)) Out[13]: [<matplotlib.lines.Line2D instance at 0x40f631ac>] In [14]: set(gca(), yscale='log') Out[14]: [None] Works perfectly. Yet: In [15]: close('all') In [16]: semilogy(frange(.1,1,npts=20),frange(0.1,1,npts=20)) ERROR: min() or max() arg is an empty sequence I'd expect these two to be identical, no? Perhaps you just haven't had the time to track down all the places where this needs to be applied. At any rate, this is a huge improvement for log plots (which I happen to use every day). You've pretty much bought yourself the %run backend work, and at least a stab at the gtk stuff for ipython :) Best, f ps. Now that I'm good with ssh CVS, let me know if you finish polishing this up, and I can test it quickly and report back. I have a ton of pretty stressful log plots I can throw at it.
John Hunter wrote: >>>>>>"Fernando" == Fernando Perez <Fer...@co...> writes: > > > Fernando> On second thought, I am starting to like the > Fernando> mouse-proximity thingie: it allows you to point at a > Fernando> specific axis and set only that one, which can be very > Fernando> useful if you have a bunch of subplots and want to only > Fernando> change one specific axis. This, which I imagine would > Fernando> take some careful work at the command line, would be > Fernando> trivial to do if you could just put your mouse pointer > Fernando> over it and hit a key/button. > > I think you misunderstand my question. mouse proximity is a given. I > am referring to how to toggle log scale for the x and y axes > separately with keybindings for the *axes under the mouse point*. > > I am just as likely to want logx ans logy, which is why I wasn't > assuming 'l'. But if gnuplot does the y axis with 'l', I'm happy to > follow suit, but the question of the appropriate key for toggling the > x scale is open. Ah, gnuplot simply doesn't provide a separate x one. You get y with 'l', and if you want x, you mouse over it and do it. That's all they give you via hotkeys. You can always call the logscaling commands set logscale x I've found that solution to work well, but one person's everyday usage case is often someone else's weird corner case, so feel free to follow your own instincts. Best, f
>>>>> "Fernando" == Fernando Perez <Fer...@co...> writes: Fernando> On second thought, I am starting to like the Fernando> mouse-proximity thingie: it allows you to point at a Fernando> specific axis and set only that one, which can be very Fernando> useful if you have a bunch of subplots and want to only Fernando> change one specific axis. This, which I imagine would Fernando> take some careful work at the command line, would be Fernando> trivial to do if you could just put your mouse pointer Fernando> over it and hit a key/button. I think you misunderstand my question. mouse proximity is a given. I am referring to how to toggle log scale for the x and y axes separately with keybindings for the *axes under the mouse point*. I am just as likely to want logx ans logy, which is why I wasn't assuming 'l'. But if gnuplot does the y axis with 'l', I'm happy to follow suit, but the question of the appropriate key for toggling the x scale is open. JDH
Fernando Perez wrote: >>I would like a key binding for toggling log/linear scale for x and y >>independently. 'x' and 'y' are not good choices since they are >>overloaded with constraining axes in interactive pan/zoom with the >>toolbar. Suggestions? '1' and '2'? CTRL-x and and CTRL-y? 'l' and >>'L'? > > > I like 'l'/'L' for gnuplot consistency. Note that their implementation is a > bit funky though: 'l' toggles y-axis log (the most common case), while 'L' > toggles log on the axis closest to the mouse pointer. I'll leave it up to you > to decide whether you like this mouse-proximity thing or not. But 'l' for > y-log, which is probably the most common type of log plot, I think is nice. On second thought, I am starting to like the mouse-proximity thingie: it allows you to point at a specific axis and set only that one, which can be very useful if you have a bunch of subplots and want to only change one specific axis. This, which I imagine would take some careful work at the command line, would be trivial to do if you could just put your mouse pointer over it and hit a key/button. So now I'm +1 on following gnuplot's inspiration here. As to which y-axis a plain 'l' should modify in the presence of subplots, I'm not sure. All? The first one? Is there a concept of 'active axis' in a plot with subplots? I simply don't know mpl enough to say anything useful here. cheers, f
John Hunter wrote: > If you have data points really close to 0, eg > > 1 >>> x = arange(-2.00, 10, 0.01) > > 2 >>> amin(abs(x)) > Out[2]: 4.163336342344337e-17 > > You may a heavy performance price because so many decades are plotted, > each with minor ticks, and ticks are expensive in the current impl. I had a look at gnuplot's strategy: planck[~]> npy In [1]: x = frange(1e-40, 10, npts=1003) In [2]: gp('set logscale y') In [3]: plot x,filename='logplotex.eps' The result is here: http://amath.colorado.edu/faculty/fperez/tmp/logplotex.eps They seem to plot a maximum of 11 major ticks (that's what I'm guessing from a bunch of tests). When it fits, each major tick is a decade, but at some point their algorithm switches over (like in my example) to every 3rd, 5th, whatever-th decade, and the minor ticks become decade ticks themselves. When this happens, there are no logarithmically spaced ticks any more, obviously. This is overall a nice approach, I think. I have quite a few plots which cover 30 decades, and in matplotlib the result looks very crowded, while gnuplot's enforcement of a max of 11 (or whatever) major ticks gives a clean looking plot. Gnuplot has many problems (hence my switch -finally- to mpl), but it has over a decade of fine-tuning of its behavior and interface, so it's not a bad source of inspiration. It is mature and robust, and many of the things it does, it does really well. I'll keep bringing up areas where I feel we can benefit from it (I know it reasonably well) as I move all my code over to mpl. Cheers, f
>>>>> "Fernando" == Fernando Perez <Fer...@co...> writes: Fernando> Hmm. Is it possible that this hasn't propagated to Fernando> public CVS yet? I just updated, and this is what I get: Highly probably - public CVS lags are getting better but are still measurable backend_bases.py revision: 1.31 lines.py revision: 1.14 axes.py revision: 1.64
John Hunter wrote: > I just committed some changes to CVS for auto-log scaling of line > plots - you pay a performance hit for log plots but it appears to > work. Eg, you can do > > x = arange(-2.002, 10, 0.01) > y = sin(2*pi*x) > plot(x,y) > set(gca(), xscale='log') > > and only the positive data are plotted. Hmm. Is it possible that this hasn't propagated to public CVS yet? I just updated, and this is what I get: planck[mwadap]> pylab In [1]: x = arange(-2.002, 10, 0.01) In [2]: y = sin(2*pi*x) In [3]: plot(x,y) Out[3]: [<matplotlib.lines.Line2D instance at 0x41041f0c>] In [4]: set(gca(), xscale='log') --------------------------------------------------------------------------- exceptions.ValueError Traceback (most recent call last) /home/fperez/research/code/mwadap/<console> /usr/lib/python2.3/site-packages/matplotlib/pylab.py in set(h, *args, **kwargs) 1230 raise RuntimeError(msg) 1231 -> 1232 draw_if_interactive() 1233 return [x for x in flatten(ret)] 1234 /usr/local/home/fperez/code/python/IPython/genutils.py in wrapper(*args, **kw) /usr/lib/python2.3/site-packages/matplotlib/backends/__init__.py in draw_if_interactive() 40 def draw_if_interactive(): 41 draw_if_interactive._called = True ---> 42 __draw_int() 43 # Flag to store state, so external callers (like ipython) can keep track 44 # of draw calls. /usr/lib/python2.3/site-packages/matplotlib/backends/backend_tkagg.py in draw_if_interactive() 56 figManager = Gcf.get_active() 57 if figManager is not None: ---> 58 figManager.show() 59 60 /usr/lib/python2.3/site-packages/matplotlib/backends/backend_tkagg.py in show(self) 276 # anim.py requires this 277 if sys.platform=='win32' : self.window.update() --> 278 else: self.canvas.draw() 279 self._shown = True 280 /usr/lib/python2.3/site-packages/matplotlib/backends/backend_tkagg.py in draw(self) 141 142 def draw(self): --> 143 FigureCanvasAgg.draw(self) 144 tkagg.blit(self._tkphoto, self.renderer._renderer, 2) 145 self._master.update_idletasks() /usr/lib/python2.3/site-packages/matplotlib/backends/backend_agg.py in draw(self) 310 self.renderer = RendererAgg(w, h, self.figure.dpi) 311 self._lastKey = key --> 312 self.figure.draw(self.renderer) 313 314 def tostring_rgb(self): /usr/lib/python2.3/site-packages/matplotlib/figure.py in draw(self, renderer) 336 337 # render the axes --> 338 for a in self.axes: a.draw(renderer) 339 340 # render the figure text /usr/lib/python2.3/site-packages/matplotlib/axes.py in draw(self, renderer) 1480 if not self.get_visible(): return 1481 renderer.open_group('axes') -> 1482 self.transData.freeze() # eval the lazy objects 1483 self.transAxes.freeze() # eval the lazy objects 1484 if self.axison: ValueError: Cannot take log of nonpositive value Note that I'm running straight off the CVS directory, because the RPM rebuild/reinstall takes too long for permanent testing. What I did was just to manually copy the .so files back into the CVS dir, renamed /usr/lib/python2.3/site-packages/matplotlib to .ori, and made a symlink: planck[site-packages]> d matplotlib /usr/lib/python2.3/site-packages lrwxrwxrwx 1 root 51 Feb 4 11:18 matplotlib -> /usr/local/installers/src/matplotlib/lib/matplotlib/ This seems to work OK (I checked with a few print statements that I am indeed running off the CVS matplotlib/ dir). Since the most recent CVS update doesn't seem to change any C++ code, this should be OK, no? I'm seeing further weirdness with log plots. Try this: semilogy(frange(.1,1,npts=20),frange(0.1,1,npts=20)) semilogy(frange(.1,1,npts=20),frange(0.0,1,npts=20)) semilogy(frange(.1,1,npts=20),frange(0.1,1,npts=20)) Not only does the second one crash, but then, the third line (identical to the first) also crashes. Something is left in an internally inconsistent state, and essentially all log plots become impossible afterwards. The only solution is to restart pylab altogether. > If you have data points really close to 0, eg > > 1 >>> x = arange(-2.00, 10, 0.01) > > 2 >>> amin(abs(x)) > Out[2]: 4.163336342344337e-17 > > You may a heavy performance price because so many decades are plotted, > each with minor ticks, and ticks are expensive in the current impl. > > I am also implementing some default keypress events on the pylab > figure manager canvas. Eg 'g' to toggle grid mode. > > I would like a key binding for toggling log/linear scale for x and y > independently. 'x' and 'y' are not good choices since they are > overloaded with constraining axes in interactive pan/zoom with the > toolbar. Suggestions? '1' and '2'? CTRL-x and and CTRL-y? 'l' and > 'L'? I like 'l'/'L' for gnuplot consistency. Note that their implementation is a bit funky though: 'l' toggles y-axis log (the most common case), while 'L' toggles log on the axis closest to the mouse pointer. I'll leave it up to you to decide whether you like this mouse-proximity thing or not. But 'l' for y-log, which is probably the most common type of log plot, I think is nice. > Are there other keybindings people would like to see implemented in > the default pylab figures? 'r' for the ruler thingie? Best, f
I just committed some changes to CVS for auto-log scaling of line plots - you pay a performance hit for log plots but it appears to work. Eg, you can do x = arange(-2.002, 10, 0.01) y = sin(2*pi*x) plot(x,y) set(gca(), xscale='log') and only the positive data are plotted. If you have data points really close to 0, eg 1 >>> x = arange(-2.00, 10, 0.01) 2 >>> amin(abs(x)) Out[2]: 4.163336342344337e-17 You may a heavy performance price because so many decades are plotted, each with minor ticks, and ticks are expensive in the current impl. I am also implementing some default keypress events on the pylab figure manager canvas. Eg 'g' to toggle grid mode. I would like a key binding for toggling log/linear scale for x and y independently. 'x' and 'y' are not good choices since they are overloaded with constraining axes in interactive pan/zoom with the toolbar. Suggestions? '1' and '2'? CTRL-x and and CTRL-y? 'l' and 'L'? Are there other keybindings people would like to see implemented in the default pylab figures? JDH
>>>>> "John" == John Hunter <jdh...@ac...> writes: John> The bad news is I don't know how and where the error crept John> in. I'll do some digging. God Bless diff -- fixed in CVS. Make sure you have CVS revision of legend.py 1.35 or later. JDH
>>>>> "Fernando" == Fernando Perez <Fer...@co...> writes: Fernando> Hi all, I was just trying to make some plots with Fernando> legends in them, by following the damped exponential Fernando> example from pages 17-18 in the PDF user's guide. My Fernando> results are strange looking: the legend box size is Fernando> completely wrong, and the on-screen version has the Fernando> markers outside the box. The generated png does put the Fernando> markers in the right place, though. I'm using the TkAgg Fernando> backend, all in ipython-pylab. I've put up two pngs on Fernando> the net for reference: Hey Fernando, The good news is that matplotlib legends really do not look that big and stupid -- this is a CVS bug (0.71 works), eg http://matplotlib.sourceforge.net/screenshots.html#legend_demo The bad news is I don't know how and where the error crept in. I'll do some digging. Thanks for letting me know! JDH