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John, I had some questions about this resize work. Here is the code for resize from backend_gtk.py: def resize(self, w, h): 'set the drawing area size in pixels' winw, winh = self.parent.parent.get_size() tmp, tmp, myw, myh = self.allocation padw = winw-myw padh = winh-myh self.parent.parent.resize(w+padw, h+padh) I'm a little concerned about this implementation. It looks like the widget is telling it's parent's parent to resize. Doesn't this mean that the ability of the widget to be used as a modular component is reduced because this code requires a certain parent child relationship? I think it's fairly important that a widget have only very minimum interactions with it's parent. Is there some way this could be implemented that doesn't require the child widget to be calling methods on the parent? If I understand the basic premise you've outlined below, you want a resize in the child (the drawing widget) to cause the parent window to resize. Only the parent can figure out what it's size needs to be (since it knows about it's margins, toolbars, etc). On the surface, it seems like there are two ways to handling this: 1) Tell the window to resize the canvas. The window can use it's own layout classes, etc and correctly resize itself and the canvas. 2) Tell the canvas to resize and have this trigger a window resize. I think the first option is much cleaner. However, if that isn't possible, I suggest that we do something like this: - Tell the canvas to resize. It should resize itself and emit some type of 'plotCanvasResize' signal (GUI callback). - When the window is originally constructed, it would attach a method on the window to this signal so that we basically get the same behavior as 1) above. Telling the canvas to resize emits the signal which calls the window method to do the real resizing. The canvas widget never knows that it's part of the window at all. Of course this assumes that we have access to signal/slot (in Qt terms) systems in the Python layer. I'd also suggest that we stay away from calling it 'resize' since most GUI toolkits already have resize methods/attributes that mean very specific things. Thoughts? Ted > There is a new method in the figure canvas in CVS that I would like > the maintainers of the various GUI backends to implement > > class FigureCanvasYourBackend > > def resize(self, w, h): > """ > set the canvas size in pixels > """ > pass > > This should set the canvas (not window) size and trigger a GUI resize > event so that the window is resized accordingly. There is a reference > implementation in backend_gtk.py. You should be able to lift the > logic for computing the new canvas size directly from that code. > > Among other things, this will allow better control of the canvas size > from a script or shell. Eg, the following works with GTKAgg in an > interactive session: > > In [1]: fig = figure() > In [2]: fig.set_figsize_inches(3,4,forward=True) > In [3]: fig.canvas.resize(500,600) > > Ie, you can set the canvas size either in pixels or inches depending > on which method you choose. > > Also, I added a new connect signal 'resize_event' that triggers a > backend_bases.ResizeEvent on a canvas.resize. You should call > > self.resize_event() > > from the part of your code that handles GUI configure events (see for > example the GTK and GTKAgg backends). Note depending on your toolkit, > you may not want to call this from the FigureCanvas.resize method. > Eg, in GTK* calling "canvas.resize" triggers a call to > canvas.configure_event, which in turn sets the new figure size > properties and once all this is done, calls canvas.resize_event. > > Here is some test code > > from pylab import figure, connect, show > fig = figure() > def resize(event): > print 'resize canvas', event.width, event.height > > connect('resize_event', resize) > show() > > Checking in lib/matplotlib/backend_bases.py; > /cvsroot/matplotlib/matplotlib/lib/matplotlib/backend_bases.py,v <-- > backend_bases.py > new revision: 1.69; previous revision: 1.68 > > Thanks! > JDH > > Ted Drain Jet Propulsion Laboratory ted...@jp...
On 10/7/05, Robert Kern <rk...@uc...> wrote: > > John Hunter wrote: > >>>>>>"Paul" =3D=3D Paul Barrett <peb...@gm...> writes: > > > > Paul> I have data that has error bars and upper limits. (Actually > > Paul> they are lower limits, since the Y axis is in stellar > > Paul> magnitudes and is inverted.) My suggestion is use a negative > > Paul> error value to indicate a limit in which case an arrow would > > Paul> be drawn, instead of an error bar. This feature would only > > Paul> apply to the case of asymmetric error bars and not to the > > Paul> symmetric case. I can produce a patch if this suggestion is > > Paul> agreeable. > > > > I certainly don't have a problem with this and would be happy to > > include these extensions to the errorbar function. I wonder if the > > arrow is the best indicator for a limit, though I can't think of a > > better one at the moment. Also, does this handle limits in either > > direction (up or down) as well as left to right? > > Arrows are often used to indicate error bars which end outside of the > displayed area of the plot. I would also recommend against using > negative error values to indicate limits instead of errors. It smells of > FORTRAN. :-) Yes, it does smell of FORTRAN. However, my motive for suggesting negative error values is that it allows the user to specify the length of the limit arrow and numeric arrays to be used for input. The other option would be to use a string, e.g.'limit(2)', as a marker. This will complicate the implementation, but that is less of a concern to me than usability. I think that the ability to specify the length of the arrow is needed. This could b= e an optional parameter though. I'm open to suggestions. Limits should probably be implemented by a separate > object/function/whatever. > In astronomy, limit data is often associated with data having large error bars, i.e. they go hand-in-hand. So, a separate function would essentially duplicate the error bar functionality. I see no need for this duplicity. -- Paul
On 10/7/05, John Hunter <jdh...@ac...> wrote: > > >>>>> "Paul" =3D=3D Paul Barrett <peb...@gm...> writes: > > Paul> I have data that has error bars and upper limits. (Actually > Paul> they are lower limits, since the Y axis is in stellar > Paul> magnitudes and is inverted.) My suggestion is use a negative > Paul> error value to indicate a limit in which case an arrow would > Paul> be drawn, instead of an error bar. This feature would only > Paul> apply to the case of asymmetric error bars and not to the > Paul> symmetric case. I can produce a patch if this suggestion is > Paul> agreeable. > > I certainly don't have a problem with this and would be happy to > include these extensions to the errorbar function. I wonder if the > arrow is the best indicator for a limit, though I can't think of a > better one at the moment. Also, does this handle limits in either > direction (up or down) as well as left to right? > Yes, a negative value for the upper error bar will indicate an upper limit and vice versa for the lower error bar value. The same goes for left and right limits. Note that this enhancement will only affect asymmetric error bars and not symmetric ones, since the latter case doesn't make much sense to me. -- Paul
>>>>> "Kilian" == Kilian Hagemann <hag...@eg...> writes: Kilian> Hmm, I must admit I knew nothing about figures when I Kilian> posted. But now that I've done some homework, I see that Kilian> using Figure.legend is suboptimal as well because it can Kilian> neither resize the axes accordingly nor place outside Kilian> legends for each subplot automatically. Hey Killian, OK, I am happy to include this because I think the auto-resizing capability is useful (eg following the colorbar model). Now that you are aware of the figure legend, please take a look at your self.parent handling because parent can be an Axes or a Figure. You will want to check for isaxes before calling self.parent.get_position() and associated functions. Also, as a matter of style and efficiency, I prefer to avoid multiple function calls in lines like figwidth = self.get_figure().get_figwidth()*float(self.get_figure().get_dpi()) figheight = self.get_figure().get_figheight()*float(self.get_figure().get_dpi()) rather fig = self.get_figure() dpi = fig.get_dpi() figheight = fig.get_figheight()*dpi figwidth = fig.get_figwidth()*dpi dpi is already a float.... But even more pithily <wink> w, h = fig.canvas.get_width_height() Also, although these aren't written down anywhere (wiki entry needed so feel free to make one!) the matplotlib coding conventions are classes: UpperCase functions and methods: underscore_separated attributes and variables : lower of lowerUpper so vars like space_needed should be spaceneeded or spaceNeeded. Ditto for the fudge_* vars and new_aw and so on. Finally, I think your patch against your own tree, because it contains lines like - 'upper outside right' : 11, + 'upper outside right' : 11, # these only make sense with axes legends Eg, it is removing things that do not exist in matplotlib CVS -- make sure you apply diff against mpl CVS and not your own tree ! JDH
>>>>> "Kilian" == Kilian Hagemann <hag...@eg...> writes: Kilian> Dear developers, On Monday I sent an email to the Kilian> matplotlib-users list Kilian> (http://sourceforge.net/mailarchive/forum.php?thread_id=8391378&forum_id=33405) Kilian> asking if it was possible to have a 'centered' axis. Kilian> As I received no reply and couldn't find any other info, I Kilian> assume that this functionality is not present in Kilian> matplotlib-0.84. Am I right or is there a way? Sorry. I answered this question quite recently in another thread http://sourceforge.net/mailarchive/message.php?msg_id=13146574 which shows a hackish way that doesn't give you ticks Kilian> Cause if the lines of the x and y axis can only be plotted Kilian> on the lower/left edge of the axes/subplot I'd be keen to Kilian> enhance the code to make this flexible. Seems like I'd be Kilian> targeting axes.py and axis.py, but I'd also have to know Kilian> how this is done in Matlab to keep compatibility (I did Kilian> Matlab 6 years ago and don't remember anything). This would be a very nice feature and one I and others have been wanting for a long time. axes.py and axis.py are the right modules to look into. I don't know how matlab does it; it is a good idea to look into this for inspiration and API compatibility but we don't need to follow their implementation slavishly if there is a better one. I don't think it would be a lot of work to do this. You will want to make the edgecolor and facecolor of the axes patch the same as indicated in the thread above, and the add a Line2D to the XAxis and YAxis classes, and support placing them at an arbitrary location. The only tricky bit is that the axis classes work with some of the darker matplotlib transformation magic, which is hard for most people to understand because I do transformations in a nonstandard way. Nonetheless, they are reasonably well documented in the class documentation. I think it would be useful to support multiple axis lines per axes (eg two y scales). Chaco makes the axis a line property which is fairly different from the matplotlib approach but makes it easy to do things like drag a line from one axes to another with the axis coming along with it. Not sure if this is the right approach or not. Good luck! Please keep us posted with implementation ideas and feel free to ask a lot of questions. JDH
John Hunter wrote: >>>>>>"Paul" == Paul Barrett <peb...@gm...> writes: > > Paul> I have data that has error bars and upper limits. (Actually > Paul> they are lower limits, since the Y axis is in stellar > Paul> magnitudes and is inverted.) My suggestion is use a negative > Paul> error value to indicate a limit in which case an arrow would > Paul> be drawn, instead of an error bar. This feature would only > Paul> apply to the case of asymmetric error bars and not to the > Paul> symmetric case. I can produce a patch if this suggestion is > Paul> agreeable. > > I certainly don't have a problem with this and would be happy to > include these extensions to the errorbar function. I wonder if the > arrow is the best indicator for a limit, though I can't think of a > better one at the moment. Also, does this handle limits in either > direction (up or down) as well as left to right? Arrows are often used to indicate error bars which end outside of the displayed area of the plot. I would also recommend against using negative error values to indicate limits instead of errors. It smells of FORTRAN. :-) Limits should probably be implemented by a separate object/function/whatever. -- Robert Kern rk...@uc... "In the fields of hell where the grass grows high Are the graves of dreams allowed to die." -- Richard Harter
>>>>> "Paul" == Paul Barrett <peb...@gm...> writes: Paul> I have data that has error bars and upper limits. (Actually Paul> they are lower limits, since the Y axis is in stellar Paul> magnitudes and is inverted.) My suggestion is use a negative Paul> error value to indicate a limit in which case an arrow would Paul> be drawn, instead of an error bar. This feature would only Paul> apply to the case of asymmetric error bars and not to the Paul> symmetric case. I can produce a patch if this suggestion is Paul> agreeable. I certainly don't have a problem with this and would be happy to include these extensions to the errorbar function. I wonder if the arrow is the best indicator for a limit, though I can't think of a better one at the moment. Also, does this handle limits in either direction (up or down) as well as left to right? JDH
Dear developers, On Monday I sent an email to the matplotlib-users list (http://sourceforge.net/mailarchive/forum.php?thread_id=8391378&forum_id=33405) asking if it was possible to have a 'centered' axis. As I received no reply and couldn't find any other info, I assume that this functionality is not present in matplotlib-0.84. Am I right or is there a way? Cause if the lines of the x and y axis can only be plotted on the lower/left edge of the axes/subplot I'd be keen to enhance the code to make this flexible. Seems like I'd be targeting axes.py and axis.py, but I'd also have to know how this is done in Matlab to keep compatibility (I did Matlab 6 years ago and don't remember anything). -- Kilian Hagemann Climate Systems Analysis Group University of Cape Town Republic of South Africa Tel(w): ++27 21 650 2748
On Thursday 06 October 2005 23:52, you pondered: > > Are you aware of Figure.legend, which is designed to do what you > describe (place a legend outside the axes). Hmm, I must admit I knew nothing about figures when I posted. But now that I've done some homework, I see that using Figure.legend is suboptimal as well because it can neither resize the axes accordingly nor place outside legends for each subplot automatically. > See also > examples/figlegend_demo.py. I don't think your patch made it through > (at least I couldn't read it) but if there are extra features you need > (like auto-resizing the axes) I think these will be best placed in > Figure.legend. Somehow my patch got truncated. Here it is again. I still think that legends.py is the place to have the resizing code as in this way you can do it with arbitrary number of subplots & layouts. In figure.py I would imagine this to be difficult with arbitrary number of axes. Oh, by the way there was a request sometime ago for an automated way to place legends outside: http://sourceforge.net/mailarchive/message.php?msg_id=11106725 Have a look at the patch and tell me what you think. -- Kilian Hagemann Climate Systems Analysis Group University of Cape Town Republic of South Africa Tel(w): ++27 21 650 2748
>>>>> "Kilian" == Kilian Hagemann <hag...@eg...> writes: Kilian> Oh, and please bear with me, this is the first time I've Kilian> contributed a meaningful patch to an open source project. Are you aware of Figure.legend, which is designed to do what you describe (place a legend outside the axes). See also examples/figlegend_demo.py. I don't think your patch made it through (at least I couldn't read it) but if there are extra features you need (like auto-resizing the axes) I think these will be best placed in Figure.legend. http://matplotlib.sourceforge.net/matplotlib.figure.html#Figure-legend Thanks! JDH
Hi there, I recently discovered matplotlib after there were some things that good old gnuplot couldn't do, and quickly came to some of matplotlib's limitations. But since it's written in python which is my favorite language :-) I hacked together the attached patch. It basically implements legend placement outside right of the axes. This means three new options for the loc parameter in Legend's constructor: 'upper outside right', 'center outside right' and 'lower outside right', corresponding to codes 11-13. I didn't bother to have legends left, below or above the plot. One problem that I immediately came across was fitting the legend next to the subplot. I thus made the legend resize the axes by default so that it fits neatly next to it. This necessitates a small change in the drawing algorithm in the Axes class as the axes need to be resized before they're drawn, and the legend must be drawn *after* the axes. The whole thing works pretty well in what I've tested so far, but can be turned off by using resize_axes=False, a new keyword for Legend's constructor. Further, the 'best' location now checks all possible inside locations and if it doesn't find a perfect spot puts it 'center outside right' instead of at the least problematic place. Finally I cleaned up some redundant code in legend.py and two minor bugs, one related to error checking of the loc parameter, the other to near-perfect legend positioning in case it's frame uses a non-standard linewidth. Bugs and caveats: Don't try to resize the axes when resize_axes is on. In my scripts this seems to make no difference, but in gtk's interactive resizing function this gives unexpected results. Any chance of incorporating this enhancement in the next release? Oh, and please bear with me, this is the first time I've contributed a meaningful patch to an open source project. Regards, -- Kilian Hagemann Climate Systems Analysis Group University of Cape Town Republic of South Africa Tel(w): ++27 21 650 2748
I have data that has error bars and upper limits. (Actually they are lower limits, since the Y axis is in stellar magnitudes and is inverted.) My suggestion is use a negative error value to indicate a limit in which case an arrow would be drawn, instead of an error bar. This feature would only apply to the case of asymmetric error bars and not to the symmetric case. I can produce a patch if this suggestion is agreeable. -- Paul
Hi John, Attached is the Axes.xaxis_date(), yaxis_date() patch. I implemented the suggestions you made, including the extra keyword args to plot_date(). I was happy to see the date_ticker_factory() function was so similar to what I'd implemented on my own. Great minds think alike, I guess. Cheers, Michael On Mon, 3 Oct 2005, John Hunter wrote: >>>>>> "Michael" writes: > > Michael> Hi John, I've been making spacecraft trajectory "Pork > Michael> Chop Plots", a contour plot of a z-value (such amount of > Michael> fuel required) over a range of Earth departure date > Michael> x-values and Mars arrival date y-values. > > Michael> Since I needed dates on both x and y axes, it was useful > Michael> for me to factor out the date locator/formatter selection > Michael> code from plot_date() into two Axes methods: xaxis_date() > Michael> and yaxis_date(). > > Michael> The plot_date() implementation then becomes just a call > Michael> to plot() followed by a call to xaxis_date(). > > I think this is a good idea. A few suggestions > > matplotlib 0.84 / CVS already has the guts of plot_date factored out > in date_ticker_factory > > locator, formatter = date_ticker_factory(span, tz) > > which appears to be the same thing as your chooseDateFmt. So you'll > want to use that instead. Note also that matplotlib naming > conventions for functions and methods is lower case and underscore > separated. > > I think it would be useful to add the following kwargs to plot_date to > support your funcitonality > > > def plot_date(self, d, y, fmt='bo', tz=None, > xdate=True, ydate=False, **kwargs): > > Michael> My current implementation is below. Is this > Michael> general-purpose enough for me to submit? If so, I'll > Michael> make up some diff files and mail them in. > > Yep, with the changes above this would be great. > > Thanks! > JDH > -- ======================================================================== Michael Brady Phone: 818-354-4957 Jet Propulsion Laboratory (M/S 301-140L) 4800 Oak Grove Drive Pasadena, CA 91109 ========================================================================
>>>>> "Steve" == Steve Chaplin <ste...@ya...> writes: Steve> Should matplotlib have turned itself into a widget library Steve> / GUI toolkit? I know that for a long time John resisted Steve> the temptation to add widgets to matplotlib and wanted Steve> matplotlib to focus on being a plotting library. I agree Steve> with this view and think the danger now is that matplotlib Steve> will become too big and bloated and harder to install (like Steve> the old SciPy?). Hey Steve, If I'm not mistaken, the complexity of the core matplotlib build has not changed in quite a while -- basically we've required zlib, png, freetype and C++ since 0.5. Yes, some backends require additional complexity (eg GTKAgg, the new WXAgg blit functionality) but you can simply turn these options off in setup.py if you don't need them; in the next few weeks I'm going to try and replace _gtkagg with pure python using python buffers. All of the changes to support blitting, widgets and so on have either been pure python or changes to existing extension code (eg _backend_agg.cpp and _gtkagg.cpp). Also, the size of the widgets module, which seems to bother you, is miniscule > wc lib/matplotlib/widgets.py 985 3004 32510 lib/matplotlib/widgets.py I don't want mpl to become a widget library. I did want to add some support for controlling the subplot parameters, a very frequent gripe. I could have say "dear backend maintainers, please add these sliders and buttons to make this tool" and we would still be waiting. I don't think any of the backends other than GTK* which I added have implemented the resize functionality I requested on Sept 14th. That doesn't really bother me too much, because I know people are busy with other projects, but to the extent that I can get low level functionality that lets the frontend do these things, I and others can can roll out functionality that benefits almost all users much more efficiently. I implemented sliders and buttons because I needed them. They are pure python, took me less than a day, do something useful, work out of the box across backends, and make up a small fraction of the total code size. Looks like a win-win to me. I implemented other widgets as an afterthought the same day as proof of concept, with the thought that if someone wants to make a *matplotlib tool* if they did it using the matplotlib widgets and events it would immediately be available to everyone. Most GUI work in python cannot be shared because it is tk specific, wx specific and so on, and I wanted to find a way around this problem. Steve> I would prefer to see a 'matplotlib-core' which is a Steve> minimal module that focuses purely on plotting Steve> graphs. Other optional modules (like 'matplotlib-toolkits', Steve> 'matplotlib-widgets', etc) could then extend Steve> 'matplotlib-core' by providing extra features. I think the distinction between plotting and interacting with your plot is not so clear. Sure, some small fraction of mpl users just generate static graphs, but the majority I would guess actually use things like matplotlib Events regularly (ie every time they use the pan/zoom tools). Should these be addons, or part of the core? I'm not opposed to this kind of packaging if it were done right (eg if everyone had something roughly equivalent to debian's apt. I think the vast majority of users want something that "just works". Nadia has been working on pulling all of the non-matplotlib dependencies out of the tree (CXX, Agg, png, zlib, pytz, dateutil) and revamping the build system to grab a tarball off the internet if a configure system doesn't detect them. This would make matplotlib CVS and the src distro much ligher, which I'm sure all the developers who regularly do CVS checkouts will appreciate since the damned pytz directories take forever. This will definitely be a step in the right direction, especially if we can get it to work across platforms. As far as widgets are concerned, I don' think they can be placed in an optional toolkit because the subplot tool requires them. At under 1000 lines of pure python, I also don't see the motivation. Contrast this with basemap, which is over 10MB with lots of extension code. Or would you like to see the toolbar and all of it's functionality rolled into an option addon? JDH
John Hunter wrote: >>>>>>"Jeff" == Jeff Whitaker <js...@fa...> writes: >>>>>> >>>>>> > > Jeff> Anyone know how the default axes rectangle is set? The > Jeff> default width and height are apparently not the same > > >>>> from pylab import * ax=axes() ax.get_position() > Jeff> [0.125, 0.099999999999999978, 0.77500000000000002, > Jeff> 0.80000000000000004] > > > Jeff> I'd like the last two numbers to be identical (say 0.8), > Jeff> that way I can be sure that a plot will have a certain > Jeff> aspect ratio if the figure dimensions have that aspect > Jeff> ratio. > >If no args are passed to axes, a subplot(111) is created. If you want >to control the rectangle, just pass in the l,b,w,h args > > ax = axes([0.1, 0.1, 0.8, 0.8]) > >If you want to see how the default subplots are created, see >axes.Subplot and the subplot params > > left : 0.125 # the left side of the subplots of the figure > right : 0.9 # the right side of the subplots of the figure > bottom : 0.1 # the bottom of the subplots of the figure > top : 0.9 # the top of the subplots of the figure > wspace : 0.2 # the amount of width reserved for blank space between subplots > hspace : 0.2 # the amount of height reserved for white space between subplots > >JDH > >PS: thanks for the basemap notes -- I presented them at scipy and >there appeared to be a fair amount of interest in it. > > John: Thanks - I knew about setting the rect manually, but I didn't know the defaults were in subplot.params. I want to override those defaults in basemap so that the width and height are both 0.8 (they are 0.775 and 0.8 now). That way the map will have the right aspect ratio without the user having to set the axes rect manually. I've set it up so that rcParams['subplot.params.left'] is set to 0.1 when basemap is imported (a warning is printed notifying the user that the defaults have been changed, and rcdefaults() can be used to get the old ones back). Thanks a lot for presenting that material at SciPy - I've noticed an upswing in downloads since your talk. -Jeff -- Jeffrey S. Whitaker Phone : (303)497-6313 Meteorologist FAX : (303)497-6449 NOAA/OAR/CDC R/CDC1 Email : Jef...@no... 325 Broadway Office : Skaggs Research Cntr 1D-124 Boulder, CO, USA 80303-3328 Web : http://tinyurl.com/5telg
>>>>> "Michael" == Michael Brady <mb...@jp...> writes: Michael> Hi John, I've been making spacecraft trajectory "Pork Michael> Chop Plots", a contour plot of a z-value (such amount of Michael> fuel required) over a range of Earth departure date Michael> x-values and Mars arrival date y-values. Michael> Since I needed dates on both x and y axes, it was useful Michael> for me to factor out the date locator/formatter selection Michael> code from plot_date() into two Axes methods: xaxis_date() Michael> and yaxis_date(). Michael> The plot_date() implementation then becomes just a call Michael> to plot() followed by a call to xaxis_date(). I think this is a good idea. A few suggestions matplotlib 0.84 / CVS already has the guts of plot_date factored out in date_ticker_factory locator, formatter = date_ticker_factory(span, tz) which appears to be the same thing as your chooseDateFmt. So you'll want to use that instead. Note also that matplotlib naming conventions for functions and methods is lower case and underscore separated. I think it would be useful to add the following kwargs to plot_date to support your funcitonality def plot_date(self, d, y, fmt='bo', tz=None, xdate=True, ydate=False, **kwargs): Michael> My current implementation is below. Is this Michael> general-purpose enough for me to submit? If so, I'll Michael> make up some diff files and mail them in. Yep, with the changes above this would be great. Thanks! JDH
>>>>> "Jeff" == Jeff Whitaker <js...@fa...> writes: Jeff> Anyone know how the default axes rectangle is set? The Jeff> default width and height are apparently not the same >>>> from pylab import * ax=axes() ax.get_position() Jeff> [0.125, 0.099999999999999978, 0.77500000000000002, Jeff> 0.80000000000000004] Jeff> I'd like the last two numbers to be identical (say 0.8), Jeff> that way I can be sure that a plot will have a certain Jeff> aspect ratio if the figure dimensions have that aspect Jeff> ratio. If no args are passed to axes, a subplot(111) is created. If you want to control the rectangle, just pass in the l,b,w,h args ax = axes([0.1, 0.1, 0.8, 0.8]) If you want to see how the default subplots are created, see axes.Subplot and the subplot params left : 0.125 # the left side of the subplots of the figure right : 0.9 # the right side of the subplots of the figure bottom : 0.1 # the bottom of the subplots of the figure top : 0.9 # the top of the subplots of the figure wspace : 0.2 # the amount of width reserved for blank space between subplots hspace : 0.2 # the amount of height reserved for white space between subplots JDH PS: thanks for the basemap notes -- I presented them at scipy and there appeared to be a fair amount of interest in it.
Anyone know how the default axes rectangle is set? The default width and height are apparently not the same >>> from pylab import * >>> ax=axes() >>> ax.get_position() [0.125, 0.099999999999999978, 0.77500000000000002, 0.80000000000000004] I'd like the last two numbers to be identical (say 0.8), that way I can be sure that a plot will have a certain aspect ratio if the figure dimensions have that aspect ratio. -Jeff -- Jeffrey S. Whitaker Phone : (303)497-6313 NOAA/OAR/CDC R/CDC1 FAX : (303)497-6449 325 Broadway Web : http://www.cdc.noaa.gov/~jsw Boulder, CO, USA 80305-3328 Office: Skaggs Research Cntr 1D-124
Hi John, I've been making spacecraft trajectory "Pork Chop Plots", a contour plot of a z-value (such amount of fuel required) over a range of Earth departure date x-values and Mars arrival date y-values. Since I needed dates on both x and y axes, it was useful for me to factor out the date locator/formatter selection code from plot_date() into two Axes methods: xaxis_date() and yaxis_date(). The plot_date() implementation then becomes just a call to plot() followed by a call to xaxis_date(). My current implementation is below. Is this general-purpose enough for me to submit? If so, I'll make up some diff files and mail them in. Thanks, Michael #=========================================================================== def xaxis_date(self, tz=None): """Choose date ticks and labels for the x-axis. = INPUT VARIABLES - tz The timezone to use in plotting the dates. Defaults to rc value. """ span = self.dataLim.intervalx().span() locator, formatter = self.chooseDateFmt( span, tz ) self.xaxis.set_major_locator(locator) self.xaxis.set_major_formatter(formatter) #=========================================================================== def yaxis_date(self, tz=None): """Choose date ticks and labels for the y-axis. = INPUT VARIABLES - tz The timezone to use in plotting the dates. Defaults to rc value. """ span = self.dataLim.intervaly().span() locator, formatter = self.chooseDateFmt( span, tz ) self.yaxis.set_major_locator(locator) self.yaxis.set_major_formatter(formatter) #=========================================================================== def chooseDateFmt(self, span, tz=None): """Chooses an appropriate date formatter and tick locator for a span. = INPUT VARIABLES - span The span of the plot data. - tz The timezone to use in plotting the dates. Defaults to rc value. = RETURN VALUE - A tuple of ( locator, formatter ) for the input span. """ # The code below was copied from Axes.plot_date(). if span==0: span = SEC_PER_HOUR minutes = span*24*60 hours = span*24 days = span weeks = span/7. months = span/31. # approx years = span/365. numticks = 5 if years>numticks: locator = YearLocator(int(years/numticks), tz=tz) # define fmt = '%Y' elif months>numticks: locator = MonthLocator(tz=tz) fmt = '%b %Y' elif weeks>numticks: locator = WeekdayLocator(tz=tz) fmt = '%a, %b %d' elif days>numticks: locator = DayLocator(interval=math.ceil(days/numticks), tz=tz) fmt = '%b %d' elif hours>numticks: locator = HourLocator(interval=math.ceil(hours/numticks), tz=tz) fmt = '%H:%M\n%b %d' elif minutes>numticks: locator = MinuteLocator(interval=math.ceil(minutes/numticks), tz=tz) fmt = '%H:%M:%S' else: locator = MinuteLocator(tz=tz) fmt = '%H:%M:%S' formatter = DateFormatter(fmt, tz=tz) return locator, formatter ======================================================================== Michael Brady Phone: 818-354-4957 Jet Propulsion Laboratory (M/S 301-140L) Fax: 818-393-6388 4800 Oak Grove Drive Pasadena, CA 91109 E-mail: Mic...@jp... ========================================================================