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Sorry, This was just a silly mistake. I forgot declare the selectors as class variables (by adding self in front of them). -Aman On Tue, Sep 7, 2010 at 1:37 PM, Aman Thakral <ama...@gm...> wrote: > Hi, > > I seem to be encountering a strange problem. I'm using a SpanSelector and > a RectangularSelector in my application and they seem to be working in Linux > but not in Windows. I'm using wxpython as the gui layer. Has anyone else > encountered similar issues? > > Thanks, > Aman > -- Aman Thakral B.Eng & Biosci, M.Eng Design
Perfect thank you, no wonder I didnt find it, plt.gca().add_collection(lc) never found its way to my radar. Cheers, Brian On Sep 7, 2010, at 7:58 PM, Ryan May wrote: > On Tue, Sep 7, 2010 at 6:50 PM, Brian Larsen <bal...@la...> wrote: >> Hey all, >> I think I know the answer here as "no" or something, but say I have a curve >> I want to plot and I want the color to change along the curve to denote the >> 3rd variable is there anyway to do this is matplotlib? >> What I mean is take the simple plot >> from pylab import * >> plot(range(30), range(30, 60), lw=10) >> and say that the 3rd variable is >> inten = [val ** 2 for val in range(30)] >> then can the line change color along its length according to a specified >> color table? >> In IDL this is done by just giving a color array with the same length as the >> data then the line changes with the current colortable. > > Try this: > > http://matplotlib.sourceforge.net/examples/pylab_examples/multicolored_line.html > > Ryan > > -- > Ryan May > Graduate Research Assistant > School of Meteorology > University of Oklahoma -- Brian A. Larsen Space Science and Applications Group ISR-1 Los Alamos National Laboratory PO Box 1663, MS-D466 Los Alamos, NM 87545 USA (For overnight add: SM-30, Bikini Atoll Road) Phone: 505-665-7691 Fax: 505-665-7395 email: bal...@la... Correspondence / Technical data or Software Publicly Available
This is of interest to me, and it's nice to know that this is do-able with matplotlib, but like many of the examples, I find it sorely lacking in documentation. For example, why are the points and segments arrays shaped so specifically the way they are? Why the call to set_array? Could the same thing be accomplished with a call to set_facecolor? I hope the same things can be accomplished in a more straightforward way. Any illumination on these points would be appreciated. Jon > On Tue, Sep 7, 2010 at 6:50 PM, Brian Larsen > <bal...@la...> wrote: > > Hey all, > > I think I know the answer here as "no" or something, but > say I have a curve > > I want to plot and I want the color to change along the > curve to denote the > > 3rd variable is there anyway to do this is matplotlib? > > What I mean is take the simple plot > > from pylab import * > > plot(range(30), range(30, 60), lw=10) > > and say that the 3rd variable is > > inten = [val ** 2 for val in range(30)] > > then can the line change color along its length according to > a specified > > color table? > > In IDL this is done by just giving a color array with the > same length as the > > data then the line changes with the current colortable. > > Try this: > > http://matplotlib.sourceforge.net/examples/pylab_examples/multicolored_line.html > > Ryan > > -- > Ryan May > Graduate Research Assistant > School of Meteorology > University of Oklahoma
2010年9月8日 Guillaume Chérel <gui...@gm...>: > It works great with patches of circles. Thank you. > > Also, I want my circles to look round, so I use the command axis('equal'). > Is there any way to make sure that the area I defined with xlim() and ylim() > won't be cut off. I'd rather have one dimension expanded than the other one > shrunk. Can I control that? You can make it so that axes box itself is changed instead of your data limits: import matplotlib.pyplot as plt ax = plt.gca() ax.set_aspect('equal','box') Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma
Images can placed at arbitrary position (using the extent keyword). I think this is enough as far as you're careful with the aspect. Looking at the wikipedia example, I don't see any reason that this cannot be done with matplotlib. Regards, -JJ On Wed, Sep 8, 2010 at 6:34 AM, Joshua Holbrook <jos...@gm...> wrote: > Hey y'all, > > I recently read about Chernoff faces > (http://en.wikipedia.org/wiki/Chernoff_face) in one of Edward Tufte's > books (great read btw) and would like to mess around with them in > matplotlib. My current approach is to generate the faces as images, > and then use them as markers on an x-y plot (like the example I > found in the Tufte book). I just realized, though, that I have no idea how to > incorporate images as position markers in matplotlib, or if it's even > possible. My search of the mpl docs didn't turn up much. > > Any ideas? > > > --Joshua Holbrook > > ------------------------------------------------------------------------------ > This SF.net Dev2Dev email is sponsored by: > > Show off your parallel programming skills. > Enter the Intel(R) Threading Challenge 2010. > http://p.sf.net/sfu/intel-thread-sfd > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users >
It works great with patches of circles. Thank you. Also, I want my circles to look round, so I use the command axis('equal'). Is there any way to make sure that the area I defined with xlim() and ylim() won't be cut off. I'd rather have one dimension expanded than the other one shrunk. Can I control that? thanks, guillaume Le 07/09/2010 18:05, Benjamin Root a écrit : > 2010年9月7日 Guillaume Chérel <gui...@gm... > <mailto:gui...@gm...>> > > Hello, > > I'm trying to draw circles with the scatter function. They are > supposed > to represent trees in the savannah. It is thus important that they are > displayed with a proper size, that is, one which represents their > actual > size on the field. After quite some confusion, I've found out (I > think) > that the size argument one can specify with the scatter function is > given as a disk's surface in pixels square (I think that's what means > the "points^2" in the documentation and from my own tests) > > What I would like is to give a surface in unit^2, where "unit" is the > unit of my data, and which you can read on the plot's axes ticks. For > example, each tree has coordinates like x=3500, y=2210. (The unit here > is centimeters but we don't really need to know this). Say I want to > draw a tree which canopy is 200 cm wide. That makes a disk which > radius > is 100, or surface 100^2*PI. How can I draw this? > > Many thanks, > Guillaume > > > > Guillaume, > > Using scatter is probably not the way to go about what you want. The > circles for scatter are a fixed size and if you zoom in, they will not > scale accordingly. > > You probably want to create patches of Circles: > > http://matplotlib.sourceforge.net/api/artist_api.html#matplotlib.patches.Circle > http://www.mail-archive.com/mat...@li.../msg06786.html > > Or even utilize a collection of Circles: > > http://matplotlib.sourceforge.net/api/collections_api.html#matplotlib.collections.CircleCollection > > Note that for a CircleCollection, you would use 'offset' to indicate > the center of each circle. After creating the collection, you would > then use ax.add_collection() function to add that collection to the axes. > > I hope that is helpful. > Ben Root
It works great with patches of circles. Thank you. Also, I want my circles to look round, so I use the command axis('equal'). Is there any way to make sure that the area I defined with xlim() and ylim() won't be cut off. I'd rather have one dimension expanded than the other one shrunk. Can I control that? thanks, guillaume Le 07/09/2010 18:05, Benjamin Root a écrit : > 2010年9月7日 Guillaume Chérel <gui...@gm... > <mailto:gui...@gm...>> > > Hello, > > I'm trying to draw circles with the scatter function. They are > supposed > to represent trees in the savannah. It is thus important that they are > displayed with a proper size, that is, one which represents their > actual > size on the field. After quite some confusion, I've found out (I > think) > that the size argument one can specify with the scatter function is > given as a disk's surface in pixels square (I think that's what means > the "points^2" in the documentation and from my own tests) > > What I would like is to give a surface in unit^2, where "unit" is the > unit of my data, and which you can read on the plot's axes ticks. For > example, each tree has coordinates like x=3500, y=2210. (The unit here > is centimeters but we don't really need to know this). Say I want to > draw a tree which canopy is 200 cm wide. That makes a disk which > radius > is 100, or surface 100^2*PI. How can I draw this? > > Many thanks, > Guillaume > > > > Guillaume, > > Using scatter is probably not the way to go about what you want. The > circles for scatter are a fixed size and if you zoom in, they will not > scale accordingly. > > You probably want to create patches of Circles: > > http://matplotlib.sourceforge.net/api/artist_api.html#matplotlib.patches.Circle > http://www.mail-archive.com/mat...@li.../msg06786.html > > Or even utilize a collection of Circles: > > http://matplotlib.sourceforge.net/api/collections_api.html#matplotlib.collections.CircleCollection > > Note that for a CircleCollection, you would use 'offset' to indicate > the center of each circle. After creating the collection, you would > then use ax.add_collection() function to add that collection to the axes. > > I hope that is helpful. > Ben Root
On 09/07/2010 07:33 PM, Philippe Crave wrote: > hi, > > sorry to bring this up again. > style haven't found how to draw my plot faster than > self.fig.canvas.draw(), after a set_data() If you need to change the scale of the plot when you update the data, then I don't see any alternative to redoing the whole plot. If that is too slow, then mpl may simply be the wrong tool for the job. Parts of mpl have been nicely optimized for speed, but generating a large number of subplots is not among them. I don't expect this will change any time soon. The tick generation and labeling is the main time sink. If I generate 20 blank subplots, with default ticks and labels, each draw takes 420 ms on my machine. If I set all the ticks to the empty list, it drops to 34 ms. Eric > > thanks > > 2010年9月1日 Philippe Crave<phi...@gm...>: >> Hi, >> >> I use qt4 backend. >> I update some lines doing something like that: >> >> def draw_curves(self, datas, x): >> for y in datas: >> self.lines[i].set_data(x, y) >> min_y, max_y = self.min_max(y) >> self.ax[i].axis((0, x[-1], min_y, max_y)) >> #self.ax[i].draw_artist(self.lines[i]) >> #self.fig.canvas.blit(self.ax[i].bbox) >> self.fig.canvas.draw() >> >> >> the self.fig.canvas.draw() is very slow. (I have 20 subplot in that figure). >> I tried to use: >> self.ax[i].draw_artist(self.lines[i]) >> self.fig.canvas.blit(self.ax[i].bbox) >> it's very fast. But it does not update the scale of the plot. >> and it does not remove the old datas. >> >> Can someone help me on that ? >> if I plot a sin(x) at first, I get it between 0 and 1. then, if I plot >> 2.sin(x), it does not update the zoom to 0-2 >> >> thank you, >> Philippe >> > > ------------------------------------------------------------------------------ > This SF.net Dev2Dev email is sponsored by: > > Show off your parallel programming skills. > Enter the Intel(R) Threading Challenge 2010. > http://p.sf.net/sfu/intel-thread-sfd > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
hi, sorry to bring this up again. style haven't found how to draw my plot faster than self.fig.canvas.draw(), after a set_data() thanks 2010年9月1日 Philippe Crave <phi...@gm...>: > Hi, > > I use qt4 backend. > I update some lines doing something like that: > > def draw_curves(self, datas, x): > for y in datas: > self.lines[i].set_data(x, y) > min_y, max_y = self.min_max(y) > self.ax[i].axis((0, x[-1], min_y, max_y)) > #self.ax[i].draw_artist(self.lines[i]) > #self.fig.canvas.blit(self.ax[i].bbox) > self.fig.canvas.draw() > > > the self.fig.canvas.draw() is very slow. (I have 20 subplot in that figure). > I tried to use: > self.ax[i].draw_artist(self.lines[i]) > self.fig.canvas.blit(self.ax[i].bbox) > it's very fast. But it does not update the scale of the plot. > and it does not remove the old datas. > > Can someone help me on that ? > if I plot a sin(x) at first, I get it between 0 and 1. then, if I plot > 2.sin(x), it does not update the zoom to 0-2 > > thank you, > Philippe >
On Tue, Sep 7, 2010 at 6:50 PM, Brian Larsen <bal...@la...> wrote: > Hey all, > I think I know the answer here as "no" or something, but say I have a curve > I want to plot and I want the color to change along the curve to denote the > 3rd variable is there anyway to do this is matplotlib? > What I mean is take the simple plot > from pylab import * > plot(range(30), range(30, 60), lw=10) > and say that the 3rd variable is > inten = [val ** 2 for val in range(30)] > then can the line change color along its length according to a specified > color table? > In IDL this is done by just giving a color array with the same length as the > data then the line changes with the current colortable. Try this: http://matplotlib.sourceforge.net/examples/pylab_examples/multicolored_line.html Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma
Hello, Today we have made Grima available as free software under the MIT license. Grima is a pygtk+ widget that embeds matplotlib. Basically, this means that Grima allows matplotlib to play nicely with the GTK+ main loop. Grima is hosted on GitHub at http://github.com/cdsi/grima. Please note that this is a very early alpha release. There is very little documentation on how to use Grima, or on its future plans. Our needs are related to being able to visualize arbitrary sets of time series data (like device measurements), as well as store and retrieve this data in a modular way. We plan to provide a mechanism to work with structured JSON data in couchdb or redis. For now, applications simply pass x and y values per the current matplotlib API. We have decided to make Grima available at this point so that others have the opportunity to evolve it beyond our own limited scope. Contributions (ideas, critiques, patches) are welcomed. To start, please take a look at: http://github.com/cdsi/grima/blob/master/bin/grima-subplot.py. I am more than happy to answer any questions. You may contact me directly at to...@cr..., or at cds...@go.... The latter is a Google Group that covers Grima as well as some other bits of free software also released today. A list of these are up at http://github.com/cdsi. Thank you, -Tom PS - A special thanks to the matplotlib community, and to http://unpythonic.blogspot.com/2007/08/using-threads-in-pygtk.html for all of the excellent work upon which Grima is based. -- Visit our website: http://software6.net/ Follow us on Twitter: http://twitter.com/software6
Hey all, I think I know the answer here as "no" or something, but say I have a curve I want to plot and I want the color to change along the curve to denote the 3rd variable is there anyway to do this is matplotlib? What I mean is take the simple plot from pylab import * plot(range(30), range(30, 60), lw=10) and say that the 3rd variable is inten = [val ** 2 for val in range(30)] then can the line change color along its length according to a specified color table? In IDL this is done by just giving a color array with the same length as the data then the line changes with the current colortable. Thanks much, Brian -- Brian A. Larsen Space Science and Applications Group ISR-1 Los Alamos National Laboratory PO Box 1663, MS-D466 Los Alamos, NM 87545 USA (For overnight add: SM-30, Bikini Atoll Road) Phone: 505-665-7691 Fax: 505-665-7395 email: bal...@la... Correspondence / Technical data or Software Publicly Available
Hey y'all, I recently read about Chernoff faces (http://en.wikipedia.org/wiki/Chernoff_face) in one of Edward Tufte's books (great read btw) and would like to mess around with them in matplotlib. My current approach is to generate the faces as images, and then use them as markers on an x-y plot (like the example I found in the Tufte book). I just realized, though, that I have no idea how to incorporate images as position markers in matplotlib, or if it's even possible. My search of the mpl docs didn't turn up much. Any ideas? --Joshua Holbrook
Enthought Python Distribution Webinar September 10 This Friday,Warren Weckesser will host the first of three webinars in a series on solving differential equations in Python. We will take a close look at the two tools available for solving ordinary differential equations in SciPy: the "odeint" function and the "ode" class. Two examples will be discussed: (1) the famous Lorenz equations that exhibit chaos, and (2) the Gray-Scott reaction-diffusion equations in 1D, from which we will obtain a system of ordinary differential equations by using the "Method of Lines". The demonstrations also include 3D plots and animation using Matplotlib. Enthought Python Distribution Webinar How do I...solve differential equations with Python? Part I: SciPy Tools Friday, September 10: 1pm CST/6pm UTC Wait list (for non EPD subscribers): email:am...@en... Early in 2011, Warren will host Part II: boundary value problems, and in the spring he'll follow up with a third installment to the series. Have a fantastic September, The Enthought Team
Hi, I seem to be encountering a strange problem. I'm using a SpanSelector and a RectangularSelector in my application and they seem to be working in Linux but not in Windows. I'm using wxpython as the gui layer. Has anyone else encountered similar issues? Thanks, Aman
Dear Joe, finally I had time to come back to my python scritp for the contour plots. You're code works very nicelly and does exactly what I need. Thank you for the help Francesco 2010年7月26日 Joe Kington <jki...@wi...>: > It sounds like you're wanting a gaussian kernel density estimate (KDE) (not > the desktop!). The other options you mentioned are for interpolation, and > are not at all what you're wanting to do. > > You can use scipy.stats.kde.gaussian_kde(). However, it currently doesn't > take a weights array, so you'll need to modify it for your use case. > > If you prefer, I have faster version of a gaussian KDE that can take a > weights array. It's actually slower than the scipy's gaussian kde for a low > number of points, but for hundreds, thousands, or millions of points, it's > several orders of magnitude faster. (Though the speedup depends on the > covariance of the points... higher covariance = slower, generally speaking) > > Here's a quick pastebin of the code. http://pastebin.com/LNdYCZgw > > To use it, you do something like the below... (assuming the code in the > pastebin is saved in a file called fast_kde.py) > > import numpy as np > import matplotlib.pyplot as plt > from fast_kde import fast_kde > > # From your description of your data... > weights, x, y = np.loadtxt('chain.txt', usecols=(0,4,6)).T > > kde_grid = fast_kde(x, y, gridsize=(200,200), weights=weights) > > # Plot the grid > plt.figure() > plt.imshow(kde_grid, extent=(x.min(), x.max(), y.max(), y.min()) > > # Reverse the y-axis > plt.gca().invert_yaxis() > > plt.show() > > Hope that helps a bit, > -Joe > > > > > On Sat, Jul 24, 2010 at 3:56 AM, montefra <fra...@go...> > wrote: >> >> Hi, >> >> I am writing a program that reads three columns (one column containing the >> weights, the other two containing the values I want to plot) from a file >> containing the results from a MonteCarlo Markov Chain. The file contains >> thousends of lines. Then create the 2D histogram and make contourplots. >> Here >> is a sample of the code (I don't know if is correct, it's just to show >> what >> I do) >> >> >>> import numpy as np >> >>> import matplotlib.pyplot as mplp >> >>> chain = np.loadtxt("chain.txt", usecols=[0,4,6]) #read columns 0 >> >>> (the >> >>> weights), 4 and 6 (the data), from the file "chain.txt" >> >>> h2D, xe, ye = np.histogram2D(chain[:,1],chain[:,2], >> >>> weights=chain[:,0]) >> >>> #create the 2D histogram >> >>> x = (xe[:-1] + xe[1:])/2. #x and y values for the plot (I use the mean >> >>> of each bin) >> >>> y = (ye[:-1] + ye[1:])/2. >> >>> mplp.figure() #open the figure >> >>> mplp.contourf(x, y, h2D.T, origin='lower') #contour plot >> >> As it is the contours are not smooth and they look not that nice. After >> days >> of searches I've found three methods and tried, unsuccesfully, to apply >> them >> 1) 2d interpolation: I got "segmentation fault" (on a quadcore machine >> with >> 8Gb of RAM) >> 2) Rbf (radial basis functions): I got wrong contours >> 3) ndimage: it creates spurious features (like secondary peaks parallel to >> the direction of the main one) >> >> Before beginning with Python, I used to use IDL to plot, and there is a >> function 'smooth' that smooth for you 2D histograms. I haven't found >> anything similar for Python. >> Does anyone have an idea or suggestion on how to do it? >> >> Thank in advance >> Francesco >> >> -- >> View this message in context: >> http://old.nabble.com/Smooth-contourplots-tp29253884p29253884.html >> Sent from the matplotlib - users mailing list archive at Nabble.com. >> >> >> >> ------------------------------------------------------------------------------ >> The Palm PDK Hot Apps Program offers developers who use the >> Plug-In Development Kit to bring their C/C++ apps to Palm for a share >> of 1ドル Million in cash or HP Products. Visit us here for more details: >> http://ad.doubleclick.net/clk;226879339;13503038;l? >> http://clk.atdmt.com/CRS/go/247765532/direct/01/ >> _______________________________________________ >> Matplotlib-users mailing list >> Mat...@li... >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > -- personals: mon...@ya..., mon...@ho... (messenger), fra...@go.... work: mon...@mp... http://picasaweb.google.it/franz.bergesund
2010年9月7日 Guillaume Chérel <gui...@gm...> > Hello, > > I'm trying to draw circles with the scatter function. They are supposed > to represent trees in the savannah. It is thus important that they are > displayed with a proper size, that is, one which represents their actual > size on the field. After quite some confusion, I've found out (I think) > that the size argument one can specify with the scatter function is > given as a disk's surface in pixels square (I think that's what means > the "points^2" in the documentation and from my own tests) > > What I would like is to give a surface in unit^2, where "unit" is the > unit of my data, and which you can read on the plot's axes ticks. For > example, each tree has coordinates like x=3500, y=2210. (The unit here > is centimeters but we don't really need to know this). Say I want to > draw a tree which canopy is 200 cm wide. That makes a disk which radius > is 100, or surface 100^2*PI. How can I draw this? > > Many thanks, > Guillaume > > > Guillaume, Using scatter is probably not the way to go about what you want. The circles for scatter are a fixed size and if you zoom in, they will not scale accordingly. You probably want to create patches of Circles: http://matplotlib.sourceforge.net/api/artist_api.html#matplotlib.patches.Circle http://www.mail-archive.com/mat...@li.../msg06786.html Or even utilize a collection of Circles: http://matplotlib.sourceforge.net/api/collections_api.html#matplotlib.collections.CircleCollection Note that for a CircleCollection, you would use 'offset' to indicate the center of each circle. After creating the collection, you would then use ax.add_collection() function to add that collection to the axes. I hope that is helpful. Ben Root
Hello, I'm trying to draw circles with the scatter function. They are supposed to represent trees in the savannah. It is thus important that they are displayed with a proper size, that is, one which represents their actual size on the field. After quite some confusion, I've found out (I think) that the size argument one can specify with the scatter function is given as a disk's surface in pixels square (I think that's what means the "points^2" in the documentation and from my own tests) What I would like is to give a surface in unit^2, where "unit" is the unit of my data, and which you can read on the plot's axes ticks. For example, each tree has coordinates like x=3500, y=2210. (The unit here is centimeters but we don't really need to know this). Say I want to draw a tree which canopy is 200 cm wide. That makes a disk which radius is 100, or surface 100^2*PI. How can I draw this? Many thanks, Guillaume
Hi all, is there an easy way to draw an arrow in a 3D Plot (just a single arrow). I couldn't find any useful example in the 1.0.0 docu. Best regards, Torsten.
On Tue, Sep 7, 2010 at 11:04 AM, Paul Ivanov <piv...@gm...> wrote: > Is this a reasonable way of achieving the desired result? > Yes. You may take a look at the legend guide. http://matplotlib.sourceforge.net/users/legend_guide.html For your original question, it is not possible to do that with the current legend implementation. However, you may put the legend inside the AnnotationBbox, which enables this. I'm posting the example for any future reference. Regards, -JJ # small example ax = plt.subplot(1,1,1) ax.plot([0,1], label='ax1') leg = ax.legend() ax.legend_ = None # remove the legend from the axes. ax2 = ax.twinx() ax2.plot([1,0], 'r--',label='ax2') leg2 = ax2.legend() # create a legend # add leg as AnnotationBbox from matplotlib.offsetbox import AnnotationBbox leg3 = AnnotationBbox(leg._legend_box, (0, 1), xybox=(-5, 0), xycoords=leg2.legendPatch, boxcoords="offset points", box_alignment=(1., 1.), pad=0, ) # adjust zorder so that leg3 is drawn after leg2 leg3.zorder = leg2.zorder+0.1 ax2.add_artist(leg3)
Paul Ivanov, on 2010年09月06日 18:01, wrote: > I want to have two legends (from different axes) positioned right up > against on another. > > Here's a static example, except I want the second legend to be defined > relative to the first (if leg is moved, I want leg2 to move as well). I > can't seem to figure out the proper bbox_to_anchor and bbox_transform > parameters to pass to the second legend() to make this work. > > # small example > ax = plt.subplot(1,1,1) > ax2 = ax.twinx() > ax.plot([0,1], label='ax1') > ax2.plot([1,0], 'r--',label='ax2') > leg = ax.legend(loc='lower left', borderaxespad=0, > bbox_to_anchor=(.85,.85)) > leg2 = ax2.legend(loc='upper left', borderaxespad=0, > bbox_to_anchor=(.85,.85)) > I guess I really just want one legend, so I figured out an alternative solution: # alternative to having two legends ax = plt.subplot(1,1,1) ax2 = ax.twinx() lines= ax.plot([0,1], label='ax1') lines2= ax2.plot([4,3], 'r--',label='ax2') lines.extend(lines2) labels = [l.get_label() for l in lines] leg = ax.legend(lines, labels) Is this a reasonable way of achieving the desired result? thanks, Paul
I want to have two legends (from different axes) positioned right up against on another. Here's a static example, except I want the second legend to be defined relative to the first (if leg is moved, I want leg2 to move as well). I can't seem to figure out the proper bbox_to_anchor and bbox_transform parameters to pass to the second legend() to make this work. # small example ax = plt.subplot(1,1,1) ax2 = ax.twinx() ax.plot([0,1], label='ax1') ax2.plot([1,0], 'r--',label='ax2') leg = ax.legend(loc='lower left', borderaxespad=0, bbox_to_anchor=(.85,.85)) leg2 = ax2.legend(loc='upper left', borderaxespad=0, bbox_to_anchor=(.85,.85)) thanks in advance, Paul Ivanov
Hello, I have a Qt4 application with dynamic embedded matplotlib plotting. The application allows the user to add and remove lines from the plot. This all works well, but I have found that updating the legend is causing a memory leak. What is the proper way to update the legend in an animated/dynamic context? The attached stand alone example exemplifies the problem. On my system, with matplotlib.__version__ '1.0.0' compiled from SVN, the memory slowly increases as the script runs. This does not happen if I remove the ax.legend() call. The del ax.legend_ line seems to have no effect. I tried finding the artists associated with the legend What's the appropriate way to update the legend to avoid this behavior? I just found ax.legend_.remove() but it raises NotImplementedError Thanks, Glenn
On Mon, Sep 6, 2010 at 3:28 PM, Michele De Stefano <mic...@gm...> wrote: > I think the answer is yes (at least for me). A behavior like the one > of ipyhton is fine. Thanks for the answer. If anyone agrees or disagrees, I would like to know. > > Eric, is DreamPie able to run parallel jobs like IPython or not ? > If not, are you thinking to support a behavior like that ? > > I think it is very useful for trying to run parallel jobs > interactively, most of all if you want to test MPI programs. DreamPie doesn't support running parallel jobs. I don't plan to support such a feature in DreamPie - I actually think it should be the job of a shell-independent library. The job of the shell would be to let you interact easily with the library. Thanks for the feedback! Noam
Thank you, JJ, this solves my problems. I have one question to your reply: Jae-Joon Lee wrote: > > col, leg = "b", "test" > errorbar([1,2,3], [1,2,1],xerr=[0.1, 0.1, 0.1], yerr=[0.1, 0.1, 0.1], > fmt='.',color=col) > l2, = plot([],[], "+", color=col) > l2.remove() # remove from the axes > > legend([l2], [leg]) > Does it make a difference whether I remove l2 from the axes or not? I can't see that it is plotting anything at all so I am curious as to what I am missing here.. Cheers, Karianne -- View this message in context: http://old.nabble.com/legend%3A-changing-the-text-colour-tp29614647p29632843.html Sent from the matplotlib - users mailing list archive at Nabble.com.