From: Francesco M. <fra...@go...> - 2011-02-01 16:58:39
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Dear all, I'm producing a single figure with subplots arrange in a single columns. They all share the same x range but the y variable change from subplot to subplot In order have a nicer figure I hide the first and the last y label of each subplot in the following way > ytl = subpl.get_ymajorticklabels() > ytl[0].set_visible(False) > ytl[-1].set_visible(False) > It was well in most cases. But I've noticed that in some plot the first and/or the last label remains. In this cases, if I "print ytl", it writes "<a list of n Text yticklabel objects>", where "n" is larger by 1 or 2 than the number of labels shown before I make them invisible. So I end up having some label (nearly) exactly on the upper and/or bottom range of the plot. Is there a way to force the axis to return exactly the number of labels shown in the plot? Thanks in advance, Francesco |
From: Francesco M. <fra...@go...> - 2011-02-04 16:01:44
Attachments:
example.png
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Dear all again, I've tried to play with it again, but I couldn't find a solution for the problem. For clarity I report an example of what each of the subplots looks like: > import numpy as np > import matplotlib.pyplot as plt > mean = np.array([-0.9206394, -0.90127456, -0.91983625, -0.97765539, -1.02991184, -1.02267017, -0.97730167, -0.93715172, -0.94324653, -0.92884379]) > stddev = np.array([0.16351397, 0.15075966, 0.13413909, 0.15404823, 0.13559582, 0.13109754, 0.12128598, 0.11589682, 0.11921571, 0.10866761]) > > ax = plt.figure().add_axes([0.1,0.1,0.8,0.8]) > ax.errorbar(np.arange(10,20)/100., mean, yerr=stddev) > > ax.set_xlim([0.095, 0.195]) > lab = ax.get_ymajorticklabels() > > print lab > for i in lab: > print i > > plt.show() as output of this script I get > <a list of 7 Text yticklabel objects> > Text(0,0,'') > Text(0,0,'') > Text(0,0,'') > Text(0,0,'') > Text(0,0,'') > Text(0,0,'') > Text(0,0,'') In the plot instead I only have only 5 y tick labels, as visible from the attachment. In this case if I set the first and the last label invisible, nothing changes, and if I have other plots under this the plot becomes ugly/unreadable. I hope to have been clearer than in my previous mail. Any suggestion on how to fix or find a workaround in order to get the same number of tick labels as the ones actually plotted. Thank in advance Fra 2011/2/1 Francesco Montesano <fra...@go...>: > Dear all, > > I'm producing a single figure with subplots arrange in a single columns. > They all share the same x range but the y variable change from subplot to > subplot > > In order have a nicer figure I hide the first and the last y label of each > subplot in the following way >> >> ytl = subpl.get_ymajorticklabels() >> ytl[0].set_visible(False) >> ytl[-1].set_visible(False) > > It was well in most cases. But I've noticed that in some plot the first > and/or the last label remains. > In this cases, if I "print ytl", it writes "<a list of n Text yticklabel > objects>", where "n" is larger by 1 or 2 than the number of labels shown > before I make them invisible. > So I end up having some label (nearly) exactly on the upper and/or bottom > range of the plot. > > Is there a way to force the axis to return exactly the number of labels > shown in the plot? > > Thanks in advance, > > Francesco > > > -- personals: mon...@ya..., mon...@ho... (messenger), fra...@go.... work: mon...@mp... http://picasaweb.google.it/franz.bergesund |
From: Paul I. <piv...@gm...> - 2011-02-06 08:17:29
Attachments:
hide-ticklabels.png
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Francesco Montesano, on 2011-02-04 17:01, wrote: > Dear all again, > > I've tried to play with it again, but I couldn't find a > solution for the problem. For clarity I report an example of > what each of the subplots looks like: Hi Francesco, thanks for the clarification, here are two ways to get the look you want. I added some comments to help you understand what was going on before. (The resulting figure is attached, just in case). import numpy as np import matplotlib.pyplot as plt mean=np.array([-0.9206394, -0.90127456, -0.91983625, -0.97765539, -1.02991184, -1.02267017, -0.97730167, -0.93715172, -0.94324653, -0.92884379]) stddev= np.array([0.16351397,0.15075966,0.13413909,0.15404823,0.13559582, 0.13109754,0.12128598,0.11589682,0.11921571,0.10866761]) ax = plt.figure().add_axes([0.1,0.1,0.8,0.8]) ax.errorbar(np.arange(10,20)/100., mean, yerr=stddev) ax.set_xlim([0.095, 0.195]) lab = ax.get_ymajorticklabels() plt.draw() # ticks only get text assigned during a call to draw print lab for i in lab: print i # note that \u2212 is a unicode minus sign # this work for the first draw - relies on l.get_text() returning # nothing for labels which aren't used/drawn - which isn't the # case in general after panning and zooming interactively shown_lab = [l for l in lab if l.get_text()] shown_lab[0].set_visible(False) shown_lab[-1].set_visible(False) ## alternative solution without extra draw(). more robust, can be ## used even after initial draw. #ymin,ymax = ax.get_ylim() #tl = ax.yaxis.get_majorticklocs() #lab[(tl<ymin).sum()].set_visible(False) #lab[-(tl>ymax).sum()-1].set_visible(False) ## hybrid of the two. #ymin,ymax = ax.get_ylim() #tl = ax.yaxis.get_majorticklocs() #shown_lab = [l for l,t in zip(lab,tl) if t>ymin and t<ymax) #shown_lab[0].set_visible(False) #shown_lab[-1].set_visible(False) plt.show() best, -- Paul Ivanov 314 address only used for lists, off-list direct email at: http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 |
From: Jae-Joon L. <lee...@gm...> - 2011-02-06 11:18:58
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For an interactive use, you may use callbacks to update the visibility of ticks automatically. Regards, -JJ import matplotlib.transforms as mtransforms def update_yticks(ax): axis = ax.yaxis interval = axis.get_view_interval() # get visible ticks myticks = [t for t in axis.iter_ticks() \ if mtransforms.interval_contains(interval, t[1])] # make all ticks visible again for mytick in myticks: mytick[0].label1.set_visible(True) # make first tick invisible myticks[0][0].label1.set_visible(False) # make last tick invisible myticks[-1][0].label1.set_visible(False) import matplotlib.pyplot as plt ax = plt.subplot(111) update_yticks(ax) cid = ax.callbacks.connect('ylim_changed', update_yticks) On Sun, Feb 6, 2011 at 5:17 PM, Paul Ivanov <piv...@gm...> wrote: > Francesco Montesano, on 2011-02-04 17:01, wrote: >> Dear all again, >> >> I've tried to play with it again, but I couldn't find a >> solution for the problem. For clarity I report an example of >> what each of the subplots looks like: > > Hi Francesco, > > thanks for the clarification, here are two ways to get the look > you want. I added some comments to help you understand what was > going on before. (The resulting figure is attached, just in case). > > import numpy as np > import matplotlib.pyplot as plt > mean=np.array([-0.9206394, -0.90127456, -0.91983625, -0.97765539, -1.02991184, > -1.02267017, -0.97730167, -0.93715172, -0.94324653, -0.92884379]) > stddev= np.array([0.16351397,0.15075966,0.13413909,0.15404823,0.13559582, 0.13109754,0.12128598,0.11589682,0.11921571,0.10866761]) > > ax = plt.figure().add_axes([0.1,0.1,0.8,0.8]) > ax.errorbar(np.arange(10,20)/100., mean, yerr=stddev) > > ax.set_xlim([0.095, 0.195]) > > lab = ax.get_ymajorticklabels() > plt.draw() # ticks only get text assigned during a call to draw > print lab > for i in lab: > print i # note that \u2212 is a unicode minus sign > > # this work for the first draw - relies on l.get_text() returning > # nothing for labels which aren't used/drawn - which isn't the > # case in general after panning and zooming interactively > shown_lab = [l for l in lab if l.get_text()] > shown_lab[0].set_visible(False) > shown_lab[-1].set_visible(False) > > ## alternative solution without extra draw(). more robust, can be > ## used even after initial draw. > #ymin,ymax = ax.get_ylim() > #tl = ax.yaxis.get_majorticklocs() > #lab[(tl<ymin).sum()].set_visible(False) > #lab[-(tl>ymax).sum()-1].set_visible(False) > > ## hybrid of the two. > #ymin,ymax = ax.get_ylim() > #tl = ax.yaxis.get_majorticklocs() > #shown_lab = [l for l,t in zip(lab,tl) if t>ymin and t<ymax) > #shown_lab[0].set_visible(False) > #shown_lab[-1].set_visible(False) > > plt.show() > > > best, > -- > Paul Ivanov > 314 address only used for lists, off-list direct email at: > http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7 > > -----BEGIN PGP SIGNATURE----- > Version: GnuPG v1.4.10 (GNU/Linux) > > iEYEARECAAYFAk1OWQMACgkQe+cmRQ8+KPekfgCfcY+R1vb2i/l/AoVsFZwsyqCC > ihoAn1uni4kEu4Kq+B0IdCu26Kw1aA9Q > =B6ZO > -----END PGP SIGNATURE----- > > ------------------------------------------------------------------------------ > The modern datacenter depends on network connectivity to access resources > and provide services. The best practices for maximizing a physical server's > connectivity to a physical network are well understood - see how these > rules translate into the virtual world? > http://p.sf.net/sfu/oracle-sfdevnlfb > _______________________________________________ > Matplotlib-users mailing list > Mat...@li... > https://lists.sourceforge.net/lists/listinfo/matplotlib-users > > |