hide labels

Community matplotlib-users
1

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 “”, 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
2

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 <franz.bergesund@...982...>:

example.png
example.png812×612 13.6 KB

···

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
>", 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: montyfra@...174..., monte_fra@...32... (messenger),
franz.bergesund@...3264...
work: montefra@...2911...

http://picasaweb.google.it/franz.bergesund

3

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,

hide-ticklabels.png

···

--
Paul Ivanov
314 address only used for lists, off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

4

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 <pivanov314@...287...> 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

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