matplotlib-users Mailing List for matplotlib

On Wed, Sep 7, 2011 at 3:13 PM, Matthew Koichi Grimes <mk...@cs...>wrote:
> Thanks Ben, I for one would be very interested in any workarounds you might
> find that don't require an upgrade from 1.0.1.
>
> -- Matt
>
>
Ok, looks like the hiding of the 3d axes was a feature added after the v1.0
release (but before I started working on mplot3d). This patch should enable
the basic feature without interfering with existing functions. To hide the
axes, you would have to set the private member "_axis3don" to False, like
so:
ax = plt.gca(projection='3d')
ax._axis3don = False
If you do it this way, then you will get what you want now, and your code
will still be compatible with mplot3d when you upgrade (although the
preferred method would be to call set_axis_on() or set_axis_off()).
I hope that helps!
Ben Root

Thanks Ben, I for one would be very interested in any workarounds you might
find that don't require an upgrade from 1.0.1.
-- Matt
On Wed, Sep 7, 2011 at 4:04 PM, Benjamin Root <ben...@ou...> wrote:
> On Wed, Sep 7, 2011 at 2:43 PM, Joe Kington <jki...@wi...> wrote:
>
>> Interestingly, things work perfectly with the latest build from guithub.
>> Presumably the bug was fixed already?
>>
>>
> Uhm, sure! I totally intended for that nasty bug to be fixed for the
> upcoming release... <_<
>
> Seriously, though, I made many changes to mplot3d as a part of my
> refactoring efforts. I would not be surprised if things magically break or
> get fixed because of it. I am glad you can confirm that the latest build
> works. I will take a peek at the v1.0.1 branch and see if there is an
> obvious fix for them.
>
> Ben Root
>
>

On Wed, Sep 7, 2011 at 2:43 PM, Joe Kington <jki...@wi...> wrote:
> Interestingly, things work perfectly with the latest build from guithub.
> Presumably the bug was fixed already?
>
>
Uhm, sure! I totally intended for that nasty bug to be fixed for the
upcoming release... <_<
Seriously, though, I made many changes to mplot3d as a part of my
refactoring efforts. I would not be surprised if things magically break or
get fixed because of it. I am glad you can confirm that the latest build
works. I will take a peek at the v1.0.1 branch and see if there is an
obvious fix for them.
Ben Root

Interestingly, things work perfectly with the latest build from guithub.
Presumably the bug was fixed already?
On Wed, Sep 7, 2011 at 2:40 PM, Matthew Koichi Grimes <mk...@cs...>wrote:
> I tried Joe's code, with the call to ax.set_axis_off() moved to right after
> add_subplot(), as Ben suggested. The axes are still not disappearing, nor do
> they disappear when I interact with it (by rotating the plot).
>
> -- Matt
>
>
> On Wed, Sep 7, 2011 at 3:21 PM, Benjamin Root <ben...@ou...> wrote:
>
>> On Wed, Sep 7, 2011 at 2:14 PM, Joe Kington <jki...@wi...> wrote:
>>
>>> This no longer seems to work with matplotlib 1.0.1.
>>>
>>> As a quick example:
>>>
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> from mpl_toolkits.mplot3d import Axes3D
>>>
>>> fig = plt.figure()
>>> ax = fig.add_subplot(111, projection='3d')
>>>
>>> x,y,z,c = np.random.random((4,10))
>>> ax.scatter(x, y, z, c=c)
>>> ax.set_axis_off()
>>>
>>> plt.show()
>>>
>>> The attached .png shows the result on my system... Is this a bug, or am I
>>> doing something strange?
>>>
>>> Thanks!
>>> -Joe
>>>
>>>
>> Hmmm, try putting that call right after the add_subplot() call. I don't
>> have time to test it out right now, but I wonder if the axes are being drawn
>> once prior to the call to set_axis_off(). I would also be interested to
>> know if the axes disappear when you interact with it.
>>
>> Ben Root
>>
>>
>

I tried Joe's code, with the call to ax.set_axis_off() moved to right after
add_subplot(), as Ben suggested. The axes are still not disappearing, nor do
they disappear when I interact with it (by rotating the plot).
-- Matt
On Wed, Sep 7, 2011 at 3:21 PM, Benjamin Root <ben...@ou...> wrote:
> On Wed, Sep 7, 2011 at 2:14 PM, Joe Kington <jki...@wi...> wrote:
>
>> This no longer seems to work with matplotlib 1.0.1.
>>
>> As a quick example:
>>
>> import numpy as np
>> import matplotlib.pyplot as plt
>> from mpl_toolkits.mplot3d import Axes3D
>>
>> fig = plt.figure()
>> ax = fig.add_subplot(111, projection='3d')
>>
>> x,y,z,c = np.random.random((4,10))
>> ax.scatter(x, y, z, c=c)
>> ax.set_axis_off()
>>
>> plt.show()
>>
>> The attached .png shows the result on my system... Is this a bug, or am I
>> doing something strange?
>>
>> Thanks!
>> -Joe
>>
>>
> Hmmm, try putting that call right after the add_subplot() call. I don't
> have time to test it out right now, but I wonder if the axes are being drawn
> once prior to the call to set_axis_off(). I would also be interested to
> know if the axes disappear when you interact with it.
>
> Ben Root
>
>

I see the same thing here (from within ipython -pylab), and moving the 
ax.set_axis_off() immediately after the add_subplot call doesn't 
change anything. Interacting with the plot doesn't change anything 
either.
Ethan
On Sep 7, 2011, at 1:21 PM, Benjamin Root wrote:
> On Wed, Sep 7, 2011 at 2:14 PM, Joe Kington <jki...@wi...> wrote:
> This no longer seems to work with matplotlib 1.0.1.
>
> As a quick example:
>
> import numpy as np
> import matplotlib.pyplot as plt
> from mpl_toolkits.mplot3d import Axes3D
>
> fig = plt.figure()
> ax = fig.add_subplot(111, projection='3d')
>
> x,y,z,c = np.random.random((4,10))
> ax.scatter(x, y, z, c=c)
> ax.set_axis_off()
>
> plt.show()
>
> The attached .png shows the result on my system... Is this a bug, or 
> am I doing something strange?
>
> Thanks!
> -Joe
>
>
> Hmmm, try putting that call right after the add_subplot() call. I 
> don't have time to test it out right now, but I wonder if the axes 
> are being drawn once prior to the call to set_axis_off(). I would 
> also be interested to know if the axes disappear when you interact 
> with it.
>
> Ben Root
>
> ------------------------------------------------------------------------------
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> Virtualization increases hardware utilization and delivers a new 
> level of
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On Wed, Sep 7, 2011 at 2:14 PM, Joe Kington <jki...@wi...> wrote:
> This no longer seems to work with matplotlib 1.0.1.
>
> As a quick example:
>
> import numpy as np
> import matplotlib.pyplot as plt
> from mpl_toolkits.mplot3d import Axes3D
>
> fig = plt.figure()
> ax = fig.add_subplot(111, projection='3d')
>
> x,y,z,c = np.random.random((4,10))
> ax.scatter(x, y, z, c=c)
> ax.set_axis_off()
>
> plt.show()
>
> The attached .png shows the result on my system... Is this a bug, or am I
> doing something strange?
>
> Thanks!
> -Joe
>
>
Hmmm, try putting that call right after the add_subplot() call. I don't
have time to test it out right now, but I wonder if the axes are being drawn
once prior to the call to set_axis_off(). I would also be interested to
know if the axes disappear when you interact with it.
Ben Root

On Wed, Sep 7, 2011 at 1:34 PM, Matthew Koichi Grimes <mk...@cs...>wrote:
> How can I make a 3D plot without showing the axes?
>
> When plotting a 3d plot, Matplotlib not only draws the x, y, and z
> axes, it also draws light gray grids on the x-y, y-z, and x-z planes.
> I would like to draw a "free-floating" 3D graph, with none of these
> elements. My matplotlib.__version__ is 1.0.1.
>
> Stuff I've tried:
>
> # Doesn't work; this hides the plot, not the axes
> my_3d_axes.set_visible(False)
>
> # Doesn't do anything. Also, there's no get_zaxis() function.
> my_3d_axes.get_xaxis().set_visible(False)
> my_3d_axes.get_yaxis().set_visible(False)
>
> -- Matt
>
>
Matt,
Try "my_3d_axes.set_axis_off()". I should probably override set_visible()
to work as expected...
Ben Root

How can I make a 3D plot without showing the axes?
When plotting a 3d plot, Matplotlib not only draws the x, y, and z
axes, it also draws light gray grids on the x-y, y-z, and x-z planes.
I would like to draw a "free-floating" 3D graph, with none of these
elements. My matplotlib.__version__ is 1.0.1.
Stuff I've tried:
# Doesn't work; this hides the plot, not the axes
my_3d_axes.set_visible(False)
# Doesn't do anything. Also, there's no get_zaxis() function.
my_3d_axes.get_xaxis().set_visible(False)
my_3d_axes.get_yaxis().set_visible(False)
-- Matt

Hi,
As the subject shows, I am trying to create a custom ticker (class??) that
has pretty formatted log tick.
Instead of just 10^-5, 10^-5, etc, is something more like
[1-10^-2, 1-10^-3, 1-10^-4] etc
I am histogram'n a set of data that is very close to 1, basically ranging
from 0.990 and 0.9922, but mostly being centered on 0.9921. I would love to
see meaningful labels.
Any ideas?
-- 
View this message in context: http://old.nabble.com/1-10%5E-1-Custom-Log-Ticker-tp32414832p32414832.html
Sent from the matplotlib - users mailing list archive at Nabble.com.

Jae-Joon,
Thanks! That worked perfectly.
Brad
On Tue, Sep 6, 2011 at 6:46 PM, Jae-Joon Lee <lee...@gm...> wrote:
> In matplotlib, patches have two colors; facecolor and edgecolor.
> So, try something like this
>
> arrowprops=dict(facecolor=((0.549,0.176,0.0156)),
> edgecolor=(0.549,0.176,0.0156),
> shrink=0.02,width=1,headwidth=6,frac=0.05),
>
> Regards,
>
> -JJ
>
>
> On Wed, Sep 7, 2011 at 10:35 AM, Brad Malone <bra...@gm...>
> wrote:
> > Hi, I am trying to draw a brown arrow to a particular part of my figure
> but
> > am having some difficulty. The code I'm currently using is something
> like:
> >>
> >> annotate('notice
> >> this',xy=(119.628,-7.9158),xytext=(0.8,0.5),textcoords='axes fraction'
> >>
> >>
> ,arrowprops=dict(facecolor=((0.549,0.176,0.0156)),shrink=0.02,width=1,headwidth=
> >>
> >>
> 6,frac=0.05),fontsize=12,horizontalalignment='right',verticalalignment='top',color=((0.549,0.176,0.0156)))
> >
> > However, when I do this it only makes the HEAD of the arrow brown, while
> the
> > body of the arrow is still black. What am I missing?
> > Lastly (and unrelated to the topic) when I insert such a figure in Latex
> it
> > looks fine in my later-generated PDF. But if I increase the fontsize part
> of
> > the figure gets cut off. What's the best way to fix this? In the past I
> > would usually just toy around and mess with the BoundingBox in the *eps
> > file, but I wondered if there was a more legitimate way.
> > Thanks for the help! I appreciate it.
> > Brad
> >
> ------------------------------------------------------------------------------
> > Using storage to extend the benefits of virtualization and iSCSI
> > Virtualization increases hardware utilization and delivers a new level of
> > agility. Learn what those decisions are and how to modernize your storage
> > and backup environments for virtualization.
> > http://www.accelacomm.com/jaw/sfnl/114/51434361/
> > _______________________________________________
> > Matplotlib-users mailing list
> > Mat...@li...
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >
> >
>

In matplotlib, patches have two colors; facecolor and edgecolor.
So, try something like this
 arrowprops=dict(facecolor=((0.549,0.176,0.0156)),
 edgecolor=(0.549,0.176,0.0156),
 shrink=0.02,width=1,headwidth=6,frac=0.05),
Regards,
-JJ
On Wed, Sep 7, 2011 at 10:35 AM, Brad Malone <bra...@gm...> wrote:
> Hi, I am trying to draw a brown arrow to a particular part of my figure but
> am having some difficulty. The code I'm currently using is something like:
>>
>> annotate('notice
>> this',xy=(119.628,-7.9158),xytext=(0.8,0.5),textcoords='axes fraction'
>>
>> ,arrowprops=dict(facecolor=((0.549,0.176,0.0156)),shrink=0.02,width=1,headwidth=
>>
>> 6,frac=0.05),fontsize=12,horizontalalignment='right',verticalalignment='top',color=((0.549,0.176,0.0156)))
>
> However, when I do this it only makes the HEAD of the arrow brown, while the
> body of the arrow is still black. What am I missing?
> Lastly (and unrelated to the topic) when I insert such a figure in Latex it
> looks fine in my later-generated PDF. But if I increase the fontsize part of
> the figure gets cut off. What's the best way to fix this? In the past I
> would usually just toy around and mess with the BoundingBox in the *eps
> file, but I wondered if there was a more legitimate way.
> Thanks for the help! I appreciate it.
> Brad
> ------------------------------------------------------------------------------
> Using storage to extend the benefits of virtualization and iSCSI
> Virtualization increases hardware utilization and delivers a new level of
> agility. Learn what those decisions are and how to modernize your storage
> and backup environments for virtualization.
> http://www.accelacomm.com/jaw/sfnl/114/51434361/
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
>

Hi, I am trying to draw a brown arrow to a particular part of my figure but
am having some difficulty. The code I'm currently using is something like:
annotate('notice
> this',xy=(119.628,-7.9158),xytext=(0.8,0.5),textcoords='axes fraction'
>
> ,arrowprops=dict(facecolor=((0.549,0.176,0.0156)),shrink=0.02,width=1,headwidth=
>
> 6,frac=0.05),fontsize=12,horizontalalignment='right',verticalalignment='top',color=((0.549,0.176,0.0156)))
However, when I do this it only makes the HEAD of the arrow brown, while the
body of the arrow is still black. What am I missing?
Lastly (and unrelated to the topic) when I insert such a figure in Latex it
looks fine in my later-generated PDF. But if I increase the fontsize part of
the figure gets cut off. What's the best way to fix this? In the past I
would usually just toy around and mess with the BoundingBox in the *eps
file, but I wondered if there was a more legitimate way.
Thanks for the help! I appreciate it.
Brad

On Wed, Sep 7, 2011 at 12:47 AM, Jeffrey Blackburne
<jbl...@al...> wrote:
> It would be nice to have. Since the patch edge seemed to be using a "round" style and I wanted "miter", my workaround was just to use a separate step plot to overlay the outline. But for more general cases (e.g., a bar plot not created from a histogram or if I wanted a "bevel" style), I'm not sure how I would do it.
>
> Thanks,
> Jeff
>
I also agree that this needs to be supported.
Meanwhile, a workaround is to use the patheffects module.
For example,
from matplotlib.patheffects import Stroke
b = bar([0, 1, 2], [1, 0.5, 2], linewidth=10, fc="none")
for p in b:
 p.set_path_effects([Stroke(joinstyle="miter")])
-JJ

On 09/06/2011 12:55 PM, Paul Hobson wrote:
> On Tue, Sep 6, 2011 at 12:58 PM, Benjamin Root<ben...@ou...> wrote:
>>
>> I don't know the full details, but the idea was that we didn't want to have
>> SciPy as a dependency, so mlab was used to replicate many of the functions
>> found in SciPy. I don't know why the calling conventions are different,
>> though.
>>
>> Ben Root
>
> Apologies for drifting off-topic. I understand the desire to not
> require scipy, but how likely is that to change? I've written a BCa
> bootstrapper[1] for boxplots, but it needs scipy, so I can't
> contribute it back to the community.
If you are asking whether matplotlib will ever depend on scipy, the 
answer is "no", not in any future I can foresee. Its purpose is 
plotting, not calculating. There are some simple deviations from this 
mission--spectral plots and histograms, for example--but they depend 
only on numpy. Maybe your BCa code can be contributed to scipy?
Eric
>
> [1] - http://staff.ustc.edu.cn/~zwp/teach/Stat-Comp/Efron_Bootstrap_CIs.pdf
>
>
> Cheers,
> -paul
>
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