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It sounds like you were using the right approach, you just got a bit lost
on what some of the keyword parameters to annotate, etc do.
Here's an example that should do what you want:
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
fig, ax = plt.subplots()
# Set the axis limits as you wanted...
ax.set_ylim([-0.6, 1.1])
# Set major and minor tick intervals
# We could just set the tick locations manually, but this way you'll keep
the
# same intervals when you zoom/pan/etc.
ax.yaxis.set_major_locator(MultipleLocator(1))
ax.yaxis.set_minor_locator(MultipleLocator(0.1))
# Make the bottom spine "float" instead of being at the bottom of the plot
ax.spines['bottom'].set_position(('data', 0))
# Hide the top and right spines (Similar to your sketch)
for position in ['right', 'top']:
 ax.spines[position].set_visible(False)
# Turn off the top, right, and bottom major and minor ticks (as in your
sketch)
ax.tick_params(which='both', top=False, right=False, bottom=False,
 labelbottom=False)
# Draw a 15 point long arrow that will always be at the top-left corner of
# the axes. The key is that we're specifying a location of (0,1) in
# "axes fraction" coordinates. We then place an empty text string 15
_points_
# above this (the `xytext` parameter controls the amount, `textcoords`
controls
# how it's interpreted). Then, we draw an arrow connecting the top left
corner
# of the axes to the (empty and not drawn) text string.
ax.annotate('', xy=(0,1), xycoords='axes fraction', xytext=(0,15),
 textcoords='offset points', ha='center',
 arrowprops=dict(arrowstyle='<|-', shrinkA=0, shrinkB=0,
 facecolor='black'))
plt.show()
Hope that helps!
-Joe
On Fri, Jun 15, 2012 at 7:34 AM, Asbach, Mark <
mar...@ia...> wrote:
> Hi there,
>
> I'm sorry to ask such a newbie question, but I'd like to format a custom
> box plot and although there are numerous examples on the web and tons of
> docstrings in matplotlib, I'm stuck somehow. My problems center around axes
> / spines. In detail, my problems are:
>
> 1) I want an y-axis on the left that spans from -0.6 to 1.1, ends in an
> arrow, has major ticks at 0 and 1 and minor ticks at [0.1...0.9]
> As far as I understand, there is no option to let spines end in an arrow
> head, so I have to draw the myself. I get the ticks to appear at the right
> positions and the y-range to be as desired - however, the spine line is not
> drawn over the full y-range, but only where there is data in the diagram.
> Also, I copied the arrow annotation code blindly from an older post on this
> list, but do not understand how I can adapt the arrow head to appear at a
> data position (instead of at the corner of the Axes area). One problem is,
> that I get ticks on the right although that spine was disabled.
>
> 2) I want some kind of x-axis at y==0, without ticks and without arrow
> Using some methods on the spines, I can disable the top spine and move the
> bottom spine to zero. However, as with the y-axis, I cannot control from
> where to where the line itself is drawn.
>
> As attachments, you'll find a hand sketch of what my graph should look
> like and matplotlib code that goes nearly all the way.
>
> I would be very happy about a hint on how to fix the problems left.
>
> Thanks an advance,
> Mark
>
>
>
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>

Thanks Ben and Francesco. The zorder option didn't work, I'll use mayavi or
try to make it work as is. And as for setting the z axis limits, I found
that that line has to be placed after all plotting commands in the script.
Benjamin Root-2 wrote:
> 
> Ananduri,
> 
> On Fri, Jun 15, 2012 at 8:47 AM, ananduri <aru...@gm...> wrote:
> 
>>
>> Hello,
>>
>> I have some minor questions regarding matplotlib. I'm using it to make a
>> 3d
>> plot, displaying a surface, it's contour map, a line climbing the surface
>> and its projection onto the contour map.
>>
>> http://old.nabble.com/file/p34015720/landscape_draft.pnglandscape_draft.png
>>
>> As you can see, when the lines cross the contourf, they are somewhat
>> obscured. Before I made the contourf transparent, the lines were blocked,
>> even though they were above the contour plot when I viewed the picture
>> from
>> a different angle. Can this be fixed? I want the lines to appear on top
>> of
>> the contour plot.
>>
>>
> Unfortunately, no. Matplotlib was originally designed as a 2D layering
> renderer. The mplot3d toolkit tries to work within that framework, but in
> the end, each artist object has to be represented by a single 3rd
> dimension
> coordinate (the layer), and so when two artists share bounding box
> regions,
> physically incorrect results will happen. Please see this FAQ:
> 
> http://matplotlib.sourceforge.net/mpl_toolkits/mplot3d/faq.html#my-3d-plot-doesn-t-look-right-at-certain-viewing-angles
> 
> 
> 
>> Also, I am trying to extend the z axis to be lower. This is most of the
>> code
>> I'm using:
>>
>> fig=plt.figure(1)
>> ax=fig.gca(projection='3d')
>>
>> x=np.arange(0,2.5,.02)
>> y=np.arange(0,2.3,.02)
>> x,y=np.meshgrid(x,y)
>>
>> ax.plot_surface(x,y,Z(x,y),alpha=0.3)
>>
>> cset=ax.contourf(x,y,Z(x,y),zdir='z',offset=-2,
>> cmap=plt.cm.jet,levels=np.linspace(0,9,100),alpha=0.5)
>>
>> ax.set_xlabel('x')
>> ax.set_ylabel('y')
>>
>> ax.set_zlim(-2,8) #This is where I try to change the z axis limits.
>>
>> plt.show()
>>
>> I'm excluding the code which plots the lines. ax.set_zlim doesn't do
>> anything; why is this?
>>
> 
> That would depend on which version of matplotlib you are using. The
> v1.1.x
> branch should have that working properly.
> 
> Cheers!
> Ben Root
> 
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> Exclusive live event will cover all the ways today's security and 
> threat landscape has changed and how IT managers can respond. Discussions 
> will include endpoint security, mobile security and the latest in malware 
> threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/
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> 
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