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Showing 4 results of 4

From: herbie13 <g.h...@du...> - 2011年03月14日 13:06:04
Hello,
I basically have a Chi-Squared distribution that is dependent on 3
variables.
eg. X2(x, y, z)
What I would like to do is be able to plot the chi-squared + 1 surface in
3-dimensions.
eg. I would like to have the three axes as x, y and z. and then have a
surface (its going to look like a closed blob effectively) that maps the
chi-squared plus one surface.
I have no idea how to do this though. Is it possible? any ideas?
-- 
View this message in context: http://old.nabble.com/3d-Surface-Contour-Plot-tp31143849p31143849.html
Sent from the matplotlib - users mailing list archive at Nabble.com.
From: Jae-Joon L. <lee...@gm...> - 2011年03月14日 07:14:38
For this to work correctly, you need to manually keep two axes in sync
(you can use a callback). Also note that this approach cannot be used
with aspect=1 & adjustable=bbox.
Another way is to use axes_grid1 toolkit.
Here is the modified version of your script w/ axes_grid1.
Regards,
-JJ
import numpy as np
import matplotlib
import matplotlib.colorbar as cb
import matplotlib.pyplot as plt
y = np.reshape(np.arange(0, 1000000, 1), (20000, 50))
test = 'hot'
f1 = plt.figure(1)
f1.patch.set_facecolor('#c0c0c0')
import mpl_toolkits.axes_grid1 as axes_grid1
# use axes_grid1.host_axes
ax1 = axes_grid1.host_axes([0.09, 0.15, 0.82, 0.80])
axc = f1.add_axes([0.09, 0.05, 0.82, 0.05])
im1 = ax1.imshow(y, cmap=test, aspect='auto', origin='lower')
cb.Colorbar(axc, im1, orientation='horizontal')
# use twin() not twinx()
ax2 = ax1.twin()
# make ticklabels on the top invisible
ax2.axis["top"].toggle(ticklabels=False)
fmtr = matplotlib.ticker.FuncFormatter(lambda x,pos: "%.2f"% (x*2,))
ax2.yaxis.set_major_formatter(fmtr)
plt.show()
On Sat, Mar 12, 2011 at 9:01 AM, Thomas Brezinski
<th...@ar...> wrote:
> Jason Stone, on 2011年02月18日 14:39, wrote:
>> Good afternoon all,
>> One last matplotlib question for the group for today. On one of my GUI
>> plots, I'm calling imshow on an array of data (to display it in the same
>> way
>> MATLAB's imagesc command does). I'd like to add a second y-axis to the
>> right side of the plot that is completely dependent on the values on the
>> primary y-axis. Essentially, for each y-axis tick point, I'll put the
>> y-axis 'value' into a formula and then put the result on the second
>> y-axis.
>> I did this in MATLAB by essentially overlaying a second set of axes over
>> the plot, but I haven't found the exact way to do it with matplotlib yet.
>> I've seen a few examples online, but they all use the second overlaid
>> plot
>> to actually plot new data - I wouldn't be doing this.
>> Would I need to use the twinx (or twiny) function?
>> Are there examples of this on the web that I haven't found that somebody
>> could point me towards?
>
> Hi Jason,
>
> here's an example that does what you want, using e^x as the
> formula, change the paramter to fmtr to suit your needs:
>
> ax = plt.subplot(1,1,1)
> ax.plot(np.sin(np.linspace(0,np.pi)))
> ax2 = ax.twinx()
> ax2._sharey = ax # share both x and y
> fmtr = mpl.ticker.FuncFormatter(lambda x,pos: "%.2f"%np.exp(x))
> ax2.yaxis.set_major_formatter(fmtr)
> plt.draw()
>
> best,
> --
> Paul Ivanov
> 314 address only used for lists, off-list direct email at:
> http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7
>
>
> Paul,
> I am currently doing something very similar and was hoping I could ask for a
> little clarification. I want to have two y axes where the ticks are in the
> same locations and the 2nd y-axis labels are just twice the 1st y-axis
> labels. When I implement your example, I don't quite understand how to
> ensure the ticks are at the same locations. Also, when the data changes to a
> new image, the 1st y-axis updates but the 2nd y-axis does not. Is there a
> convenient way to force both to update each time, or does the figure need to
> be cleared and essentially built from scratch each time.
>
> for example, with the following code:
>
> import numpy as np
> import matplotlib
> import matplotlib.colorbar as cb
> import matplotlib.pyplot as plt
>
> y = np.reshape(np.arange(0, 1000000, 1), (20000, 50))
> test = 'hot'
> f1 = plt.figure(1)
> f1.patch.set_facecolor('#c0c0c0')
> ax1 = f1.add_axes([0.09, 0.15, 0.82, 0.80])
> axc = f1.add_axes([0.09, 0.05, 0.82, 0.05])
> im1 = ax1.imshow(y, cmap=test, aspect='auto', origin='lower')
> cb.Colorbar(axc, im1, orientation='horizontal')
> ax2 = ax1.twinx()
> ax2._sharey = ax1 # share both x and y
> fmtr = matplotlib.ticker.FuncFormatter(lambda x,pos: "%.2f"%np.exp(x))
> ax2.yaxis.set_major_formatter(fmtr)
> plt.show()
>
> The ticks on the right are obviously at different locations compared to the
> left ticks. Also, if imshow was to be called a new array of data, the ticks
> on the right would remain the same. So is there an easy way to force the
> locations to be the same, and is there an easy way force the right y-axis to
> update each time? Thank you very much for your time and help.
>
> -Thomas
>
>
>
>
> -----BEGIN PGP SIGNATURE-----
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>
> iEYEARECAAYFAk1kEfIACgkQe+cmRQ8+KPe0vACfSMtFJ9KSRwqU34j6QevaSZqD
> qM0An2WHMyKisrwDIyKaCcuygrsWvZbX
> =OIU1
> -----END PGP SIGNATURE-----
>
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From: John F. G. <joh...@gm...> - 2011年03月14日 02:49:49
I would like to construct a 3d plot consisting of several 2d quiver plots on
orthogonal, intersecting planes. Is this possible with matplotlib? In matlab
I do it by construct several 2d graph and then reorienting them in the 3d
space using the 'rotate' function. E.g. 
xaxis = [1 0 0];
h = quiver('v6', z, y, w, v, 'k');
rotate(h, xaxis, 90, [0 0 0]);
This produces a 2d quiver plot of [v,w](y,z) oriented along the y,z axes of
the 3d space, and then I do the same for x,y and x,z quiver plots.
Any ideas for matplotib 3d? Thanks!
John Gibson
-- 
View this message in context: http://old.nabble.com/orienting-2d-plots-in-3d-tp31140854p31140854.html
Sent from the matplotlib - users mailing list archive at Nabble.com.
From: Nicolas S. <sch...@gm...> - 2011年03月14日 01:18:52
Thanks much for the reply!
I'll try your advice as soon as I can.
BTW, I don't think this is a Solaris-related problem.
If you look at the pointers in my original post, the same error can
happen on other arch (I confess it can be for other reasons though).
-n
On Sun, Mar 13, 2011 at 1:03 PM, Jouni K. Seppänen <jk...@ik...> wrote:
> Nicolas SCHEFFER <sch...@gm...> writes:
>
>> I didn't get much reply on this issue, so I'm just trying to resurrect
>> the question.
>
> Probably not many devs using Solaris, so no-one has been able to
> reproduce this.
>
>>> #12 0xfffffd7ff4a22fd8 in py_to_agg_transformation_matrix
>>> (obj=0x774380, errors=<value optimized out>) at
>>> src/agg_py_transforms.cpp:22
>>> #13 0xfffffd7ff4a32e7c in _path_module::update_path_extents
>>> (this=<value optimized out>, args=...) at src/path.cpp:380
>
> So it's in transforms-related code, but we can't see the locals. First
> I'd try to recompile without optimizations and (hoping it still crashes)
> inspect the local variables in these frames in gdb. Or maybe make the
> functions print out their arguments and any other relevant locals.
>
> --
> Jouni K. Seppänen
> http://www.iki.fi/jks
>
>
> ------------------------------------------------------------------------------
> Colocation vs. Managed Hosting
> A question and answer guide to determining the best fit
> for your organization - today and in the future.
> http://p.sf.net/sfu/internap-sfd2d
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Showing 4 results of 4

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