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Hello Eric and Fernando,
thank you very much for your answers. It helped :-/ I think I was a
bit too fast here. Eric, you are precisely right, I should have done
more investigation before. I think this issue (my issue) should be
clarified now. I was just alert by the feedback of other users about
hang-ups, I don't know if it was a good idea to bring this to the
list, though. My apologises. Just had too many hidden hang-ups in my
own threaded Tkinter code.
Talking is cheap :-/
Friedrich
2010年10月10日 Fernando Perez <fpe...@gm...>:
> Two things to note:
>
> - ipython, even in the 0.10 series, uses threads for the Qt, Gtk and
> Wx backends, but *not* for Tk, because python automatically pumps the
> Tk event loop when the console blocks on reading (via the C API
> PyOSInputHook call). So there is exactly *zero* threading added by
> ipython in the specific case of a Tk backend.
This is very interesting, I always asked myself how this works.
> - in the 0.11 ipython series, we abandoned threading altogether (it's
> just too brittle) and moved to a model similar to the Tk one for *all*
> backends, we now use PyOSInputHook with all mpl backends.
>
> hth,
>
> f

Hello,
I needed to use "stem" for complex impulse vectors and found that it
was too much work to make it behave. I therefore wrote "cstem" which
is intended for complex impulse vectors. It takes x (optional) and z
vectors, and a small number of special keyword parameters -- remaining
keywords are handed off to "plot" during plotting.
I've tried making it as similar to "stem" as I found useful, but it is
not a drop-in replacement. It is written as a function, not an axis
method, but if found useful to others, changing it over should not be
difficult.
The code has ReST docstring including example of use:
 >>> z = np.random.uniform(size=10) + 1j*np.random.uniform(size=10)
 >>> cstem(z)
 or, using explicit x axis and keeping handles
 >>> x = np.r_[1:3:10j]
 >>> r_mark, i_mark, r_line, i_line, baseline = cstem(x, z)
License: anything BSD-ish that is broadly used in matplotlib already.
Enjoy! Comments/suggestions welcome.
-- 
Tom Grydeland
 <Tom.Grydeland@(gmail.com)>

I push the new example in r8740.
Thanks.
-JJ
On Sat, Oct 9, 2010 at 12:15 AM, Stan West <sta...@nr...> wrote:
> Greetings. I initially encountered some difficulty following the
> multiple_yaxis_with_spines example, especially regarding what the functions
> make_patch_spines_invisible and make_spine_invisible were doing to the par2
> axes and why. For example, make_spine_invisible is really making one of the
> spines visible. I'd like to offer the attached modifications, which mainly
> simplify the manipulations and add explanatory comments. Minor changes
> include removing access to a global variable in make_patch_spines_invisible
> and removing a duplicated set_xlabel. The generated figure is unchanged.
>
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