matplotlib-devel Mailing List for matplotlib

On Wed, Oct 6, 2010 at 3:45 PM, braingram <bra...@gm...> wrote:
> I fiddled around with the mplot3d axes3d panning today with some
> useful results. I've never submitted a patch before so please let me
> know if I did so incorrectly.
>
> On a related note, I noticed that middle mouse click+drags were not
> triggering 'motion_notify_event' events with the mac osx backend.
> However, when I Option(Alt) left mouse click+dragged The events were
> being triggered. I'm not sure if this is a osx thing or something to
> do with how the backend is passing on the event.
>
>
Thanks for this, but if I recall, the panning feature was disabled because
of problems with (not) clipping the image outside the viewing area (which is
noticeable when doing subplots). Which backends have you tested this for?
Note, I haven't time to test patches to mplot3d for another 2 weeks.
As an additional request, the mouse_init() function should have another
keyword argument added for pan_btn=2, and then use that to initialize
self._pan_btn in the function. Then, instead of checking if the button
number is equal to 2, it should compare against self._pan_btn.
Ben Root

Hello,
I apologize in advance if this is not an appropriate question for the list.
I have relatively small project that I am stuck on a few (probably
small) points. Is anyone here is interested in earning a modest
consultation fee to "hold my hand" through the rough patches?
If so, please e-mail me directly -- lounds { } gmail -- and I will
send you additional details.
Thank you,
Jeremy

I fiddled around with the mplot3d axes3d panning today with some
useful results. I've never submitted a patch before so please let me
know if I did so incorrectly.
On a related note, I noticed that middle mouse click+drags were not
triggering 'motion_notify_event' events with the mac osx backend.
However, when I Option(Alt) left mouse click+dragged The events were
being triggered. I'm not sure if this is a osx thing or something to
do with how the backend is passing on the event.

"""
Demonstrates that, as of v. 1.0.0, Axes.autoscale_view always uses tight 
scaling when all children are images, regardless of the passed *tight* 
parameter. Effectively, tight=False acts like tight=None.
"""
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick
field = np.array([[0, 1], [1, 0]]) # image data
extent = l, r, b, t = (-1.5, 1.5, -1.5, 1.5) # Extents will lie between ticks.
tight_seq = (None, False, True) # values of *tight* to test
# Make two rows and a column of subplots for each *tight* value.
fig, axes = plt.subplots(2, len(tight_seq))
for ax in axes.flat: # In all subplots, 
 ax.imshow(field, extent=extent) # show the image
 ax.xaxis.set_major_locator(mtick.MultipleLocator(1)) # and set locators.
 ax.yaxis.set_major_locator(mtick.MultipleLocator(1))
for ax in axes[1]: # In the second row, 
 ax.plot([l, r], [b, t], 'g-') # plot a line across the image.
for ax_row in axes:
 for (ax, tight) in zip(ax_row, tight_seq): # Apply each *tight* value
 ax.autoscale_view(tight=tight) # to the subplot...
 if ax.is_first_row():
 ax.set_title('tight = %s' % tight) # and title.
plt.show()