matplotlib-users Mailing List for matplotlib

On Tue, Nov 13, 2012 at 8:38 AM, David Brunell <qua...@gm...> wrote:
> Hello, I have what I hope is a simple question. When producing a
> figure/plot, I have a window which pops up with the figure inside and a few
> tool buttons along the bottom, including "Zoom to rectangle." Clicking the
> Zoom tool button, I'm presented with a black crosshair to select my zoom
> rectangle. Many of the images I work with are predominantly black; is
> there any way to change the color of the crosshair so as to make it more
> visible? Thanks.
Hi David,
Unfortunately, those widgets are backend specific, so changing them is not
trivial in general, since each toolkit has its own way of specifying the
cursor. With that said, you can try to figure out if there's a way to do it
for your backend `import matplotlib as mpl; mpl.get_backend()` will tell
you which backend you're using, and then you'll need to look in the
relevant source code for where the cursor is define.
If you don't know where your matplotlib code lives, you can the path of the
relevant files using this:
 import matplotlib.backends as b
 import os
 os.path.dirname(b.__file__)
There, you'll find files for all of the backends, and the `cursord`
dictionary in most of them is what specifies how the widgets look. I'm not
sure which toolkits allow one to change the color of the default cursors,
but some of them allow you to even specify your own color images, so it
should be possible.
An alternative, of course, would be to change the colormap you're plotting
with, or add an alpha value to the images you're plotting so that the black
widgets can be seen. Maybe it's inelegant, but looks like the path of least
resistance...
best,
-- 
Paul Ivanov
314 address only used for lists, off-list direct email at:
http://pirsquared.org | GPG/PGP key id: 0x0F3E28F7

In article 
<CAJSg89LEe=HCx...@ma...>,
 Alexey Shamrin <sh...@gm...> 
 wrote:
> Thank you for 1.2.0 release!
> 
> Could you please make it clear that matplotlib requires
> python.org-Python sourceforge.net-NumPy? Telling about it during
> installation would be great.
This is described in three places:
- The description of the file on the download page
- The name of the file on the download page
- The ReadMe file in the binary installer
Note that the official binary installers for numpy and scipy are also 
for python.org python, and as far as I know they do no more than the 
matplotlib installer as far as informing the user of this fact.
It is bdist_mpkg that makes these installers, and it could be better 
about checking compatibility. But that is a known issue.
I don't know about messages about "system python", though that vaguely 
rings a bell as a bdist_mpkg issue.
I'll add information about numpy to the ReadMe for future binary 
installers. Aside from that, I believe I've done everything I reasonably 
can to clarify the requirements for the binary installer.
-- Russell

All,
I am attempting to plot a base map with extents which are outside of the
figure using the following code:
#Map
lon_min = -101.5
lon_max = -94.5
lat_min = -32.5
lat_max = -27.5
m = Basemap(projection='aeqd',llcrnrlat=lat_min,urcrnrlat=lat_max,
 llcrnrlon=lon_min,urcrnrlon=lon_max,lon_0=-97.7328,
lat_0=-30.0906,resolution=None, rsphere=(1737400.0,1737400.0))
 #Read the input image
input_basemap = gdal.Open('Mare_Orientale_Volc_AzEqui.png')
input_band = input_basemap.GetRasterBand(1)
bmap = input_band.ReadAsArray()
 #The bounds of the input image using gdalinfo
LL = (-204690.290, -162184.543)
UR = (200909.710, 176915.457)
I know that I need to use pcolormesh() to get my map visualized. I also
believe that I need to use the transform_scalar function to get from pixel
space to map projected space. My input image is not in Lat/Lon, but in
pixel space. Any suggestions on getting my image to display in projected
space?
Best,
Jay

Hello, I have what I hope is a simple question. When producing a
figure/plot, I have a window which pops up with the figure inside and a few
tool buttons along the bottom, including "Zoom to rectangle." Clicking the
Zoom tool button, I'm presented with a black crosshair to select my zoom
rectangle. Many of the images I work with are predominantly black; is
there any way to change the color of the crosshair so as to make it more
visible? Thanks.

2012年11月13日 Benjamin Root <ben...@ou...>
>
>
> On Tue, Nov 13, 2012 at 6:16 AM, Francesco Montesano <
> fra...@gm...> wrote:
>
>> Dear matplolibers,
>>
>> when dealing with multi-axes plot sometimes would be nice to use
>> figure-wide x and y labels.
>> On the web I've found some suggestion on how to do this, but I found
>> no solution valid in the general case and that integrate in the
>> matplotlib ecosystem.
>> The ideal would be to have a "set_xlabel" and "set_ylabel" method in the
>> Figure class, with the same api of the corresponding Axes methods.
>>
>> As a proof of concept I've written a class derived from Figure , which
>> implements the two methods simply adding a horizontal (vertical) text below
>> (left of) the lowest (leftmost) axes.
>> The class together with a short example is attached.
>> I'm aware that the current implementation is really poor (no integration
>> with tight_layout, the padding must be adjusted by hand, a problem in
>> particular for the y label).
>>
>> The best is to use "self.xaxis.set_label_text(xlabel, fontdict,
>> **kwargs)" as in the Axis set_xlabel (as I gather this create a label that
>> is rendered in the correct position accounting for ticklabels, ticks,
>> tight_layout, etc). To do this one would have to create:
>>
>> - a figure-wide invisible axes that encloses all the other
>> axes/subplots, and whose dimension has to be updated every time a new
>> axis/subplot is added (this should be easily done) with only the label
>> visible. This could also allow to use axis features, like twin axis.
>> - just the required axis (invisible) that hosts the labels. I think
>> that this approach is less demanding computationally, but I don't know how
>> much sense have two axis not attached to axes.
>>
>> Any suggestions/hints on how to implement these methods in a better way
>> is very welcome.
>>
>> If there is no opposition, later in the day I'll submit PR on github with
>> the two new method and see if we can get something out of this idea.
>>
>> Cheers,
>> Francesco
>>
>>
> I am not exactly sure if this is the same as what you are thinking, but
> the axes objects have a "label_outer()" method that would turn on and off
> the visibility of various axis components based on their location in a
> subplot grid. You call it for each axes in a subplot grid.
>
> Cheers!
> Ben Root
>
> Hi Ben,
sorry that I'm not being clear. My scope is to have the a unique x and y
label as in "figure_label.png" instead a x and y label for each outer axes
as in "axes_label.png".
This could be done not writing axes labels and then using a simple text on
the left and bottom, but I think that set_[xy]label method in class Figure
(as the method legend) is much neater.
Besides can improve readability of plots with lots of panels showing the
same quantities.
Is it clearer now?
Francesco

On Tue, Nov 13, 2012 at 6:16 AM, Francesco Montesano <
fra...@gm...> wrote:
> Dear matplolibers,
>
> when dealing with multi-axes plot sometimes would be nice to use
> figure-wide x and y labels.
> On the web I've found some suggestion on how to do this, but I found
> no solution valid in the general case and that integrate in the
> matplotlib ecosystem.
> The ideal would be to have a "set_xlabel" and "set_ylabel" method in the
> Figure class, with the same api of the corresponding Axes methods.
>
> As a proof of concept I've written a class derived from Figure , which
> implements the two methods simply adding a horizontal (vertical) text below
> (left of) the lowest (leftmost) axes.
> The class together with a short example is attached.
> I'm aware that the current implementation is really poor (no integration
> with tight_layout, the padding must be adjusted by hand, a problem in
> particular for the y label).
>
> The best is to use "self.xaxis.set_label_text(xlabel, fontdict, **kwargs)"
> as in the Axis set_xlabel (as I gather this create a label that is rendered
> in the correct position accounting for ticklabels, ticks, tight_layout,
> etc). To do this one would have to create:
>
> - a figure-wide invisible axes that encloses all the other
> axes/subplots, and whose dimension has to be updated every time a new
> axis/subplot is added (this should be easily done) with only the label
> visible. This could also allow to use axis features, like twin axis.
> - just the required axis (invisible) that hosts the labels. I think
> that this approach is less demanding computationally, but I don't know how
> much sense have two axis not attached to axes.
>
> Any suggestions/hints on how to implement these methods in a better way is
> very welcome.
>
> If there is no opposition, later in the day I'll submit PR on github with
> the two new method and see if we can get something out of this idea.
>
> Cheers,
> Francesco
>
>
I am not exactly sure if this is the same as what you are thinking, but the
axes objects have a "label_outer()" method that would turn on and off the
visibility of various axis components based on their location in a subplot
grid. You call it for each axes in a subplot grid.
Cheers!
Ben Root

Dear matplolibers,
when dealing with multi-axes plot sometimes would be nice to use
figure-wide x and y labels.
On the web I've found some suggestion on how to do this, but I found
no solution valid in the general case and that integrate in the
matplotlib ecosystem.
The ideal would be to have a "set_xlabel" and "set_ylabel" method in the
Figure class, with the same api of the corresponding Axes methods.
As a proof of concept I've written a class derived from Figure , which
implements the two methods simply adding a horizontal (vertical) text below
(left of) the lowest (leftmost) axes.
The class together with a short example is attached.
I'm aware that the current implementation is really poor (no integration
with tight_layout, the padding must be adjusted by hand, a problem in
particular for the y label).
The best is to use "self.xaxis.set_label_text(xlabel, fontdict, **kwargs)"
as in the Axis set_xlabel (as I gather this create a label that is rendered
in the correct position accounting for ticklabels, ticks, tight_layout,
etc). To do this one would have to create:
 - a figure-wide invisible axes that encloses all the other
 axes/subplots, and whose dimension has to be updated every time a new
 axis/subplot is added (this should be easily done) with only the label
 visible. This could also allow to use axis features, like twin axis.
 - just the required axis (invisible) that hosts the labels. I think that
 this approach is less demanding computationally, but I don't know how much
 sense have two axis not attached to axes.
Any suggestions/hints on how to implement these methods in a better way is
very welcome.
If there is no opposition, later in the day I'll submit PR on github with
the two new method and see if we can get something out of this idea.
Cheers,
Francesco

I've just run into this problem myself. I think I've tracked down the
offending code to lines 1910-1916 of
/usr/lib/pymodules/pythn2.7/matplotlib/axes.py
this is within the function definition for draw()
-----
if self.axison and not inframe:
 if self._axisbelow:
 self.xaxis.set_zorder(0.5)
 self.yaxis.set_zorder(0.5
 else:
 self.xaxis.set_zorder(2.5)
 self.yaxis.set_zorder(2.5)
-----
In particular, the zorder of 2.5 is being set by lines 1915-1916 (the last
of the lines copied above.
Seems the source of the bug to me, but I have no idea what the procedure is
for getting it logged and fixed.
-Michael Woods