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I am creating a scatter plot using pyplot.scatter(), and adding a colorbar
via pyplot.colorbar().  The result is very nice, except that there is a
large amount of empty space between the right-hand edge of the axes and the
figure window.  When I adjust the right-hand margin using something like         
pyplot.subplots_adjust(right=0.95), the right-hand margin is in fact
reduced, but the colorbar remains in the same location and is consequently
inside the axes.  Any advice will be appreciated.
-- 
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Matthias Michler wrote:
> Hello list,
>
> I'm not an expert in axes3d, but in case the feature which Nicolas requested 
> is not possible in an easy manner up to now, I propose an additional kwarg 
> for axes3d.Axes3D.contour. Something like *offset*. If offset is None the 
> z-values of the contour lines corresponds to given Z and otherwise offset is 
> used for the z-values of the contour lines.
> I attached a changed axes3d.py and a patch against current svn. The result is 
> illustrated in the contour3d_demo.png.
>
> Could any of the experts have a look at it and tell me if this could be 
> useful, please?
>
> Thanks in advance for any comments.
>
> Kind regards
> Matthias 
>
> On Wednesday 30 September 2009 19:22:42 Nicolas Bigaouette wrote:
>   
>> Hi,
>> I have a nice plot_surface() using mplot3d (see attachement).
>>
>> I'd like to project the surface on the axis xoy, xoz and yoz with a
>> contour, similar to this figure:
>> http://homepages.ulb.ac.be/~dgonze/INFO/matlab/fig19.jpg
>>
>> Is it possible using matplotlib and mplot3d?
>>
>> Thanx!
>>     
>
>   
Hi Matthias,

I committed your patch to a github branch of MPL, but I'll let Reinier
actually commit something based on this to MPL.
http://github.com/astraw/matplotlib/tree/dev/michler-3d-contourf-offsets

-Andrew

On Fri, Oct 9, 2009 at 10:41 AM, Renato Alves <rj...@ig...>wrote:

> Hi everyone,
>
> I've been using matplotlib for a while but mostly using the pyplot
> functions and going as far as changing their initial input parameters.
>
> Now I need to make a boxplot and include names on the X axis as opposed
> to the default numbers.
>
> I've searched extensively on the docs and using google but I reached a
> dead end. So, could someone point me in the direction of how can I
> change the plot to use names instead of numbers on the x axis (vertical
> boxplot) or y axis (horizontal boxplot)?
>
> Thanks,
> Renato
>
>
> ------------------------------------------------------------------------------
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>


In Ipython -pylab

I[1]: a = np.random.rand(10)
I[3]: b = np.random.rand(10)
I[4]: boxplot([a,b], positions=[1,2])
I[5]: locs, labels = xticks([1,2], ['a', 'b'])


#for fine-tuning

setp(labels, 'rotation', 'horizontal')
xticklabels = getp(gca(), 'xticklabels')
yticklabels = getp(gca(), 'yticklabels')
setp(xticklabels, fontsize=14, weight='bold')
setp(yticklabels, fontsize=14, weight='bold')

Cheers :)

-- 
Gökhan

Hi everyone,

I've been using matplotlib for a while but mostly using the pyplot
functions and going as far as changing their initial input parameters.

Now I need to make a boxplot and include names on the X axis as opposed
to the default numbers.

I've searched extensively on the docs and using google but I reached a
dead end. So, could someone point me in the direction of how can I
change the plot to use names instead of numbers on the x axis (vertical
boxplot) or y axis (horizontal boxplot)?

Thanks,
Renato

I applied the patch to the tarball and built. It works perfectly.
Your responsiveness is very impressive.
Thanks,

Yann

On 10/09/2009 05:27 PM, Michael Droettboom wrote:
> Thanks.  This is definitely a bug.  I just fixed it in SVN r7858.
>
> http://matplotlib.svn.sourceforge.net/viewvc/matplotlib?view=rev&revision=7858 
>
>
> Unfortunately, this requires a recompile.  You can build from SVN, or 
> download the 0.99.1 tarball and manually apply the above patch.
>
> Mike
>
> Yann Goudard wrote:
>> Hi,
>>
>> I notice hatch is not drawn correctly when I zoom in axes.
>>
>> #!/usr/bin/env python
>> import matplotlib.pyplot as plt
>> from matplotlib.patches import Rectangle
>>
>> axes = plt.subplot(111)
>> axes.add_patch(Rectangle((0, 0), 1, 1, fill=False, hatch="/"))
>> plt.show()
>>
>> Is there a way to fix it ?
>>
>> Regards,
>>
>> Yann
>>
>>
>>
>> ------------------------------------------------------------------------------ 
>>
>> Come build with us! The BlackBerry(R) Developer Conference in SF, CA
>> is the only developer event you need to attend this year. Jumpstart your
>> developing skills, take BlackBerry mobile applications to market and 
>> stay ahead of the curve. Join us from November 9 - 12, 2009. Register 
>> now!
>> http://p.sf.net/sfu/devconference
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

Thanks.  This is definitely a bug.  I just fixed it in SVN r7858.

http://matplotlib.svn.sourceforge.net/viewvc/matplotlib?view=rev&revision=7858

Unfortunately, this requires a recompile.  You can build from SVN, or 
download the 0.99.1 tarball and manually apply the above patch.

Mike

Yann Goudard wrote:
> Hi,
>
> I notice hatch is not drawn correctly when I zoom in axes.
>
> #!/usr/bin/env python
> import matplotlib.pyplot as plt
> from matplotlib.patches import Rectangle
>
> axes = plt.subplot(111)
> axes.add_patch(Rectangle((0, 0), 1, 1, fill=False, hatch="/"))
> plt.show()
>
> Is there a way to fix it ?
>
> Regards,
>
> Yann
>
>
>
> ------------------------------------------------------------------------------
> Come build with us! The BlackBerry(R) Developer Conference in SF, CA
> is the only developer event you need to attend this year. Jumpstart your
> developing skills, take BlackBerry mobile applications to market and stay 
> ahead of the curve. Join us from November 9 - 12, 2009. Register now!
> http://p.sf.net/sfu/devconference
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>   

-- 
Michael Droettboom
Science Software Branch
Operations and Engineering Division
Space Telescope Science Institute
Operated by AURA for NASA

Hi,

I notice hatch is not drawn correctly when I zoom in axes.

#!/usr/bin/env python
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle

axes = plt.subplot(111)
axes.add_patch(Rectangle((0, 0), 1, 1, fill=False, hatch="/"))
plt.show()

Is there a way to fix it ?

Regards,

Yann

Hi,

I want to make a plot with ordinary subplots, each of which has a
second axes set created with twinx().  Now, the second axes are
always drawn over the first, but I want the "main" data, which is
associated with the left Y axis, to be in front. (If I understand
the code correctly, the zorder doesn't help here since it only
applies to stuff within one axes set.)

I've already tried reversing the order of the two axes in figure.axes,
but that results in (apparently) only the first axes being drawn.
Is there a way to get this working?

thanks,
Georg

Hi,

I found strange behavior in matplotlib.text.Text. 
set_backgroundcolor(self, color) allows to init text background and edge 
colors but we can only alter backgroundcolor.

# line 728
def set_backgroundcolor(self, color):
         """
         Set the background color of the text by updating the bbox.

         .. seealso::

             :meth:`set_bbox`
                To change the position of the bounding box.

         ACCEPTS: any matplotlib color
         """
         if self._bbox is None:
             self._bbox = dict(facecolor=color, edgecolor=color)
         else:
             self._bbox.update(dict(facecolor=color))

I think the last line might be like :
self._bbox.update(dict(facecolor=color, edgecolor=color))

I notice it because I use a dark background for axis and texts but I 
replace it by a white one when I print figure. With current code, it 
remains a dark border arround my texts.

Regards,

Yann

Hello,

Continuing on my previous email, I'm using this example:

http://matplotlib.sourceforge.net/examples/animation/animation_blit_qt4.html

 

def __init__(self):

        FigureCanvas.__init__(self, Figure())

 

        self.ax = self.figure.add_subplot(111)

        self.ax.set_position([0.1,0.05,0.5,0.9])     

 

works, but:

 

def __init__(self):

        FigureCanvas.__init__(self, Figure())

 

        self.ax = self.figure.add_subplot(111)

        self.ax.set_position([0.1,0.1,0.5,0.9])

        

is not working L, the region is wrongly blitted and some part of the graph
is not restored.

 

I think there is a bug in the refresh of the bounding box or something like
this.

 

Using matplotlib 0.99.1.1 python2.5 win32 pyqt4 4.4.3.7 (given with
python(x,y) 2.1.17)

 

Laurent

John [H2O] wrote:
> Jeff,
>
> Here's a quick snippet. I've looked at the test.py file provided with the
> basemap examples. What I am unclear on are the different ways in which nx
> and ny are defined. I would like to have this 'automatically' defined, based
> solely on variables from my input object.. say for example a netcdf file
> that has len and lon dimensions defined. 
>   

John:  I don't have time to look at your code right now, but let me just 
make some general comments about plotting images on maps.  If you want 
to use imshow, the data your are plotting must coincide exactly with 
your map plot area.  So, for example if you want to plot a global 
lat/lon grid on a north polar stereographic projection, you have to 
interpolate to a rectangular grid in projection coordinates that fits in 
the map region.  However, in practice I find it's almost never worth 
doing this.  You can plot the data in the native coordinates on almost 
any map projection region using pcolormesh or contourf,  Just calculate 
the x,y values of the of the data grid, and pass those values along with 
the data to either one of those methods.  Is there any particular reason 
you want to use imshow, instead of pcolormesh or contourf?

-Jeff
> Below is my crude stab at it, but I am clearly having some problems. I guess
> the point is, maybe it's not possible to have a Basemap instance with
> extents beyond the imshow object. Then perhaps I need to make sure that when
> I set up the Basemap instance, I pass the H.outlon0 to llcrnrlon for
> example. But is that necessary?
>
> Thanks!
>
> #!/usr/bin/env python
>
> import matplotlib.pyplot as plt
> from mpl_toolkits.basemap import Basemap
> import numpy as np
>
>
>
> def plot_imshow_custom(H,transform=True ):
>     """
>     function to automagically plot an mxn array of arbitrary lats/lons
>     """
>     data = H.data
>     print data.shape
>     
>     m =
> Basemap(projection='npstere',boundinglat=10,lon_0=270,resolution='l')
>     fig = plt.figure()
>     ax = fig.gca()
>  
>     print "Preparing to plot %s with dimensions:" % H.name
>     print "lon0, numx, dx:"
>     print H.outlon0, H.numxgrid, H.dxout
>     print "lat0, numy, dy:"
>     print H.outlat0, H.numygrid, H.dyout
>     
>     
>     ## set up transformations for the data array
>     ## THIS IS WHERE I NEED SOME HELP:
>     if m.projection not in ['cyl','merc','mill']:
>         lats = np.arange( H.outlat0, ( H.outlat0 + ( H.numygrid*H.dyout ) ),
> H.dyout )[:-1]
>         lons = np.arange( H.outlon0, ( H.outlon0 + ( H.numxgrid*H.dxout ) ),
> H.dxout )[:-1]
>         data = data[:-1,:-1]
>     else:
>         lats = np.arange( H.outlat0, ( H.outlat0 + ( H.numygrid*H.dyout ) ),
> H.dyout )
>         lons = np.arange( H.outlon0, ( H.outlon0 + ( H.numxgrid*H.dxout ) ),
> H.dxout )
>     print data.shape
>     ## transform to nx x ny regularly spaced native projection grid
>     if transform:
>         if m.projection not in ['cyl','merc','mill']:
>             dx = 2.*np.pi*m.rmajor/len(lons)
>             dy = 2.*np.pi*m.rminor/len(lats)
>         else:
>             dx = len(lons)
>             dy = len(lats)
>         nx = int((m.xmax-m.xmin)/dx)+1; 
>         ny = int((m.ymax-m.ymin)/dy)+1
>         print nx
>         if nx is 1:
>             topodat = data
>         else:
>             topodat = m.transform_scalar(data,lons,lats,nx,ny)
>     else:
>         topodat = data
>
>
>     ## Get the current axes, and properties for use later
>     pos = ax.get_position()
>     l, b, w, h = pos.bounds
>
>     ## Set up the IMAGE
>     colmap = plt.get_cmap('gist_ncar')
>     im = m.imshow(topodat,cmap=colmap)
>     m.drawcoastlines()
>
>     return fig
>
>
> class SuperDict(dict):
>     """just so I can use . notation"""
>     def __getattr__(self, attr):
>         return self[attr]
>     def __setattr__(self, attr, value):
>         self[attr] = value
>
> if __name__ == "__main__":
>     
>     H = SuperDict()
>     H.name = 'working example'
>     H.outlat0 = -90
>     H.numygrid = 180
>     H.dyout = 1.
>     H.outlon0 = -179
>     H.numxgrid = 360
>     H.dxout = 1.0
>     H.data = np.random.rand(H.numygrid,H.numxgrid)
>     print H.data.shape
>     fig = plot_imshow_custom(H,transform=True)
>     plt.show()
>     print 'it worked'
>     try:
>         H.name = 'Not working example'
>         H.outlat0 = 40
>         H.numygrid = 100
>         H.dyout = 0.5
>         H.outlon0 = -179
>         H.numxgrid = 110
>         H.dxout = 0.5
>         H.data = np.random.rand(H.numygrid,H.numxgrid)
>         fig = plot_imshow_custom(H)
>         print 'huh?'
>         plt.show()
>         
>     except:
>         print "As I said, it's not working..."
>
>
>
>
> Jeff Whitaker wrote:
>   
>> John [H2O] wrote:
>>     
>>> I'm trying to 'automate' a few components within basemap. I have a pretty
>>> complicated, and assuredly poorly written, set of functions that allow me
>>> to
>>> 'dynamically' plot a grid of data (lon,lat).
>>>
>>> Here is one section where I try to deal with transforming the data based
>>> on
>>> the projection. 'data' is a grid, often of size 720x360 or 720x180,
>>> representing full globe or hemisphere at 0.5 degree resolution.
>>> 'outlon0',
>>> outlat0', and 'd*out' are the llcrnr coordinates and step. 'transform' is
>>> an
>>> option, that is set to True by default:
>>>
>>> 1680     ## set up transformations for the data array 
>>> 1681     if m.projection not in ['cyl','merc','mill']:
>>> 1682         lats = np.arange( outlat0, ( outlat0 + ( numygrid*dyout ) ),
>>> dyout )[:-1]
>>> 1683         lons = np.arange( outlon0, ( outlon0 + ( numxgrid*dxout ) ),
>>> dxout )[:-1]
>>> 1684         data = data[:-1,:-1]
>>> 1685     else:
>>> 1686         lats = np.arange( outlat0, ( outlat0 + ( numygrid*dyout ) ),
>>> dyout )
>>> 1687         lons = np.arange( outlon0, ( outlon0 + ( numxgrid*dxout ) ),
>>> dxout )
>>> 1688 
>>> 1689     ## transform to nx x ny regularly spaced native projection grid
>>> 1690     if transform:
>>> 1691         dx = 2.*np.pi*m.rmajor/len(lons)
>>> 1692         nx = int((m.xmax-m.xmin)/dx)+1; ny =
>>> int((m.ymax-m.ymin)/dx)+1
>>> 1693         if nx is 1:
>>> 1694             topodat = data
>>> 1695         else:
>>> 1696             topodat = m.transform_scalar(data,lons,lats,nx,ny)
>>> 1697     else:
>>> 1698         topodat = data
>>>
>>> The problem is, when I use the approach with a 'cyl' grid, then
>>> subsequently
>>> try to draw the lsmask, I get a failure. Is this approach incorrect? I
>>> had
>>> to use the if nx is 1 statement because it was crashing with zero
>>> division
>>> error in some cases.
>>>
>>> Thanks.
>>>   
>>>       
>> John:  Please supply us with a self-contained example triggering the 
>> error that we can run.
>>
>> -Jeff
>>
>> ------------------------------------------------------------------------------
>> Come build with us! The BlackBerry® Developer Conference in SF, CA
>> is the only developer event you need to attend this year. Jumpstart your
>> developing skills, take BlackBerry mobile applications to market and stay 
>> ahead of the curve. Join us from November 9-12, 2009. Register
>> now!
>> http://p.sf.net/sfu/devconf
>> _______________________________________________
>> Matplotlib-users mailing list
>> Mat...@li...
>> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>>
>>
>>     
>
>