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I have checked with all the interpolation modes and the only one that
behaves badly is 'nearest'. There are them:
http://dl.dropbox.com/u/1351211/Interpolation_modes.zip
On Mon, Apr 18, 2011 at 12:46 PM, Emanuele Passera
<ema...@tr...> wrote:
> Hello everybody,
>
> I am experiencing a strange behavior with the imshow() function when
> using the nearest interpolation method.
>
> Executing the code listed below, I obtain a good image when using the
> bilinear interpolation method
> and a totally white image when using the nearest interpolation method.
> I have attached the input data buffer and the resulting images too.
>
>
> import numpy as n
> import pylab as p
>
> # input data
> dataFile = "/users/lelepass/python/test_imagesc/buffer.float"
> samples = 15
> lines = 39
> imagescCanvasXDim = 800
> imagescCanvasDpi = 100
> data_aspect_ratio = 0.75707855955290304
> vMin = -3.3467740682968197
> vMax = 0.65322593170318011
> outImageFileBilinear =
> "/users/lelepass/python/test_imagesc/subpxAzBilinear.png"
> outImageFileNearest =
> "/users/lelepass/python/test_imagesc/subpxAzNearest.png"
>
> # loading input data file
> s = file(dataFile, 'rb').read()
> data = n.fromstring(s, 'f')
> data.shape = lines, samples
> data = n.transpose(data)
>
> # image canvas dimension setting
> xAxisInches = float(imagescCanvasXDim) / float(imagescCanvasDpi)
> yPixelsDim = imagescCanvasXDim * data_aspect_ratio
> yAxisInches = float(yPixelsDim) / float(imagescCanvasDpi)
>
> ################################
> #    bilinear image     #
> ################################
> # image canvas
> canvasObj = p.figure(facecolor="w", edgecolor="w", figsize=(xAxisInches,
> yAxisInches), frameon=True, dpi=imagescCanvasDpi)
> # axis setting
> axisLocationList = [0,0,1,1]
> axisObj = canvasObj.add_axes(axisLocationList)
> axisObj.axesPatch.set_alpha(1)
> # colormap
> colorMap = p.cm.jet_r
> # bilinear image drawing
> p.imshow(data, cmap=colorMap, vmin=vMin, vmax=vMax,
> interpolation="bilinear", origin="lower", aspect="auto", alpha=1)
> reversing = axisObj.set_ylim(axisObj.get_ylim()[::-1])
> # bilinear image saving and closing
> canvasObj.savefig(outImageFileBilinear, dpi=imagescCanvasDpi)
> p.close()
>
> ################################
> #    nearest image     #
> ################################
> # image canvas
> canvasObj = p.figure(facecolor="w", edgecolor="w", figsize=(xAxisInches,
> yAxisInches), frameon=True, dpi=imagescCanvasDpi)
> # axis setting
> axisLocationList = [0,0,1,1]
> axisObj = canvasObj.add_axes(axisLocationList)
> axisObj.axesPatch.set_alpha(1)
> # colormap
> colorMap = p.cm.jet_r
> # nearest image drawing
> p.imshow(data, cmap=colorMap, vmin=vMin, vmax=vMax, interpolation="nearest",
> origin="lower", aspect="auto", alpha=1)
> reversing = axisObj.set_ylim(axisObj.get_ylim()[::-1])
> # nearest image saving and closing
> canvasObj.savefig(outImageFileNearest, dpi=imagescCanvasDpi)
> p.close()
>
>
>
> I use matplotlib to generate a lot of images in batch mode and this
> behavior appear not to be deterministic. It seems to depend on the input
> data buffer.
> Can anyone help me ?
>
> I use
> Linux openSUSE 11.3 (x86_64)
> Linux sat1 2.6.34.7-0.7-default #1 SMP 2010年12月13日 11:13:53 +0100 x86_64
> x86_64 x86_64 GNU/Linux
> Python    2.6.5
> numpy    1.5.1
> matplotlib  1.0.1 with backend Agg v2.2
>
>
> If it can be of some help this strange behavior does not appear with a
> system
> Linux Ubuntu 9.10
> Linux joshua 2.6.28-11-server #42-Ubuntu SMP Fri Apr 17 02:48:10 UTC 2009
> i686 GNU/Linux
> Python    2.6.4
> numpy    1.3.0
> matplotlib  0.99.0 with backend Agg v2.2
>
> Executing the script with verbosity I get the subsequent output
> python /users/lelepass/python/test_imagesc/test.py --verbose-helpful
>
> $HOME=/users/lelepass
> CONFIGDIR=/users/lelepass/.matplotlib
>
> Bad key "numerix" on line 30 in
> /users/lelepass/.matplotlib/matplotlibrc.
> You probably need to get an updated matplotlibrc file from
> http://matplotlib.sf.net/_static/matplotlibrc or from the matplotlib source
> distribution
> matplotlib data path /usr/lib64/python2.6/site-packages/matplotlib/mpl-data
> loaded rc file /users/lelepass/.matplotlib/matplotlibrc
> matplotlib version 1.0.1
> verbose.level helpful
> interactive is False
> units is True
> platform is linux2
> Using fontManager instance from /users/lelepass/.matplotlib/fontList.cache
> backend agg version v2.2
> findfont: Matching
> :family=sans-serif:style=normal:variant=normal:weight=normal:stretch=normal:size=medium
> to Bitstream Vera Sans
> (/usr/lib64/python2.6/site-packages/matplotlib/mpl-data/fonts/ttf/Vera.ttf)
> with score of 0.000000
>
>
> Thank you all.
> Bye.
>
>
>
>
>
> Emanuele Passera
>
> Software Engineer
>
> Tele-Rilevamento Europa - T.R.E. srl
> Via Vittoria Colonna, 7
> 20149 Milano – Italia
> Tel.: +39.02.4343.121 - Fax: +39.02.4343.1230
> ema...@tr... - www.treuropa.com
>
>
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>

On 04/18/2011 06:07 AM, Muffles wrote:
>
> Ive seen lots of examples around, but i cant seem to adapt any to my
> implementation.
> The only thing i want is to change what values the colorbar shows. In the
> colorbar there are values from 1 to 1e+9, and im only interested in the
> values from 1e+4 to 1e+9...
>
> pc = ax.pcolor(pr[2].transpose(),norm=LogNorm(vmin=1),cmap=cm.jet)
Have you tried using vmin=1e4 above?
>
> ax.set_yticks(np.arange(0-(arr_agl[0]*escala)/1000,
> (arr_agl[600]*escala)/1000, escala))
> ax.set_yticklabels(range(20))
>
> ax.set_ylim(0, 600)
> ax.set_xlim(0,len(valores2))
> ax.xaxis.LABELPAD = 18
>
> for label in ax.get_xticklabels() + ax.get_yticklabels():
> label.set_fontsize(16)
>
> plt.xlabel('Time of Measurement',fontsize=16)
> plt.ylabel('HEIGHT above ground level, km',fontsize=16)
>
> colorbar = fig.colorbar(pc)
With the suggested change to vmin, you might want to use the colorbar 
kwarg extend='min'.
Eric
>
> Thx...

Do you have a minimal script that reproduces this error?
Cheers,
Mike
On 04/18/2011 07:37 AM, Muffles wrote:
> Hello all,
> I am getting this error, and im not very experienced with matplotlib, but in
> most files this code worked, but in some i just get this error:
>
> Traceback (most recent call last):
> File "/home/paoli/public_html/netcdf2png.py", line 128, in<module>
> colorbar = fig.colorbar(pc)
> File "/usr/lib/python2.5/site-packages/matplotlib/figure.py", line 1022,
> in colorbar
> cb = cbar.Colorbar(cax, mappable, **kw)
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 616,
> in __init__
> ColorbarBase.__init__(self, ax, **kw)
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 214,
> in __init__
> self.draw_all()
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 225,
> in draw_all
> self._config_axes(X, Y)
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 252,
> in _config_axes
> ticks, ticklabels, offset_string = self._ticker()
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 388,
> in _ticker
> b = np.array(locator())
> File "/usr/lib/python2.5/site-packages/matplotlib/ticker.py", line 1006,
> in __call__
> vmax = math.log(vmax)/math.log(b)
> OverflowError: math range error
> Traceback (most recent call last):
> File "/home/paoli/public_html/netcdf2png.py", line 128, in<module>
> colorbar = fig.colorbar(pc)
> File "/usr/lib/python2.5/site-packages/matplotlib/figure.py", line 1022,
> in colorbar
> cb = cbar.Colorbar(cax, mappable, **kw)
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 616,
> in __init__
> ColorbarBase.__init__(self, ax, **kw)
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 214,
> in __init__
> self.draw_all()
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 225,
> in draw_all
> self._config_axes(X, Y)
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 252,
> in _config_axes
> ticks, ticklabels, offset_string = self._ticker()
> File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 388,
> in _ticker
> b = np.array(locator())
> File "/usr/lib/python2.5/site-packages/matplotlib/ticker.py", line 1006,
> in __call__
> vmax = math.log(vmax)/math.log(b)
> OverflowError: math range error
>
>
> Is there any workaround?
> Thx in advance!

Ive seen lots of examples around, but i cant seem to adapt any to my
implementation.
The only thing i want is to change what values the colorbar shows. In the
colorbar there are values from 1 to 1e+9, and im only interested in the
values from 1e+4 to 1e+9...
pc = ax.pcolor(pr[2].transpose(),norm=LogNorm(vmin=1),cmap=cm.jet)
ax.set_yticks(np.arange(0-(arr_agl[0]*escala)/1000,
(arr_agl[600]*escala)/1000, escala))
ax.set_yticklabels(range(20)) 
ax.set_ylim(0, 600)
ax.set_xlim(0,len(valores2))
ax.xaxis.LABELPAD = 18
for label in ax.get_xticklabels() + ax.get_yticklabels():
 label.set_fontsize(16) 
plt.xlabel('Time of Measurement',fontsize=16)
plt.ylabel('HEIGHT above ground level, km',fontsize=16)
colorbar = fig.colorbar(pc)
Thx...
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Hello,
don't know the foo behind it, but using
ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d %H:%M:%S'))
works.
Regards,
Sebastian
On Sun, 2011年04月17日 at 19:52 -0700, jfortiv wrote:
> Hello, 
> 
> I'm trying to create a bar chart that looks something like a gannt chart...
> 
> See the simple example here:
> 
> http://www.promana.net/making-use-of-gantt-charts/
> 
> I'm trying to utilize barh() and fmt_xdata to accomplish this with the
> following:
> 
> #~~~~~~~~~~~~~~~~~~~~~~~
> 
> date1 = datetime.datetime( 2000, 3, 2)
> date2 = datetime.datetime( 2000, 3, 6)
> delta = datetime.timedelta(hours=6)
> dates = mdates.drange(date1, date2, delta)
> 
> val = mdates.drange(date1,date2,delta) # the bar lengths
> pos = range(len(val)) # the bar centers on the y axis
> height=0.5 # the bar height
> left=mdates.drange(date1,date2,delta) # the bar starting position
> 
> fig = plt.figure()
> ax = fig.add_subplot(111)
> ax.barh(pos,val,height=height,left=left,align='center',alpha=0.3)
> ax.fmt_xdata = mdates.DateFormatter('%Y-%m-%d %H:%M:%S')
> 
> #~~~~~~~~~~~~~~~~~~~~~~~
> 
> 
> Even with ax.fmt_xdata, I'm simply getting numbers on the x-axis instead of
> dates. Can anyone offer some pointers?
> 
> Thanks,
> James

Actually, I think he's wanting a set aspect, right? Either way, it's just
"aspect=1.5" or "aspect=0.6667" depending on the orientation he wants.
On Mon, Apr 18, 2011 at 6:37 AM, Sebastian Berg
<seb...@si...>wrote:
> The solution is already the aspect='auto', ie:
>
> import numpy as np
> from matplotlib import pyplot as plt
> a = np.arange(100).reshape(10,10)
> plt.imshow(a, aspect='auto')
>
> aspect='auto' is what you were looking for, the documentation (as you
> probably already found is for example at:
>
> http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.imshow
> or in interactive help.
>
>
> On Sun, 2011年04月17日 at 23:16 +0200, Paolo Zaffino wrote:
> > Thanks for the reply.
> > I checked in the help...I didn't understand what I must to use.
> > Should you post me the link of the guide of this setting?
> > Thanks!
> >
> >
> > Il 16/04/2011 10:47, Sebastian Berg ha scritto:
> > > Hello,
> > >
> > > check the help ;). you can set aspect='auto' or something fixed.
> > >
> > > Regards,
> > >
> > > Sebastian
> > >
> > > On Sat, 2011年04月16日 at 10:43 +0200, Paolo Zaffino wrote:
> > >> Hi at all,
> > >> I have a numpy matrix (an image) and I'd like to show it.
> > >> I thought to use show function, but I have a question.
> > >> I don't want that the pixel have dimension 1x1 unit but I want for
> > >> example 1X1.5 unit (I don't want a square but a rectangle).
> > >> How can I do this?
> > >> Thanks in advance.
> > >> Paolo
> > >>
> > >>
> ------------------------------------------------------------------------------
> > >> Benefiting from Server Virtualization: Beyond Initial Workload
> > >> Consolidation -- Increasing the use of server virtualization is a top
> > >> priority.Virtualization can reduce costs, simplify management, and
> improve
> > >> application availability and disaster protection. Learn more about
> boosting
> > >> the value of server virtualization.
> http://p.sf.net/sfu/vmware-sfdev2dev
> > >> _______________________________________________
> > >> Matplotlib-users mailing list
> > >> Mat...@li...
> > >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> > >>
> > >
> > >
> > >
> ------------------------------------------------------------------------------
> > > Benefiting from Server Virtualization: Beyond Initial Workload
> > > Consolidation -- Increasing the use of server virtualization is a top
> > > priority.Virtualization can reduce costs, simplify management, and
> improve
> > > application availability and disaster protection. Learn more about
> boosting
> > > the value of server virtualization.
> http://p.sf.net/sfu/vmware-sfdev2dev
> > > _______________________________________________
> > > Matplotlib-users mailing list
> > > Mat...@li...
> > > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> > >
> >
> >
> >
> ------------------------------------------------------------------------------
> > Benefiting from Server Virtualization: Beyond Initial Workload
> > Consolidation -- Increasing the use of server virtualization is a top
> > priority.Virtualization can reduce costs, simplify management, and
> improve
> > application availability and disaster protection. Learn more about
> boosting
> > the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev
> > _______________________________________________
> > Matplotlib-users mailing list
> > Mat...@li...
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >
>
>
>
>
> ------------------------------------------------------------------------------
> Benefiting from Server Virtualization: Beyond Initial Workload
> Consolidation -- Increasing the use of server virtualization is a top
> priority.Virtualization can reduce costs, simplify management, and improve
> application availability and disaster protection. Learn more about boosting
> the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev
> _______________________________________________
> Matplotlib-users mailing list
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> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

The solution is already the aspect='auto', ie:
import numpy as np
from matplotlib import pyplot as plt
a = np.arange(100).reshape(10,10)
plt.imshow(a, aspect='auto')
aspect='auto' is what you were looking for, the documentation (as you
probably already found is for example at:
http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.imshow
or in interactive help.
On Sun, 2011年04月17日 at 23:16 +0200, Paolo Zaffino wrote:
> Thanks for the reply.
> I checked in the help...I didn't understand what I must to use.
> Should you post me the link of the guide of this setting?
> Thanks!
> 
> 
> Il 16/04/2011 10:47, Sebastian Berg ha scritto:
> > Hello,
> >
> > check the help ;). you can set aspect='auto' or something fixed.
> >
> > Regards,
> >
> > Sebastian
> >
> > On Sat, 2011年04月16日 at 10:43 +0200, Paolo Zaffino wrote:
> >> Hi at all,
> >> I have a numpy matrix (an image) and I'd like to show it.
> >> I thought to use show function, but I have a question.
> >> I don't want that the pixel have dimension 1x1 unit but I want for
> >> example 1X1.5 unit (I don't want a square but a rectangle).
> >> How can I do this?
> >> Thanks in advance.
> >> Paolo
> >>
> >> ------------------------------------------------------------------------------
> >> Benefiting from Server Virtualization: Beyond Initial Workload
> >> Consolidation -- Increasing the use of server virtualization is a top
> >> priority.Virtualization can reduce costs, simplify management, and improve
> >> application availability and disaster protection. Learn more about boosting
> >> the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev
> >> _______________________________________________
> >> Matplotlib-users mailing list
> >> Mat...@li...
> >> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >>
> >
> >
> > ------------------------------------------------------------------------------
> > Benefiting from Server Virtualization: Beyond Initial Workload
> > Consolidation -- Increasing the use of server virtualization is a top
> > priority.Virtualization can reduce costs, simplify management, and improve
> > application availability and disaster protection. Learn more about boosting
> > the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev
> > _______________________________________________
> > Matplotlib-users mailing list
> > Mat...@li...
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> >
> 
> 
> ------------------------------------------------------------------------------
> Benefiting from Server Virtualization: Beyond Initial Workload 
> Consolidation -- Increasing the use of server virtualization is a top
> priority.Virtualization can reduce costs, simplify management, and improve 
> application availability and disaster protection. Learn more about boosting 
> the value of server virtualization. http://p.sf.net/sfu/vmware-sfdev2dev
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 

Hello all,
I am getting this error, and im not very experienced with matplotlib, but in
most files this code worked, but in some i just get this error:
Traceback (most recent call last):
 File "/home/paoli/public_html/netcdf2png.py", line 128, in <module>
 colorbar = fig.colorbar(pc)
 File "/usr/lib/python2.5/site-packages/matplotlib/figure.py", line 1022,
in colorbar
 cb = cbar.Colorbar(cax, mappable, **kw)
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 616,
in __init__
 ColorbarBase.__init__(self, ax, **kw)
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 214,
in __init__
 self.draw_all()
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 225,
in draw_all
 self._config_axes(X, Y)
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 252,
in _config_axes
 ticks, ticklabels, offset_string = self._ticker()
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 388,
in _ticker
 b = np.array(locator())
 File "/usr/lib/python2.5/site-packages/matplotlib/ticker.py", line 1006,
in __call__
 vmax = math.log(vmax)/math.log(b)
OverflowError: math range error
Traceback (most recent call last):
 File "/home/paoli/public_html/netcdf2png.py", line 128, in <module>
 colorbar = fig.colorbar(pc)
 File "/usr/lib/python2.5/site-packages/matplotlib/figure.py", line 1022,
in colorbar
 cb = cbar.Colorbar(cax, mappable, **kw)
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 616,
in __init__
 ColorbarBase.__init__(self, ax, **kw)
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 214,
in __init__
 self.draw_all()
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 225,
in draw_all
 self._config_axes(X, Y)
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 252,
in _config_axes
 ticks, ticklabels, offset_string = self._ticker()
 File "/usr/lib/python2.5/site-packages/matplotlib/colorbar.py", line 388,
in _ticker
 b = np.array(locator())
 File "/usr/lib/python2.5/site-packages/matplotlib/ticker.py", line 1006,
in __call__
 vmax = math.log(vmax)/math.log(b)
OverflowError: math range error
Is there any workaround?
Thx in advance!
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Hello all,
i created some program to read from netcdf files and plot the data, and it
seems to work ok. But when i try to run an older file, it just shows this:
Traceback (most recent call last):
 File "netcdf2png.py", line 199, in <module>
 savefig("range.png")
 File "/usr/lib/pymodules/python2.6/matplotlib/pyplot.py", line 356, in
savefig
 return fig.savefig(*args, **kwargs)
 File "/usr/lib/pymodules/python2.6/matplotlib/figure.py", line 1032, in
savefig
 self.canvas.print_figure(*args, **kwargs)
 File "/usr/lib/pymodules/python2.6/matplotlib/backend_bases.py", line
1476, in print_figure
 **kwargs)
 File "/usr/lib/pymodules/python2.6/matplotlib/backends/backend_agg.py",
line 358, in print_png
 FigureCanvasAgg.draw(self)
 File "/usr/lib/pymodules/python2.6/matplotlib/backends/backend_agg.py",
line 314, in draw
 self.figure.draw(self.renderer)
 File "/usr/lib/pymodules/python2.6/matplotlib/artist.py", line 46, in
draw_wrapper
 draw(artist, renderer, *args, **kwargs)
 File "/usr/lib/pymodules/python2.6/matplotlib/figure.py", line 773, in
draw
 for a in self.axes: a.draw(renderer)
 File "/usr/lib/pymodules/python2.6/matplotlib/artist.py", line 46, in
draw_wrapper
 draw(artist, renderer, *args, **kwargs)
 File "/usr/lib/pymodules/python2.6/matplotlib/axes.py", line 1735, in draw
 a.draw(renderer)
 File "/usr/lib/pymodules/python2.6/matplotlib/collections.py", line 704,
in draw
 return Collection.draw(self, renderer)
 File "/usr/lib/pymodules/python2.6/matplotlib/artist.py", line 46, in
draw_wrapper
 draw(artist, renderer, *args, **kwargs)
 File "/usr/lib/pymodules/python2.6/matplotlib/collections.py", line 201,
in draw
 self.update_scalarmappable()
 File "/usr/lib/pymodules/python2.6/matplotlib/collections.py", line 477,
in update_scalarmappable
 self._facecolors = self.to_rgba(self._A, self._alpha)
 File "/usr/lib/pymodules/python2.6/matplotlib/cm.py", line 166, in to_rgba
 x = self.norm(x)
 File "/usr/lib/pymodules/python2.6/matplotlib/colors.py", line 825, in
__call__
 raise ValueError("minvalue must be less than or equal to maxvalue")
ValueError: minvalue must be less than or equal to maxvalue
Any ideas?
Thx in advance
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Hello,
Suppose I create a matplotlib figure and plot things in it.
In pylab it would be like:
from pylab import *
figure(1)
plot([1,2,3],[1,2,3],'r*',label='label1')
plot([1,2,3],[2,3,4],'r',label='label2')
legend(loc='upper right')
text(1.2,3,'nice figure')
xlabel('xlabel')
ylabel('ylabel')
show()
Now, after creating figure(1), I would like to make figure(2) that is
completely identical to figure(1).
is this possible?
Does anyone know how?
Thanks,
Eli

Hi Eric,
Thanks for the quick fix.
I can confirm it works for me (on windows with PyQt4.7).
The problem reported with TkAgg was possibly a mistake, as I am unable to 
reproduce it now...
Please consider the issue solved.
Re: Constrained zoom to x axis broken ?
by efiring Apr 17, 2011; 11:14pm :: Rate this Message: - Use ratings to 
moderate (?)
Reply | Print | View Threaded | Show Only this Message
On 04/17/2011 07:59 AM, Eric Firing wrote:
> On 04/16/2011 08:44 PM, butterw@... wrote:
>> > > http://matplotlib.sourceforge.net/users/navigation_toolbar.html
>> Constrained zoom to x axis (hold x key + left click zoom icon) is broken
>> for me with master.
>> Tested with TkAgg, Qt4Agg backend
>> features was working on mpl 1.0.0
> It works for me with gtk and Tk, but not with qt4.
> Eric
... [show rest of quote]
https://github.com/matplotlib/matplotlib/pull/86
Above is a fix for qt4.
Eric
------------------------------------------------------------------------------

Hello, 
I'm trying to create a bar chart that looks something like a gannt chart...
See the simple example here:
http://www.promana.net/making-use-of-gantt-charts/
I'm trying to utilize barh() and fmt_xdata to accomplish this with the
following:
#~~~~~~~~~~~~~~~~~~~~~~~
date1 = datetime.datetime( 2000, 3, 2)
date2 = datetime.datetime( 2000, 3, 6)
delta = datetime.timedelta(hours=6)
dates = mdates.drange(date1, date2, delta)
val = mdates.drange(date1,date2,delta) # the bar lengths
pos = range(len(val)) # the bar centers on the y axis
height=0.5 # the bar height
left=mdates.drange(date1,date2,delta) # the bar starting position
fig = plt.figure()
ax = fig.add_subplot(111)
ax.barh(pos,val,height=height,left=left,align='center',alpha=0.3)
ax.fmt_xdata = mdates.DateFormatter('%Y-%m-%d %H:%M:%S')
#~~~~~~~~~~~~~~~~~~~~~~~
Even with ax.fmt_xdata, I'm simply getting numbers on the x-axis instead of
dates. Can anyone offer some pointers?
Thanks,
James
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