matplotlib-users Mailing List for matplotlib

>>>>> "Christopher" == Christopher Barker <Chr...@no...> writes:
 Christopher> That I don't know. The Agg renderer certainly can do
 Christopher> a nice job with gradients, but I don't know if MPL
 Christopher> support that.
You can emulate gradients using matplotlib images -- either with colormaps or
defining your own rgba endpoints for the gradients. Here's an example
of an axes background gradient
 from pylab import figure, show, nx, cm
 fig = figure()
 xmin, xmax = xlim = 0,2
 ymin, ymax = ylim = -1,1
 ax = fig.add_subplot(111, xlim=xlim, ylim=ylim,
 autoscale_on=False)
 X = [[.6, .6],[.7,.7]]
 ax.imshow(X, interpolation='bicubic', cmap=cm.Blues,
 extent=(xmin, xmax, ymin, ymax), alpha=1)
 t = nx.arange(xmin, xmax,0.01)
 ax.plot(t, nx.sin(2*nx.pi*t), lw=2, color='black')
 show()
Likewise, you can make your own gradient bars charts:
 from pylab import figure, show, nx, cm
 def gbar(ax, x, y, width=0.5, bottom=0):
 X = [[.6, .6],[.7,.7]]
 for left,top in zip(x, y):
 right = left+width
 ax.imshow(X, interpolation='bicubic', cmap=cm.Blues,
 extent=(left, right, bottom, top), alpha=1)
 fig = figure()
 xmin, xmax = xlim = 0,10
 ymin, ymax = ylim = 0,1
 ax = fig.add_subplot(111, xlim=xlim, ylim=ylim,
 autoscale_on=False)
 X = [[.6, .6],[.7,.7]]
 ax.imshow(X, interpolation='bicubic', cmap=cm.copper,
 extent=(xmin, xmax, ymin, ymax), alpha=1)
 N = 10
 x = nx.arange(N)+0.25
 y = nx.mlab.rand(N)
 gbar(ax, x, y, width=0.7)
 ax.set_aspect('normal')
 show()
Viewer discretion is advised.
If you want to get clever, you can define patterns and fills this way
too. We should add an interface to expose this functionality more
readily...
JDH

Bryan wrote:
> Hi all, I am working on a UI design, and I just found out about 
> matplotlib. I would like to learn if some of the following graphs are 
> possible using matplotlib with wxPython
If you want to use MPL with wxPython like that, be sure to check out wxmpl.
> http://www.geocities.com/belred1/image1.jpg
> 
> Does anyone know if matplotlib has rich charting functionality with 
> gradients and shading that could provide the same experience as the 
> performance charts on the right.
I don't think it has the nifty shading. Other than that, it can do it all.
> How difficult would this be to implement?
That I don't know. The Agg renderer certainly can do a nice job with 
gradients, but I don't know if MPL support that.
-Chris
-- 
Christopher Barker, Ph.D.
Oceanographer
 		
NOAA/OR&R/HAZMAT (206) 526-6959 voice
7600 Sand Point Way NE (206) 526-6329 fax
Seattle, WA 98115 (206) 526-6317 main reception
Chr...@no...

http://www.scipy.org/Cookbook/Matplotlib/Animations
You can get pretty good framerates using the blitting technique
described in the link above.
On 5/14/06, Allan Noriel Estrella <all...@gm...> wrote:
> Can I implement realtime plotting in matplotlib? The data will be coming
> from the serial port. The plotting will be similar to an oscilloscope. Ca=
n
> you suggest matplotlib modules I can use for this particular application.
> Thanks
>

>>>>> "clovis" == clovis <cl...@pe...> writes:
 clovis> All, I followed up the 'memory leak' discussion in the
 clovis> sourceforge list and I know the Matplotlib-FAQ entry about
 clovis> this subject. I've also seen John Hunter's post about the
 clovis> need of matching figure/close pairs. Anyway, I still feel
 clovis> that there are problems in this subject, which can be
 clovis> exposed by the following script (for Windows, but can
 clovis> easily be adapted to Unix).
 clovis> As can be seen by the results (also given below), there is
 clovis> a steady increase in memory usage which is not recovered!
If I recall correctly, there is a known leak in tkagg when you create
multiple canvases, and this is in Tk and not matplotlib proper. Todd
may have something to add here. 
JDH

Hi happy matplolib users,
 Very, very nice feature, this zooming functionality is perfect.
Thanks again to the matplotlib team for the great work.
I simply have one question:
 How can I use this zooming key in my app. which is embedding matplotlib
in GTK ?
David
2006年5月16日, sophana <so...@zi...>:
>
> I made a patch on the sourceforge site that does what you need.
> you can select which layer(s) you interact with (move/pan)
>
> Daniel McQuillen wrote:
>
>
> Hi everybody. Question about multiple Y axes...
>
>
> I've seen a few posts regarding using the trick of laying one axes over
> top of the other to simulate a second Y axis -- as demonstrated in the
> matplotlib example file two_scales.py.
>
> However, in the application I'm building, the user should be able to
> select points ("outliers") for either axis. With the current approach, th=
e
> user can't select the bottom graph's points (or pan or zoom it).
>
>
> Is there a way to bring the bottom graph into "focus"?
>
> Thanks in advance for any tips.
>
>
> =3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=
=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D=3D
> Daniel McQuillen
> Oakland, CA
>
>
>

I made a patch on the sourceforge site that does what you need.
you can select which layer(s) you interact with (move/pan)
Daniel McQuillen wrote:
>
> Hi everybody. Question about multiple Y axes...
>
> I've seen a few posts regarding using the trick of laying one axes 
> over top of the other to simulate a second Y axis -- as demonstrated 
> in the matplotlib example file two_scales.py.
>
> However, in the application I'm building, the user should be able to 
> select points ("outliers") for either axis. With the current approach, 
> the user can't select the bottom graph's points (or pan or zoom it).
>
> Is there a way to bring the bottom graph into "focus"?
>
> Thanks in advance for any tips.
>
>
> =====================================
> Daniel McQuillen
> Oakland, CA
>