matplotlib-users Mailing List for matplotlib (Page 6)

Hi,

This is my first post to the list so hi everyone!

I am trying to build matplotlib on a freshly installed CentOS 4 workstation.

I have read the FAQ about build problems with pygtk 2.4 is the problem fixed in my version?

[root@institut-c33109 matplotlib-0.87.2]# rpm -qa | grep pygtk
pygtk2-2.4.0-1

When I try python setup.py build it ends with:

error: Command "gcc -pthread -fno-strict-aliasing -DNDEBUG -O2 -g -pipe
-m32 -march=i386 -mtune=pentium4 -D_GNU_SOURCE -fPIC -fPIC
-I/usr/share/tcl8.4/../../include -I/usr/share/tk8.4/../../include
-I/usr/local/include -I/usr/include -I. -Isrc -Iswig -Iagg23/include -I.
-I/usr/local/include -I/usr/include -I.
-I/usr/share/tcl8.4/../../include/freetype2
-I/usr/share/tk8.4/../../include/freetype2
-I/usr/local/include/freetype2 -I/usr/include/freetype2 -I./freetype2
-Isrc/freetype2 -Iswig/freetype2 -Iagg23/include/freetype2 -I./freetype2
-I/usr/local/include/freetype2 -I/usr/include/freetype2 -I./freetype2
-I/usr/include/python2.3 -c src/_tkagg.cpp -o
build/temp.linux-i686-2.3/src/_tkagg.o" failed with exit status 1

I also have an error at the beginning that says I miss tk.h, my system is in french so I will not paste this part.

Thanks for your help and time,

Etienne

Hi,

when I use savefig() to save the image, it saves it in the bin directory 
of the instance (../instance/bin/)
when I try to pass the path in the name (savefig('path/image.png')), I 
get an error :*

Type error : RuntimeError*
*Error value : Could not open file /home/image.png

*How can I set the save directory ?
thks

>>>>> "andrea" == andrea gavana@tin it <and...@ti...> writes:

    andrea> Hello John & NG, thank you very much for your answer. I
    andrea> had actually make it working using Line2D instances for
    andrea> every point in the plot (every well location has its own
    andrea> Line2D object associated). It works reasonably well, but I
    andrea> have some doubts about my implementation...  First of all,
    andrea> I don't know how actually *delete* a Line2D from the plot

ax.lines.remove(someline)

    andrea> (when the well should be hidden) and, moreover, when I
    andrea> have a large number of wells it takes quite a long time to
    andrea> create all the Line2D instances and plot them...  Do you
    andrea> think it will work faster/better if I use a
    andrea> RegularPolyCollection?

Yes, plotting a large number of Line2D instances will be significantly
slower than using a collection.  Give it a try!

JDH

Hello John & NG,

    thank you very much for your answer. I had 
actually make it working using Line2D instances for every point in the 
plot (every well location has its own Line2D object associated). It 
works reasonably well, but I have some doubts about my 
implementation...
First of all, I don't know how actually *delete* a 
Line2D from the plot (when the well should be hidden) and, moreover, 
when I have a large number of wells it takes quite a long time to 
create all the Line2D instances and plot them...
Do you think it will 
work faster/better if I use a RegularPolyCollection?

Thank you very 
much for your suggestions.

Andrea.

>----Original Message----
>From: 
jdh...@ac...
>Date: 18-Apr-2006 16:16
>To: 
"and...@ti..."<and...@ti...>
>Cc: <matplotlib-
us...@li...>
>Subj: Re: [Matplotlib-users] Single Point 
Stored Plot
>
>>>>>> "andrea" == andrea gavana@tin it 
<and...@ti...> writes:
>
>    andrea> Hello NG, I am facing a 
small problem for which I was
>    andrea> unable to find a solution. 
Basically, I have to make a
>    andrea> scatter plot of x, y 
coordinates (they represents oil
>    andrea> wells positions) on a 2D 
map, but I have some constraints:
>
>    andrea> 1) I would like to 
have each point as a separate "plot
>    andrea> object", because the 
user may decide to hide/show only a
>    andrea> particular well, or 
show/hide them all, or show/hide
>    andrea> whatever combination of 
wells.  2) At the moment when the
>    andrea> class that holds a 
single well position/status is created,
>    andrea> the plot window 
may not be there (because is the user that
>    andrea> decides when to 
open a new plot window).
>
>    andrea> I have tried something like:
>
>Hey Andrea, sorry for the delay.  This is a neat problem and one that
>collections were designed to solve.  You probably want to use a
>RegularPolyCollection rather than a PolyCollection (the latter is for
>arbitrary polygons and you must compute all the vertices yourself).
>Here is an example that allows you to add and delete markers -- it
>inserts them with random positions and colors.  You should be able to
>adapt it to your application quite easily.
>
>import random
>from 
matplotlib.colors import colorConverter
>from matplotlib.collections 
import RegularPolyCollection 
>import matplotlib.cm as cm
>from pylab 
import figure, show, nx
>
>fig = figure()
>ax = fig.add_subplot(111, 
xlim=(0,1), ylim=(0,1), autoscale_on=False)
>ax.set_title("Press 'a' to 
add a point, 'd' to delete one")
># a single point
>offsets = 
[(0.5,0.5)]
>facecolors = [cm.jet(0.5)]
>
>collection = 
RegularPolyCollection(
>    fig.dpi,
>    numsides=5, # a pentagon
>    
rotation=0,
>    sizes=(50,), 
>    facecolors = facecolors,
>    
edgecolors = (colorConverter.to_rgba('black'),),
>    linewidths = 
(1,),
>    offsets = offsets,
>    transOffset = ax.transData,
>    )
>
>ax.add_collection(collection)
>
>def onpress(event):
>    """
>    
press 'a' to add a random point from the collection, 'd' to delete one
>    """
>    if event.key=='a':
>        x,y = nx.mlab.rand(2)
>        color = cm.jet(nx.mlab.rand())
>        offsets.append((x,y))
>        facecolors.append(color)
>        fig.canvas.draw()
>    elif 
event.key=='d':
>        N = len(offsets)
>        if N>0:
>            
ind = random.randint(0,N-1)
>            offsets.pop(ind)
>            
facecolors.pop(ind)
>            fig.canvas.draw()
>
>fig.canvas.
mpl_connect('key_press_event', onpress)
>
>show()
>

Eric Firing wrote:
> Andrea,
> 
>  I agree, the colorbar should dynamically update.  A workaround might be 
> to simply call colorbar every time you update the image data.
> 
> At least part of a longer-term solution may be to change colorbar so 
> that instead of always using contourf, it uses imshow when it is being 
> used with a nearly continuous set of colors instead of a small discrete 
> set.
> 
> I have not had time to look at this closely, but I can add it to my list.
> 
> Eric
> 

Although updating the colorbar when the image data changes should be the 
default behaviour will there be a way to keep the colorbar from 
changing? I've got a visualization application where an image changes 
according to the position it's currently displaying but I want to keep 
the colorbar that reflects the largest value. Right now I just display 
first the image that has the largest value and the colorbar stays the 
same. Whatever the buggy behaviour an application has someone is taking 
advantage of it :-)

João Silva

On Apr 18, 2006, at 4:15 AM, massimo sandal wrote:
> Just a question: Why is the replot hack needed? It works, but I  
> tried without, and it seems that mpl is not able to redraw itself  
> correctly with a draw() call. Is it a known mpl bug/issue/"feature"?

It's more of a WxMpl problem.  Matplotlib's Axes class has no concept  
of "zoom" history.  WxMpl keeps track of the zoom history (e.g. axes  
view limits) separately, but doesn't make any attempt to integrate  
that into PlotPanel.draw().

I've only come to realize this was a problem recently, as I've begun  
to use WxMpl in increasingly interactive situations.  I've been  
planning to take care of saving and restoring the view limits  
automatically in PlotPanel.draw() so library users won't have think  
about it.  Perhaps the right thing to do is put a matplotlib patch  
together to add zoom(xlim, ylim) and unzoom() methods to Axes.

> Also, it would be nice to add something about the issue of clicking  
> data in the wxmpl docs, just for the relief of dumb newbies like  
> me. I can sketch it for you if you like.

Don't worry about it, it sounds like you have enough on your plate.   
I'll add something to the tutorial before the next release.

> If there are other wxmpl-related issues, I'll take the liberty to  
> let you know!

Please do, and don't hesitate to let me know if there are features  
that you think would be valuable.

As an aside, you should take a look at the current development  
version [1].  I think I've finally managed to remove any traces of  
crosshair junk due to repaints, window focus changes, etc.  The hope  
is that this will make for a more polished user experience.

Ken

[1] http://svn.csrri.iit.edu/mr-software/wxmpl/trunk

>>>>> "Duncan" == Duncan Brown <db...@li...> writes:

    Duncan> Is there some kind of maximum size for a
    Duncan> matplotlib.lines.Line2D instance? I am trying to make
    Duncan> plots of noise for signal processing, and matplotlib fails
    Duncan> to plot the entire array of data. For example, if I
    Duncan> generate 262144 random numbers with

This was a bug in the line drawing functionality of the Agg backend,
and it is fixed in svn revision 2300.  Thanks for the report!

JDH

>>>>> "andrea" == andrea gavana@tin it <and...@ti...> writes:

    andrea> Hello NG, I am facing a small problem for which I was
    andrea> unable to find a solution. Basically, I have to make a
    andrea> scatter plot of x, y coordinates (they represents oil
    andrea> wells positions) on a 2D map, but I have some constraints:

    andrea> 1) I would like to have each point as a separate "plot
    andrea> object", because the user may decide to hide/show only a
    andrea> particular well, or show/hide them all, or show/hide
    andrea> whatever combination of wells.  2) At the moment when the
    andrea> class that holds a single well position/status is created,
    andrea> the plot window may not be there (because is the user that
    andrea> decides when to open a new plot window).

    andrea> I have tried something like:

Hey Andrea, sorry for the delay.  This is a neat problem and one that
collections were designed to solve.  You probably want to use a
RegularPolyCollection rather than a PolyCollection (the latter is for
arbitrary polygons and you must compute all the vertices yourself).
Here is an example that allows you to add and delete markers -- it
inserts them with random positions and colors.  You should be able to
adapt it to your application quite easily.

import random
from matplotlib.colors import colorConverter
from matplotlib.collections import RegularPolyCollection 
import matplotlib.cm as cm
from pylab import figure, show, nx

fig = figure()
ax = fig.add_subplot(111, xlim=(0,1), ylim=(0,1), autoscale_on=False)
ax.set_title("Press 'a' to add a point, 'd' to delete one")
# a single point
offsets = [(0.5,0.5)]
facecolors = [cm.jet(0.5)]

collection = RegularPolyCollection(
    fig.dpi,
    numsides=5, # a pentagon
    rotation=0,
    sizes=(50,), 
    facecolors = facecolors,
    edgecolors = (colorConverter.to_rgba('black'),),
    linewidths = (1,),
    offsets = offsets,
    transOffset = ax.transData,
    )

ax.add_collection(collection)

def onpress(event):
    """
    press 'a' to add a random point from the collection, 'd' to delete one
    """
    if event.key=='a':
        x,y = nx.mlab.rand(2)
        color = cm.jet(nx.mlab.rand())
        offsets.append((x,y))
        facecolors.append(color)
        fig.canvas.draw()
    elif event.key=='d':
        N = len(offsets)
        if N>0:
            ind = random.randint(0,N-1)
            offsets.pop(ind)
            facecolors.pop(ind)
            fig.canvas.draw()

fig.canvas.mpl_connect('key_press_event', onpress)

show()

John Hunter wrote:
>     John> I don't have one and I don't think it's good design for my
>     John> software installer to go creating one for people as part of
>     John> a larger software installation. I think that sniffing would
>     John> be a better (complementary, not replacement) solution, so
>     John> that whichever the user decides to install, it just works.
>
> You have a few options.  You can set the rc parameters inside your
> script, you do not need to change a system wide rc file
>
>   from matplotlib import rcParams
>   rcParams['numerix'] = 'numpy'
>   #...now import matplotlib.numerix, pylab, etc...
>   
That's what I'm currently using, actually (see start of this thread).
> You can also provide per directory configuration files.  Ie, you can
> create a matplotlibrc file (http://matplotlib.sf.net/matplotlibrc) in
> the same dir as your main-level script, and it will respect that one
> so you need not worry about overriding a system rc file when you
> install your software.
>   
I already have a config file for our application, if I did anything like 
this it would be to add an extra option to our existing config file, not 
create an additional one. Although this one was nice to know.
>     John> For now I will select numpy. Is that the one that Matplotlib
>     John> looks for first?
>
> There are two issues here: build time configuration and run time
> configuration.  We used to do neither, now at built time we try and
> find one of numpy/numarray/Numeric (in that order) and then generate
> an rc file with the found one as the default.
>
> We could also do run time dynamic imports.  I'm of two minds here: the
> more we try and do automatically, the harder it is to detect and fix
> bugs and problems when they arise.  The setup is already pretty
> complex, if we are automatically choosing numerix and backend
> settings, I could see some difficulties in debugging problems.  But I
> can see the advantages to it as well...
>   
I'm thinking that *if* a preference has been specified, that should be 
used (and possibly throw and error if it fails). But if no preference is 
specified, then a sniffing approach should work, something like the 
following, which has worked for me without any issues so far, on a 
number of different platforms. This approach would facilitate debugging, 
knowing that you can force a particular numeric-array import.

try:
    import psyco
    psyco.full()
    print "Running with PSYCO optimisation..."
except ImportError:
    pass

-- 
John Pye
Department of Mechanical and Manufacturing Engineering
University of New South Wales, Sydney, Australia
http://pye.dyndns.org/

Is anyone using matplotlib with the GTK backend with pygtk version 2.0.0?
If not I'd like to change backend_gtk.py to require pygtk 2.2.0 or higher.

Steve

Send instant messages to your online friends http://au.messenger.yahoo.com 

>>>>> "John" == John Pye <joh...@st...> writes:

    John> I don't have one and I don't think it's good design for my
    John> software installer to go creating one for people as part of
    John> a larger software installation. I think that sniffing would
    John> be a better (complementary, not replacement) solution, so
    John> that whichever the user decides to install, it just works.

You have a few options.  You can set the rc parameters inside your
script, you do not need to change a system wide rc file

  from matplotlib import rcParams
  rcParams['numerix'] = 'numpy'
  #...now import matplotlib.numerix, pylab, etc...

You can also provide per directory configuration files.  Ie, you can
create a matplotlibrc file (http://matplotlib.sf.net/matplotlibrc) in
the same dir as your main-level script, and it will respect that one
so you need not worry about overriding a system rc file when you
install your software.

    John> For now I will select numpy. Is that the one that Matplotlib
    John> looks for first?

There are two issues here: build time configuration and run time
configuration.  We used to do neither, now at built time we try and
find one of numpy/numarray/Numeric (in that order) and then generate
an rc file with the found one as the default.

We could also do run time dynamic imports.  I'm of two minds here: the
more we try and do automatically, the harder it is to detect and fix
bugs and problems when they arise.  The setup is already pretty
complex, if we are automatically choosing numerix and backend
settings, I could see some difficulties in debugging problems.  But I
can see the advantages to it as well...

JDH

>>>>> "Malte" == Malte Marquarding <Mal...@cs...> writes:


    Malte> Laziness ;-) Thanks, I just needed to know if there is
    Malte> something I might have overlooked.  I just couldn't think
    Malte> of a case where you would want to change the tick label
    Malte> size on an individual basis, so I thought there would be a
    Malte> method in "axes.xaxis/axes.yaxis" to do this to the whole
    Malte> list.

    Malte> Is this something which could be added to the Formatter
    Malte> classes, or maybe a Styler Class to change Font properties
    Malte> and colors.

You can change the default tick label size by setting an rc
configuration parameter -- http://matplotlib.sf.net/matplotlibrc.  See
the properties

  xtick.major.size     : 4      # major tick size in points
  xtick.minor.size     : 2      # minor tick size in points
  xtick.major.pad      : 4      # distance to major tick label in points
  xtick.minor.pad      : 4      # distance to the minor tick label in points
  xtick.color          : k      # color of the tick labels
  xtick.labelsize      : 12     # fontsize of the tick labels
  xtick.direction      : in     # direction: in or out

and ditto for yaxis.  Also, if you like to save typing, you can use
the setp functionality to set multiple properties for multiple objects
w/o changing the defaults

  setp(ax.get_xticklabels(), fontsize=12, color='red')


JDH

Hi,
sorry if I haven't been alive for a while but...

> Always happy to help save a life!  ;-)

...yes, it seems it's working, and my life is (temporarily) safe! :D

Thanks a lot for your help. The mix of learning wx, threading and 
matplotlib (plus a bunch of other things, like XML libs) all at once 
(and all almost in my spare time) was driving me mad... that's the life 
of grad students.

Just a question: Why is the replot hack needed? It works, but I tried 
without, and it seems that mpl is not able to redraw itself correctly 
with a draw() call. Is it a known mpl bug/issue/"feature"?

Also, it would be nice to add something about the issue of clicking data 
in the wxmpl docs, just for the relief of dumb newbies like me. I can 
sketch it for you if you like.

If there are other wxmpl-related issues, I'll take the liberty to let 
you know!

m.


-- 
Massimo Sandal
University of Bologna
Department of Biochemistry "G.Moruzzi"

snail mail:
Via Irnerio 48, 40126 Bologna, Italy

email:
mas...@un...

tel: +39-051-2094388
fax: +39-051-2094387

There was a thread on this subject (eps without figure frame) awhile back (for 
example, http://sourceforge.net/mailarchive/message.php?msg_id=13894773), but 
I could not find a final solution posted. 

Here's what worked for me:

fig = figure()
setp(fig.figurePatch, width=0.0, height=0.0, facecolor=anycolor, 
edgecolor=anycolor, linewidth=0.0)

The only difference with the previous posts is to set the width and height of 
the figurePatch Rectangle to zero.

I don't have one and I don't think it's good design for my software 
installer to go creating one for people as part of a larger software 
installation. I think that sniffing would be a better (complementary, 
not replacement) solution, so that whichever the user decides to 
install, it just works.

For now I will select numpy. Is that the one that Matplotlib looks for 
first?

Ryan Krauss wrote:
> just set
> numerix : numpy
> in your matplotlibrc and all will be happy.
-- 
John Pye
Department of Mechanical and Manufacturing Engineering
University of New South Wales, Sydney, Australia
http://pye.dyndns.org/

Laziness ;-)

Thanks, I just needed to know if there is something I might have overlooked.
I just couldn't think of a case where you would want to change the tick label 
size on an individual basis, so I thought there would be a method in 
"axes.xaxis/axes.yaxis"  to do this to the whole list.

Is this something which could be added to the Formatter classes, or maybe a 
Styler Class to change Font properties and colors.

Cheers,
Malte.

On Tuesday 18 April 2006 13:48, you wrote:
> >>>>> "Malte" == Malte Marquarding <Mal...@cs...> writes:
>
>     Malte> Hi, I have a related question.  How do I change the
>     Malte> (font)size of the ticklabels, without having to step
>     Malte> through them?
>
> What is wrong with stepping through them?
>
> JDH

>>>>> "Malte" == Malte Marquarding <Mal...@cs...> writes:

    Malte> Hi, I have a related question.  How do I change the
    Malte> (font)size of the ticklabels, without having to step
    Malte> through them?  

What is wrong with stepping through them?

JDH

Hi,

I have a related question.  How do I change the (font)size of the ticklabels, 
without having to step through them?
I have "ganged" plots and am scaling fonts by a factor depending on nrows and 
ncolumns. 
I also need this for the size of the legend "labels"

Cheers,
Malte

On Friday 14 April 2006 04:25, Ryan Krauss wrote:
> The new formatter works pretty well.  One change though, the last line
> should be:
>
> else: return LogFormatterMathtext.__call__(self, x, pos)
>
> Thanks,
>
> John
>
> On 4/13/06, John Hunter <jdh...@ac...> wrote:
> > >>>>> "Ryan" == Ryan Krauss <rya...@gm...> writes:
> >
> >     Ryan> My love of large fonts is causing a problem.  If you look at
> >     Ryan> the attached figure, I typically have x and y tick marks
> >     Ryan> that nearly collide in the lower left hand corner of each
> >     Ryan> subplot.  I typically end up setting the yticks by hand, but
> >     Ryan> this isn't super convienent for each plot.  I am about to
> >     Ryan> right a function to drop the lowest ytick label, but is
> >     Ryan> there a better approach?
> >
> > Increase the xtick.major.pad and/or ytick.major.pad rc settings by a
> > couple of points.
> >
> > Alternatively, if you do want to drop the leftmost xtick label, for
> > instance, you can easily derive a custom formatter.  Here you are using
> > the LogFormatterMathtext
> >
> > from matplotlib.ticker import LogFormatterMathtext
> >
> > class MyFormatter(LogFormatterMathtext):
> >     def __call__(self, x, pos=None):
> >         if pos==0: return ''  # pos=0 is the first tick
> >         else: return LogFormatterMathtext(self, x, pos)
> >
> > ax.xaxis.set_major_formatter(MyFormatter())
> >
> > Nice looking figure!
> > JDH
>

just set
numerix : numpy
in your matplotlibrc and all will be happy.

Ryan

On 4/17/06, Gary Ruben <gr...@bi...> wrote:
> Hi John,
>
> John Pye wrote:
> > Hi all
> >
> > I'm having a bit of trouble making sense of all the different
> > numeric-array libraries that Matplotlib uses and allows. We're using
> > Matplotlib as part of a larger application, and I want to make sure we
> > use the best combination of libraries.
> >
> > Is it a case of 'whichever you like' or is one of the numeric-array
> > libraries clearly better and more stable than the others?
>
> They're all very stable, but I believe Numeric is explicitly not being
> supported anymore and numarray will probably eventually stop being
> supported in favour of numpy. numpy is very stable now, so my advice it
> to use numpy. This is an easier decision now than it was a few months
> ago since numpy will soon hit its 1.0 release. One post on this or the
> developer list suggested that Numeric and numarray support will
> eventually be removed from Matplotlib, but I think we are talking way
> off in the future for that.
>
> > Also, what is Scipy doing these days? Is matplotlib still buried away
> > inside it, as I believe it was, or have they switched to another
> > plotting library altogether? I saw something about 'dynamic plots' but =
I
> > wasn't sure it was at stable or development stage.
>
> Matplotlib was never a part of scipy. You may be thinking of gplt or
> xplt (from memory). Matplotlib remains completely separate from scipy
> but requires one of Numeric, numarray or numpy - your choice.
>
> > Finally, from the documentation of Matplotlib, I got the impression tha=
t
> > it would 'sniff out' and find a suitable numeric-array library. Instead
> > it seems that it only tries to include one ('numeric' as I recall), and
> > if you want to use any other one it won't try for it, you have to
> > manually tell it so using something like the following. Would some
> > automated attempt to load the numeric-array libraries, in order of most
> > preferred to least preferred, be appropriate in the matplotlib code?
>
> You're right; it doesn't sniff out the package you want, although I
> think it would be nice if it did. However, this will soon be unimportant
> because everyone will be using numpy and that will become the default.
>
> > import matplotlib
> > import numarray
> > matplotlib.rcParams['numerix'] =3D 'numarray' import pylab
> >
> > If I want to "back the winning horse" here, which numeric library shoul=
d
> > I tell the users of our software to install?
> >
> > Cheers
> > JP
>
> Makybe Diva =3D numpy
>
> i.e. it's a one horse race.
>
> Gary
>
>
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Dear Martinho,

"fill" is just a thin wrapper around matplotlib.patches.Polygon, which 
is just a thin wrapper around the backend's draw polygon functionality. 
It appears that Agg, at least, fills in the inside of the shape you've 
drawn.  The matplotlib developers should probably incorporate some sort 
of triangulation algorithm so that polygons such as yours get drawn 
properly. In the meantime, perhaps you're interested in such an 
algorithm yourself: http://www.cs.unc.edu/~dm/CODE/GEM/chapter.html

Cheers!
Andrew

Martinho MA wrote:

> the command fill(x,y), where x,y are:
>
> In [274]: x,y
> Out[274]:
> ([-9.       ,-9.       ,-8.       ,-8.       ,-9.       ,-9.       
> ,-8.7659284,
>      -8.7659284,-8.7645363,-8.6595349,-8.649452 ,-8.6487604,-8.647775 ,
>      -8.6458589,-8.6474525,-8.5967471,-8.4710347,-8.4494473,-8.3825453,
>      -8.2483344,-8.0963785,-8.1251909,-8.2621139,-8.2901728,-8.2729088,
>      -8.2487353,-8.3169042,-8.3374447,-8.3708706,-8.486742 ,-8.4865633,
>      -8.5783225,-8.6306292,-8.7659284,],
> [ 40.506093, 41.2     , 41.2     , 40.2     , 40.2     , 40.506093, 
> 40.506093,
>       40.506093, 40.578751, 40.923346, 40.970168, 40.978045, 40.986113,
>       40.995789, 41.004918, 41.016188, 41.026401, 41.047271, 41.003575,
>       41.057014, 40.980312, 40.929052, 40.780916, 40.667243, 40.604054,
>       40.510189, 40.491699, 40.427127, 40.340239, 40.289163, 40.332598,
>       40.417435, 40.435353, 40.506093,])
>
>
> was supposed to fill outside some polygon (it does with matlab)
> With matplotlib it fills all including the inside the  polygon!!
> Can someone tell me fill(x,y) is not working in this case as with 
> matlab ?
>
> Thanks
>
>
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Hi John,

John Pye wrote:
> Hi all
> 
> I'm having a bit of trouble making sense of all the different 
> numeric-array libraries that Matplotlib uses and allows. We're using 
> Matplotlib as part of a larger application, and I want to make sure we 
> use the best combination of libraries.
> 
> Is it a case of 'whichever you like' or is one of the numeric-array 
> libraries clearly better and more stable than the others?

They're all very stable, but I believe Numeric is explicitly not being 
supported anymore and numarray will probably eventually stop being 
supported in favour of numpy. numpy is very stable now, so my advice it 
to use numpy. This is an easier decision now than it was a few months 
ago since numpy will soon hit its 1.0 release. One post on this or the 
developer list suggested that Numeric and numarray support will 
eventually be removed from Matplotlib, but I think we are talking way 
off in the future for that.

> Also, what is Scipy doing these days? Is matplotlib still buried away 
> inside it, as I believe it was, or have they switched to another 
> plotting library altogether? I saw something about 'dynamic plots' but I 
> wasn't sure it was at stable or development stage.

Matplotlib was never a part of scipy. You may be thinking of gplt or 
xplt (from memory). Matplotlib remains completely separate from scipy 
but requires one of Numeric, numarray or numpy - your choice.

> Finally, from the documentation of Matplotlib, I got the impression that 
> it would 'sniff out' and find a suitable numeric-array library. Instead 
> it seems that it only tries to include one ('numeric' as I recall), and 
> if you want to use any other one it won't try for it, you have to 
> manually tell it so using something like the following. Would some 
> automated attempt to load the numeric-array libraries, in order of most 
> preferred to least preferred, be appropriate in the matplotlib code?

You're right; it doesn't sniff out the package you want, although I 
think it would be nice if it did. However, this will soon be unimportant 
because everyone will be using numpy and that will become the default.

> import matplotlib
> import numarray
> matplotlib.rcParams['numerix'] = 'numarray' import pylab
> 
> If I want to "back the winning horse" here, which numeric library should 
> I tell the users of our software to install?
> 
> Cheers
> JP

Makybe Diva = numpy

i.e. it's a one horse race.

Gary

Hi all

I'm having a bit of trouble making sense of all the different 
numeric-array libraries that Matplotlib uses and allows. We're using 
Matplotlib as part of a larger application, and I want to make sure we 
use the best combination of libraries.

Is it a case of 'whichever you like' or is one of the numeric-array 
libraries clearly better and more stable than the others?

Also, what is Scipy doing these days? Is matplotlib still buried away 
inside it, as I believe it was, or have they switched to another 
plotting library altogether? I saw something about 'dynamic plots' but I 
wasn't sure it was at stable or development stage.

Finally, from the documentation of Matplotlib, I got the impression that 
it would 'sniff out' and find a suitable numeric-array library. Instead 
it seems that it only tries to include one ('numeric' as I recall), and 
if you want to use any other one it won't try for it, you have to 
manually tell it so using something like the following. Would some 
automated attempt to load the numeric-array libraries, in order of most 
preferred to least preferred, be appropriate in the matplotlib code?

import matplotlib
import numarray
matplotlib.rcParams['numerix'] = 'numarray' 
import pylab

If I want to "back the winning horse" here, which numeric library should 
I tell the users of our software to install?

Cheers
JP

-- 
John Pye
Department of Mechanical and Manufacturing Engineering
University of New South Wales, Sydney, Australia
http://pye.dyndns.org/

Hi,

I'm fairly new to matplotlib and I have a question which may be  
obvious, but I haven't been able to figure out an answer.

Is there some kind of maximum size for a matplotlib.lines.Line2D  
instance? I am trying to make plots of noise for signal processing,  
and matplotlib fails to plot the entire array of data. For example,  
if I generate 262144 random numbers with

Python 2.4.1 (#1, May 16 2005, 15:19:29)
[GCC 4.0.0 20050512 (Red Hat 4.0.0-5)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
 >>> from pylab import *
 >>> x = rand(262144)
 >>> plot(x)
[<matplotlib.lines.Line2D instance at 0xb726b70c>]
 >>> xlim(0,262144)
(0, 262144)
 >>> show()

Then the plot terminates after ~ 30000 points. However, if I make the  
plot with points, e.g.

 >>> plot(x,'.')
[<matplotlib.lines.Line2D instance at 0xb728b5cc>]
 >>> show()

Then the plot looks correct. Any idea how I can make line plots of  
this? I'm using

python-matplotlib-0.86-1.fc4

Cheers,
Duncan.

-- 
Duncan Brown                                 California Institute of  
Technology
Tapir: (626) 395 8409                         MS 18-34, Pasadena, CA  
91125, USA
LIGO:  (626) 395 8812                 http://www.lsc- 
group.phys.uwm.edu/~duncan

the command fill(x,y), where x,y are:

In [274]: x,y
Out[274]:
([-9.       ,-9.       ,-8.       ,-8.       ,-9.       ,-9.       
,-8.7659284,
      -8.7659284,-8.7645363,-8.6595349,-8.649452 ,-8.6487604,-8.647775 ,
      -8.6458589,-8.6474525,-8.5967471,-8.4710347,-8.4494473,-8.3825453,
      -8.2483344,-8.0963785,-8.1251909,-8.2621139,-8.2901728,-8.2729088,
      -8.2487353,-8.3169042,-8.3374447,-8.3708706,-8.486742 ,-8.4865633,
      -8.5783225,-8.6306292,-8.7659284,],
 [ 40.506093, 41.2     , 41.2     , 40.2     , 40.2     , 40.506093, 
40.506093,
       40.506093, 40.578751, 40.923346, 40.970168, 40.978045, 40.986113,
       40.995789, 41.004918, 41.016188, 41.026401, 41.047271, 41.003575,
       41.057014, 40.980312, 40.929052, 40.780916, 40.667243, 40.604054,
       40.510189, 40.491699, 40.427127, 40.340239, 40.289163, 40.332598,
       40.417435, 40.435353, 40.506093,])


was supposed to fill outside some polygon (it does with matlab)
With matplotlib it fills all including the inside the  polygon!!
Can someone tell me fill(x,y) is not working in this case as with matlab ?

Thanks

Hello NG,

    I am facing a small problem for which I was unable to 
find a solution. Basically, I have to make a scatter plot of x, y 
coordinates (they represents oil wells positions) on a 2D map, but I 
have some constraints:

1) I would like to have each point as a 
separate "plot object", because the user may decide to hide/show only a 
particular well, or show/hide them all, or show/hide whatever 
combination of wells.
2) At the moment when the class that holds a 
single well position/status is created, the plot window may not be 
there (because is the user that decides when to open a new plot 
window).

I have tried something like:

def BuildMPLActor(self):

    # 
the MPL Actor is a single well
    point = [(xpos, ypos)]
    self.
well2d = PolyCollection(point)


And, after the user creates the plot 
window, I do:

MyAxis.add_collection(self.well2d)

Obviously, it 
doesn't work. It throws a fantastic error like the following:

<snip>
  
File "C:\Python23\Lib\site-packages\matplotlib\collections.py", line 
439
raw
    self._transOffset)
TypeError: CXX : Error creating object 
of type N2Py7SeqBaseINS_6ObjectEEE


Does anyone have some suggestion 
on how to solve this problem (if you think there are better strategies 
to implement this, I am open to all suggestions/ideas).

Thank you very 
much for your help.

Andrea.