matplotlib-users Mailing List for matplotlib

Suresh Pillai wrote:
> Thanks. Suspected as much re integer vs float.
> 
> Which brings me to the question: if we are able to debug issues 
> ourselves, should we just post to this list or the devel list or 
> contribute privately.
Definitely to one of the lists. If you think other users may be 
interested in the bug, or may have seen it and may have a solution, then 
post to the users list. I expect this will usually be the case. But 
(for example) if you see something in the code that you think should be 
done differently, but is not causing immediate problems, then you might 
want to post that the the devel list instead, on the grounds that it 
would not be of interest to users who are not also devel subscribers.
Eric
> 
> Thanks,
> Suresh

Thanks. Suspected as much re integer vs float.
Which brings me to the question: if we are able to debug issues ourselves, 
should we just post to this list or the devel list or contribute privately.
Thanks,
Suresh
On Mon, 2 Apr 2007, Eric Firing wrote:
> I see where the problem (or at least one problem) is, and I will try to get
> it fixed by tomorrow. In the meantime, I think you will get the results you
> want by simply converting your arrays to floating point:
>
> matshow(matrix.astype(float), ...)
>
> Eric
>
> Suresh Pillai wrote:
> > So I been using the log scale provided by matplotlib.colors.LogNorm, but
> > have been seing bizarre behaviour. Basically, high values are not
> > displayed properly. I give simple examples below with just two possible
> > values in the matrix, but all the same issues arise with more varied
> > values.
> > 
> > First notice that the high value (100000) is displayed as being of
> > value=1:
> > 
> > from pylab import *
> > from matplotlib.colors import LogNorm
> > 
> > matrix = ones((30,30))
> > matrix = matrix*440
> > matrix[29,29] = 100000
> > 
> > matshow(matrix, norm=LogNorm(vmin=1, vmax=1000000))
> > colorbar()
> > show()
> > 
> > The cutoff value for incorrect display (for the scale I am using) seems 
> > to
> > be at 32000:
> > 
> > from pylab import *
> > from matplotlib.colors import LogNorm
> > 
> > matrix = ones((30,30))
> > matrix = matrix*440
> > matrix[29,29] = 32000
> > 
> > matshow(matrix, norm=LogNorm(vmin=1, vmax=1000000))
> > colorbar()
> > show()
> > 
> > However, if the value is really high, the color displayed changes again,
> > although still not to the correct color (please try with values 918000,
> > 920000, and 999000 to see see it progress):
> > 
> > from pylab import *
> > from matplotlib.colors import LogNorm
> > 
> > matrix = ones((30,30))
> > matrix = matrix*440
> > matrix[29,29] = 918000
> > 
> > matshow(matrix, norm=LogNorm(vmin=1, vmax=1000000))
> > colorbar()
> > show()
> > 
> > And if one specifies no limits to LogNorm, the colorbar displayed is
> > incomplete and the colour displayed is wrong in a different way then when
> > specifying the limits (try value = 999000 as well).
> > 
> > from pylab import *
> > from matplotlib.colors import LogNorm
> > 
> > matrix = ones((30,30))
> > matrix = matrix*440
> > matrix[29,29] = 918000
> > 
> > matshow(matrix, norm=LogNorm())
> > colorbar()
> > show()
> > 
> > 
> > Either I am completely missing something or there is a major bug.
> > 
> > I am using mpl checked out from svn on 26 March.
> > 
> > Thanks,
> > Suresh
> > 
> > -------------------------------------------------------------------------
> > Take Surveys. Earn Cash. Influence the Future of IT
> > Join SourceForge.net's Techsay panel and you'll get the chance to share
> > your
> > opinions on IT & business topics through brief surveys-and earn cash
> > http://www.techsay.com/default.php?page=join.php&p=sourceforge&CID=DEVDEV
> > _______________________________________________
> > Matplotlib-users mailing list
> > Mat...@li...
> > https://lists.sourceforge.net/lists/listinfo/matplotlib-users
> 
>

I see where the problem (or at least one problem) is, and I will try to 
 get it fixed by tomorrow. In the meantime, I think you will get the 
results you want by simply converting your arrays to floating point:
matshow(matrix.astype(float), ...)
Eric
Suresh Pillai wrote:
> So I been using the log scale provided by matplotlib.colors.LogNorm, but 
> have been seing bizarre behaviour. Basically, high values are not 
> displayed properly. I give simple examples below with just two possible 
> values in the matrix, but all the same issues arise with more varied 
> values.
> 
> First notice that the high value (100000) is displayed as being of 
> value=1:
> 
> from pylab import *
> from matplotlib.colors import LogNorm
> 
> matrix = ones((30,30))
> matrix = matrix*440
> matrix[29,29] = 100000
> 
> matshow(matrix, norm=LogNorm(vmin=1, vmax=1000000))
> colorbar()
> show()
> 
> The cutoff value for incorrect display (for the scale I am using) seems to 
> be at 32000:
> 
> from pylab import *
> from matplotlib.colors import LogNorm
> 
> matrix = ones((30,30))
> matrix = matrix*440
> matrix[29,29] = 32000
> 
> matshow(matrix, norm=LogNorm(vmin=1, vmax=1000000))
> colorbar()
> show()
> 
> However, if the value is really high, the color displayed changes again, 
> although still not to the correct color (please try with values 918000, 
> 920000, and 999000 to see see it progress):
> 
> from pylab import *
> from matplotlib.colors import LogNorm
> 
> matrix = ones((30,30))
> matrix = matrix*440
> matrix[29,29] = 918000
> 
> matshow(matrix, norm=LogNorm(vmin=1, vmax=1000000))
> colorbar()
> show()
> 
> And if one specifies no limits to LogNorm, the colorbar displayed is 
> incomplete and the colour displayed is wrong in a different way then when 
> specifying the limits (try value = 999000 as well).
> 
> from pylab import *
> from matplotlib.colors import LogNorm
> 
> matrix = ones((30,30))
> matrix = matrix*440
> matrix[29,29] = 918000
> 
> matshow(matrix, norm=LogNorm())
> colorbar()
> show()
> 
> 
> Either I am completely missing something or there is a major bug.
> 
> I am using mpl checked out from svn on 26 March.
> 
> Thanks,
> Suresh
> 
> -------------------------------------------------------------------------
> Take Surveys. Earn Cash. Influence the Future of IT
> Join SourceForge.net's Techsay panel and you'll get the chance to share your
> opinions on IT & business topics through brief surveys-and earn cash
> http://www.techsay.com/default.php?page=join.php&p=sourceforge&CID=DEVDEV
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users

A really great IDE for windows users is pyScripter (
http://mmm-experts.com/Products.aspx?ProductId=4 )
It's probably the best I could try so far (and it's free).
cheers
On 3/30/07, Tim Hirzel <hi...@re...> wrote:
> As for a good IDE. I really like eclipse with pydev. For easy
> student/beginner setup, easyclipse has a nice python eclipse distribution
>
> http://www.easyeclipse.org/site/distributions/index.html
>
> I think I've tried near every python IDE setup out there over the last
> couple years, and this one wins for me.
>
> tim
> >
>
> -------------------------------------------------------------------------
> Take Surveys. Earn Cash. Influence the Future of IT
> Join SourceForge.net's Techsay panel and you'll get the chance to share your
> opinions on IT & business topics through brief surveys-and earn cash
> http://www.techsay.com/default.php?page=join.php&p=sourceforge&CID=DEVDEV
> _______________________________________________
> Matplotlib-users mailing list
> Mat...@li...
> https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>

So I been using the log scale provided by matplotlib.colors.LogNorm, but 
have been seing bizarre behaviour. Basically, high values are not 
displayed properly. I give simple examples below with just two possible 
values in the matrix, but all the same issues arise with more varied 
values.
First notice that the high value (100000) is displayed as being of 
value=1:
from pylab import *
from matplotlib.colors import LogNorm
matrix = ones((30,30))
matrix = matrix*440
matrix[29,29] = 100000
matshow(matrix, norm=LogNorm(vmin=1, vmax=1000000))
colorbar()
show()
The cutoff value for incorrect display (for the scale I am using) seems to 
be at 32000:
from pylab import *
from matplotlib.colors import LogNorm
matrix = ones((30,30))
matrix = matrix*440
matrix[29,29] = 32000
matshow(matrix, norm=LogNorm(vmin=1, vmax=1000000))
colorbar()
show()
However, if the value is really high, the color displayed changes again, 
although still not to the correct color (please try with values 918000, 
920000, and 999000 to see see it progress):
from pylab import *
from matplotlib.colors import LogNorm
matrix = ones((30,30))
matrix = matrix*440
matrix[29,29] = 918000
matshow(matrix, norm=LogNorm(vmin=1, vmax=1000000))
colorbar()
show()
And if one specifies no limits to LogNorm, the colorbar displayed is 
incomplete and the colour displayed is wrong in a different way then when 
specifying the limits (try value = 999000 as well).
from pylab import *
from matplotlib.colors import LogNorm
matrix = ones((30,30))
matrix = matrix*440
matrix[29,29] = 918000
matshow(matrix, norm=LogNorm())
colorbar()
show()
Either I am completely missing something or there is a major bug.
I am using mpl checked out from svn on 26 March.
Thanks,
Suresh

massimo sandal wrote:
> javi markez bigara ha scritto:
>> hi everyone,
>> i would like to know how to plot several linear regresions with the 
>> same group of points,,,,
Don't understand exactly what you want to do ...
> 
> what do you mean?
> 
> however, if you dig the matplotlib and the scipy documentation, you'll 
> find (a)how to plot points (easy) (b)how to calculate linear regressions 
> (this one is less straightforward than it should be, however now I don't 
> remember the details - I can check my code if you have trouble in 
> finding it by yourself).
One easy possibility (using numpy):
In [8]: import numpy as N
# make some sample data with noise
In [9]: x = N.linspace(0,10,100); y = 3*x + 5 + N.random.randn(len(x))*3
In [10]: p = N.polyfit(x, y, 1)
In [11]: p
Out[11]: array([ 3.02862193, 5.14341042])
In [12]: plot(x, y, 'o')
Out[12]: [<matplotlib.lines.Line2D instance at 0xa376aacc>]
In [13]: plot(x, N.polyval(p,x), 'r')
Out[13]: [<matplotlib.lines.Line2D instance at 0xa37734cc>]
Note: matplotlib also has random numbers (e.g. pylab.randn, but I think 
this is imported from numpy), as well as linspace and also polyfit and 
polyval, so importing numpy wouldn't even be necessary here. Another 
lin. reg. function is scipy.stats.linregress .... All roads lead to Rome.
-- 
cheers,
steve
Random number generation is the art of producing pure gibberish as 
quickly as possible.

javi markez bigara ha scritto:
> hi everyone,
> i would like to know how to plot several linear regresions with the same 
> group of points,,,,
> THANKS IN ADVANCE
what do you mean?
however, if you dig the matplotlib and the scipy documentation, you'll 
find (a)how to plot points (easy) (b)how to calculate linear regressions 
(this one is less straightforward than it should be, however now I don't 
remember the details - I can check my code if you have trouble in 
finding it by yourself).
do you use pylab or matplotlib embedded in something?
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

hi everyone,
i would like to know how to plot several linear regresions with the same 
group of points,,,,
THANKS IN ADVANCE
_________________________________________________________________
Descubre la descarga digital con MSN Music. Más de un millón de canciones. 
http://music.msn.es/

Simon Kammerer wrote:
> Hi list,
>
>
> when using clabel with basemap, it seems to me that clabel labels 
> contours outside the visible area of my maps, (see attached example).
>
> Any hints / workarounds? Or am I missing something?
>
> Regards
> Simon
>
>
> 
Simon: Yes, that's right - much of the data you are contouring falls 
outside the visible range of your map, and clabel doesn't know that. 
The only workaround I can think of is to only contour the data that's 
within the map you're interested in. One way to do this would be to 
create a masked array, with all the points outside the map region 
masked. The basemap instance has attributes xmin,xmax,ymin,ymax which 
define the corners of the map in projection coordinates - you can use 
these to determine which points on your grid are outside. Here's a 
modified version of your example that does this:
from matplotlib.toolkits.basemap import Basemap
import pylab as p
from matplotlib.numerix import ma
map = Basemap(llcrnrlon=-35.,llcrnrlat=25.,urcrnrlon=65.,urcrnrlat=55.,
 
resolution='l',area_thresh=1000.,projection='stere',lat_0=60.,lon_0=0.)
# draw coastlines, country boundaries, fill continents.
map.drawcoastlines()
map.drawcountries()
map.fillcontinents(color='coral')
# draw the edge of the map projection region (the projection limb)
#map.drawmapboundary()
# draw lat/lon grid lines every 30 degrees.
map.drawmeridians(p.arange(0,360,30))
map.drawparallels(p.arange(-90,90,30))
# make up some data on a regular lat/lon grid.
nlats = 73; nlons = 145; delta = 2.*p.pi/(nlons-1)
lats = (0.5*p.pi-delta*p.indices((nlats,nlons))[0,:,:])
lons = (delta*p.indices((nlats,nlons))[1,:,:])
wave = 0.75*(p.sin(2.*lats)**8*p.cos(4.*lons))
mean = 0.5*p.cos(2.*lats)*((p.sin(2.*lats))**2 + 2.)
# compute native map projection coordinates of lat/lon grid.
x, y = map(lons*180./p.pi, lats*180./p.pi)
mask1 = x < map.xmin
mask2 = x > map.xmax
mask3 = y > map.ymax
mask4 = y < map.ymin
mask = mask1+mask2+mask3+mask4
data = ma.masked_array(wave+mean,mask=mask)
# contour data over the map.
cs = map.contour(x,y,data,15,linewidths=1.5)
p.clabel(cs)
p.show()
-Jeff

Hi list,
when using clabel with basemap, it seems to me that clabel labels 
contours outside the visible area of my maps, (see attached example).
Any hints / workarounds? Or am I missing something?
Regards
Simon
[Modified wiki_example.py, labels visible with ortho projection, labels 
not visible with stere projection]
from matplotlib.toolkits.basemap import Basemap
import pylab as p
# set up orthographic map projection with
# perspective of satellite looking down at 50N, 100W.
# use low resolution coastlines.
#map = Basemap(projection='ortho',lat_0=50,lon_0=-100,resolution='l')
map = Basemap(llcrnrlon=-35.,llcrnrlat=25.,urcrnrlon=65.,urcrnrlat=55.,\ 
resolution='l',area_thresh=1000.,projection='stere', lat_0=60.,lon_0=0.)
# draw coastlines, country boundaries, fill continents.
map.drawcoastlines()
map.drawcountries()
map.fillcontinents(color='coral')
# draw the edge of the map projection region (the projection limb)
map.drawmapboundary()
# draw lat/lon grid lines every 30 degrees.
map.drawmeridians(p.arange(0,360,30))
map.drawparallels(p.arange(-90,90,30))
# lat/lon coordinates of five cities.
lats=[40.02,34.00,38.55,48.25,17.29]
lons=[-105.16,-119.40,-77.00,-114.21,-88.10]
cities=['Boulder, CO','Santa Cruz, CA',
 'Washington, DC','Whitefish, MT','Belize City, Belize']
# compute the native map projection coordinates for cities.
x,y = map(lons,lats)
# plot filled circles at the locations of the cities.
map.plot(x,y,'bo')
# plot the names of those five cities.
for name,xpt,ypt in zip(cities,x,y):
 p.text(xpt+50000,ypt+50000,name)
# make up some data on a regular lat/lon grid.
nlats = 73; nlons = 145; delta = 2.*p.pi/(nlons-1)
lats = (0.5*p.pi-delta*p.indices((nlats,nlons))[0,:,:])
lons = (delta*p.indices((nlats,nlons))[1,:,:])
wave = 0.75*(p.sin(2.*lats)**8*p.cos(4.*lons))
mean = 0.5*p.cos(2.*lats)*((p.sin(2.*lats))**2 + 2.)
# compute native map projection coordinates of lat/lon grid.
x, y = map(lons*180./p.pi, lats*180./p.pi)
# contour data over the map.
cs = map.contour(x,y,wave+mean,15,linewidths=1.5)
p.clabel(cs)
p.show()

Giorgio Luciano ha scritto:
> I'm aware that python/scipy were not started as a clone matlab (well 
> matlibplot was started as something similar ;)
Yes, matplotlib AFAIK wanted (and probably wants) to be something 
similar, and it's bad, because mpl is too good in itself to be forced to 
be just a matlab ripoff! :)
> and also that they should be taught as an language (and that's why I 
> prefer to use it an not to shol very useful programs like OCTAVE od 
> Scilab.. it's better for students to hava a curriculum with a true 
> programming language than with a metalanguage).
That's really good and I fully agree.
> I have to admit also that if someone there sooner or later would create 
> a workspace similar to matlab (with paste and copy, and more interactive 
> feature without tweaking too much) a lot more people would be glade to 
> replace their matlab with scipy/matplotlib.
A pythonic interacting environment IMHO should be a nice application in 
itself to write. It should have its own shell instead of relying on 
ipython (that is, it should not be a python shell, or a python shell 
*really* on steroids). I'd like to hear the pylab guys to know what they 
think.
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

Hi list,
is there a way to force clabel to label all contour lines?
Regards
Simon

Hi Archana,
Archana Ganesan wrote:
> Hi,
>
> I tried following the instructions at the py2exe site and I have also 
> uncommeneted and made it include the matplotlib.numerix package. Still 
> it doesnt seem to work. Is there any other way of compiling it into an 
> executable?
Did you try to compile the sample I enclosed the other day? Did that 
work? If not what error are you getting.
Are you using numpy or ?
Provide a small sample (with no dependencies if possible) which does not 
work for you with the corresponding setup.py.
Werner

Dear List -
Thanks for the discussion on the issue of the real strength of the
Python/matplotlib/numpy/scipy combo.
I use Python for both development and teaching, but my biggest question
concerned teaching.
When I teach, I need something easy and powerful, but also something that is
easy to install and 'feels' like other Windows software.
Furthermore, I don't want to teach them matlab (too expensive and too
restrictive) or any of its clones (cheaper, but still too restrictive).
So I settled on Python with matplotlib and am very happy with it.
In class, we always use it in interactive mode.
I use IDLE because it has a nice Windows feel to it and it comes with an
editor, even though I understand that ipython is much more powerful.
It is my experience that one of the big hurdles of using the
Python/matplotlib/numpy/scipy combo is installation. Many people are just
not comfortable installing a whole bunch of packages to get something to
work. In that respect the Enthought edition has been super (my only request
to them would be to make a new version available more frequent, but I know
they do this all for free so I even feel bad asking).
Regarding the "don't confuse the newbie" comment, I disagree. Many people
that come with a small programming background or a matlab background don't
get confused with the current documentation. I think it is pretty well done.
Maybe we need separate docs for inexperienced and experienced programmers?
The changes I suggested were to get more inexperienced programmers to join
the Python/matplotlib/numpy/scipy world.
I was re-reading the documentation on numpy in the bus this morning, in
preperation for a workshop I got to give (to mostly matlab guys). And boy,
is numpy nice. I have given the workshop several times, but always with
Numeric. I got quite some converts to matplotlib (from matlab) just because
they like the graphical output much better.
Mark

Thank for all the reply.
I will sure have a look at the video that Oliver suggest and I also 
downloaded Eclipse.
I'm "happy" that someone also shared my problems in teaching python.
I'm aware that python/scipy were not started as a clone matlab (well 
matlibplot was started as something similar ;)
and also that they should be taught as an language (and that's why I 
prefer to use it an not to shol very useful programs like OCTAVE od 
Scilab.. it's better for students to hava a curriculum with a true 
programming language than with a metalanguage).
I have to admit also that if someone there sooner or later would create 
a workspace similar to matlab (with paste and copy, and more interactive 
feature without tweaking too much) a lot more people would be glade to 
replace their matlab with scipy/matplotlib.
Giorgio

Peter L. Buschman wrote:
> 
> 
> Okay, removing the frame turns out to work like this.
> 
> ax=gca()
> setp(ax, frame_on=False)
> 
I'm new to matplotlib, and I can't even get this to work (let alone the
other fix of changing the colors). Could you elaborate about how to
implement this? I've tried putting these lines in the __init__ of the
PlotPanel() class, but I can't get it. Any help is appreciated, thank you.
-- 
View this message in context: http://www.nabble.com/Removing-the-black-border-around-a-plot--tf3409211.html#a9785048
Sent from the matplotlib - users mailing list archive at Nabble.com.

Antonino Ingargiola wrote:
> On 4/1/07, Antonino Ingargiola <tri...@gm...> wrote:
>> On 3/29/07, Ken McIvor <mc...@ii...> wrote:
> [cut]
>>>> The last think I'm not yet able to do is to update the colorbar to
>>>> autoscale with the new incoming data. The the script that follows
>>>> tries to update the colorbar too but it does not work (on matplotlib
>>>> 0.87 at least).
>>> I have no idea if this will help, but you might need to call
>>> AxesImage.changed() after calling AxesImage.set_data().
>> That doesn't help :(. I'm not jet able to update the colorbar once the
>> image has changed.
I have made a change in svn that should solve the problem. Now the 
following sequence works as expected (illustrated with ipython -pylab):
In [1]:IM = imshow(rand(3,4))
In [2]:CB = colorbar()
In [3]:IM.set_data(10*rand(3,4))
In [4]:draw()
In [5]:IM.autoscale()
In [6]:draw()
In [7]:IM.set_clim((0,20))
In [8]:draw()
The colorbar tracks the image, and either IM.autoscale or IM.set_clim 
causes the color mapping range to change for both the colorbar and the 
image.
Eric
> 
> I've found a way to update the colorbar after the image has changed:
> 
> image = imshow(data)
> colr_bar = colorbar()
> 
> ...
> 
> image.set_data(new_data)
> image.changed()
> color_bar.set_clim(vmax=newdata.max())
> draw()
> 
> The autoscale() colorbar method does not work to update a colorbar,
> but with the above code I can acheive the same result.
> 
> Thanks again.
> 
> ~ Antonio