matplotlib-users Mailing List for matplotlib

I'm trying to find a matplotlib 0.99.3 binary installer that works with 
the standard python.org Python (preferably 2.6) and hence works with Mac 
OS X 10.4 or greater. (I distribute an application that needs to run on 
a wide range of versions of Mac OS X).
The official binary I found refuses to install on my machine claiming it 
wants system python 2.6 (I happen to be running 10.5 so that's no use to 
me, and some users of my application are running 10.4).
I also tried the egg, but of course it fails -- presumably it's based on 
the same build.
If a binary isn't available I"ll make my own, but I figured I'd check 
first.
-- Russell

I have a non-matplotlib related project that requires usage of GSHHS dataset shapefiles.
The regular GSHHS dataset doesnt appear to include political boundaries, however the GSHHS dataset used by matplotlib/basemap does include country/border data. I'd like to extract matplotlib/basemap GSHHS country data & convert it to shapefile format.
specifically, the following files that are included with matplotlib/basemap:
countries_c.dat
countries_f.dat
countries_h.dat
countries_i.dat
countries_l.dat
countriesmeta_c.dat 
countriesmeta_f.dat
countriesmeta_h.dat
countriesmeta_i.dat
countriesmeta_l.dat
how can I convert these files to shapefile format, or where can I get shapefiles that already include this data & that are based on the GSHHS coastline data?
please help,
thanks,
P.Romero
 		 	 		 
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On 06/30/2010 10:40 AM, magnus_p wrote:
>
> I am trying to plot a spectrum, with lower x axis = velocity, on the upper =
> frequency
>
> The relationship between them (doppler formula) is
> f = (1-v/c)*f_0
> where f is the resulting frequency, v the velocity, c the speed of light,
> and f_0 the frequency at v=0, ie. the v_lsr.
>
> I have tried to solve it by looking at
> http://matplotlib.sourceforge.net/examples/axes_grid/parasite_simple2.html
> http://matplotlib.sourceforge.net/examples/axes_grid/parasite_simple2.html
> , where it is solved by
>
> pm_to_kms = 1./206265.*2300*3.085e18/3.15e7/1.e5
> aux_trans = matplotlib.transforms.Affine2D().scale(pm_to_kms, 1.)
> ax_pm = ax_kms.twin(aux_trans)
> ax_pm.set_viewlim_mode("transform")
>
> well, my problem is that it is not a simple scaling law, but a linear
> function.
>
> Anyone know how to solve this?
>
> Magnus
I had a similar problem when I needed to plot some data in terms of 
frequency and wavelength. See the attached example script.
Regards,
João Silva

Hello,
I have a subplot with 4 lines.
I display the legend.
I can remove a line easily with something like del(self.ax.lines[n]).
But how can I remove the line in the legend ?
I found that I can remove all the lines, add news ones, but all the
lines (new and deleted) remain in the legend.
thanks for helping
Philippe

I am trying to plot some data over a mesh using the plot_surface
method. However when I plot my data, everything is the same color
when I expected to get a nice rainbow of colors as in the example:
http://matplotlib.sourceforge.net/examples/mplot3d/surface3d_demo.html
I have attached a simple script to show what I did as well as the
result. Essentially, I just copied the above demo, but put my own
data in. I think the problem arises because I have "holes" in my
data, or areas where the data is zero. These zeros throw the scaling
off so I tried to eliminate their effect, but this messed everything
up.
Essentially my question is: how can I get a nice color distribution
while at the same time avoid the extreme scaling issues associated
with some data being zero (while all the other data is ~16)?
Thanks,
Jeremy

I am trying to plot a spectrum, with lower x axis = velocity, on the upper =
frequency
The relationship between them (doppler formula) is 
f = (1-v/c)*f_0 
where f is the resulting frequency, v the velocity, c the speed of light,
and f_0 the frequency at v=0, ie. the v_lsr.
I have tried to solve it by looking at 
http://matplotlib.sourceforge.net/examples/axes_grid/parasite_simple2.html
http://matplotlib.sourceforge.net/examples/axes_grid/parasite_simple2.html 
, where it is solved by 
pm_to_kms = 1./206265.*2300*3.085e18/3.15e7/1.e5
aux_trans = matplotlib.transforms.Affine2D().scale(pm_to_kms, 1.)
ax_pm = ax_kms.twin(aux_trans)
ax_pm.set_viewlim_mode("transform")
well, my problem is that it is not a simple scaling law, but a linear
function.
Anyone know how to solve this?
Magnus
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