Re: [Matplotlib-users] Crash when using matplotlib.tri.LinearTriInterpolator

[Hartmut K. <har...@gm...>]

> > I ran the example on my machine (which is a 64-bit Linux box with 8 GB
> of
> > RAM; Python 2.7, matplotlib 1.3.1) and it runs fine. However, it does
> use
> > around 2 GB of memory, perhaps slightly more. I think the memory usage
> > might be a problem for you if you are using 32-bit Windows. I'm not
> > familiar with the details but I believe the memory available to a single
> > 32-bit process on Win32 may be only 2 GB. I'm also not familiar with the
> > data you provided, but is it possible to reduce to number of points in
> > order to test if memory limitations are the underlying problemhere?
> 
> Nod, your suspicion is correct. The python interpreter bails out once the
> memory footprint reaches 2GBytes. That leaves us with the question if this
> is a quality of implementation issue - using up 2GBytes of main memory for
> 1 million node elements seems to be a bit excessive...
> 
> Thanks everybody for verifying anyways!

Just to round that issue up - I tried running this using Python 2.7 (64Bit) and it does not crash anymore. The memory requirement grows up to almost 4GByte. 

I will verify whether I can get the results I hope for and will report back.

Thanks again!
Regards Hartmut
---------------
http://boost-spirit.com
http://stellar.cct.lsu.edu

> 
> Regards Hartmut
> ---------------
> http://boost-spirit.com
> http://stellar.cct.lsu.edu
> 
> >
> >
> >
> > On 11 August 2014 14:54, Hartmut Kaiser <har...@gm...>
> wrote:
> > Ian,
> >
> > > I'm running into a crash while trying to construct a
> > > tri.LinearTriInterpolator. Here is the short version of the code:
> > >
> > >     import netCDF4
> > >     import matplotlib.tri as tri
> > >
> > >     var = netCDF4.Dataset('filename.cdf').variables
> > >     x = var['x'][:]
> > >     y = var['y'][:]
> > >     data = var['zeta_max'][:]
> > >     elems = var['element'][:, :]-1
> > >
> > >     triang = tri.Triangulation(x, y, triangles=elems)
> > >
> > >     # this crashes the python interpreter
> > >     interp = tri.LinearTriInterpolator(triang, data)
> > >
> > > The data arrays (x, y, data, elems) are fairly large (>1 mio
> elements),
> > > all
> > > represented as numpy arrays (as returned by netCDF4). The 'data' array
> > is
> > > a
> > > masked array and contains masked values.
> > >
> > > If somebody cares, I'd be able to post a link to the netCDF data file
> > > causing this.
> > >
> > > All this happens when using matplotlib 1.3.1, Win32, Python 2.7.
> > >
> > > Any help would be highly appreciated!
> > > Regards Hartmut
> > >
> > > Hartmut,
> > > That is an excellent issue report; all the relevant information and
> > > nothing extraneous.  Hence the quick response.
> > > The second argument to TriLinearInterpolator (and other
> TriInterpolator
> > > classes), i.e. your 'data' array, is expected to be an array of the
> same
> > > size as the 'x' and 'y' arrays.  It is not expecting a masked
> array.  If
> > a
> > > masked array is used the mask will be ignored, and so the values
> behind
> > > the mask will be used as though they were real values.  If my memory
> of
> > > netCDF is correct, this will be whatever 'FillValue' is defined for
> the
> > > file, but it may depend on what is used to generate the netCDF file.
> > > I would normally expect the code to work but produce useless
> output.  A
> > > crash is possible though.  It would be best if you could post a link
> to
> > > the netCDF file and I will take a closer look to check there is not
> > > something else going wrong.
> > Thanks for the quick response!
> >
> > Here is the data file: http://tinyurl.com/ms7vzxw. I did some more
> > experiments. The picture stays unchanged, even if I fill the masked
> values
> > in the array with some real numbers (I'm not saying that this would give
> > me any sensible results...):
> >
> >     import netCDF4
> >     import matplotlib.tri as tri
> >     var = netCDF4.Dataset('maxele.63.nc').variables
> >     x = var['x'][:]
> >     y = var['y'][:]
> >     data = var['zeta_max'][:]
> >     elems = var['element'][:, :]-1
> >
> >     triang = tri.Triangulation(x, y, triangles=elems)
> >     data = data.filled(0.0)
> >
> >     # this still crashes the python interpreter
> >     interp = tri.LinearTriInterpolator(triang, data)
> >
> > Thanks again!
> > Regards Hartmut
> > ---------------
> > http://boost-spirit.com
> > http://stellar.cct.lsu.edu
> >
> >
> >
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> >
> > --
> > Dr Andrew Dawson
> > Atmospheric, Oceanic & Planetary Physics
> > Clarendon Laboratory
> > Parks Road
> > Oxford OX1 3PU, UK
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> > Email: da...@at...
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