[SciPy-User] kriging module
Mon Dec 6 08:22:22 CST 2010
no really familiar with Git, I just see I have given a bad address...
So, if anyone want to test, here is the good one :
I'll really appreciate any comment, thanks
2010/11/24 Anand Patil <email@example.com>:
> Hi everyone,
> I'm the author PyMC's GP module. Sorry to come late to this thread.
> The discussion of my module has been on target, and thanks very much
> for the kind words... as everyone here knows it's nice when people
> notice code that you've worked hard on. I have a couple of hopefully
> relevant things to say about it.
> First, the GP module is broader in scope than what people typically
> mean by GP regression and kriging. The statistical model underlying
> typical GPR/K says that the data are normally distributed with
> expectations equal to the GP's value at particular, known locations.
> Further, the mean and covariance parameters of the field, as well as
> the variance of the data, are typically fixed before starting the
> With the GP module, the mean and covariance parameters can be unknown,
> and the data can depend on the field in any way; as a random example,
> each data point could be Gamma distributed, with parameters determined
> by a nonlinear transformation of the field's value at several unknown
> That said, the module has a very pronounced fast path that restricts
> its practical model space to Bayesian geostatistics, which means the
> aforementioned locations have to be known before starting the
> regression. This is still a superset of GPR/K. There are numerous
> examples of the GP module in use for Bayesian geostatistics at
> Second, the parts of the GP module that would help with GPR/K are not
> very tightly bound to either the rest of PyMC or the Bayesian
> paradigm, and could be pulled out. These parts are the Mean,
> Covariance and Realization objects, functions like observe and
> point_predict, and their components; but not the GP submodels and step
> methods mentioned in the user guide.
> Any questions on the GP module are welcome at groups.google.com/p/
> pymc. I'm looking forward to checking out the work in progress on the
> On Nov 23, 2:45 pm, "Dharhas Pothina"
> <Dharhas.Poth...@twdb.state.tx.us> wrote:
>> We were planning to project our irregular data onto a cartesian grid and try and use matplotlib to visualize the variograms. I don't think I know enough about the math ofkrigingto be of much help in the coding but I might be able to give your module a try if I can find time between deadlines.
>> - dharhas
>> >>> Lionel Roubeyrie <lionel.roubey...@gmail.com> 11/22/2010 9:15 AM >>>
>> I have tried hpgl and had some discussions with one of the main
>> developper, but hpgl works only on cartesian (regular) grid where I
>> want to have the possibility to have predictions on irregular points
>> and have the possibility to visualize variograms
>> 2010/11/22 Dharhas Pothina <Dharhas.Poth...@twdb.state.tx.us>:
>> > What about this package?http://hpgl.sourceforge.net/
>> > I was looking for a kridging module recently and came across this. I haven't tried it out yet but am getting ready to. It uses numpy arrays and also is able to read/write GSLib files. GSLib seems to be a fairly established command line library in the Geostats world.
>> > - dharhas
>> > On Sat, Nov 20, 2010 at 12:56 PM, Lionel Roubeyrie <
>> > lionel.roubey...@gmail.com> wrote:
>> >> Hi all,
>> >> I have written a simple module forkrigingcomputation (ordinary
>> >>krigingfor the moment), it's not optimized and maybe some minors
>> >> errors are inside but I think it delivers corrects results. Is there
>> >> some people here that can help me for optimize the code or just to
>> >> have a try? I don't know the politic of this mailing-list against
>> >> joined files, so I don't send it here for now.
>> >> Thanks
>> >> --
>> >> Lionel Roubeyrie
>> >> lionel.roubey...@gmail.com
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>> Lionel Roubeyrie
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