I agree with Michalel, Monica and Isobel: R is a great choice! There are
a lot of packges for spatial statistics and interpolation, but there is
lack of more "advanced" techniques, like DK, multigaussian Kr, ... so,
Adrian, your is a very good project!! Finally, there are R packages to
build GUI (gtk, qt, java...).
Kind regards,
stefano
Michael Grant ha scritto:
SORRY PREVIOUS MATERIAL SENT BEFORE COMPLETED!!! Just a couple of comments.
1.) R has been my main programming language for a number of years now. I am
involved with a mix of enivronmental tasks--statsitcs, geostatsitcs, site
characterization, fate and transport, risk assessment. It is powerful,
accessible and one can be productive very quickly. So much high-level
functionality is already built into it, it is multi-platform and has production
quality graphics. Oh yes, database connectivity is supurb.
I have not grown comfortable the the geostats packages--certainly I have used
parts of several of them. Sometime back noticed different variograms from one
of the packages--sorry can't remember--and GEOEAS, It was nothing major, just
one used the mid-point distance in the lags and the other used the average lag
difference. Looking--quickly I admit--at the R-package's documentation it was
clear that no discussion was there. That left me wondering how many other
'little decisions' are wired into the package(s). Still I use them, but with
caution. A standard R list response applies -- look at the code ;o)
The point here is that
--- Isobel Clark <[EMAIL PROTECTED]> wrote:
Have you looked at R? It is free and designed for statistical analysis.
Isobel
Adrián Martínez Vargas <[EMAIL PROTECTED]> wrote:
Hello List
I'm interesting to open a project for build a geostatistical open source
software, with this criteria:
a) extreme simple code
b) Math is most important, graphic is secondary.
c) Modular, as GSLIB, to make easy changes.
d) Star with basic (variograms and kriging)
e) End with advanced (plurigaussian, DK, or yours on methods)
f) This item is for your advice...
The question is what do you prefer for programming
Matlab: is really easy, but it is not free... (I hope the code is free, the
you can compile executable or c code in an institution with matlab license...)
C, C++, know for a lot of peoples, bunt not as simple as programmers says.
The advantage is that exist a lot of free compilers and toolkits as QT,
glade, Visual studio C++, etc. there is also a lot of preprogramming
algorithms...
Python, it is really easy, and simple, it is possible to do also GUI with
QT python, is platform free and interpreted language (you roon directly de
source code, the system: windows, linux, etc. doesn't matter )
Other really easy programming languages can be used, as visual basic, but
it is only for windows...
Fortran is obsolete.
TCL or Visual TCL, It is interpreted language as Python, but too slow, it
is really useful to build GUIs.
My Idea is make a GUI with visual TCL and make separate executables, as in
GSLIB, with matlab (compiled), or use C++ for math...
Finally, I was trying to play with SGEMS, but it is not as simple as it
look...
What is your advice?
Dr. Adrian Martínez Vargas
Revista Minería y Geología (Editor Principal)
ISMM, Las Coloradas, s/n
Moa, Holguín,
Cuba
CP. 83329
http://www.ismm.edu.cu/revistamg/index.htm
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--
Stefano Pegoretti, PhD student
Università degli Studi di Trento (Italy)
Dipartimento di Fisica (Physics dept.)
email: [EMAIL PROTECTED]
