A large number of answers point to use R, also C++. I feel that the best choice is to work with C++ and embed that to R, and also Octave (free clone of matlab). Before to start to programming it is necessary to build a clear design of the project (I think that UML is a nice choice to chare this design) It is important to remember that the purpose is to generate Free Modular Code, with short number of lines and ease to understand, that will allow the non expert in programming to change the code and add their own ideas and geostatistical methods. A few line code is possible with the non FREE Matlab, but it exist Octave, it is free, open source, compilable, and it is possible to generate clean c source code, it also can run Matlab M files
Isobel Clark I apologise about Fortran Best regards Adrian -----Original Message----- From: "sebastiano\.trevisani" <[EMAIL PROTECTED]> To: "amvargas" <[EMAIL PROTECTED]>, "ai-geostats" <[email protected]> Date: Sun, 30 Dec 2007 09:02:12 +0100 Subject: Re: AI-GEOSTATS: New geostatistical open source software > Hi! > > If you have to write new geostatistical code I think that an object > oriented and > generic programming language should be chosen (in primis c++ , it is > efficient, it is compatible with > c, you can wrap it and work inside R). > The point is that in order to have a great code that is > easy understandable, maintainable and integrable you need > to build your system (for example using UML language) very accurately > and > taking into account the main actions you are performing when doing > geostatistical analysis...that today means to do a lot of different > things. > I think that such projecting should be performed by many people working > together > trying to get some convergence first on which objects should be built > in order > to put together a good system. What I would like to say is that the > conceptualization > (in objects, relation between objects, and function) of the > "geostatistical analysis" should > come from a really deep analysis and a general consensus. > Think for example about the problem of spatial (well, now we need > spatiotemporal) indexing that becomes > really important for search strategies when you have many data: which > kind of indexing to use? > could be an idea to use PostGis framework? > > One of the most complete geotatistical software is ISatis and the > target > should be to build something similar but more flexible. > Then the new Geostat Code should take care about > the temporal dimension of data not only spatial. > Finally I don't think that graphic is secondary above all during > explorative data analysis and spatial continuity study. > > I hope that my opinions could be useful. > Bye > Sebastiano Trevisani > > > + > + To post a message to the list, send it to [email protected] > + To unsubscribe, send email to majordomo@ jrc.it with no subject and > "unsubscribe ai-geostats" in the message body. DO NOT SEND > Subscribe/Unsubscribe requests to the list > + As a general service to list users, please remember to post a summary > of any useful responses to your questions. > + Support to the forum can be found at http://www.ai-geostats.org/
