In article <[EMAIL PROTECTED]>, <[EMAIL PROTECTED]> wrote: >Ray Tomes wrote: >> Hi Folks >> >> I am an old codger who has much experience with computers >> in the distant past before all this object oriented stuff. >> Also I have loads of software in such languages as FORTRAN >> and BASIC, QBASIC etc that is very useful except that it >> really doesn't like to run on modern operating systems and >> has hopeless graphics resolution and lack of ease of use in >> some ways. > >The Fortran code, which I assume is Fortran 77 or earlier, should run >fine on "modern operating systems" using free (g77, g95, or gfortran) >or commercial compilers. > >> My desire is to get all the facilities available in my >> old programs working in a modern platform with flexible >> and high-res graphics and easy to use. Ideally I might >> find some good coders that are interested in the subject >> who would assist me, alternatively some help in getting >> started because there is so much info and so many resources >> and libraries etc that I don't know where to start. >> >> My package will have the following capabilities: >> 1. Able to read time series data in a variety of formats. >> 2. Able to create, manipulate and save time series files. >> 3. Able to do vector arithmetic on time series, including >> dozens of functions. > >Fortran 90 and later versions have array operations, as does NumPy. You >could convert parts of the FORTRAN code to F90 > >> 4. Loop and macro facilities to simplify repetitive stuff. >> 5. Flexible high-resolution graphic presentation. >> 6. Built in functions to include: >> FFT / fourier analysis, MESA / maximum entropy spectral analysis, >> multiple regression, canonical correlation etc etc etc. >> I have code for all these mostly in FORTRAN, some QBASIC. >> >> The applications of the package include: >> 1. Analysis of time series data from many branches of science. >> 2. Economic / business models including forecasting. >> 3. Markets, stocks, commodities forecasting. >> 4. Interdisciplinary causal analysis. >> 5. Many more > >There exist public domain codes for many of the topics you mention, and >I think several are part of NumPy. Many statistical algorithms are in >R, for which the underlying C and Fortran code is available. I suggest >that you identify which of your algorithms are not publicly available >and focus on those, making an R package of them. I am interested in >MESA. Then you can exploit the R graphics and language (called S) and >have your work easily accessible to many users. >
The original poster has received much good advice. I'll reinforce a couple of points: 1. Flexibility, high usability, and appealing graphics indeed are worth the effort. They can be achieved withOUT object orientation, though, and you absolutely should consider modernization of your existing *BASIC, Fortran, and so on. Don't let lack of a compiler block your progress; I'm sure we can help locate appropriate ones for you. 2. Python is indeed a great vehicle for this sort of work, as I've argued in the past <URL: http://phaseit.net/claird/comp.programming/open_source_science.html >. For your particular circumstances, though, I applaud Mr. Beliavsky's suggestion that you look into R <URL: http://www-106.ibm.com/developerworks/linux/library/l-sc16.html >. You might get even quicker satisfaction, with a somewhat lower long-term ceiling, through Yorick <URL: http://wiki.tcl.tk/yorick >. I understand that you were thinking in terms of enlistment of fellow developers. You might well be best off, though, with another round of research and experimentation on your own. -- http://mail.python.org/mailman/listinfo/python-list