Making a time series analysis package in python - advice or assistancesought

Discussion in 'Python' started by Ray Tomes, Jul 7, 2006.

  1. Ray Tomes

    Ray Tomes Guest

    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.

    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.
    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

    If you are seriously interested in this, then please contact
    me by email at ray(at)tomes(dot)biz which is the email from
    which this message was sent without the ".remove" part (anti-
    spam measure).

    Ray Tomes
    http://ray.tomes.biz/
    http://www.cyclesresearchinstitute.org/
    Ray Tomes, Jul 7, 2006
    #1
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  2. Ray Tomes

    Tim Leslie Guest

    Re: Making a time series analysis package in python - advice orassistance sought

    Hi Ray,

    As a first step you might want to look at numpy/scipy/matplotlib

    numpy (numpy.scipy.org) provides the underlying data structures (array
    and matrices among other things) you require. This will handle all
    your vector stuff, reading/writing to and from files, "loop macros",
    etc.

    scipy (www.scipy.org) provides a set of scientific programming
    libraries, including stats, fft and many other things. Have a look
    around and see if it already does what you want.

    matplotlib (http://matplotlib.sourceforge.net/) takes care of all your
    plotting needs, and plays nice with numpy and scipy.

    HTH

    Tim

    On 7/7/06, 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.
    >
    > 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.
    > 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
    >
    > If you are seriously interested in this, then please contact
    > me by email at ray(at)tomes(dot)biz which is the email from
    > which this message was sent without the ".remove" part (anti-
    > spam measure).
    >
    > Ray Tomes
    > http://ray.tomes.biz/
    > http://www.cyclesresearchinstitute.org/
    > --
    > http://mail.python.org/mailman/listinfo/python-list
    >
    Tim Leslie, Jul 7, 2006
    #2
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  3. Ray Tomes

    Terry Reedy Guest

    Re: Making a time series analysis package in python - advice orassistancesought

    "Ray Tomes" <> wrote in message
    news:e8kk4u$8b6$...
    > 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.
    > 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.


    As Tim said, work with numpy/scipy. I believe it include programs or
    modules to wrap Fortran and make Fortran function accessible from Python.
    I believe these are the same as what they used for some of the functions
    included.

    If you find some broadly useful functions missing, consider making a
    contribution. I know FFT is already included but I do not know about MESA.

    Terry Jan Reedy
    Terry Reedy, Jul 7, 2006
    #3
  4. Ray Tomes

    Guest

    Re: Making a time series analysis package in python - advice or assistance sought

    Ray Tomes:
    > 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.
    > 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.


    It seems quite doable. Beside doing vector arithmetic with SciPy, and
    plotting/generating graphs with MatPlotLib, you may need a GUI toolkit,
    like Tkinter (built-in), wxpython, etc:
    http://pythoncard.sourceforge.net/
    http://www.wxpython.org/
    etc.

    Designing good GUIs requires some time.

    The "Loop and macro facilities" can be done in Python itself.

    To use Fortran from Python:
    http://cens.ioc.ee/projects/f2py2e/

    Bye,
    bearophile
    , Jul 7, 2006
    #4
  5. Ray Tomes

    Guest

    Re: Making a time series analysis package in python - advice or assistance sought

    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.
    , Jul 7, 2006
    #5
  6. Re: Making a time series analysis package in python - advice or assistance sought

    In article <>,
    <> 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.
    Cameron Laird, Jul 7, 2006
    #6
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