Scientific computing and data visualization.

Discussion in 'Python' started by Fie Pye, Sep 6, 2006.

  1. Fie Pye

    Fie Pye Guest

    Hallo

    I would like to have a high class open source tools for scientific computing and powerful 2D and 3D data visualisation. Therefore I chose python, numpy and scipy as a base. Now I am in search for a visualisation tool. I tried matplotlib and py_opendx with OpenDx. OpenDx seems to me very good but the project py_opendx looks like closed. After py_opendx instalation and subsequent testing I got an error that needs discussion with author or an experienced user. Unfortunately a mail to author returned as undeliverable.

    Does anybody now about suitable visualisation tool?

    Does anybody have an experience with OpenDx and py_opendx instalation?

    Thanks for your response.

    fiepye
    Fie Pye, Sep 6, 2006
    #1
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  2. Fie Pye

    Matteo Guest

    Fie Pye wrote:
    > Hallo
    >
    > I would like to have a high class open source tools for scientific computing and powerful 2D and 3D data visualisation. Therefore I chose python, numpy and scipy as a base. Now I am in search for a visualisation tool. I tried matplotlib and py_opendx with OpenDx. OpenDx seems to me very good but the project py_opendx looks like closed. After py_opendx instalation and subsequent testing I got an error that needs discussion with author or an experienced user. Unfortunately a mail to author returned as undeliverable.
    >
    > Does anybody now about suitable visualisation tool?
    >
    > Does anybody have an experience with OpenDx and py_opendx instalation?
    >
    > Thanks for your response.
    >
    > fiepye


    As another poster pointed out below, VTK is a very strong vis tool. It
    is actively supported and has bindings to several languages (C++,
    Python, Java, and Tcl at last count). I have used the combination of
    python and VTK together to produce many scientific visualizations,
    including production quality animations (Usually, I use Python/VTK to
    generate isosurfaces or the like, and import the resulting geometry
    data into Maya or another high-quality renderer)

    One hurdle to overcome is transferring array data from Numeric/Numpy
    into VTK. I have a sort of ad-hoc method to do that (mainly for volume
    data). If anyone knows of any elegant solution, or a module to ease the
    pain, I'd like to hear about it.

    If you are working with NetCDF files, you may wish to add
    ScientificPython (distinct from SciPy) to your toolset. It has a very
    nice NetCDF interface. Unfortunately, it is ancient, and you would have
    to install Numeric Python (ancestor to NumPy). However, it is easy to
    convert Numeric arrays into Numpy arrays:
    >>> my_numpy_array=numpy.array(my_numeric_array)



    -matt
    Matteo, Sep 6, 2006
    #2
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  3. Matteo wrote:

    > One hurdle to overcome is transferring array data from Numeric/Numpy
    > into VTK. I have a sort of ad-hoc method to do that (mainly for volume
    > data). If anyone knows of any elegant solution, or a module to ease the
    > pain, I'd like to hear about it.


    https://svn.enthought.com/enthought/wiki/TVTK

    Much, much, MUCH nicer interface to VTK than the plain bindings that come by
    default. And built from the ground up to seamlessly couple numpy with VTK.

    Cheers,

    f
    Fernando Perez, Sep 6, 2006
    #3
  4. Fie Pye

    Robert Kern Guest

    Matteo wrote:
    > If you are working with NetCDF files, you may wish to add
    > ScientificPython (distinct from SciPy) to your toolset. It has a very
    > nice NetCDF interface. Unfortunately, it is ancient, and you would have
    > to install Numeric Python (ancestor to NumPy). However, it is easy to
    > convert Numeric arrays into Numpy arrays:
    >>>> my_numpy_array=numpy.array(my_numeric_array)


    The NetCDF interface has been ported to numpy and currently resides in the scipy
    sandbox.

    http://svn.scipy.org/svn/scipy/trunk/Lib/sandbox/netcdf/

    --
    Robert Kern

    "I have come to believe that the whole world is an enigma, a harmless enigma
    that is made terrible by our own mad attempt to interpret it as though it had
    an underlying truth."
    -- Umberto Eco
    Robert Kern, Sep 6, 2006
    #4
  5. Fie Pye

    Guest

    A commonly used data analysis framework is root (http://root.cern.ch).
    It offers a object oriented C++ framework with all kind of things one
    needs for plotting and data visualization. It comes along with PyRoot,
    an interface making the root objects available to Python.
    Take a look at the root manual for examples, it also contains a section
    describing the use of PyRoot.

    Cheers! Bernhard
    , Sep 7, 2006
    #5
  6. Fie Pye

    Paul F. Kunz Guest

    "Fie Pye" <> writes:

    > Hallo
    >
    > I would like to have a high class open source tools for scientific computing and powerful 2D and 3D data visualisation. Therefore I chose python, numpy and scipy as a base. Now I am in search for a visualisation tool. I tried matplotlib and py_opendx with OpenDx. OpenDx seems to me very good but the project py_opendx looks like closed. After py_opendx instalation and subsequent testing I got an error that needs discussion with author or an experienced user. Unfortunately a mail to author returned as undeliverable.
    >
    > Does anybody now about suitable visualisation tool?
    >

    Have you looked at HippoDraw?

    http://www.slac.stanford.edu/grk/ek/hippodraw
    Paul F. Kunz, Sep 13, 2006
    #6
  7. Paul F. Kunz wrote:
    > "Fie Pye" <> writes:
    >
    >
    >> Hallo
    >>
    >> I would like to have a high class open source tools for scientific computing and powerful 2D and 3D data visualisation. Therefore I chose python, numpy and scipy as a base. Now I am in search for a visualisation tool. I tried matplotlib and py_opendx with OpenDx. OpenDx seems to me very good but the project py_opendx looks like closed. After py_opendx instalation and subsequent testing I got an error that needs discussion with author or an experienced user. Unfortunately a mail to author returned as undeliverable.
    >>
    >> Does anybody now about suitable visualisation tool?
    >>

    >
    > Have you looked at HippoDraw?
    >
    > http://www.slac.stanford.edu/grk/ek/hippodraw

    http://www.slac.stanford.edu/grp/ek/hippodraw/

    Claudio Grondi
    Claudio Grondi, Sep 13, 2006
    #7
  8. Fie Pye wrote:
    > Hallo
    >
    > I would like to have a high class open source tools for scientific computing and powerful 2D and 3D data visualisation. Therefore I chose python, numpy and scipy as a base. Now I am in search for a visualisation tool. I tried matplotlib and py_opendx with OpenDx. OpenDx seems to me very good but the project py_opendx looks like closed. After py_opendx instalation and subsequent testing I got an error that needs discussion with author or an experienced user. Unfortunately a mail to author returned as undeliverable.
    >
    > Does anybody now about suitable visualisation tool?
    >
    > Does anybody have an experience with OpenDx and py_opendx instalation?
    >
    > Thanks for your response.
    >
    > fiepye
    >
    >
    >


    What sort of "scientific computing" and visualization do you have in
    mind? I enjoy R for much of my work. See http://www.r-project.org/

    Plz let us know what you have discovered, and what you have settled on.

    Tchuss,
    DaveB
    David J. Braden, Sep 14, 2006
    #8
  9. wrote:
    > A commonly used data analysis framework is root (http://root.cern.ch).
    > It offers a object oriented C++ framework with all kind of things one
    > needs for plotting and data visualization. It comes along with PyRoot,
    > an interface making the root objects available to Python.
    > Take a look at the root manual for examples, it also contains a section
    > describing the use of PyRoot.


    I can definitively second that. ROOT is a bit hard to learn but very,
    very powerful and PyRoot is really a pleasure to work with.

    Cheers,

    Carl Friedrich Bolz
    Carl Friedrich Bolz, Oct 6, 2006
    #9
  10. Hi,

    * Carl Friedrich Bolz <> wrote:
    > wrote:
    >> A commonly used data analysis framework is root (http://root.cern.ch).
    >> It offers a object oriented C++ framework with all kind of things one
    >> needs for plotting and data visualization. It comes along with PyRoot,
    >> an interface making the root objects available to Python.
    >> Take a look at the root manual for examples, it also contains a section
    >> describing the use of PyRoot.

    >
    > I can definitively second that. ROOT is a bit hard to learn but very,
    > very powerful and PyRoot is really a pleasure to work with.


    It sounds interesting. Right now, I use matplotlib for
    2D plotting and vtk for 3D. Do you have any experience and
    can give some recommendations?

    Greetings!
    Fabian
    Fabian Braennstroem, Oct 7, 2006
    #10
  11. Fie Pye

    Guest

    > > I can definitively second that. ROOT is a bit hard to learn but very,
    > > very powerful and PyRoot is really a pleasure to work with.

    >
    > It sounds interesting. Right now, I use matplotlib for
    > 2D plotting and vtk for 3D. Do you have any experience and
    > can give some recommendations?


    Hi Fabian!

    I recommend using matplotlib for data visualization, because the usage
    of the plotting commands is much(!!!) more convenient. In ROOT you have
    to create objects before you can draw your diagrams. The constructor
    often requires arguments about the number of space points, axis length,
    name etc. On the other hand, the figure itself has a GUI to manipulate
    the plot, which sometimes is nicer than doing everything in the script.
    In particular the 3D visualization seems to be more comprehensive (lots
    of drawing options, rotation of the plot with the mouse, changing of
    visualization lego, surf, contour plots etc.).

    ROOT has more than plotting. For example it has a whole bunch of
    containers to store very large amounts of data (within complex
    datastructures), fitting routines, minimizers etc. But you get that
    with scipy and numpy.

    I'm using 80% of the time matplotlib because it's much quicker for
    quick glances at your data. If I need sophisitcated 3D plots, I use
    ROOT, but I would love to switch to matplotlib for this, as well.

    My guess is that using python and matplotlib with scipy speeds up my
    work by at least 30% in comparison to using purely ROOT (and code in
    C++). And even 10-15% in comparison to the usage of ROOT with pyRoot.

    Enjoy! Bernhard
    , Oct 8, 2006
    #11
  12. Hi Bernhard,

    * <> wrote:
    >> > I can definitively second that. ROOT is a bit hard to learn but very,
    >> > very powerful and PyRoot is really a pleasure to work with.

    >>
    >> It sounds interesting. Right now, I use matplotlib for
    >> 2D plotting and vtk for 3D. Do you have any experience and
    >> can give some recommendations?

    >
    > Hi Fabian!
    >
    > I recommend using matplotlib for data visualization, because the usage
    > of the plotting commands is much(!!!) more convenient. In ROOT you have
    > to create objects before you can draw your diagrams. The constructor
    > often requires arguments about the number of space points, axis length,
    > name etc. On the other hand, the figure itself has a GUI to manipulate
    > the plot, which sometimes is nicer than doing everything in the script.
    > In particular the 3D visualization seems to be more comprehensive (lots
    > of drawing options, rotation of the plot with the mouse, changing of
    > visualization lego, surf, contour plots etc.).
    >
    > ROOT has more than plotting. For example it has a whole bunch of
    > containers to store very large amounts of data (within complex
    > datastructures), fitting routines, minimizers etc. But you get that
    > with scipy and numpy.
    >
    > I'm using 80% of the time matplotlib because it's much quicker for
    > quick glances at your data. If I need sophisitcated 3D plots, I use
    > ROOT, but I would love to switch to matplotlib for this, as well.
    >
    > My guess is that using python and matplotlib with scipy speeds up my
    > work by at least 30% in comparison to using purely ROOT (and code in
    > C++). And even 10-15% in comparison to the usage of ROOT with pyRoot.


    Thanks for your advice!

    Greetings!
    Fabian
    Fabian Braennstroem, Oct 8, 2006
    #12
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