Re: Scientific computing and data visualization.
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 -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
Hi Bernhard, * [EMAIL PROTECTED] [EMAIL PROTECTED] 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 -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
Hi, * Carl Friedrich Bolz [EMAIL PROTECTED] wrote: [EMAIL PROTECTED] 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 -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
[EMAIL PROTECTED] 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 -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
Fie Pye [EMAIL PROTECTED] 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://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
Paul F. Kunz wrote: Fie Pye [EMAIL PROTECTED] 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 -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
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 -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
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 -- http://mail.python.org/mailman/listinfo/python-list
Scientific computing and data visualization.
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 -- http://mail.python.org/mailman/listinfo/python-list
Scientific computing and data visualization.
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 -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
FieI would like to have a high class open source tools for Fiescientific computing and powerful 2D and 3D data Fievisualisation. Therefore I chose python, numpy and scipy as Fiea base. Now I am in search for a visualisation tool. I tried Fiematplotlib and py_opendx with OpenDx. OpenDx seems to me Fievery good but the project py_opendx looks like closed. After Fiepy_opendx instalation and subsequent testing I got an error Fiethat needs discussion with author or an experienced Fieuser. Unfortunately a mail to author returned as Fieundeliverable. Have you considered VTK and/or MayaVi? Skip -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
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 -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
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 -- http://mail.python.org/mailman/listinfo/python-list
Re: Scientific computing and data visualization.
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 -- http://mail.python.org/mailman/listinfo/python-list
