On Mon, Dec 5, 2011 at 5:29 PM, Aaron <[email protected]> wrote: > Hello everyone, > > Our mechanical engineering department at our university is currently > working to replace MATLAB with a Python Suite and I've recently > discovered Spyder along the way. In order for this project to go > forward, we need to have install procedures prepared for Windows, > Ubuntu, and Mac OS X. The situation with Windows is quite simple with > the install of python(x,y), but this masks a lot of details that need > to be addressed when doing an Ubuntu install (have not tried Mac > yet). I was hoping that someone in this group could please tell me > the bare minimums that need to be installed for Spyder to operate as a > suitable MATLAB replacement. For example, using the Synaptic Package > Manager in Ubuntu 11.10, I was able to complete a Spyder install. > Afterwards, I opened the program and began using commands listed in > the numpy tutorial. The question is, have all dependencies been taken > care of, allowing me to begin running Spyder after installing via > Synaptic Package Manager? Or do I need to follow a more detailed > procedure? In case you need to know, I have moderate experience in > Ubuntu and I am a decent MATLAB user trying to break through to the > Python world. I don't have a learned Python community in my > department and any help that you could give would be great.
Unlike MatLab, python isn't really monolothic, which means you can have as many or as few capabilities as you want. For a Matlab replacement, absolutely essential modules would be: numpy - this provides a matlab-like multidimensional array and some other matlab-like capabilities like basic signal processing. matplotlib - this provides matlab-like 2D plotting (and experimental 3D plotting). You can't use this without numpy. To make a more complete matlab replacement, these would be very useful: scipy - provides a lot of advanced scientific and engineering functions and tools, built on top of numpy. Numpy provides the equivalent of the core matlab installation, while scipy provides the equivalent of many of the more specialized matlab toolboxes sympy - provides symbolic manipulation, like maple or mathematica pylint - a source code style and error checker, useful if you use mlint in matlab mpi4py - if you are using supercomputer, clusters, or other obscenely parallel systems or use mpi, this provides a good python interface for them. rpy - provides a python interface for the R statistics language. There are other modules in these categories (for instance there are a bunch of plotting packages), and many more specialized modules. If we knew more about what you wanted to do, it might make it easier. -Todd -- You received this message because you are subscribed to the Google Groups "spyder" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/spyderlib?hl=en.
