I would say it largely depends on what people in your field use. I use Matlab on a desktop for data analysis and Fortran/Python for HPC number crunching (astronomy/planetary science).
Recent releases of Matlab have seen heavy optimization in number crunching and the parallel processing toolbox is incredibly simple to use. The plotting and graphing tools are second to none and very intuitive if you want to visualize multi-dimensional datasets. For integration of visualization, editing and debugging in one scientifically-oriented IDE, it can't be beat. Plus it sounds like you're familiar with GNU Octave.
Python is a better language in my opinion, but lacks some of the 'do-science-straight-out-of-the-box' feel that Matlab is good at. Python obviously has the advantage of being free. The best scientific package is the Enthought Python Distribution which integrates their Canopy IDE with numpy, matplotlib and other great python modules. Free licenses are available to student/academic users.
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I would say it largely depends on what people in your field use. I use Matlab on a desktop for data analysis and Fortran/Python for HPC number crunching (astronomy/planetary science). Recent releases of Matlab have seen heavy optimization in number crunching and the parallel processing toolbox is incredibly simple to use. The plotting and graphing tools are second to none and very intuitive if you want to visualize multi-dimensional datasets. For integration of visualization, editing and debugging in one scientifically-oriented IDE, it can't be beat. Plus it sounds like you're familiar with GNU Octave. Python is a better language in my opinion, but lacks some of the 'do-science-straight-out-of-the-box' feel that Matlab is good at. Python obviously has the advantage of being free. The best scientific package is the Enthought Python Distribution which integrates their Canopy IDE with numpy, matplotlib and other great python modules. Free licenses are available to student/academic users.