As a practicing scientist interested in open source scientific software, you should consider learning Python if you don't know it already. If you do know some Python, then take a hard look at projects like:
[1] Sage: http://www.sagemath.org/ (Sage is scientific software that bundles many of the packages outlined below)
[2] SciPy: http://www.scipy.org/ Open-source software for mathematics, science, and engineering.
[6] RPy: http://rpy.sourceforge.net/ Python bindings to the open source R statistical package (modeled after and compatible with S statistical software), which opens up the vast world of statistical computing to Python.
As a chemist, you might also be interested in some of the following Python packages, mentioned in a blog post of Python for chemists [1]:
Cheminformatics
OpenBabel (Pybel), RDKit, OEChem, Daylight (PyDaylight), Cambios Molecular Toolkit, Frowns, PyBabel and MolKit (both part of MGLTools)
Most of the packages listed above feature performance-critical code written in optimized C or Fortran, so they run fast -- much faster than most equivalent proprietary platforms. Really, if you've not looked closely at what Python has to offer, please do yourself a favor and take a close look. If you already know a programming language, you could probably be using Python comfortably in a week or two.
[1] Sage: http://www.sagemath.org/ (Sage is scientific software that bundles many of the packages outlined below)
[2] SciPy: http://www.scipy.org/ Open-source software for mathematics, science, and engineering.
[3] NumPy: http://numpy.scipy.org/ Linear algebra for Python.
[4] Scikit-learn: http://scikit-learn.org/stable/ Machine learning in Python.
[5] Matplotlib: http://matplotlib.sourceforge.net/ Python graphing and plotting library.
[6] RPy: http://rpy.sourceforge.net/ Python bindings to the open source R statistical package (modeled after and compatible with S statistical software), which opens up the vast world of statistical computing to Python.
As a chemist, you might also be interested in some of the following Python packages, mentioned in a blog post of Python for chemists [1]:
Cheminformatics
OpenBabel (Pybel), RDKit, OEChem, Daylight (PyDaylight), Cambios Molecular Toolkit, Frowns, PyBabel and MolKit (both part of MGLTools)
Computational chemistry
OpenBabel, cclib, QMForge, GaussSum, PyQuante, NWChem, Maestro/Jaguar, MMTK
Visualisation
CCP1GUI, PyMOL, PMV, Zeobuilder, Chimera, VMD, Avogadro
Most of the packages listed above feature performance-critical code written in optimized C or Fortran, so they run fast -- much faster than most equivalent proprietary platforms. Really, if you've not looked closely at what Python has to offer, please do yourself a favor and take a close look. If you already know a programming language, you could probably be using Python comfortably in a week or two.
1. Python -- the scripting language of chemistry. http://baoilleach.blogspot.com/2008/03/python-scripting-lang...