Updated my Python install and NumPy/SciPy on my Mountain Lion machine. A couple of sites provided great guidance:
* “Python, NumPy, SciPy instructions”:http://www.thisisthegreenroom.com/2011/installing-python-numpy-scipy-matplotlib-and-ipython-on-lion/ provide good guidance on getting python, brew, virtualenv, and bumpy up to date on osx 10.8. The scipy instructions are busted tho
* “SciPy instructions on StackOverflow”:http://stackoverflow.com/questions/12092306/how-to-install-scipy-with-pip-on-mac-mountain-lion-os-x-v10-8. Once you have Python and Numpy installed, these steps solved the SciPy install. OK well no they didn’t. Still working on.
* UPDATE: Back to a later post from the first author: “Compiling SciPy on Mountain Lion”:http://www.thisisthegreenroom.com/2012/compiling-scipy-on-mountain-lion/ — and I have SciPy working now.
Reardon abused me (not really) for still using Matlab and goaded me to look into the ImageJ world. So I am learning. Seems like I need to get smart on
* “ImageJ”:http://rsbweb.nih.gov/ij/ and the “Fiji”:http://pacific.mpi-cbg.de/wiki/index.php/Main_Page distribution
* Python derivatives like “Jython”:http://www.jython.org/ for ImageJ scripting and “NumPy/SciPy”:http://numpy.scipy.org/ for numeric/array processing
* There are a ton of other scripting language choices but seems like python covers this well enough. I don’t want the brain damage of “Clojure”:http://clojure.org/.
Other stuff to learn? I’ll have to pick up an editor and source management tool as well. The benefit of all this? Any code I write should be faster, more easily redistributable, and there is a large support community. The disadvantage? I have to assemble all these piece-parts to get something equivalent to MatLab, so more time d&*king around with software which is time taken away from research focus. And the Matlab universe has a pretty good support community too, so not clear I am trading up there. Certainly the ImageJ/Jython/NumPy path is “cooler” along a certain dimension, but do I care?