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Frequently Asked Questions on pyCoAn

What is pyCoAn?

pyCoAn is the next generation Correlative Analysis software system, combining the power of the original CoAn package with the flexibility of Python.  It is installed as a python package which provides access to all the original CoAn processing options, and lots more besides.

Should I use CoAn or pyCoAn?

If you're new to Correlative Analysis, we recommend you start with pyCoAn.  This is where most of our development efforts are focused, to make the software as widely usable (and useful) as possible.

Will pyCoAn run on Linux?

Yes, pyCoAn consists of a series of python packages and C and Fortran compiled extensions.  It will run on 64-bit Linux, and requires python2.4 or newer (however python 3.x is not supported at the present time). The binary distribution ships with python 2.7.

Wiil pyCoAn run on Windows?

We are planning to make pyCoAn available for Windows users, using the Cygwin project.   

Will pyCoAn run on Mac OS X?

pyCoAn can be readily compiled and installed on Mac OS X (Intel). We are currently working on a binary distribution for Mac OS X systems.  Stay tuned for announcements! 

Why does the pyCoAn test suite fail with "Segmentation Fault (core dumped)" on Fedora 14?

We are still investigating this issue, but we have so far determined it to be related to building the pyCoAn package with the shipped version of gfortran (release 4.5.1).  As an easy workaround, you can install g77  and then specify this compiler when you rebuild pyCoAn.  The commands below should be issued in the top level pyCoAn source directory:

sudo yum install compat-gcc-34-g77
python clean
rm -rf ./build
python build_ext --inplace --fcompiler=gnu

Note that you select the compiler by type and not by name.  Hence --fcompiler=gnu requests that the g77 compiler be used, and --fcompiler=gnu95 requests the gfortran compiler.  As documented on the installation pages for pyCoAn, if you with the build pyCoAn with g77, you must also build CCP4 with g77.

How do I choose which mechanism to use when reading density maps?

In most cases you don't even have to think about it.  Just open the file and the best available (i.e. built in at compile time) mechanism will be selected for you:

>>> m = Map('sample.ccp4')

However, you can select which mechanism to use if you so desire, selecting between the io module explicitly. 

>>> m = Map('sample.ccp4', io='eman')

Currently available mechanisms include 'eman', 'imod', 'pil', 'ccp4', 'itk', 'skim' (scikit-image) and 'astro' (astropy, primarily for .fits). 'star' file support is in progress.

At any time you can check to see which I/O mechanism was used for any Map object:

>>> print m.iolib