GitHub - petercombs/YildizLabCode: Collection of tools for mapping and combining 2-color data

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Collection of tools for mapping and combining 2-color data

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Name		Name	Last commit message	Last commit date
Latest commit History 43 Commits
AURA-LICENSE.txt		AURA-LICENSE.txt
AlignToAxos.py		AlignToAxos.py
Analysis.py		Analysis.py
CRAPL-LICENSE.txt		CRAPL-LICENSE.txt
CombineMatlabSpots.py		CombineMatlabSpots.py
CombineWHDynein.py		CombineWHDynein.py
CombineWHSpots.py		CombineWHSpots.py
CompareFits.py		CompareFits.py
DrawMap.py		DrawMap.py
Imager.py		Imager.py
JoinFiles.py		JoinFiles.py
MakeSecondPass.py		MakeSecondPass.py
Mapping.py		Mapping.py
PCTrack.py		PCTrack.py
PlottingBetter.py		PlottingBetter.py
Postprocessing.py		Postprocessing.py
ProcessAll.m		ProcessAll.m
ProcessDyns.py		ProcessDyns.py
Processing.py		Processing.py
QueueTest.py		QueueTest.py
README		README
SplitFile.py		SplitFile.py
SpotlistData2XML.py		SpotlistData2XML.py
WHData2XML.py		WHData2XML.py
WHFiles2XML.py		WHFiles2XML.py
WHRemapper.py		WHRemapper.py
XML2spotlist.py		XML2spotlist.py
__init__.py		__init__.py
fitgauss.py		fitgauss.py
insight2spotlist.py		insight2spotlist.py
magic_srun.py		magic_srun.py
protocol.md		protocol.md
pyfits.py		pyfits.py
rec.py		rec.py
semipolar.py		semipolar.py

Repository files navigation

Table of Contents:
I. Introduction
II. Dependencies
III. Licensce (CRAPL v0) 


===============================================================================
I. Introduction
===============================================================================

This package contains a number of utility functions and full-fledged software
that I wrote to do two-color, super-resolution colocalization.  Full details
will be provided in a paper tentatively scheduled to be ready for submission in
Fall 2011.  


Vague instructions on use is available on the Yildiz Lab wiki at
http://www.ocf.berkeley.edu/~yildiz/wiki/index.php?title=Peter%27s_Lab_Methods

===============================================================================
II. Dependencies
===============================================================================

This code requires:
* Python (v2.6 or better --- certain functions use 2.6s exception catching syntax)
* SciPy (Tested with 0.8.0b1) - http://scipy.org/Download
* Matplotlib (Tested with 0.99.3) - http://matplotlib.sourceforge.net/
o pyfits (The important bit happens to be included, and is Copyright (C) 2005
	Association of Universities for Research in Austronomy (AURA) and covered under
	a separate license, available in this repo under AURA-LICENSE or at
	www.stsci.edu/resources/software_hardware/pyraf/LICENSE)
    - http://www.stsci.edu/resources/software_hardware/pyfits

The Enthought Python Distribution is especially nice for getting everything you need, 
and is free for academic use.

Critical steps assume that you have access to WHTrackHighRes, a FIONA program
written (I believe) by Bruce Cohen.  Contact Ahmet Yildiz ([email protected])
for access to this.  Alternatively, you can write your own---output is assumed
to be a tab-separated list of positions in nanometers, with two header lines
and the following column order: x, y, sx, sy, N, where N is your best attempt
at guessing the number of photons

===============================================================================
III. License
===============================================================================

The included software was written by Peter Combs ([email protected]),
and is released under the CRAPL v0 beta license.  For more details, see
CRAPL-LICENSE.txt