r8984 - /1.3/sample_scripts/full_analysis.py -- March 20, 2009 - 15:22

Author: bugman
Date: Fri Mar 20 15:22:14 2009
New Revision: 8984

URL: http://svn.gna.org/viewcvs/relax?rev=8984&view=rev
Log:
Fixed a bad apostrophe character causing the script to fail.


Modified:
    1.3/sample_scripts/full_analysis.py

Modified: 1.3/sample_scripts/full_analysis.py
URL: 
http://svn.gna.org/viewcvs/relax/1.3/sample_scripts/full_analysis.py?rev=8984&r1=8983&r2=8984&view=diff
==============================================================================
--- 1.3/sample_scripts/full_analysis.py (original)
+++ 1.3/sample_scripts/full_analysis.py Fri Mar 20 15:22:14 2009
@@ -36,19 +36,19 @@
 
 Other references for features of this script include model-free model 
selection using Akaike's Information Criterion:
 
-    d’Auvergne, E. J. and Gooley, P. R. (2003). The use of model selection 
in the model-free analysis of protein dynamics. J. Biomol. NMR, 25(1), 25-39.
+    d'Auvergne, E. J. and Gooley, P. R. (2003). The use of model selection 
in the model-free analysis of protein dynamics. J. Biomol. NMR, 25(1), 25-39.
 
 The elimination of failed model-free models and Monte Carlo simulations:
 
-    d’Auvergne, E. J. and Gooley, P. R. (2006). Model-free model 
elimination: A new step in the model-free dynamic analysis of NMR relaxation 
data. J. Biomol. NMR, 35(2), 117-135.
+    d'Auvergne, E. J. and Gooley, P. R. (2006). Model-free model 
elimination: A new step in the model-free dynamic analysis of NMR relaxation 
data. J. Biomol. NMR, 35(2), 117-135.
 
 Significant model-free optimisation improvements:
 
-    d’Auvergne, E. J. and Gooley, P. R. (2008a). Optimisation of NMR 
dynamic models I. Minimisation algorithms and their performance within the 
model-free and Brownian rotational diffusion spaces. J. Biomol. NMR, 40(2), 
107-109.
+    d'Auvergne, E. J. and Gooley, P. R. (2008a). Optimisation of NMR dynamic 
models I. Minimisation algorithms and their performance within the model-free 
and Brownian rotational diffusion spaces. J. Biomol. NMR, 40(2), 107-109.
 
 Rather than searching for the lowest chi-squared value, this script searches 
for the model with the lowest AIC criterion.  This complex multi-universe, 
multi-dimensional search is formulated using set theory as the universal 
solution:
 
-    d’Auvergne, E. J. and Gooley, P. R. (2007). Set theory formulation of 
the model-free problem and the diffusion seeded model-free paradigm. 3(7), 
483-494.
+    d'Auvergne, E. J. and Gooley, P. R. (2007). Set theory formulation of 
the model-free problem and the diffusion seeded model-free paradigm. 3(7), 
483-494.
 
 The basic three references for the original and extended model-free theories 
are: