Author: bugman Date: Fri Jul 12 09:19:05 2013 New Revision: 20276 URL: http://svn.gna.org/viewcvs/relax?rev=20276&view=rev Log: Updated the lib.dispersion.ns_2site_star module with additional information from Paul Schanda. The details come from http://thread.gmane.org/gmane.science.nmr.relax.devel/4132/focus=4135. The exchange-free R2 value parameter names have been changed to match the convention of the other lib.dispersion modules. Modified: branches/relax_disp/lib/dispersion/ns_2site_star.py Modified: branches/relax_disp/lib/dispersion/ns_2site_star.py URL: http://svn.gna.org/viewcvs/relax/branches/relax_disp/lib/dispersion/ns_2site_star.py?rev=20276&r1=20275&r2=20276&view=diff ============================================================================== --- branches/relax_disp/lib/dispersion/ns_2site_star.py (original) +++ branches/relax_disp/lib/dispersion/ns_2site_star.py Fri Jul 12 09:19:05 2013 @@ -38,22 +38,22 @@ from scipy.linalg import expm -def r2eff_ns_2site_star(R2E=None, R2G=None, fg=None, kge=None, keg=None, tcpmg=None, cpmg_frqs=None, back_calc=None, num_points=None): +def r2eff_ns_2site_star(r20a=None, r20b=None, fg=None, kge=None, keg=None, tcpmg=None, cpmg_frqs=None, back_calc=None, num_points=None): """The 2-site numerical solution to the Bloch-McConnell equation using complex conjugate matrices. This function calculates and stores the R2eff values. - @keyword R2E: Unknown. - @type R2E: unknown - @keyword R2G: Unknown. - @type R2G: unknown + @keyword r20a: The R2 value for state A in the absence of exchange. + @type r20a: float + @keyword r20b: The R2 value for state A in the absence of exchange. + @type r20b: float @keyword fg: Unknown. @type fg: unknown - @keyword kge: Unknown. - @type kge: unknown - @keyword keg: Unknown. - @type keg: unknown + @keyword kge: The forward exchange rate. + @type kge: float + @keyword keg: The reverse exchange rate. + @type keg: float @keyword tcpmg: Unknown. @type tcpmg: unknown @keyword cpmg_frqs: The CPMG nu1 frequencies. @@ -65,7 +65,7 @@ """ # Initialise some structures. - Rr = -1.0 * matrix([[R2G, 0.0],[0.0, R2E]]) + Rr = -1.0 * matrix([[r20b, 0.0],[0.0, r20a]]) Rex = -1.0 * matrix([[kge, -keg],[-kge, keg]]) RCS = complex(0.0, -1.0) * matrix([[0.0, 0.0],[0.0, fg]]) R = Rr + Rex + RCS