Author: tlinnet Date: Fri Jun 20 17:54:33 2014 New Revision: 24216 URL: http://svn.gna.org/viewcvs/relax?rev=24216&view=rev Log: Documentation and input fix for ns mmq 2site. The m1 and m2 matrices are populated inside the lib function. Task #7807 (https://gna.org/task/index.php?7807): Speed-up of dispersion models for Clustered analysis. Modified: branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py Modified: branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py URL: http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py?rev=24216&r1=24215&r2=24216&view=diff ============================================================================== --- branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py (original) +++ branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py Fri Jun 20 17:54:33 2014 @@ -78,10 +78,6 @@ @type M0: numpy float64, rank-1, 7D array @keyword F_vector: The observable magnitisation vector. This defaults to [1, 0] for X observable magnitisation. @type F_vector: numpy rank-1, 2D float64 array - @keyword m1: A complex numpy matrix to be populated. - @type m1: numpy rank-2, 2D complex64 array - @keyword m2: A complex numpy matrix to be populated. - @type m2: numpy rank-2, 2D complex64 array @keyword R20A: The transverse, spin-spin relaxation rate for state A. @type R20A: numpy float array of rank [NS][NM][NO][ND] @keyword R20B: The transverse, spin-spin relaxation rate for state B. @@ -229,7 +225,7 @@ back_calc[si, mi, oi, i]= -inv_tcpmg[si, mi, oi, i] * log(Mx / pA) -def r2eff_ns_mmq_2site_sq_dq_zq(M0=None, F_vector=array([1, 0], float64), m1=None, m2=None, R20A=None, R20B=None, pA=None, dw=None, dwH=None, kex=None, inv_tcpmg=None, tcp=None, back_calc=None, num_points=None, power=None): +def r2eff_ns_mmq_2site_sq_dq_zq(M0=None, F_vector=array([1, 0], float64), R20A=None, R20B=None, pA=None, dw=None, dwH=None, kex=None, inv_tcpmg=None, tcp=None, back_calc=None, num_points=None, power=None): """The 2-site numerical solution to the Bloch-McConnell equation for SQ, ZQ, and DQ data. The notation used here comes from: