Author: bugman Date: Thu Jun 6 18:44:59 2013 New Revision: 19904 URL: http://svn.gna.org/viewcvs/relax?rev=19904&view=rev Log: Variable renaming in the lib.dispersion.m61 module. The variable names are now more suited to R1rho-type data, rather than CPMG-type data. Modified: branches/relax_disp/lib/dispersion/m61.py branches/relax_disp/target_functions/relax_disp.py Modified: branches/relax_disp/lib/dispersion/m61.py URL: http://svn.gna.org/viewcvs/relax/branches/relax_disp/lib/dispersion/m61.py?rev=19904&r1=19903&r2=19904&view=diff ============================================================================== --- branches/relax_disp/lib/dispersion/m61.py (original) +++ branches/relax_disp/lib/dispersion/m61.py Thu Jun 6 18:44:59 2013 @@ -44,38 +44,38 @@ from math import pi, sin -def r2eff_M61(r1rho0=None, phi_ex=None, kex=None, theta=pi/2, cpmg_frqs=None, back_calc=None, num_points=None): +def r2eff_M61(r1rho_prime=None, phi_ex=None, kex=None, theta=pi/2, spin_lock_fields=None, back_calc=None, num_points=None): """Calculate the R2eff values for the M61 model. See the module docstring for details. - @keyword r1rho0: The R1rho0 parameter value (R1rho with no exchange). - @type r1rho0: float - @keyword phi_ex: The phi_ex parameter value (pA * pB * delta_omega^2). - @type phi_ex: float - @keyword kex: The kex parameter value (the exchange rate in rad/s). - @type kex: float - @keyword theta: The rotating frame tilt angle. - @type theta: float - @keyword cpmg_frqs: The CPMG nu1 frequencies. - @type cpmg_frqs: numpy rank-1 float array - @keyword back_calc: The array for holding the back calculated R2eff values. Each element corresponds to one of the CPMG nu1 frequencies. - @type back_calc: numpy rank-1 float array - @keyword num_points: The number of points on the dispersion curve, equal to the length of the cpmg_frqs and back_calc arguments. - @type num_poinst: int + @keyword r1rho_prime: The R1rho_prime parameter value (R1rho with no exchange). + @type r1rho_prime: float + @keyword phi_ex: The phi_ex parameter value (pA * pB * delta_omega^2). + @type phi_ex: float + @keyword kex: The kex parameter value (the exchange rate in rad/s). + @type kex: float + @keyword theta: The rotating frame tilt angle. + @type theta: float + @keyword spin_lock_fields: The CPMG nu1 frequencies. + @type spin_lock_fields: numpy rank-1 float array + @keyword back_calc: The array for holding the back calculated R1rho values. Each element corresponds to one of the spin-lock fields. + @type back_calc: numpy rank-1 float array + @keyword num_points: The number of points on the dispersion curve, equal to the length of the spin_lock_fields and back_calc arguments. + @type num_poinst: int """ # Loop over the time points, back calculating the R2eff values. for i in range(num_points): # Catch zeros (to avoid pointless mathematical operations). if phi_ex == 0.0 or kex == 0.0: - back_calc[i] = r20 + back_calc[i] = r1rho_prime # Avoid divide by zero. - elif kex == 0.0 and cpmg_frqs[i] == 0.0: + elif kex == 0.0 and spin_lock_fields[i] == 0.0: back_calc[i] = 1e100 # The full formula. else: - back_calc[i] = r1rho0 + sin(theta) * phi_ex * kex / (kex**2 + cpmg_frqs[i]**2) + back_calc[i] = r1rho_prime + sin(theta) * phi_ex * kex / (kex**2 + spin_lock_fields[i]**2) Modified: branches/relax_disp/target_functions/relax_disp.py URL: http://svn.gna.org/viewcvs/relax/branches/relax_disp/target_functions/relax_disp.py?rev=19904&r1=19903&r2=19904&view=diff ============================================================================== --- branches/relax_disp/target_functions/relax_disp.py (original) +++ branches/relax_disp/target_functions/relax_disp.py Thu Jun 6 18:44:59 2013 @@ -240,7 +240,7 @@ phi_ex_scaled = phi_ex * self.frqs[spin_index, frq_index]**2 # Back calculate the R2eff values. - r2eff_M61(r20=R20[frq_index], phi_ex=phi_ex_scaled, kex=kex, cpmg_frqs=self.cpmg_frqs, back_calc=self.back_calc[spin_index, frq_index], num_points=self.num_disp_points) + r2eff_M61(r1rho_prime=R20[frq_index], phi_ex=phi_ex_scaled, kex=kex, spin_lock_fields=self.cpmg_frqs, back_calc=self.back_calc[spin_index, frq_index], num_points=self.num_disp_points) # For all missing data points, set the back-calculated value to the measured values so that it has no effect on the chi-squared value. for point_index in range(self.num_disp_points):