Author: tlinnet Date: Tue May 20 01:47:30 2014 New Revision: 23246 URL: http://svn.gna.org/viewcvs/relax?rev=23246&view=rev Log: Math-domain catching for model: 'NS CPMG 2-site expanded'. task #7793: (https://gna.org/task/?7793) Speed-up of dispersion models. This is to implement catching of math domain errors, before they occur. These can be found via the --numpy-raise function to the systemtests. To make the code look clean, the class object "back_calc" is no longer being updated per time point, but is updated in the relax_disp target function in one go. Modified: branches/disp_speed/lib/dispersion/ns_cpmg_2site_expanded.py branches/disp_speed/target_functions/relax_disp.py Modified: branches/disp_speed/lib/dispersion/ns_cpmg_2site_expanded.py URL: http://svn.gna.org/viewcvs/relax/branches/disp_speed/lib/dispersion/ns_cpmg_2site_expanded.py?rev=23246&r1=23245&r2=23246&view=diff ============================================================================== --- branches/disp_speed/lib/dispersion/ns_cpmg_2site_expanded.py (original) +++ branches/disp_speed/lib/dispersion/ns_cpmg_2site_expanded.py Tue May 20 01:47:30 2014 @@ -235,14 +235,13 @@ """ # Python module imports. -from math import log -from numpy import exp, power, sqrt +from numpy import array, exp, isfinite, power, log, min, sqrt, sum # relax module imports. from lib.float import isNaN -def r2eff_ns_cpmg_2site_expanded(r20=None, pA=None, dw=None, k_AB=None, k_BA=None, relax_time=None, inv_relax_time=None, tcp=None, back_calc=None, num_points=None, num_cpmg=None): +def r2eff_ns_cpmg_2site_expanded(r20=None, pA=None, dw=None, k_AB=None, k_BA=None, relax_time=None, inv_relax_time=None, tcp=None, num_points=None, num_cpmg=None): """The 2-site numerical solution to the Bloch-McConnell equation using complex conjugate matrices. This function calculates and stores the R2eff values. @@ -264,9 +263,7 @@ @type inv_relax_time: float @keyword tcp: The tau_CPMG times (1 / 4.nu1). @type tcp: 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 tcp and back_calc arguments. + @keyword num_points: The number of points on the dispersion curve, equal to the length of the tcp . @type num_points: int @keyword num_cpmg: The array of numbers of CPMG blocks. @type num_cpmg: numpy int16, rank-1 array @@ -342,7 +339,15 @@ t116 = power(0.5*(t97_t99 + t112), t115) t118 = 1.0/t112 t120 = t97_nt99 + t112 - t122 = power(0.5*(t97_t99 - t112), t115) + + half_t97_t99_m_t112 = 0.5*(t97_t99 - t112) + # Catch math domain error of power(val < 1.e-7, 40). + # This is when abs(half_t97_t99_m_t112) < 1.e-7. + if min(abs(half_t97_t99_m_t112.real)) < 1.e-7: + R2eff = array([1e100]*num_points) + return R2eff + + t122 = power(half_t97_t99_m_t112, t115) t127 = 0.5/t108 t120_t122 = t120*t122 t139 = 0.5/(k_AB + k_BA) * ((t120_t122 - t113*t116)*t118*k_BA + (t120_t122 - t116*t120)*t127*t113*t118*k_AB) @@ -355,8 +360,11 @@ Mx = intensity / intensity0 # Calculate the R2eff using a two-point approximation, i.e. assuming that the decay is mono-exponential, and store it for each dispersion point. - for i in range(num_points): - if Mx[i] <= 0.0 or isNaN(Mx[i]): - back_calc[i] = 1e99 - else: - back_calc[i]= -inv_relax_time * log(Mx[i]) + R2eff = -inv_relax_time * log(Mx) + + # Catch errors, taking a sum over array is the fastest way to check for + # +/- inf (infinity) and nan (not a number). + if not isfinite(sum(R2eff)) or min(Mx) <= 0.0 or not isfinite(sum(Mx)): + R2eff = array([1e100]*num_points) + + return R2eff Modified: branches/disp_speed/target_functions/relax_disp.py URL: http://svn.gna.org/viewcvs/relax/branches/disp_speed/target_functions/relax_disp.py?rev=23246&r1=23245&r2=23246&view=diff ============================================================================== --- branches/disp_speed/target_functions/relax_disp.py (original) +++ branches/disp_speed/target_functions/relax_disp.py Tue May 20 01:47:30 2014 @@ -1480,7 +1480,7 @@ dw_frq = dw[si] * self.frqs[0][si][mi] # Back calculate the R2eff values. - r2eff_ns_cpmg_2site_expanded(r20=R20[r20_index], pA=pA, dw=dw_frq, k_AB=k_AB, k_BA=k_BA, relax_time=self.relax_times[0][mi], inv_relax_time=self.inv_relax_times[0][mi], tcp=self.tau_cpmg[0][mi], back_calc=self.back_calc[0][si][mi][0], num_points=self.num_disp_points[0][si][mi][0], num_cpmg=self.power[0][mi]) + self.back_calc[0][si][mi][0] = r2eff_ns_cpmg_2site_expanded(r20=R20[r20_index], pA=pA, dw=dw_frq, k_AB=k_AB, k_BA=k_BA, relax_time=self.relax_times[0][mi], inv_relax_time=self.inv_relax_times[0][mi], tcp=self.tau_cpmg[0][mi], num_points=self.num_disp_points[0][si][mi][0], num_cpmg=self.power[0][mi]) # 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 di in range(self.num_disp_points[0][si][mi][0]):