Author: tlinnet Date: Fri Jun 20 17:42:56 2014 New Revision: 24212 URL: http://svn.gna.org/viewcvs/relax?rev=24212&view=rev Log: Moved the calculation of the matrix exponential out of for loops for ns mmq 3site mq. 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_3site.py Modified: branches/disp_spin_speed/lib/dispersion/ns_mmq_3site.py URL: http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/dispersion/ns_mmq_3site.py?rev=24212&r1=24211&r2=24212&view=diff ============================================================================== --- branches/disp_spin_speed/lib/dispersion/ns_mmq_3site.py (original) +++ branches/disp_spin_speed/lib/dispersion/ns_mmq_3site.py Fri Jun 20 17:42:56 2014 @@ -62,7 +62,7 @@ # relax module imports. from lib.float import isNaN from lib.dispersion.ns_matrices import rmmq_3site, rmmq_3site_rankN -from lib.linear_algebra.matrix_exponential import matrix_exponential +from lib.linear_algebra.matrix_exponential import matrix_exponential, matrix_exponential_rankN from lib.linear_algebra.matrix_power import square_matrix_power @@ -150,6 +150,16 @@ # Z- matrix component. m2_mat = rmmq_3site_rankN(R20A=R20A, R20B=R20B, R20C=R20C, dw_AB=dw_AB - dwH_AB, dw_AC=dw_AC - dwH_AC, k_AB=k_AB, k_BA=k_BA, k_BC=k_BC, k_CB=k_CB, k_AC=k_AC, k_CA=k_CA, tcp=tcp) + # The M1 and M2 matrices. + # Equivalent to D+. + M1_mat = matrix_exponential_rankN(m1_mat) + # Equivalent to Z-. + M2_mat = matrix_exponential_rankN(m2_mat) + + # The complex conjugates M1* and M2* + M1_star_mat = conj(M1_mat) + M2_star_mat = conj(M2_mat) + # Loop over spins. for si in range(NS): # Loop over the spectrometer frequencies. @@ -162,20 +172,24 @@ # Loop over the time points, back calculating the R2eff values. for i in range(num_points_i): # The M1 and M2 matrices. - M1 = matrix_exponential(m1_mat[si, mi, oi, i]) # Equivalent to D+. - M2 = matrix_exponential(m2_mat[si, mi, oi, i]) # Equivalent to Z-. + # Equivalent to D+. + M1_i = M1_mat[si, mi, oi, i] + # Equivalent to Z-. + M2_i = M2_mat[si, mi, oi, i] # The complex conjugates M1* and M2* - M1_star = conj(M1) # Equivalent to D+*. - M2_star = conj(M2) # Equivalent to Z-*. + # Equivalent to D+*. + M1_star_i = M1_star_mat[si, mi, oi, i] + # Equivalent to Z-*. + M2_star_i = M2_star_mat[si, mi, oi, i] # Repetitive dot products (minimised for speed). - M1_M2 = dot(M1, M2) - M2_M1 = dot(M2, M1) + M1_M2 = dot(M1_i, M2_i) + M2_M1 = dot(M2_i, M1_i) M1_M2_M2_M1 = dot(M1_M2, M2_M1) M2_M1_M1_M2 = dot(M2_M1, M1_M2) - M1_M2_star = dot(M1_star, M2_star) - M2_M1_star = dot(M2_star, M1_star) + M1_M2_star = dot(M1_star_i, M2_star_i) + M2_M1_star = dot(M2_star_i, M1_star_i) M1_M2_M2_M1_star = dot(M1_M2_star, M2_M1_star) M2_M1_M1_M2_star = dot(M2_M1_star, M1_M2_star)