Author: tlinnet Date: Fri Jun 20 09:18:00 2014 New Revision: 24189 URL: http://svn.gna.org/viewcvs/relax?rev=24189&view=rev Log: Implemented the collection of the multidimensional matrix m1 and m2 in model ns mmq 2site. Inserted also a check, that the newly computed matrix is equal. They are, to the 6 digit. 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=24189&r1=24188&r2=24189&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 09:18:00 2014 @@ -51,7 +51,7 @@ # Python module imports. from math import floor -from numpy import array, conj, dot, float64, log +from numpy import array, conj, complex64, dot, float64, log, multiply, sum # relax module imports. from lib.float import isNaN @@ -81,6 +81,76 @@ matrix[0, 1] = k_BA matrix[1, 0] = k_AB matrix[1, 1] = -k_BA + 1.j*dw - R20B + + +def populate_matrix_rankN(R20A=None, R20B=None, dw=None, k_AB=None, k_BA=None, tcp=None): + """The Bloch-McConnell matrix for 2-site exchange, for rank [NE][NS][NM][NO][ND][2][2]. + + @keyword R20A: The transverse, spin-spin relaxation rate for state A. + @type R20A: numpy float array of rank [NE][NS][NM][NO][ND] + @keyword R20B: The transverse, spin-spin relaxation rate for state B. + @type R20B: numpy float array of rank [NE][NS][NM][NO][ND] + @keyword dw: The combined chemical exchange difference parameters between states A and B in rad/s. This can be any combination of dw and dwH. + @type dw: numpy float array of rank [NE][NS][NM][NO][ND] + @keyword k_AB: The rate of exchange from site A to B (rad/s). + @type k_AB: float + @keyword k_BA: The rate of exchange from site B to A (rad/s). + @type k_BA: float + @keyword tcp: The tau_CPMG times (1 / 4.nu1). + @type tcp: numpy float array of rank [NE][NS][NM][NO][ND] + @return: The relaxation matrix. + @rtype: numpy float array of rank [NE][NS][NM][NO][ND][2][2] + """ + + # Pre-multiply with tcp. + r20a_tcp = R20A * tcp + r20b_tcp = R20B * tcp + k_AB_tcp = k_AB * tcp + k_BA_tcp = k_BA * tcp + # Complex dw. + dw_tcp_C = dw * tcp * 1j + + # Fill in the elements. + #matrix[0, 0] = -k_AB - R20A + #matrix[0, 1] = k_BA + #matrix[1, 0] = k_AB + #matrix[1, 1] = -k_BA + 1.j*dw - R20B + + m_r20a = array([ + [-1.0, 0.0], + [0.0, 0.0],], complex64) + + m_r20b = array([ + [0.0, 0.0], + [0.0, -1.0],], complex64) + + m_k_AB = array([ + [-1.0, 0.0], + [1.0, 0.0],], complex64) + + m_k_BA = array([ + [0.0, 1.0], + [0.0, -1.0],], complex64) + + m_dw = array([ + [0.0, 0.0], + [0.0, 1.0],], complex64) + + # Multiply and expand. + m_r20a_tcp = multiply.outer( r20a_tcp, m_r20a ) + m_r20b_tcp = multiply.outer( r20b_tcp, m_r20b ) + + # Multiply and expand. + m_k_AB_tcp = multiply.outer( k_AB_tcp, m_k_AB ) + m_k_BA_tcp = multiply.outer( k_BA_tcp, m_k_BA ) + + # Multiply and expand. + m_dw_tcp_C = multiply.outer( dw_tcp_C, m_dw ) + + # Collect matrix. + matrix = (m_r20a_tcp + m_r20b_tcp + m_k_AB_tcp + m_k_BA_tcp + m_dw_tcp_C) + + return matrix def r2eff_ns_mmq_2site_mq(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): @@ -141,6 +211,10 @@ # Extract shape of experiment. NS, NM, NO = num_points.shape + # Populate the m1 and m2 matrices (only once per function call for speed). + m1_mat = populate_matrix_rankN(R20A=R20A, R20B=R20B, dw=-dw - dwH, k_AB=k_AB, k_BA=k_BA, tcp=tcp) + m2_mat = populate_matrix_rankN(R20A=R20A, R20B=R20B, dw=dw - dwH, k_AB=k_AB, k_BA=k_BA, tcp=tcp) + # Loop over spins. for si in range(NS): # Loop over the spectrometer frequencies. @@ -160,6 +234,23 @@ # Loop over the time points, back calculating the R2eff values. for i in range(num_points_i): + m1_mat_i = m1_mat[si, mi, oi, i] + m2_mat_i = m2_mat[si, mi, oi, i] + + diff_m1 = abs(sum(m1*tcp[si, mi, oi, i] - m1_mat_i)) + if diff_m1 > 1.0e-06: + print diff_m1 + print m1*tcp[si, mi, oi, i] + print m1_mat_i + print asd + + diff_m2 = abs(sum(m2*tcp[si, mi, oi, i] - m2_mat_i)) + if diff_m2 > 1.0e-06: + print diff_m2 + print m2*tcp[si, mi, oi, i] + print m2_mat_i + print asd + # The M1 and M2 matrices. M1 = matrix_exponential(m1*tcp[si, mi, oi, i]) # Equivalent to D+. M2 = matrix_exponential(m2*tcp[si, mi, oi, i]) # Equivalent to Z-.