Author: tlinnet
Date: Thu Jun 19 20:17:47 2014
New Revision: 24165
URL: http://svn.gna.org/viewcvs/relax?rev=24165&view=rev
Log:
Added the ns matrice, rr1rho_3d_rankN, to collect the multi dimensional 3D
exchange matrix, of rank [NE][NS][NM][NO][ND][6][6].
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_matrices.py
Modified: branches/disp_spin_speed/lib/dispersion/ns_matrices.py
URL:
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/dispersion/ns_matrices.py?rev=24165&r1=24164&r2=24165&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/dispersion/ns_matrices.py (original)
+++ branches/disp_spin_speed/lib/dispersion/ns_matrices.py Thu Jun 19
20:17:47 2014
@@ -462,3 +462,134 @@
matrix[3, 0] = k_AB
matrix[4, 1] = k_AB
matrix[5, 2] = k_AB
+
+
+def rr1rho_3d_rankN(R1=None, r1rho_prime=None, pA=None, pB=None, dw=None,
omega=None, offset=None, w1=None, k_AB=None, k_BA=None):
+ """Definition of the multidimensional 3D exchange matrix, of rank
[NE][NS][NM][NO][ND][6][6].
+
+ This code originates from the funNumrho.m file from the Skrynikov &
Tollinger code (the sim_all.tar file
https://gna.org/support/download.php?file_id=18404 attached to
https://gna.org/task/?7712#comment5).
+
+
+ @keyword R1: The longitudinal, spin-lattice relaxation rate.
+ @type R1: numpy float array of rank [NE][NS][NM][NO][ND]
+ @keyword r1rho_prime: The R1rho transverse, spin-spin relaxation rate
in the absence of exchange.
+ @type r1rho_prime: numpy float array of rank [NE][NS][NM][NO][ND]
+ @keyword pA: The population of state A.
+ @type pA: float
+ @keyword pB: The population of state B.
+ @type pB: float
+ @keyword dw: The chemical exchange difference between states
A and B in rad/s.
+ @type dw: numpy float array of rank [NS][NM][NO][ND]
+ @keyword omega: The chemical shift for the spin in rad/s.
+ @type omega: numpy float array of rank [NS][NM][NO][ND]
+ @keyword offset: The spin-lock offsets for the data.
+ @type offset: numpy float array of rank [NS][NM][NO][ND]
+ @keyword w1: The spin-lock field strength in rad/s.
+ @type w1: numpy float array of rank [NE][NS][NM][NO][ND]
+ @keyword k_AB: The forward exchange rate from state A to state
B.
+ @type k_AB: float
+ @keyword k_BA: The reverse exchange rate from state B to state
A.
+ @type k_BA: float
+ @keyword k_BA: The reverse exchange rate from state B to state
A.
+ @type k_BA: float
+ @return: The relaxation matrix.
+ @rtype: numpy float array of rank
[NE][NS][NM][NO][ND][6][6]
+ """
+
+ # Wa: The chemical shift offset of state A from the spin-lock. Larmor
frequency [s^-1].
+ Wa = omega
+ # Wb: The chemical shift offset of state A from the spin-lock. Larmor
frequency [s^-1].
+ Wb = omega + dw
+
+ # Population-averaged Larmor frequency [s^-1].
+ W = pA*Wa + pB*Wb
+
+ # Offset of spin-lock from A.
+ dA = Wa - offset
+
+ # Offset of spin-lock from B.
+ dB = Wb - offset
+
+ # Offset of spin-lock from population-average.
+ d = W - offset
+
+ wA=dA
+ wB=dB
+
+
+ m_r1rho_prime = array([
+ [-1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, -1.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, -1.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, -1.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0], ])
+
+ m_wA = array([
+ [0.0, -1.0, 0.0, 0.0, 0.0, 0.0],
+ [1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0], ])
+
+ m_wB = array([
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, -1.0, 0.0],
+ [0.0, 0.0, 0.0, 1.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0], ])
+
+ m_w1 = array([
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, -1.0, 0.0, 0.0, 0.0],
+ [0.0, 1.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, -1.0],
+ [0.0, 0.0, 0.0, 0.0, 1.0, 0.0], ])
+
+ m_k_AB = array([
+ [-1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, -1.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, -1.0, 0.0, 0.0, 0.0],
+ [1.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 1.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 1.0, 0.0, 0.0, 0.0], ])
+
+ m_k_BA = array([
+ [0.0, 0.0, 0.0, 1.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 1.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 1.0],
+ [0.0, 0.0, 0.0, -1.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, -1.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, -1.0], ])
+
+ m_R1 = array([
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, -1.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
+ [0.0, 0.0, 0.0, 0.0, 0.0, -1.0], ])
+
+ # Multiply and expand.
+ mat_r1rho_prime = multiply.outer( r1rho_prime, m_r1rho_prime )
+
+ mat_wA = multiply.outer( wA, m_wA )
+ mat_wB = multiply.outer( wB, m_wB )
+
+ mat_w1 = multiply.outer( w1, m_w1 )
+
+ mat_k_AB = multiply.outer( k_AB, m_k_AB )
+ mat_k_BA = multiply.outer( k_BA, m_k_BA )
+
+ mat_R1 = multiply.outer( R1, m_R1 )
+
+ # Collect matrix.
+ matrix = (mat_r1rho_prime + mat_wA + mat_wB
+ + mat_w1 + mat_k_AB + mat_k_BA
+ + mat_R1)
+
+ # Return the matrix.
+ return matrix
r24165 - /branches/disp_spin_speed/lib/dispersion/ns_matrices.py