Author: tlinnet
Date: Thu Jun 19 21:05:51 2014
New Revision: 24173
URL: http://svn.gna.org/viewcvs/relax?rev=24173&view=rev
Log:
Cleaned up the code of NS R1rho 2site, and removed the matrix argument to the
function.
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_r1rho_2site.py
Modified: branches/disp_spin_speed/lib/dispersion/ns_r1rho_2site.py
URL:
http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/lib/dispersion/ns_r1rho_2site.py?rev=24173&r1=24172&r2=24173&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/dispersion/ns_r1rho_2site.py (original)
+++ branches/disp_spin_speed/lib/dispersion/ns_r1rho_2site.py Thu Jun 19
21:05:51 2014
@@ -59,7 +59,7 @@
from lib.linear_algebra.matrix_exponential import matrix_exponential,
matrix_exponential_rankN
-def ns_r1rho_2site(M0=None, matrix=None, r1rho_prime=None, omega=None,
offset=None, r1=0.0, pA=None, dw=None, kex=None, spin_lock_fields=None,
relax_time=None, inv_relax_time=None, back_calc=None, num_points=None):
+def ns_r1rho_2site(M0=None, r1rho_prime=None, omega=None, offset=None,
r1=0.0, pA=None, dw=None, kex=None, spin_lock_fields=None, relax_time=None,
inv_relax_time=None, back_calc=None, num_points=None):
"""The 2-site numerical solution to the Bloch-McConnell equation for
R1rho data.
This function calculates and stores the R1rho values.
@@ -67,8 +67,6 @@
@keyword M0: This is a vector that contains the initial
magnetizations corresponding to the A and B state transverse magnetizations.
@type M0: numpy float64, rank-1, 7D array
- @keyword matrix: A numpy array to be populated to create the
evolution matrix.
- @type matrix: numpy rank-2, 6D float64 array
@keyword r1rho_prime: The R1rho_prime parameter value (R1rho with
no exchange).
@type r1rho_prime: numpy float array of rank [NS][NM][NO][ND]
@keyword omega: The chemical shift for the spin in rad/s.
@@ -115,31 +113,17 @@
for mi in range(NM):
# Loop over offsets:
for oi in range(NO):
- # Extract parameters from array.
- omega_i = omega[0, si, mi, oi, 0]
- offset_i = offset[0, si, mi, oi, 0]
- r1_i = r1[0, si, mi, oi, 0]
- dw_i = dw[0, si, mi, oi, 0]
-
- r1rho_prime_i = r1rho_prime[0, si, mi, oi]
- spin_lock_fields_i = spin_lock_fields[0, si, mi, oi]
- relax_time_i = relax_time[0, si, mi, oi]
- inv_relax_time_i = inv_relax_time[0, si, mi, oi]
- back_calc_i = back_calc[0, si, mi, oi]
+ # Extract number of points.
num_points_i = num_points[0, si, mi, oi]
# Repetitive calculations (to speed up calculations).
- Wa = omega_i # Larmor frequency [s^-1].
- Wb = omega_i + dw_i # Larmor frequency [s^-1].
- W = pA*Wa + pB*Wb # Population-averaged Larmor
frequency [s^-1].
- dA = Wa - offset_i # Offset of spin-lock from A.
- dB = Wb - offset_i # Offset of spin-lock from B.
- d = W - offset_i # Offset of spin-lock from
population-average.
+ # Offset of spin-lock from A.
+ dA = omega[0, si, mi, oi, 0] - offset[0, si, mi, oi, 0]
# Loop over the time points, back calculating the R2eff
values.
for j in range(num_points_i):
# The following lines rotate the magnetization previous
to spin-lock into the weff frame.
- theta = atan2(spin_lock_fields_i[j], dA)
+ theta = atan2(spin_lock_fields[0, si, mi, oi, j], dA)
M0[0] = sin(theta) # The A state initial X
magnetisation.
M0[2] = cos(theta) # The A state initial Z
magnetisation.
@@ -147,10 +131,11 @@
Rexpo_i = Rexpo_mat[0, si, mi, oi, j]
# Magnetization evolution.
- MA = dot(M0, dot(Rexpo_i, M0))
+ MA = dot(Rexpo_i, M0)
+ MA = dot(M0, MA)
# The next lines calculate the R1rho using a two-point
approximation, i.e. assuming that the decay is mono-exponential.
if MA <= 0.0 or isNaN(MA):
back_calc[0, si, mi, oi, j] = 1e99
else:
- back_calc[0, si, mi, oi, j]= -inv_relax_time_i[j] *
log(MA)
+ back_calc[0, si, mi, oi, j]= -inv_relax_time[0, si,
mi, oi, j] * log(MA)
r24173 - /branches/disp_spin_speed/lib/dispersion/ns_r1rho_2site.py