Author: tlinnet
Date: Fri Jun 20 17:42:54 2014
New Revision: 24211
URL: http://svn.gna.org/viewcvs/relax?rev=24211&view=rev
Log:
Started using the newly created highher dimensional Bloch-McConnell matrix
for 3-site exchange.
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=24211&r1=24210&r2=24211&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
17:42:54 2014
@@ -157,39 +157,13 @@
# Loop over offsets:
for oi in range(NO):
# Extract parameters from array.
- r20a_i = R20A[si, mi, oi, 0]
- r20b_i = R20B[si, mi, oi, 0]
- r20c_i = R20C[si, mi, oi, 0]
-
- dw_AB_i = dw_AB[si, mi, oi, 0]
- dw_AC_i = dw_AC[si, mi, oi, 0]
- dwH_AB_i = dwH_AB[si, mi, oi, 0]
- dwH_AC_i = dwH_AC[si, mi, oi, 0]
num_points_i = num_points[si, mi, oi]
-
- # Populate the m1 and m2 matrices (only once per function
call for speed).
- rmmq_3site(matrix=m1, R20A=r20a_i, R20B=r20b_i,
R20C=r20c_i, dw_AB=-dw_AB_i - dwH_AB_i, dw_AC=-dw_AC_i - dwH_AC_i,
k_AB=k_AB, k_BA=k_BA, k_BC=k_BC, k_CB=k_CB, k_AC=k_AC, k_CA=k_CA) # D+
matrix component.
- rmmq_3site(matrix=m2, R20A=r20a_i, R20B=r20b_i,
R20C=r20c_i, dw_AB=dw_AB_i - dwH_AB_i, dw_AC=dw_AC_i - dwH_AC_i, k_AB=k_AB,
k_BA=k_BA, k_BC=k_BC, k_CB=k_CB, k_AC=k_AC, k_CA=k_CA) # Z- matrix
component.
# 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]
- diff_m1 = m1*tcp[si, mi, oi, i] - m1_mat_i
- if abs(sum(diff_m1)) > 1e-5:
- print abs(sum(diff_m1))
- print diff_m1
- print asd
-
- m2_mat_i = m2_mat[si, mi, oi, i]
- diff_m2 = m2*tcp[si, mi, oi, i] - m2_mat_i
- if abs(sum(diff_m2)) > 1e-5:
- print abs(sum(diff_m2))
- print diff_m2
- 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-.
+ M1 = matrix_exponential(m1_mat[si, mi, oi, i]) #
Equivalent to D+.
+ M2 = matrix_exponential(m2_mat[si, mi, oi, i]) #
Equivalent to Z-.
# The complex conjugates M1* and M2*
M1_star = conj(M1) # Equivalent to D+*.
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