Author: tlinnet
Date: Tue Jun 17 15:49:54 2014
New Revision: 24039
URL: http://svn.gna.org/viewcvs/relax?rev=24039&view=rev
Log:
Fix for shortening the variables names.
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
branches/disp_spin_speed/lib/dispersion/ns_mmq_3site.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=24039&r1=24038&r2=24039&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py (original)
+++ branches/disp_spin_speed/lib/dispersion/ns_mmq_2site.py Tue Jun 17
15:49:54 2014
@@ -142,18 +142,18 @@
# Loop over offsets:
for oi in range(NO):
- r20a_si_mi_oi = R20A[si, mi, oi, 0]
- r20b_si_mi_oi = R20B[si, mi, oi, 0]
- dw_si_mi_oi = dw[si, mi, oi, 0]
- dwH_si_mi_oi = dwH[si, mi, oi, 0]
- num_points_si_mi_oi = num_points[si, mi, oi]
+ r20a_i = R20A[si, mi, oi, 0]
+ r20b_i = R20B[si, mi, oi, 0]
+ dw_i = dw[si, mi, oi, 0]
+ dwH_i = dwH[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).
- populate_matrix(matrix=m1, R20A=r20a_si_mi_oi,
R20B=r20b_si_mi_oi, dw=-dw_si_mi_oi - dwH_si_mi_oi, k_AB=k_AB, k_BA=k_BA)
# D+ matrix component.
- populate_matrix(matrix=m2, R20A=r20a_si_mi_oi,
R20B=r20b_si_mi_oi, dw=dw_si_mi_oi - dwH_si_mi_oi, k_AB=k_AB, k_BA=k_BA) #
Z- matrix component.
+ populate_matrix(matrix=m1, R20A=r20a_i, R20B=r20b_i,
dw=-dw_i - dwH_i, k_AB=k_AB, k_BA=k_BA) # D+ matrix component.
+ populate_matrix(matrix=m2, R20A=r20a_i, R20B=r20b_i, dw=dw_i
- dwH_i, k_AB=k_AB, k_BA=k_BA) # Z- matrix component.
# Loop over the time points, back calculating the R2eff
values.
- for i in range(num_points_si_mi_oi):
+ for i in range(num_points_i):
# 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-.
@@ -292,17 +292,17 @@
# Loop over offsets:
for oi in range(NO):
- r20a_si_mi_oi = R20A[si, mi, oi, 0]
- r20b_si_mi_oi = R20B[si, mi, oi, 0]
- dw_si_mi_oi = dw[si, mi, oi, 0]
- num_points_si_mi_oi = num_points[si, mi, oi]
+ r20a_i = R20A[si, mi, oi, 0]
+ r20b_i = R20B[si, mi, oi, 0]
+ dw_i = dw[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).
- populate_matrix(matrix=m1, R20A=r20a_si_mi_oi ,
R20B=r20b_si_mi_oi, dw=dw_si_mi_oi, k_AB=k_AB, k_BA=k_BA)
- populate_matrix(matrix=m2, R20A=r20a_si_mi_oi ,
R20B=r20b_si_mi_oi, dw=-dw_si_mi_oi, k_AB=k_AB, k_BA=k_BA)
+ populate_matrix(matrix=m1, R20A=r20a_i , R20B=r20b_i,
dw=dw_i, k_AB=k_AB, k_BA=k_BA)
+ populate_matrix(matrix=m2, R20A=r20a_i , R20B=r20b_i,
dw=-dw_i, k_AB=k_AB, k_BA=k_BA)
# Loop over the time points, back calculating the R2eff
values.
- for i in range(num_points_si_mi_oi):
+ for i in range(num_points_i):
# The A+/- matrices.
A_pos = matrix_exponential(m1*tcp[si, mi, oi, i])
A_neg = matrix_exponential(m2*tcp[si, mi, oi, i])
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=24039&r1=24038&r2=24039&view=diff
==============================================================================
--- branches/disp_spin_speed/lib/dispersion/ns_mmq_3site.py (original)
+++ branches/disp_spin_speed/lib/dispersion/ns_mmq_3site.py Tue Jun 17
15:49:54 2014
@@ -185,22 +185,22 @@
# Loop over offsets:
for oi in range(NO):
- r20a_si_mi_oi = R20A[si, mi, oi, 0]
- r20b_si_mi_oi = R20B[si, mi, oi, 0]
- r20c_si_mi_oi = R20C[si, mi, oi, 0]
-
- dw_AB_si_mi_oi=dw_AB[si, mi, oi, 0]
- dw_AC_si_mi_oi=dw_AC[si, mi, oi, 0]
- dwH_AB_si_mi_oi=dwH_AB[si, mi, oi, 0]
- dwH_AC_si_mi_oi=dwH_AC[si, mi, oi, 0]
- num_points_si_mi_oi = num_points[si, mi, oi]
+ 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).
- populate_matrix(matrix=m1, R20A=r20a_si_mi_oi,
R20B=r20b_si_mi_oi, R20C=r20c_si_mi_oi, dw_AB=-dw_AB_si_mi_oi -
dwH_AB_si_mi_oi, dw_AC=-dw_AC_si_mi_oi - dwH_AC_si_mi_oi, 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.
- populate_matrix(matrix=m2, R20A=r20a_si_mi_oi,
R20B=r20b_si_mi_oi, R20C=r20c_si_mi_oi, dw_AB=dw_AB_si_mi_oi -
dwH_AB_si_mi_oi, dw_AC=dw_AC_si_mi_oi - dwH_AC_si_mi_oi, 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.
+ populate_matrix(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.
+ populate_matrix(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_si_mi_oi):
+ for i in range(num_points_i):
# 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-.
@@ -346,22 +346,22 @@
# Loop over offsets:
for oi in range(NO):
- r20a_si_mi_oi = R20A[si, mi, oi, 0]
- r20b_si_mi_oi = R20B[si, mi, oi, 0]
- r20c_si_mi_oi = R20C[si, mi, oi, 0]
-
- dw_AB_si_mi_oi=dw_AB[si, mi, oi, 0]
- dw_AC_si_mi_oi=dw_AC[si, mi, oi, 0]
- dwH_AB_si_mi_oi=dwH_AB[si, mi, oi, 0]
- dwH_AC_si_mi_oi=dwH_AC[si, mi, oi, 0]
- num_points_si_mi_oi = num_points[si, mi, oi]
+ 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).
- populate_matrix(matrix=m1, R20A=r20a_si_mi_oi,
R20B=r20b_si_mi_oi, R20C=r20c_si_mi_oi, dw_AB=dw_AB_si_mi_oi,
dw_AC=dw_AC_si_mi_oi, k_AB=k_AB, k_BA=k_BA, k_BC=k_BC, k_CB=k_CB, k_AC=k_AC,
k_CA=k_CA)
- populate_matrix(matrix=m2, R20A=r20a_si_mi_oi,
R20B=r20b_si_mi_oi, R20C=r20c_si_mi_oi, dw_AB=-dw_AB_si_mi_oi,
dw_AC=-dw_AC_si_mi_oi, k_AB=k_AB, k_BA=k_BA, k_BC=k_BC, k_CB=k_CB, k_AC=k_AC,
k_CA=k_CA)
+ populate_matrix(matrix=m1, R20A=r20a_i, R20B=r20b_i,
R20C=r20c_i, dw_AB=dw_AB_i, dw_AC=dw_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)
+ populate_matrix(matrix=m2, R20A=r20a_i, R20B=r20b_i,
R20C=r20c_i, dw_AB=-dw_AB_i, dw_AC=-dw_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)
# Loop over the time points, back calculating the R2eff
values.
- for i in range(num_points_si_mi_oi):
+ for i in range(num_points_i):
# The A+/- matrices.
A_pos = matrix_exponential(m1*tcp[si, mi, oi, i])
A_neg = matrix_exponential(m2*tcp[si, mi, oi, i])
r24039 - in /branches/disp_spin_speed/lib/dispersion: ns_mmq_2site.py ns_mmq_3site.py