Author: bugman
Date: Fri Feb 25 19:47:38 2011
New Revision: 12635
URL: http://svn.gna.org/viewcvs/relax?rev=12635&view=rev
Log:
This change is related to the task #6397 (https://gna.org/task/?6397)
kada _at_ chemi _dot_ muni _dot_ cz
https://mail.gna.org/public/relax-devel/2011-02/msg00076.html
https://gna.org/support/download.php?file_id=12556
This patch includes change in func_mf, func_local_tm, func_diff, func_all,
dfunc_mf, dfunc_local_tm,
dfunc_diff, dfunc_all, d2func_mf, d2func_local_tm, d2func_diff, d2func_all
functions of class Mf in
a file maths_fns/mf.py. The functions were modified in order to handle data
for more interactions.
Due to the equality of (d,d2)ri and (d,d2)ri_prime variables, the
(d,d2)ri_prime were replaced by
(d,d2)ri and the equality was removed. Moreover, (d,d2)ri was redefined as a
cumulative sum of
individual interaction contributions to the total relaxation rate or
corresponding derivatives.
Modified:
branches/cst/maths_fns/mf.py
Modified: branches/cst/maths_fns/mf.py
URL:
http://svn.gna.org/viewcvs/relax/branches/cst/maths_fns/mf.py?rev=12635&r1=12634&r2=12635&view=diff
==============================================================================
--- branches/cst/maths_fns/mf.py (original)
+++ branches/cst/maths_fns/mf.py Fri Feb 25 19:47:38 2011
@@ -436,10 +436,9 @@
data[j].create_ri_comps(data[j], params)
# Calculate the R1, R2, and sigma_noe values.
- data[j].ri_prime = data[j].create_ri_prime(data[j])
+ data.ri = data.ri + data[j].create_ri_prime(data[j])
# Calculate the NOE values.
- data.ri = data.ri_prime * 1.0
for m in xrange(data.num_ri):
if data.create_ri[m]:
data.create_ri[m](data, m, data.remap_table[m], data.get_r1,
params)
@@ -492,10 +491,9 @@
data[j].create_ri_comps(data[j], params)
# Calculate the R1, R2, and sigma_noe values.
- data[j].ri_prime = data[j].create_ri_prime(data[j])
+ data.ri = data.ri + data[j].create_ri_prime(data[j])
# Calculate the NOE values.
- data.ri = data.ri_prime * 1.0
for m in xrange(data.num_ri):
if data.create_ri[m]:
data.create_ri[m](data, m, data.remap_table[m], data.get_r1,
params)
@@ -558,10 +556,9 @@
data[j].create_ri_comps(data[j], data[j].param_values)
# Calculate the R1, R2, and sigma_noe values.
- data[j].ri_prime = data[j].create_ri_prime(data[j])
+ data.ri = data.ri + data[j].create_ri_prime(data[j])
# Calculate the NOE values.
- data.ri = data.ri_prime * 1.0
for m in xrange(data.num_ri):
if data.create_ri[m]:
data.create_ri[m](data, m, data.remap_table[m],
data.get_r1, data.param_values)
@@ -627,10 +624,10 @@
data[j].create_ri_comps(data[j], params)
# Calculate the R1, R2, and sigma_noe values.
- data[j].ri_prime = data[j].create_ri_prime(data[j])
+ data.ri = data.ri + data[j].create_ri_prime(data[j])
+
# Calculate the NOE values.
- data.ri = data.ri_prime * 1.0
for m in xrange(data.num_ri):
if data.create_ri[m]:
data.create_ri[m](data, m, data.remap_table[m],
data.get_r1, params)
@@ -684,10 +681,9 @@
data[k].create_dri_comps(data[k], params)
# Calculate the R1, R2, and sigma_noe gradients.
- data[k].dri_prime[j] = data[k].create_dri_prime[j](data[k])
+ data.dri[j] = data.dri[j] +
data[k].create_dri_prime[j](data[k])
# Loop over the relaxation values and modify the NOE gradients.
- data.dri[j] = data.dri_prime[j]
for m in xrange(data.num_ri):
if data.create_dri[m]:
data.create_dri[m](data, m, data.remap_table[m],
data.get_dr1, params, j)
@@ -749,10 +745,9 @@
data[k].create_dri_comps(data[k], params)
# Calculate the R1, R2, and sigma_noe gradients.
- data[k].dri_prime[j] = data[k].create_dri_prime[j](data[k])
+ data.dri[j] = data.dri[j] +
data[k].create_dri_prime[j](data[k])
# Loop over the relaxation values and modify the NOE gradients.
- data.dri[j] = data.dri_prime[j]
for m in xrange(data.num_ri):
if data.create_dri[m]:
data.create_dri[m](data, m, data.remap_table[m],
data.get_dr1, params, j)
@@ -829,10 +824,9 @@
data[k].create_dri_comps(data[k], data[k].param_values)
# Calculate the R1, R2, and sigma_noe gradients.
- data[k].dri_prime[j] =
data[k].create_dri_prime[j](data[k])
+ data.dri[j] = data.dri[j] +
data[k].create_dri_prime[j](data[k])
# Loop over the relaxation values and modify the NOE
gradients.
- data.dri[j] = data.dri_prime[j]
for m in xrange(data.num_ri):
if data.create_dri[m]:
data.create_dri[m](data, m, data.remap_table[m],
data.get_dr1, params, j)
@@ -912,10 +906,9 @@
data[k].create_dri_comps(data[k], params)
# Calculate the R1, R2, and sigma_noe gradients.
- data[k].dri_prime[j] =
data[k].create_dri_prime[j](data[k])
+ data.dri[j] = data.dri[j] +
data[k].create_dri_prime[j](data[k])
# Loop over the relaxation values and modify the NOE
gradients.
- data.dri[j] = data.dri_prime[j]
for m in xrange(data.num_ri):
if data.create_dri[m]:
data.create_dri[m](data, m, data.remap_table[m],
data.get_dr1, params, j)
@@ -973,10 +966,9 @@
# Calculate the R1, R2, and sigma_noe Hessians.
if data[m].create_d2ri_prime[j][k]:
- data[m].d2ri_prime[j, k] =
data[m].create_d2ri_prime[j][k](data[m])
+ data.d2ri[j, k] = data.d2ri[j, k] +
data[m].create_d2ri_prime[j][k](data[m])
# Loop over the relaxation values and modify the NOE
Hessians.
- data.d2ri[j, k] = data.d2ri_prime[j, k]
for m in xrange(data.num_ri):
if data.create_d2ri[m]:
data.create_d2ri[m](data, m, data.remap_table[m],
data.get_d2r1, params, j, k)
@@ -1028,10 +1020,9 @@
# Calculate the R1, R2, and sigma_noe Hessians.
if data[m].create_d2ri_prime[j][k]:
- data[m].d2ri_prime[j, k] =
data[m].create_d2ri_prime[j][k](data[m])
+ data.d2ri[j, k] = data.d2ri[j, k] +
data[m].create_d2ri_prime[j][k](data[m])
# Loop over the relaxation values and modify the NOE
Hessians.
- data.d2ri[j, k] = data.d2ri_prime[j, k]
for m in xrange(data.num_ri):
if data.create_d2ri[m]:
data.create_d2ri[m](data, m, data.remap_table[m],
data.get_d2r1, params, j, k)
@@ -1101,10 +1092,9 @@
# Calculate the R1, R2, and sigma_noe Hessians.
if data[m].create_d2ri_prime[j][k]:
- data[m].d2ri_prime[j, k] =
data[m].create_d2ri_prime[j][k](data[m])
+ data.d2ri[j, k] = data.d2ri[j, k] +
data[m].create_d2ri_prime[j][k](data[m])
# Loop over the relaxation values and modify the NOE
Hessians.
- data.d2ri[j, k] = data.d2ri_prime[j, k]
for m in xrange(data.num_ri):
if data.create_d2ri[m]:
data.create_d2ri[m](data, m,
data.remap_table[m], data.get_d2r1, params, j, k)
@@ -1177,10 +1167,9 @@
# Calculate the R1, R2, and sigma_noe Hessians.
if data[m].create_d2ri_prime[j][k]:
- data[m].d2ri_prime[j, k] =
data[m].create_d2ri_prime[j][k](data[m])
+ data.d2ri[j, k] = data.d2ri[j, k] +
data[m].create_d2ri_prime[j][k](data[m])
# Loop over the relaxation values and modify the NOE
Hessians.
- data.d2ri[j, k] = data.d2ri_prime[j, k]
for m in xrange(data.num_ri):
if data.create_d2ri[m]:
data.create_d2ri[m](data, m,
data.remap_table[m], data.get_d2r1, params, j, k)
r12635 - /branches/cst/maths_fns/mf.py