Author: bugman
Date: Tue Oct 7 14:33:32 2014
New Revision: 26185
URL: http://svn.gna.org/viewcvs/relax?rev=26185&view=rev
Log:
Merged revisions 26167-26174 via svnmerge from
svn+ssh://bugman@xxxxxxxxxxx/svn/relax/trunk
........
r26167 | tlinnet | 2014-10-06 17:07:49 +0200 (Mon, 06 Oct 2014) | 3 lines
In the dispersion API calculate(), used the API function model_loop() to
loop over the clusters instead.
Bug #22754 (https://gna.org/bugs/index.php?22754): The minimise.calculate()
does not calculate chi2 value for clustered residues.
........
r26168 | tlinnet | 2014-10-06 17:07:54 +0200 (Mon, 06 Oct 2014) | 5 lines
Removed then function loop_cluster_ids() from dispersion API().
This should be implemented elsewhere.
Bug #22754 (https://gna.org/bugs/index.php?22754): The minimise.calculate()
does not calculate chi2 value for clustered residues.
........
r26169 | tlinnet | 2014-10-06 17:07:55 +0200 (Mon, 06 Oct 2014) | 3 lines
Updated the API set_param_values() function to use model_loop() to get the
spin_ids from the cluster.
Bug #22754 (https://gna.org/bugs/index.php?22754): The minimise.calculate()
does not calculate chi2 value for clustered residues.
........
r26170 | tlinnet | 2014-10-06 17:07:57 +0200 (Mon, 06 Oct 2014) | 11 lines
Initial try to fix unit test test_value_set_r1_rit().
The problem is, that no spin-id can be generated, since the spins are
created manually,
"
File
"/sbinlab2/tlinnet/software/NMR-relax/relax_trunk/pipe_control/mol_res_spin.py",
line 1498, in generate_spin_id_unique
if res and res.name != None and mol._res_name_count[res.name] > 1:
AttributeError: 'MoleculeContainer' object has no attribute
'_res_name_count'
"
Bug #22754 (https://gna.org/bugs/index.php?22754): The minimise.calculate()
does not calculate chi2 value for clustered residues.
........
r26171 | tlinnet | 2014-10-06 17:21:32 +0200 (Mon, 06 Oct 2014) | 3 lines
Removed the checking of MODEL_LIST_MMQ, and spin.isotope from
optimisation.back_calc_r2eff(), since this check is already covered.
Bug #22754 (https://gna.org/bugs/index.php?22754): The minimise.calculate()
does not calculate chi2 value for clustered residues.
........
r26172 | tlinnet | 2014-10-06 18:03:28 +0200 (Mon, 06 Oct 2014) | 3 lines
Fix for references to "spin" in optimisation.back_calc_r2eff().
Bug #22754 (https://gna.org/bugs/index.php?22754): The minimise.calculate()
does not calculate chi2 value for clustered residues.
........
r26173 | tlinnet | 2014-10-06 18:03:30 +0200 (Mon, 06 Oct 2014) | 3 lines
Fix for looping performed twice in relax_disp API model_loop().
Bug #22754 (https://gna.org/bugs/index.php?22754): The minimise.calculate()
does not calculate chi2 value for clustered residues.
........
r26174 | tlinnet | 2014-10-06 18:03:32 +0200 (Mon, 06 Oct 2014) | 10 lines
Removed unused proton reference in relax_disp API calculate().
There is though some problems with these tests:
F 1.93 s for Relax_disp.test_korzhnev_2005_15n_dq_data
F 2.01 s for Relax_disp.test_korzhnev_2005_1h_mq_data
F 1.93 s for Relax_disp.test_korzhnev_2005_1h_sq_data
It is unsure where these comes from.
Bug #22754 (https://gna.org/bugs/index.php?22754): The minimise.calculate()
does not calculate chi2 value for clustered residues.
........
Modified:
branches/frame_order_cleanup/ (props changed)
branches/frame_order_cleanup/specific_analyses/relax_disp/api.py
branches/frame_order_cleanup/specific_analyses/relax_disp/optimisation.py
Propchange: branches/frame_order_cleanup/
------------------------------------------------------------------------------
--- svnmerge-integrated (original)
+++ svnmerge-integrated Tue Oct 7 14:33:32 2014
@@ -1 +1 @@
-/trunk:1-26139,26142-26166
+/trunk:1-26139,26142-26174
Modified: branches/frame_order_cleanup/specific_analyses/relax_disp/api.py
URL:
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/specific_analyses/relax_disp/api.py?rev=26185&r1=26184&r2=26185&view=diff
==============================================================================
--- branches/frame_order_cleanup/specific_analyses/relax_disp/api.py
(original)
+++ branches/frame_order_cleanup/specific_analyses/relax_disp/api.py Tue
Oct 7 14:33:32 2014
@@ -261,9 +261,6 @@
check_mol_res_spin_data()
check_model_type()
- # Get the looping list over cluster ids.
- cluster_ids, cluster_spin_list, cluster_spin_id_list,
cluster_spin_sel_list, clust_contain_spin_id_list =
self.loop_cluster_ids(spin_id=spin_id)
-
# Special exponential curve-fitting for the R2eff model.
if cdp.model_type == MODEL_R2EFF:
calculate_r2eff()
@@ -273,48 +270,30 @@
# 1H MMQ flag.
proton_mmq_flag = has_proton_mmq_cpmg()
- # Loop over the cluster ids.
- for i, cluster_id in enumerate(cluster_ids):
- # Get the spins, ids and if the cluster contains the spin of
interest.
- cluster_spins = cluster_spin_list[i]
- cluster_spin_ids = cluster_spin_id_list[i]
- spin_of_interest = clust_contain_spin_id_list[i]
-
- # If spin of interest is present:
- if spin_of_interest:
- # If it is a free free spin, then calculate per spin.
- if cluster_id == 'free spins':
- for si, spin in enumerate(cluster_spins):
- cur_spin_id = cluster_spin_ids[si]
-
- # Skip protons for MMQ data.
- if spin.model in MODEL_LIST_MMQ and spin.isotope
== '1H':
- continue
-
- # Get the attached proton.
- proton = None
- if proton_mmq_flag:
- proton =
return_attached_protons(cur_spin_id)[0]
-
- # The back calculated values.
- back_calc = back_calc_r2eff(spins=[spin],
spin_ids=[cur_spin_id], store_chi2=True)
-
- # Pack the data.
- pack_back_calc_r2eff(spin=spin,
spin_id=cur_spin_id, si=0, back_calc=back_calc,
proton_mmq_flag=proton_mmq_flag)
-
- else:
- # The back calculated values.
- back_calc = back_calc_r2eff(spins=cluster_spins,
spin_ids=cluster_spin_ids, store_chi2=True)
-
- # Pack the data.
- for si, spin in enumerate(cluster_spins):
- cur_spin_id = cluster_spin_ids[si]
-
- # Skip protons for MMQ data.
- if spin.model in MODEL_LIST_MMQ and spin.isotope
== '1H':
- continue
-
- pack_back_calc_r2eff(spin=spin,
spin_id=cur_spin_id, si=si, back_calc=back_calc,
proton_mmq_flag=proton_mmq_flag)
+ # Loop over the spin blocks.
+ model_index = -1
+ for spin_ids in self.model_loop():
+ # Increment the model index.
+ model_index += 1
+
+ # The spin containers.
+ spins = spin_ids_to_containers(spin_ids)
+
+ # Skip deselected clusters.
+ skip = True
+ for spin in spins:
+ if spin.select:
+ skip = False
+ if skip:
+ continue
+
+ # The back calculated values.
+ back_calc = back_calc_r2eff(spins=spins, spin_ids=spin_ids,
store_chi2=True)
+
+ # Pack the data.
+ for i, spin_id in enumerate(spin_ids):
+ spin = spins[i]
+ pack_back_calc_r2eff(spin=spin, spin_id=spin_id, si=i,
back_calc=back_calc, proton_mmq_flag=proton_mmq_flag)
def constraint_algorithm(self):
@@ -641,90 +620,6 @@
# Minimisation.
self.minimise(min_algor='grid', lower=lower, upper=upper, inc=inc,
scaling_matrix=scaling_matrix, constraints=constraints, verbosity=verbosity,
sim_index=sim_index)
-
-
- def loop_cluster_ids(self, spin_id=None):
- """Create list of cluster ids, its associated list of spin
containers, its associated list of spin_ids, the selection string for the
cluster id and bool to determine if spin of interest is in the cluster.
-
- @param spin_id: The spin identification string.
- @type spin_id: None
- @return: The list of cluster ids, the nested list of spin
container instances, the nested list of spin ids, the selection string for
the cluster and list of boolean if spin_id is contained in cluster_id.
- @rtype: list of str, list of list of spin container,
list of list of spin ids, list of str, list of bool
- """
-
- # Initialise cluster ids.
- cluster_ids = ['free spins']
-
- # Add the defined cluster IDs.
- if hasattr(cdp, 'clustering'):
- for key in list(cdp.clustering.keys()):
- if key not in cluster_ids:
- cluster_ids.append(key)
-
- # Now collect spins and spin_id per cluster ids.
- cluster_spin_list = []
- cluster_spin_id_list = []
- cluster_spin_sel_list = []
- clust_contain_spin_id_list = []
-
- # Loop over the cluster ids
- if hasattr(cdp, 'clustering'):
- # Now loop over the cluster_ids in the list, and collect per id.
- for cluster_id in cluster_ids:
- cluster_id_spin_list = []
- cluster_id_spin_id_list = []
- # Now loop through spins in the clustered id, and collect
- col_sel_str = ''
- mol_token = None
- for clust_spin_id in cdp.clustering[cluster_id]:
- clust_spin = return_spin(clust_spin_id)
-
- # Skip de-selected
- if not clust_spin.select:
- continue
-
- # Add to list.
- cluster_id_spin_list.append(clust_spin)
- cluster_id_spin_id_list.append(clust_spin_id)
-
- # Add id to string
- mol_token, res_token, spin_token =
tokenise(clust_spin_id)
- col_sel_str += '%s,' % (res_token)
-
- # Make selection for molecule.
- if mol_token == None:
- col_sel_str = ':' + col_sel_str
- else:
- col_sel_str = '#%s:' % mol_token + col_sel_str
-
- # Make a selection object, based on the cluster id.
- select_obj = Selection(col_sel_str)
- # Does the current cluster id contain the spin of interest.
- clust_contain_spin_id = select_obj.contains_spin_id(spin_id)
- # If the spin_id is set to None, then we calculate for all:
- if spin_id == None:
- clust_contain_spin_id = True
-
- cluster_spin_list.append(cluster_id_spin_list)
- cluster_spin_id_list.append(cluster_id_spin_id_list)
- cluster_spin_sel_list.append(col_sel_str)
- clust_contain_spin_id_list.append(clust_contain_spin_id)
-
- # If clustering has not been specified, then collect for free spins,
according to selection.
- else:
- # Now loop over selected spins.
- free_spin_list = []
- free_spin_id_list = []
- for cur_spin, cur_spin_id in spin_loop(selection=spin_id,
return_id=True, skip_desel=True):
- free_spin_list.append(cur_spin)
- free_spin_id_list.append(cur_spin_id)
-
- cluster_spin_list.append(free_spin_list)
- cluster_spin_id_list.append(free_spin_id_list)
- cluster_spin_sel_list.append(None)
- clust_contain_spin_id_list.append(True)
-
- return cluster_ids, cluster_spin_list, cluster_spin_id_list,
cluster_spin_sel_list, clust_contain_spin_id_list
def map_bounds(self, param, spin_id=None):
@@ -951,7 +846,24 @@
"""
# Loop over individual spins for the R2eff model.
- if cdp.model_type == MODEL_R2EFF:
+ if hasattr(cdp, 'model_type'):
+ if cdp.model_type == MODEL_R2EFF:
+ # The spin loop.
+ for spin, spin_id in spin_loop(return_id=True):
+ # Skip deselected spins
+ if not spin.select:
+ continue
+
+ # Yield the spin ID as a list.
+ yield [spin_id]
+
+ # The cluster loop.
+ else:
+ for spin_ids in loop_cluster(skip_desel=False):
+ yield spin_ids
+
+ # If no model is present, then set the values.
+ else:
# The spin loop.
for spin, spin_id in spin_loop(return_id=True):
# Skip deselected spins
@@ -960,11 +872,6 @@
# Yield the spin ID as a list.
yield [spin_id]
-
- # The cluster loop.
- else:
- for spin_ids in loop_cluster(skip_desel=False):
- yield spin_ids
def model_statistics(self, model_info=None, spin_id=None,
global_stats=None):
@@ -1270,46 +1177,42 @@
is_str_list(param, 'parameter name')
is_list(value, 'parameter value')
- # Get the looping list over cluster ids.
- cluster_ids, cluster_spin_list, cluster_spin_id_list,
cluster_spin_sel_list, clust_contain_spin_id_list =
self.loop_cluster_ids(spin_id=spin_id)
-
- # Loop over the cluster ids.
- for j, cluster_id in enumerate(cluster_ids):
- # Get the spins, ids and if the cluster contains the spin of
interest.
- cluster_spins = cluster_spin_list[j]
- cluster_spin_ids = cluster_spin_id_list[j]
- spin_of_interest = clust_contain_spin_id_list[j]
- cluster_spin_sel = cluster_spin_sel_list[j]
-
- # If spin of interest is present:
- if spin_of_interest:
- # If it is a free free spin, then calculate per spin.
- if cluster_id == 'free spins':
- select_string = spin_id
+ # Loop over the spin blocks.
+ model_index = -1
+ for spin_ids in self.model_loop():
+ # Increment the model index.
+ model_index += 1
+
+ # The spin containers.
+ spins = spin_ids_to_containers(spin_ids)
+
+ # Skip deselected clusters.
+ skip = True
+ for spin in spins:
+ if spin.select:
+ skip = False
+ if skip:
+ continue
+
+ # Loop over the parameters.
+ for i in range(len(param)):
+ param_i = param[i]
+ value_i = value[i]
+
+ # Is the parameter is valid?
+ if not self._PARAMS.contains(param_i):
+ raise RelaxError("The parameter '%s' is not valid for
this data pipe type." % param_i)
+
+ # If the parameter is a global parameter, then change for
all spins part of the cluster.
+ if param_i in ['pA', 'kex', 'tex', 'kB', 'kC', 'kex_AB',
'kex_BC', 'kex_AC']:
+ selection_list = spin_ids
else:
- select_string = cluster_spin_sel
-
- # Loop over the parameters.
- for i in range(len(param)):
- param_i = param[i]
- value_i = value[i]
-
- # Is the parameter is valid?
- if not self._PARAMS.contains(param_i):
- raise RelaxError("The parameter '%s' is not valid
for this data pipe type." % param_i)
-
- # If the parameter is a global parameter, then change
for all spins part of the cluster.
- if param_i in ['pA', 'kex', 'tex', 'kB', 'kC', 'kex_AB',
'kex_BC', 'kex_AC']:
- loop_select_string = select_string
- else:
- loop_select_string = spin_id
-
+ selection_list = [spin_id]
+
+ # Now loop over selections in the list.
+ for selection in selection_list:
# Spin loop.
- for spin in spin_loop(selection=loop_select_string):
- # Skip deselected spins.
- if not spin.select:
- continue
-
+ for spin in spin_loop(selection=selection):
# The object name.
obj_name = param_i
if error:
Modified:
branches/frame_order_cleanup/specific_analyses/relax_disp/optimisation.py
URL:
http://svn.gna.org/viewcvs/relax/branches/frame_order_cleanup/specific_analyses/relax_disp/optimisation.py?rev=26185&r1=26184&r2=26185&view=diff
==============================================================================
--- branches/frame_order_cleanup/specific_analyses/relax_disp/optimisation.py
(original)
+++ branches/frame_order_cleanup/specific_analyses/relax_disp/optimisation.py
Tue Oct 7 14:33:32 2014
@@ -133,11 +133,6 @@
@rtype: numpy rank-1 float array
"""
- # Skip protons for MMQ data.
- for spin in spins:
- if spin.model in MODEL_LIST_MMQ and spin.isotope == '1H':
- return
-
# Create the initial parameter vector.
param_vector = assemble_param_vector(spins=spins)
@@ -155,7 +150,7 @@
r1_setup()
offsets, spin_lock_fields_inter, chemical_shifts, tilt_angles,
Delta_omega, w_eff = return_offset_data(spins=spins, spin_ids=spin_ids,
field_count=field_count, spin_lock_offset=spin_lock_offset,
fields=spin_lock_nu1)
r1 = return_r1_data(spins=spins, spin_ids=spin_ids,
field_count=field_count)
- r1_fit = is_r1_optimised(spin.model)
+ r1_fit = is_r1_optimised(spins[0].model)
# The relaxation times.
if relax_times_new != None:
@@ -223,7 +218,7 @@
missing[ei][si][mi].append(zeros(num, int32))
# Initialise the relaxation dispersion fit functions.
- model = Dispersion(model=spin.model, num_params=param_num(spins=spins),
num_spins=len(spins), num_frq=field_count, exp_types=exp_types,
values=values, errors=errors, missing=missing, frqs=frqs, frqs_H=frqs_H,
cpmg_frqs=cpmg_frqs, spin_lock_nu1=spin_lock_nu1,
chemical_shifts=chemical_shifts, offset=offsets, tilt_angles=tilt_angles,
r1=r1, relax_times=relax_times, recalc_tau=recalc_tau, r1_fit=r1_fit)
+ model = Dispersion(model=spins[0].model,
num_params=param_num(spins=spins), num_spins=len(spins), num_frq=field_count,
exp_types=exp_types, values=values, errors=errors, missing=missing,
frqs=frqs, frqs_H=frqs_H, cpmg_frqs=cpmg_frqs, spin_lock_nu1=spin_lock_nu1,
chemical_shifts=chemical_shifts, offset=offsets, tilt_angles=tilt_angles,
r1=r1, relax_times=relax_times, recalc_tau=recalc_tau, r1_fit=r1_fit)
# Make a single function call. This will cause back calculation and the
data will be stored in the class instance.
chi2 = model.func(param_vector)
r26185 - in /branches/frame_order_cleanup: ./ specific_analyses/relax_disp/api.py specific_analyses/relax_disp/optimisation.py