Author: bugman
Date: Fri Sep 26 22:31:27 2008
New Revision: 7377
URL: http://svn.gna.org/viewcvs/relax?rev=7377&view=rev
Log:
Converted the sim_init_values() method to the new design.
Modified:
1.3/specific_fns/model_free/main.py
Modified: 1.3/specific_fns/model_free/main.py
URL:
http://svn.gna.org/viewcvs/relax/1.3/specific_fns/model_free/main.py?rev=7377&r1=7376&r2=7377&view=diff
==============================================================================
--- 1.3/specific_fns/model_free/main.py (original)
+++ 1.3/specific_fns/model_free/main.py Fri Sep 26 22:31:27 2008
@@ -2711,11 +2711,11 @@
spin.s2 = spin.s2f * spin.s2s
- def sim_init_values(self, run):
- """Function for initialising Monte Carlo parameter values."""
-
- # Arguments.
- self.run = run
+ def sim_init_values(self):
+ """Initialise the Monte Carlo parameter values."""
+
+ # Alias the current data pipe.
+ cdp = ds[ds.current_pipe]
# Determine the model type.
model_type = self.determine_model_type()
@@ -2729,22 +2729,22 @@
# List of diffusion tensor parameters.
if model_type == 'diff' or model_type == 'all':
# Spherical diffusion.
- if ds.diff[self.run].type == 'sphere':
+ if cdp.diff_tensor.type == 'sphere':
diff_params = ['tm']
# Spheroidal diffusion.
- elif ds.diff[self.run].type == 'spheroid':
+ elif cdp.diff_tensor.type == 'spheroid':
diff_params = ['tm', 'Da', 'theta', 'phi']
# Ellipsoidal diffusion.
- elif ds.diff[self.run].type == 'ellipsoid':
+ elif cdp.diff_tensor.type == 'ellipsoid':
diff_params = ['tm', 'Da', 'Dr', 'alpha', 'beta', 'gamma']
# Test if Monte Carlo parameter values have already been set.
#############################################################
- # Diffusion tensor parameters and non residue specific minimisation
statistics.
+ # Diffusion tensor parameters and non spin specific minimisation
statistics.
if model_type == 'diff' or model_type == 'all':
# Loop over the parameters.
for object_name in diff_params:
@@ -2752,7 +2752,7 @@
sim_object_name = object_name + '_sim'
# Test if the simulation object already exists.
- if hasattr(ds.diff[self.run], sim_object_name):
+ if hasattr(cdp.diff_tensor, sim_object_name):
raise RelaxError, "Monte Carlo parameter values have
already been set."
# Loop over the minimisation stats objects.
@@ -2761,14 +2761,14 @@
sim_object_name = object_name + '_sim'
# Test if the simulation object already exists.
- if hasattr(ds, sim_object_name):
+ if hasattr(cdp, sim_object_name):
raise RelaxError, "Monte Carlo parameter values have
already been set."
- # Residue specific parameters.
+ # Spin specific parameters.
if model_type != 'diff':
- for i in xrange(len(ds.res[self.run])):
- # Skip deselected residues.
- if not ds.res[self.run][i].select:
+ for spin in spin_loop():
+ # Skip deselected spins.
+ if not spin.select:
continue
# Loop over all the parameter names.
@@ -2777,7 +2777,7 @@
sim_object_name = object_name + '_sim'
# Test if the simulation object already exists.
- if hasattr(ds.res[self.run][i], sim_object_name):
+ if hasattr(spin, sim_object_name):
raise RelaxError, "Monte Carlo parameter values have
already been set."
@@ -2790,27 +2790,20 @@
sim_object_name = object_name + '_sim'
# Create the simulation object.
- setattr(ds, sim_object_name, {})
+ setattr(cdp, sim_object_name, [])
# Get the simulation object.
- sim_object = getattr(ds, sim_object_name)
-
- # Add the run.
- sim_object[self.run] = []
+ sim_object = getattr(cdp, sim_object_name)
# Loop over the simulations.
- for j in xrange(ds.sim_number[self.run]):
+ for j in xrange(cdp.sim_number):
# Get the object.
- object = getattr(ds, object_name)
-
- # Test if the object has the key self.run.
- if not object.has_key(self.run):
- continue
+ object = getattr(cdp, object_name)
# Copy and append the data.
- sim_object[self.run].append(deepcopy(object[self.run]))
-
- # Diffusion tensor parameters and non residue specific minimisation
statistics.
+ sim_object.append(deepcopy(object))
+
+ # Diffusion tensor parameters and non spin specific minimisation
statistics.
if model_type == 'diff' or model_type == 'all':
# Loop over the parameters.
for object_name in diff_params:
@@ -2818,21 +2811,21 @@
sim_object_name = object_name + '_sim'
# Create the simulation object.
- setattr(ds.diff[self.run], sim_object_name, [])
+ setattr(cdp.diff_tensor, sim_object_name, [])
# Get the simulation object.
- sim_object = getattr(ds.diff[self.run], sim_object_name)
+ sim_object = getattr(cdp.diff_tensor, sim_object_name)
# Loop over the simulations.
- for j in xrange(ds.sim_number[self.run]):
+ for j in xrange(cdp.sim_number):
# Copy and append the data.
- sim_object.append(deepcopy(getattr(ds.diff[self.run],
object_name)))
-
- # Residue specific parameters.
+ sim_object.append(deepcopy(getattr(cdp.diff_tensor,
object_name)))
+
+ # Spin specific parameters.
if model_type != 'diff':
- for i in xrange(len(ds.res[self.run])):
- # Skip deselected residues.
- if not ds.res[self.run][i].select:
+ for spin in spin_loop():
+ # Skip deselected spins.
+ if not spin.select:
continue
# Loop over all the data names.
@@ -2841,15 +2834,15 @@
sim_object_name = object_name + '_sim'
# Create the simulation object.
- setattr(ds.res[self.run][i], sim_object_name, [])
+ setattr(spin, sim_object_name, [])
# Get the simulation object.
- sim_object = getattr(ds.res[self.run][i],
sim_object_name)
+ sim_object = getattr(spin, sim_object_name)
# Loop over the simulations.
- for j in xrange(ds.sim_number[self.run]):
+ for j in xrange(cdp.sim_number):
# Copy and append the data.
-
sim_object.append(deepcopy(getattr(ds.res[self.run][i], object_name)))
+ sim_object.append(deepcopy(getattr(spin,
object_name)))
# Loop over all the minimisation object names.
for object_name in min_names:
@@ -2857,15 +2850,15 @@
sim_object_name = object_name + '_sim'
# Create the simulation object.
- setattr(ds.res[self.run][i], sim_object_name, [])
+ setattr(spin, sim_object_name, [])
# Get the simulation object.
- sim_object = getattr(ds.res[self.run][i],
sim_object_name)
+ sim_object = getattr(spin, sim_object_name)
# Loop over the simulations.
- for j in xrange(ds.sim_number[self.run]):
+ for j in xrange(cdp.sim_number):
# Copy and append the data.
-
sim_object.append(deepcopy(getattr(ds.res[self.run][i], object_name)))
+ sim_object.append(deepcopy(getattr(spin,
object_name)))
def sim_pack_data(self, spin_id, sim_data):
r7377 - /1.3/specific_fns/model_free/main.py