Author: bugman
Date: Sun Dec 9 21:45:08 2007
New Revision: 4163
URL: http://svn.gna.org/viewcvs/relax?rev=4163&view=rev
Log:
Converted the sort_params() class method into a function and renamed it to
partition_params().
Modified:
1.3/generic_fns/value.py
Modified: 1.3/generic_fns/value.py
URL:
http://svn.gna.org/viewcvs/relax/1.3/generic_fns/value.py?rev=4163&r1=4162&r2=4163&view=diff
==============================================================================
--- 1.3/generic_fns/value.py (original)
+++ 1.3/generic_fns/value.py Sun Dec 9 21:45:08 2007
@@ -31,6 +31,150 @@
from specific_fns import get_specific_fn
+def partition_params():
+ """Function for sorting and partitioning the parameters and their values.
+
+ The two major partitions are the tensor parameters and the spin specific
parameters.
+
+ @return: A tuple, of length 4, of arrays.
+ @return type: tuple of arrays
+ """
+
+ # Initialise.
+ tensor_params = []
+ tensor_values = []
+ spin_params = []
+ spin_values = []
+
+ # Separate the residue specific parameters from the diffusion tensor
parameters.
+ if param:
+ # Single parameter.
+ if type(param) == str:
+ # Get the diffusion tensor parameter name.
+ tensor_name =
relax.generic.diffusion_tensor.return_data_name(param)
+
+ # The parameter is a diffusion parameter.
+ if tensor_name:
+ # List of values.
+ if type(value) == list or type(value) == ArrayType:
+ # Parameter name.
+ for i in xrange(len(value)):
+ tensor_params.append(tensor_name)
+
+ # Parameter value.
+ tensor_values = value
+
+ # Single value.
+ else:
+ # Parameter name.
+ tensor_params.append(param)
+
+ # Parameter value.
+ tensor_values.append(value)
+
+ # The parameter is not a diffusion parameter.
+ elif return_data_name(param):
+ # List of values.
+ if type(value) == list or type(value) == ArrayType:
+ # Parameter name.
+ for i in xrange(len(value)):
+ spin_params.append(param)
+
+ # Parameter value.
+ spin_values = value
+
+ # Single value.
+ else:
+ # Parameter name.
+ spin_params.append(param)
+
+ # Parameter value.
+ spin_values.append(value)
+
+ # Unknown parameter
+ else:
+ raise RelaxUnknownParamError, param
+
+ # Multiple parameters.
+ elif type(param) == list:
+ # Loop over all parameters.
+ for i in xrange(len(param)):
+ # Get the diffusion tensor parameter name.
+ tensor_name =
relax.generic.diffusion_tensor.return_data_name(param[i])
+
+ # The parameter is a diffusion parameter.
+ if tensor_name:
+ # Parameter name.
+ tensor_params.append(tensor_name)
+
+ # Parameter value.
+ if type(value) == list or type(value) == ArrayType:
+ tensor_values.append(value[i])
+ else:
+ tensor_values.append(value)
+
+ # The parameter is not a diffusion parameter.
+ elif return_data_name(param[i]):
+ # Parameter name.
+ spin_params.append(param[i])
+
+ # Parameter value.
+ if type(value) == list or type(value) == ArrayType:
+ spin_values.append(value[i])
+ else:
+ spin_values.append(value)
+
+ # Unknown parameter
+ else:
+ raise RelaxUnknownParamError, param[i]
+
+
+ # All other parameters.
+ else:
+ # No parameter or a single parameter.
+ if param == None or type(param) == str:
+ # List of values.
+ if type(value) == list or type(value) == ArrayType:
+ # Parameter name.
+ for i in xrange(len(value)):
+ spin_params.append(param)
+
+ # Parameter value.
+ spin_values = value
+
+ # Single value.
+ else:
+ # Parameter name.
+ spin_params.append(param)
+
+ # Parameter value.
+ spin_values.append(value)
+
+ # Multiple parameters.
+ elif type(param) == list:
+ # Loop over all parameters.
+ for i in xrange(len(param)):
+ # Parameter name.
+ spin_params.append(param[i])
+
+ # Parameter value.
+ if type(value) == list or type(value) == ArrayType:
+ spin_values.append(value[i])
+ else:
+ spin_values.append(value)
+
+ # Debugging.
+ if len(tensor_params) != len(tensor_values) or len(spin_params) !=
len(spin_values):
+ print "Diff params: " + `tensor_params`
+ print "Diff values: " + `tensor_values`
+ print "Res params: " + `spin_params`
+ print "Res values: " + `spin_values`
+ raise RelaxError, "Bug in the code."
+
+ # Return the partitioned parameters and values.
+ return tensor_params, tensor_values, spin_params, spin_values
+
+
def set(val=None, param=None, spin_id=None, force=0):
"""Function for setting residue specific data values."""
@@ -61,24 +205,24 @@
# Residue specific parameters.
##############################
- if res_params:
+ if spin_params:
# Test if the sequence data is loaded.
if not relax_data_store.res.has_key(run):
raise RelaxNoSequenceError, run
# Test if the residue number is a valid regular expression.
- if type(res_num) == str:
+ if type(spin_num) == str:
try:
- compile(res_num)
+ compile(spin_num)
except:
- raise RelaxRegExpError, ('residue number', res_num)
+ raise RelaxRegExpError, ('residue number', spin_num)
# Test if the residue name is a valid regular expression.
- if res_name:
+ if spin_name:
try:
- compile(res_name)
+ compile(spin_name)
except:
- raise RelaxRegExpError, ('residue name', res_name)
+ raise RelaxRegExpError, ('residue name', spin_name)
# Test if parameter value already exists.
if not force:
@@ -88,18 +232,18 @@
if not relax_data_store.res[run][i].select:
continue
- # If 'res_num' is not None, skip the residue if there is no
match.
- if type(res_num) == int and not
relax_data_store.res[run][i].num == res_num:
+ # If 'spin_num' is not None, skip the residue if there is no
match.
+ if type(spin_num) == int and not
relax_data_store.res[run][i].num == spin_num:
continue
- elif type(res_num) == str and not match(res_num,
`relax_data_store.res[run][i].num`):
+ elif type(spin_num) == str and not match(spin_num,
`relax_data_store.res[run][i].num`):
continue
- # If 'res_name' is not None, skip the residue if there is no
match.
- if res_name != None and not match(res_name,
relax_data_store.res[run][i].name):
+ # If 'spin_name' is not None, skip the residue if there is
no match.
+ if spin_name != None and not match(spin_name,
relax_data_store.res[run][i].name):
continue
# Loop over the parameters.
- for param in res_params:
+ for param in spin_params:
if param:
# Get the value and error.
temp_value, temp_error = return_value(run, i, param)
@@ -114,19 +258,19 @@
if not relax_data_store.res[run][i].select:
continue
- # If 'res_num' is not None, skip the residue if there is no
match.
- if type(res_num) == int and not relax_data_store.res[run][i].num
== res_num:
- continue
- elif type(res_num) == str and not match(res_num,
`relax_data_store.res[run][i].num`):
- continue
-
- # If 'res_name' is not None, skip the residue if there is no
match.
- if res_name != None and not match(res_name,
relax_data_store.res[run][i].name):
+ # If 'spin_num' is not None, skip the residue if there is no
match.
+ if type(spin_num) == int and not
relax_data_store.res[run][i].num == spin_num:
+ continue
+ elif type(spin_num) == str and not match(spin_num,
`relax_data_store.res[run][i].num`):
+ continue
+
+ # If 'spin_name' is not None, skip the residue if there is no
match.
+ if spin_name != None and not match(spin_name,
relax_data_store.res[run][i].name):
continue
# Go to the specific code.
- for j in xrange(len(res_params)):
- set(run=run, value=res_values[j], error=None,
param=res_params[j], index=i)
+ for j in xrange(len(spin_params)):
+ set(run=run, value=spin_values[j], error=None,
param=spin_params[j], index=i)
# Reset the minimisation statistics.
@@ -339,13 +483,13 @@
continue
# Residue number.
- res_num = int(file_data[i][num_col])
+ spin_num = int(file_data[i][num_col])
# Residue name.
if name_col == None:
- res_name = None
+ spin_name = None
else:
- res_name = file_data[i][name_col]
+ spin_name = file_data[i][name_col]
# Value.
if file_data[i][data_col] != 'None':
@@ -362,11 +506,11 @@
# Find the index of relax_data_store.res[self.run] which
corresponds to the relaxation data set i.
index = None
for j in xrange(len(relax_data_store.res[self.run])):
- if relax_data_store.res[self.run][j].num == res_num and
(res_name == None or relax_data_store.res[self.run][j].name == res_name):
+ if relax_data_store.res[self.run][j].num == spin_num and
(spin_name == None or relax_data_store.res[self.run][j].name == spin_name):
index = j
break
if index == None:
- raise RelaxNoResError, (res_num, res_name)
+ raise RelaxNoResError, (spin_num, spin_name)
# Set the value.
set(run=run, value=value, error=error, param=self.param,
scaling=scaling, index=index)
@@ -378,141 +522,6 @@
# Reset the global minimisation statistics.
if not min_stat:
self.relax.generic.minimise.reset_min_stats(self.run)
-
-
- def sort_params(self):
- """Function for sorting the parameters and their values."""
-
- # Initialise.
- self.diff_params = []
- self.diff_values = []
- self.res_params = []
- self.res_values = []
-
- # Separate the residue specific parameters from the diffusion tensor
parameters.
- if self.param:
- # Single parameter.
- if type(self.param) == str:
- # Get the diffusion tensor parameter name.
- diff_name =
self.relax.generic.diffusion_tensor.return_data_name(self.param)
-
- # The parameter is a diffusion parameter.
- if diff_name:
- # List of values.
- if type(self.value) == list or type(self.value) ==
ArrayType:
- # Parameter name.
- for i in xrange(len(self.value)):
- self.diff_params.append(diff_name)
-
- # Parameter value.
- self.diff_values = self.value
-
- # Single value.
- else:
- # Parameter name.
- self.diff_params.append(self.param)
-
- # Parameter value.
- self.diff_values.append(self.value)
-
- # The parameter is not a diffusion parameter.
- elif self.return_data_name(self.param):
- # List of values.
- if type(self.value) == list or type(self.value) ==
ArrayType:
- # Parameter name.
- for i in xrange(len(self.value)):
- self.res_params.append(self.param)
-
- # Parameter value.
- self.res_values = self.value
-
- # Single value.
- else:
- # Parameter name.
- self.res_params.append(self.param)
-
- # Parameter value.
- self.res_values.append(self.value)
-
- # Unknown parameter
- else:
- raise RelaxUnknownParamError, self.param
-
- # Multiple parameters.
- elif type(self.param) == list:
- # Loop over all parameters.
- for i in xrange(len(self.param)):
- # Get the diffusion tensor parameter name.
- diff_name =
self.relax.generic.diffusion_tensor.return_data_name(self.param[i])
-
- # The parameter is a diffusion parameter.
- if diff_name:
- # Parameter name.
- self.diff_params.append(diff_name)
-
- # Parameter value.
- if type(self.value) == list or type(self.value) ==
ArrayType:
- self.diff_values.append(self.value[i])
- else:
- self.diff_values.append(self.value)
-
- # The parameter is not a diffusion parameter.
- elif self.return_data_name(self.param[i]):
- # Parameter name.
- self.res_params.append(self.param[i])
-
- # Parameter value.
- if type(self.value) == list or type(self.value) ==
ArrayType:
- self.res_values.append(self.value[i])
- else:
- self.res_values.append(self.value)
-
- # Unknown parameter
- else:
- raise RelaxUnknownParamError, self.param[i]
-
-
- # All other parameters.
- else:
- # No parameter or a single parameter.
- if self.param == None or type(self.param) == str:
- # List of values.
- if type(self.value) == list or type(self.value) == ArrayType:
- # Parameter name.
- for i in xrange(len(self.value)):
- self.res_params.append(self.param)
-
- # Parameter value.
- self.res_values = self.value
-
- # Single value.
- else:
- # Parameter name.
- self.res_params.append(self.param)
-
- # Parameter value.
- self.res_values.append(self.value)
-
- # Multiple parameters.
- elif type(self.param) == list:
- # Loop over all parameters.
- for i in xrange(len(self.param)):
- # Parameter name.
- self.res_params.append(self.param[i])
-
- # Parameter value.
- if type(self.value) == list or type(self.value) ==
ArrayType:
- self.res_values.append(self.value[i])
- else:
- self.res_values.append(self.value)
-
- # Debugging.
- if len(self.diff_params) != len(self.diff_values) or
len(self.res_params) != len(self.res_values):
- print "Diff params: " + `self.diff_params`
- print "Diff values: " + `self.diff_values`
- print "Res params: " + `self.res_params`
- print "Res values: " + `self.res_values`
- raise RelaxError, "Bug in the code."
def write(self, run=None, param=None, file=None, dir=None, force=0,
return_value=None):
r4163 - /1.3/generic_fns/value.py