Author: bugman
Date: Fri Aug 1 14:19:47 2008
New Revision: 7066
URL: http://svn.gna.org/viewcvs/relax?rev=7066&view=rev
Log:
Converted the read() class method into a module function.
This completes the conversion of all class methods to functions.
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=7066&r1=7065&r2=7066&view=diff
==============================================================================
--- 1.3/generic_fns/value.py (original)
+++ 1.3/generic_fns/value.py Fri Aug 1 14:19:47 2008
@@ -199,6 +199,160 @@
return spin_params, spin_values, other_params, other_values
+def read(param=None, scaling=1.0, file=None, num_col=0, name_col=1,
data_col=2, error_col=3, sep=None):
+ """Function for reading residue specific data values from a file."""
+
+ # Arguments.
+ self.param = param
+ self.scaling = scaling
+
+ # Test if the current pipe exists.
+ if not ds.current_pipe:
+ raise RelaxNoPipeError
+
+ # Test if sequence data is loaded.
+ if not exists_mol_res_spin_data():
+ raise RelaxNoSequenceError
+
+ # Function type.
+ self.function_type = ds.run_types[ds.run_names.index(self.run)]
+
+ # Minimisation parameter.
+ if self.relax.generic.minimise.return_data_name(param):
+ # Minimisation statistic flag.
+ min_stat = 1
+
+ # Specific value and error returning function.
+ return_value = self.relax.generic.minimise.return_value
+
+ # Specific set function.
+ set = self.relax.generic.minimise.set
+
+ # Normal parameter.
+ else:
+ # Minimisation statistic flag.
+ min_stat = 0
+
+ # Specific value and error returning function.
+ return_value = self.relax.specific_setup.setup('return_value',
self.function_type)
+
+ # Specific set function.
+ set = self.relax.specific_setup.setup('set', self.function_type)
+
+ # Test data corresponding to param already exists.
+ for i in xrange(len(ds.res[self.run])):
+ # Skip deselected residues.
+ if not ds.res[self.run][i].select:
+ continue
+
+ # Get the value and error.
+ value, error = return_value(self.run, i, self.param)
+
+ # Data exists.
+ if value != None or error != None:
+ raise RelaxValueError, (self.param, self.run)
+
+ # Extract the data from the file.
+ file_data = extract_data(file)
+
+ # Count the number of header lines.
+ header_lines = 0
+ for i in xrange(len(file_data)):
+ try:
+ int(file_data[i][num_col])
+ except:
+ header_lines = header_lines + 1
+ else:
+ break
+
+ # Remove the header.
+ file_data = file_data[header_lines:]
+
+ # Strip the data.
+ file_data = strip(file_data)
+
+ # Do nothing if the file does not exist.
+ if not file_data:
+ raise RelaxFileEmptyError
+
+ # Test the validity of the data.
+ for i in xrange(len(file_data)):
+ # Skip missing data.
+ if len(file_data[i]) <= data_col or len(file_data[i]) <= error_col:
+ continue
+
+ try:
+ # Number column.
+ int(file_data[i][num_col])
+
+ # Value column.
+ if file_data[i][data_col] != 'None':
+ float(file_data[i][data_col])
+
+ # Error column.
+ if error_col != None and file_data[i][error_col] != 'None':
+ float(file_data[i][error_col])
+
+ except ValueError:
+ if error_col != None:
+ if name_col != None:
+ raise RelaxError, "The data is invalid (num=" +
file_data[i][num_col] + ", name=" + file_data[i][name_col] + ", data=" +
file_data[i][data_col] + ", error=" + file_data[i][error_col] + ")."
+ else:
+ raise RelaxError, "The data is invalid (num=" +
file_data[i][num_col] + ", data=" + file_data[i][data_col] + ", error=" +
file_data[i][error_col] + ")."
+ else:
+ if name_col != None:
+ raise RelaxError, "The data is invalid (num=" +
file_data[i][num_col] + ", name=" + file_data[i][name_col] + ", data=" +
file_data[i][data_col] + ")."
+ else:
+ raise RelaxError, "The data is invalid (num=" +
file_data[i][num_col] + ", data=" + file_data[i][data_col] + ")."
+
+ # Loop over the data.
+ for i in xrange(len(file_data)):
+ # Skip missing data.
+ if len(file_data[i]) <= data_col or len(file_data[i]) <= error_col:
+ continue
+
+ # Residue number.
+ spin_num = int(file_data[i][num_col])
+
+ # Residue name.
+ if name_col == None:
+ spin_name = None
+ else:
+ spin_name = file_data[i][name_col]
+
+ # Value.
+ if file_data[i][data_col] != 'None':
+ value = float(file_data[i][data_col])
+ else:
+ value = None
+
+ # Error.
+ if error_col != None and file_data[i][error_col] != 'None':
+ error = float(file_data[i][error_col])
+ else:
+ error = None
+
+ # Find the index of ds.res[self.run] which corresponds to the
relaxation data set i.
+ index = None
+ for j in xrange(len(ds.res[self.run])):
+ if ds.res[self.run][j].num == spin_num and (spin_name == None or
ds.res[self.run][j].name == spin_name):
+ index = j
+ break
+ if index == None:
+ raise RelaxNoResError, (spin_num, spin_name)
+
+ # Set the value.
+ set(run=run, value=value, error=error, param=self.param,
scaling=scaling, index=index)
+
+ # Reset the residue specific minimisation statistics.
+ if not min_stat:
+ self.relax.generic.minimise.reset_min_stats(self.run, index)
+
+ # Reset the global minimisation statistics.
+ if not min_stat:
+ self.relax.generic.minimise.reset_min_stats(self.run)
+
+
def set(val=None, param=None, spin_id=None, force=False):
"""Function for setting residue specific data values.
@@ -459,164 +613,3 @@
# Write the data.
write_line(file, mol_name, res_num, res_name, spin.num, spin.name,
extra_format=format, extra_values=(`value`, `error`), mol_name_flag=True,
res_num_flag=True, res_name_flag=True, spin_num_flag=True,
spin_name_flag=True)
-
-
-class Value:
- def __init__(self, relax):
- """Class containing functions for the setting up of data
structures."""
-
- self.relax = relax
-
-
- def read(self, param=None, scaling=1.0, file=None, num_col=0,
name_col=1, data_col=2, error_col=3, sep=None):
- """Function for reading residue specific data values from a file."""
-
- # Arguments.
- self.param = param
- self.scaling = scaling
-
- # Test if the current pipe exists.
- if not ds.current_pipe:
- raise RelaxNoPipeError
-
- # Test if sequence data is loaded.
- if not exists_mol_res_spin_data():
- raise RelaxNoSequenceError
-
- # Function type.
- self.function_type = ds.run_types[ds.run_names.index(self.run)]
-
- # Minimisation parameter.
- if self.relax.generic.minimise.return_data_name(param):
- # Minimisation statistic flag.
- min_stat = 1
-
- # Specific value and error returning function.
- return_value = self.relax.generic.minimise.return_value
-
- # Specific set function.
- set = self.relax.generic.minimise.set
-
- # Normal parameter.
- else:
- # Minimisation statistic flag.
- min_stat = 0
-
- # Specific value and error returning function.
- return_value = self.relax.specific_setup.setup('return_value',
self.function_type)
-
- # Specific set function.
- set = self.relax.specific_setup.setup('set', self.function_type)
-
- # Test data corresponding to param already exists.
- for i in xrange(len(ds.res[self.run])):
- # Skip deselected residues.
- if not ds.res[self.run][i].select:
- continue
-
- # Get the value and error.
- value, error = return_value(self.run, i, self.param)
-
- # Data exists.
- if value != None or error != None:
- raise RelaxValueError, (self.param, self.run)
-
- # Extract the data from the file.
- file_data = extract_data(file)
-
- # Count the number of header lines.
- header_lines = 0
- for i in xrange(len(file_data)):
- try:
- int(file_data[i][num_col])
- except:
- header_lines = header_lines + 1
- else:
- break
-
- # Remove the header.
- file_data = file_data[header_lines:]
-
- # Strip the data.
- file_data = strip(file_data)
-
- # Do nothing if the file does not exist.
- if not file_data:
- raise RelaxFileEmptyError
-
- # Test the validity of the data.
- for i in xrange(len(file_data)):
- # Skip missing data.
- if len(file_data[i]) <= data_col or len(file_data[i]) <=
error_col:
- continue
-
- try:
- # Number column.
- int(file_data[i][num_col])
-
- # Value column.
- if file_data[i][data_col] != 'None':
- float(file_data[i][data_col])
-
- # Error column.
- if error_col != None and file_data[i][error_col] != 'None':
- float(file_data[i][error_col])
-
- except ValueError:
- if error_col != None:
- if name_col != None:
- raise RelaxError, "The data is invalid (num=" +
file_data[i][num_col] + ", name=" + file_data[i][name_col] + ", data=" +
file_data[i][data_col] + ", error=" + file_data[i][error_col] + ")."
- else:
- raise RelaxError, "The data is invalid (num=" +
file_data[i][num_col] + ", data=" + file_data[i][data_col] + ", error=" +
file_data[i][error_col] + ")."
- else:
- if name_col != None:
- raise RelaxError, "The data is invalid (num=" +
file_data[i][num_col] + ", name=" + file_data[i][name_col] + ", data=" +
file_data[i][data_col] + ")."
- else:
- raise RelaxError, "The data is invalid (num=" +
file_data[i][num_col] + ", data=" + file_data[i][data_col] + ")."
-
- # Loop over the data.
- for i in xrange(len(file_data)):
- # Skip missing data.
- if len(file_data[i]) <= data_col or len(file_data[i]) <=
error_col:
- continue
-
- # Residue number.
- spin_num = int(file_data[i][num_col])
-
- # Residue name.
- if name_col == None:
- spin_name = None
- else:
- spin_name = file_data[i][name_col]
-
- # Value.
- if file_data[i][data_col] != 'None':
- value = float(file_data[i][data_col])
- else:
- value = None
-
- # Error.
- if error_col != None and file_data[i][error_col] != 'None':
- error = float(file_data[i][error_col])
- else:
- error = None
-
- # Find the index of ds.res[self.run] which corresponds to the
relaxation data set i.
- index = None
- for j in xrange(len(ds.res[self.run])):
- if ds.res[self.run][j].num == spin_num and (spin_name ==
None or ds.res[self.run][j].name == spin_name):
- index = j
- break
- if index == None:
- raise RelaxNoResError, (spin_num, spin_name)
-
- # Set the value.
- set(run=run, value=value, error=error, param=self.param,
scaling=scaling, index=index)
-
- # Reset the residue specific minimisation statistics.
- if not min_stat:
- self.relax.generic.minimise.reset_min_stats(self.run, index)
-
- # Reset the global minimisation statistics.
- if not min_stat:
- self.relax.generic.minimise.reset_min_stats(self.run)
r7066 - /1.3/generic_fns/value.py