def set(val=None, param=None, index=None, pipe=None, spin_id=None, verbosity=1, error=False, force=True, reset=True):
"""Set global or spin specific data values.
@keyword val: The parameter values.
@type val: None or list
@keyword param: The parameter names.
@type param: None, str, or list of str
@keyword index: The index for parameters which are of the list-type. This is ignored for all other types.
@type index: None or int
@keyword pipe: The data pipe the values should be placed in.
@type pipe: None or str
@keyword spin_id: The spin identification string.
@type spin_id: str
@keyword verbosity: The amount of information to print. The higher the value, the greater the verbosity.
@type verbosity: int
@keyword error: A flag which if True will allow the parameter errors to be set instead of the values.
@type error: bool
@keyword force: A flag forcing the overwriting of current values.
@type force: bool
@keyword reset: A flag which if True will cause all minimisation statistics to be reset.
@type reset: bool
"""
# Switch to the data pipe, storing the original.
if pipe:
orig_pipe = pipes.cdp_name()
pipes.switch(pipe)
# Test if the current data pipe exists.
check_pipe()
# The specific analysis API object.
api = return_api()
# Convert numpy arrays to lists, if necessary.
if isinstance(val, ndarray):
val = val.tolist()
# Invalid combinations.
if (isinstance(val, float) or isinstance(val, int)) and param == None:
raise RelaxError("The combination of a single value '%s' without specifying the parameter name is invalid." % val)
if isinstance(val, list) and isinstance(param, str):
raise RelaxError("Invalid combination: When multiple values '%s' are specified, either no parameters or a list of parameters must by supplied rather than the single parameter '%s'." % (val, param))
# Value array and parameter array of equal length.
if isinstance(val, list) and isinstance(param, list) and len(val) != len(param):
raise RelaxError("Both the value array and parameter array must be of equal length.")
# Get the parameter list if needed.
if param == None:
param = api.get_param_names()
# Convert the param to a list if needed.
if not isinstance(param, list):
param = [param]
# Convert the value to a list if needed.
if val != None and not isinstance(val, list):
val = [val] * len(param)
# Default values.
if val == None:
# Loop over the parameters, getting the default values.
val = []
for i in range(len(param)):
val.append(api.default_value(param[i]))
# Check that there is a default.
if val[-1] == None:
raise RelaxParamSetError(param[i])
# Set the parameter values.
api.set_param_values(param=param, value=val, index=index, spin_id=spin_id, error=error, force=force)
# Reset all minimisation statistics.
if reset:
minimise.reset_min_stats(verbosity=verbosity)
# Switch back.
if pipe:
pipes.switch(orig_pipe)
def copy(pipe_from=None, pipe_to=None, param=None, force=False):
"""Copy spin specific data values from pipe_from to pipe_to.
@param pipe_from: The data pipe to copy the value from. This defaults to the current data
pipe.
@type pipe_from: str
@param pipe_to: The data pipe to copy the value to. This defaults to the current data pipe.
@type pipe_to: str
@param param: The name of the parameter to copy the values of.
@type param: str
@keyword force: A flag forcing the overwriting of current values.
@type force: bool
"""
# The current data pipe.
if pipe_from == None:
pipe_from = pipes.cdp_name()
if pipe_to == None:
pipe_to = pipes.cdp_name()
pipe_orig = pipes.cdp_name()
# The second pipe does not exist.
check_pipe(pipe_to)
# Test if the sequence data for pipe_from is loaded.
if not exists_mol_res_spin_data(pipe_from):
raise RelaxNoSequenceError(pipe_from)
# Test if the sequence data for pipe_to is loaded.
if not exists_mol_res_spin_data(pipe_to):
raise RelaxNoSequenceError(pipe_to)
# The specific analysis API object.
api = return_api(pipe_name=pipe_from)
# Test if the data exists for pipe_to.
if force == False:
for spin in spin_loop(pipe=pipe_to):
# Get the value and error for pipe_to.
value, error = api.return_value(spin, param)
# Data exists.
if value != None or error != None:
raise RelaxValueError(param, pipe_to)
# Switch to the data pipe to copy values to.
pipes.switch(pipe_to)
# Copy the values.
for spin, spin_id in spin_loop(pipe=pipe_from, return_id=True):
# Get the value and error from pipe_from.
value, error = api.return_value(spin, param)
# Set the values of pipe_to.
if value != None:
set(spin_id=spin_id, val=value, param=param, pipe=pipe_to, force=force)
if error != None:
set(spin_id=spin_id, val=error, param=param, pipe=pipe_to, error=True, force=force)
# Reset all minimisation statistics.
minimise.reset_min_stats(pipe_to)
# Switch back to the original current data pipe.
pipes.switch(pipe_orig)
def read(param=None, scaling=1.0, file=None, dir=None, file_data=None, spin_id_col=None, mol_name_col=None, res_num_col=None, res_name_col=None, spin_num_col=None, spin_name_col=None, data_col=None, error_col=None, sep=None, spin_id=None):
"""Read spin specific data values from a file.
@keyword param: The name of the parameter to read.
@type param: str
@keyword scaling: A scaling factor by which all read values are multiplied by.
@type scaling: float
@keyword file: The name of the file to open.
@type file: str
@keyword dir: The directory containing the file (defaults to the current directory if None).
@type dir: str or None
@keyword file_data: An alternative to opening a file, if the data already exists in the correct format. The format is a list of lists where the first index corresponds to the row and the second the column.
@type file_data: list of lists
@keyword spin_id_col: The column containing the spin ID strings. If supplied, the mol_name_col, res_name_col, res_num_col, spin_name_col, and spin_num_col arguments must be none.
@type spin_id_col: int or None
@keyword mol_name_col: The column containing the molecule name information. If supplied, spin_id_col must be None.
@type mol_name_col: int or None
@keyword res_name_col: The column containing the residue name information. If supplied, spin_id_col must be None.
@type res_name_col: int or None
@keyword res_num_col: The column containing the residue number information. If supplied, spin_id_col must be None.
@type res_num_col: int or None
@keyword spin_name_col: The column containing the spin name information. If supplied, spin_id_col must be None.
@type spin_name_col: int or None
@keyword spin_num_col: The column containing the spin number information. If supplied, spin_id_col must be None.
@type spin_num_col: int or None
@keyword data_col: The column containing the RDC data in Hz.
@type data_col: int or None
@keyword error_col: The column containing the RDC errors.
@type error_col: int or None
@keyword sep: The column separator which, if None, defaults to whitespace.
@type sep: str or None
@keyword spin_id: The spin ID string.
@type spin_id: None or str
"""
# Test if the current pipe exists.
check_pipe()
# Test if sequence data is loaded.
if not exists_mol_res_spin_data():
raise RelaxNoSequenceError
# Minimisation statistic flag.
min_stat = False
# Alias specific analysis API object method.
api = return_api()
return_value = api.return_value
# Specific set function.
set_fn = set
# Test data corresponding to param already exists.
for spin in spin_loop():
# Skip deselected spins.
if not spin.select:
continue
# Get the value and error.
value, error = return_value(spin, param)
# Data exists.
if value != None or error != None:
raise RelaxValueError(param)
# Loop over the data.
mol_names = []
res_nums = []
res_names = []
spin_nums = []
spin_names = []
values = []
errors = []
for data in read_spin_data(file=file, dir=dir, file_data=file_data, spin_id_col=spin_id_col, mol_name_col=mol_name_col, res_num_col=res_num_col, res_name_col=res_name_col, spin_num_col=spin_num_col, spin_name_col=spin_name_col, data_col=data_col, error_col=error_col, sep=sep, spin_id=spin_id):
# Unpack.
if data_col and error_col:
mol_name, res_num, res_name, spin_num, spin_name, value, error = data
elif data_col:
mol_name, res_num, res_name, spin_num, spin_name, value = data
error = None
else:
mol_name, res_num, res_name, spin_num, spin_name, error = data
value = None
# Set the value.
id = generate_spin_id_unique(mol_name=mol_name, res_num=res_num, res_name=res_name, spin_num=spin_num, spin_name=spin_name)
set_fn(val=value, error=error, param=param, spin_id=id)
# Append the data for printout.
mol_names.append(mol_name)
res_nums.append(res_num)
res_names.append(res_name)
spin_nums.append(spin_num)
spin_names.append(spin_name)
values.append(value)
errors.append(error)
# Print out.
write_spin_data(file=sys.stdout, mol_names=mol_names, res_nums=res_nums, res_names=res_names, spin_nums=spin_nums, spin_names=spin_names, data=values, data_name=param, error=errors, error_name='%s_error'%param)
# Reset the minimisation statistics.
if api.set(param) == 'min':
minimise.reset_min_stats()
def copy(pipe_from=None, pipe_to=None, param=None, force=False):
"""Copy spin specific data values from pipe_from to pipe_to.
@param pipe_from: The data pipe to copy the value from. This defaults to the current data
pipe.
@type pipe_from: str
@param pipe_to: The data pipe to copy the value to. This defaults to the current data pipe.
@type pipe_to: str
@param param: The name of the parameter to copy the values of.
@type param: str
@keyword force: A flag forcing the overwriting of current values.
@type force: bool
"""
# The current data pipe.
if pipe_from == None:
pipe_from = pipes.cdp_name()
if pipe_to == None:
pipe_to = pipes.cdp_name()
pipe_orig = pipes.cdp_name()
# The second pipe does not exist.
check_pipe(pipe_to)
# Test if the sequence data for pipe_from is loaded.
if not exists_mol_res_spin_data(pipe_from):
raise RelaxNoSequenceError(pipe_from)
# Test if the sequence data for pipe_to is loaded.
if not exists_mol_res_spin_data(pipe_to):
raise RelaxNoSequenceError(pipe_to)
# The specific analysis API object.
api = return_api(pipe_name=pipe_from)
# Test if the data exists for pipe_to.
if force == False:
for spin in spin_loop(pipe=pipe_to):
# Get the value and error for pipe_to.
value, error = api.return_value(spin, param)
# Data exists.
if value != None or error != None:
raise RelaxValueError(param, pipe_to)
# Switch to the data pipe to copy values to.
pipes.switch(pipe_to)
# Copy the values.
for spin, spin_id in spin_loop(pipe=pipe_from, return_id=True):
# Get the value and error from pipe_from.
value, error = api.return_value(spin, param)
# Set the values of pipe_to.
if value != None:
set(spin_id=spin_id, val=value, param=param, pipe=pipe_to, force=force)
if error != None:
set(spin_id=spin_id, val=error, param=param, pipe=pipe_to, error=True, force=force)
# Reset all minimisation statistics.
minimise.reset_min_stats(pipe_to)
# Switch back to the original current data pipe.
pipes.switch(pipe_orig)
def set(val=None, param=None, index=None, pipe=None, spin_id=None, verbosity=1, error=False, force=True, reset=True):
"""Set global or spin specific data values.
@keyword val: The parameter values.
@type val: None or list
@keyword param: The parameter names.
@type param: None, str, or list of str
@keyword index: The index for parameters which are of the list-type. This is ignored for all other types.
@type index: None or int
@keyword pipe: The data pipe the values should be placed in.
@type pipe: None or str
@keyword spin_id: The spin identification string.
@type spin_id: str
@keyword verbosity: The amount of information to print. The higher the value, the greater the verbosity.
@type verbosity: int
@keyword error: A flag which if True will allow the parameter errors to be set instead of the values.
@type error: bool
@keyword force: A flag forcing the overwriting of current values.
@type force: bool
@keyword reset: A flag which if True will cause all minimisation statistics to be reset.
@type reset: bool
"""
# Switch to the data pipe, storing the original.
if pipe:
orig_pipe = pipes.cdp_name()
pipes.switch(pipe)
# Test if the current data pipe exists.
check_pipe()
# The specific analysis API object.
api = return_api()
# Convert numpy arrays to lists, if necessary.
if isinstance(val, ndarray):
val = val.tolist()
# Invalid combinations.
if (isinstance(val, float) or isinstance(val, int)) and param == None:
raise RelaxError("The combination of a single value '%s' without specifying the parameter name is invalid." % val)
if isinstance(val, list) and isinstance(param, str):
raise RelaxError("Invalid combination: When multiple values '%s' are specified, either no parameters or a list of parameters must by supplied rather than the single parameter '%s'." % (val, param))
# Value array and parameter array of equal length.
if isinstance(val, list) and isinstance(param, list) and len(val) != len(param):
raise RelaxError("Both the value array and parameter array must be of equal length.")
# Get the parameter list if needed.
if param == None:
param = api.get_param_names()
# Convert the param to a list if needed.
if not isinstance(param, list):
param = [param]
# Convert the value to a list if needed.
if val != None and not isinstance(val, list):
val = [val] * len(param)
# Default values.
if val == None:
# Loop over the parameters, getting the default values.
val = []
for i in range(len(param)):
val.append(api.default_value(param[i]))
# Check that there is a default.
if val[-1] == None:
raise RelaxParamSetError(param[i])
# Set the parameter values.
api.set_param_values(param=param, value=val, index=index, spin_id=spin_id, error=error, force=force)
# Reset all minimisation statistics.
if reset:
minimise.reset_min_stats(verbosity=verbosity)
# Switch back.
if pipe:
pipes.switch(orig_pipe)
def read(param=None, scaling=1.0, file=None, dir=None, file_data=None, spin_id_col=None, mol_name_col=None, res_num_col=None, res_name_col=None, spin_num_col=None, spin_name_col=None, data_col=None, error_col=None, sep=None, spin_id=None):
"""Read spin specific data values from a file.
@keyword param: The name of the parameter to read.
@type param: str
@keyword scaling: A scaling factor by which all read values are multiplied by.
@type scaling: float
@keyword file: The name of the file to open.
@type file: str
@keyword dir: The directory containing the file (defaults to the current directory if None).
@type dir: str or None
@keyword file_data: An alternative to opening a file, if the data already exists in the correct format. The format is a list of lists where the first index corresponds to the row and the second the column.
@type file_data: list of lists
@keyword spin_id_col: The column containing the spin ID strings. If supplied, the mol_name_col, res_name_col, res_num_col, spin_name_col, and spin_num_col arguments must be none.
@type spin_id_col: int or None
@keyword mol_name_col: The column containing the molecule name information. If supplied, spin_id_col must be None.
@type mol_name_col: int or None
@keyword res_name_col: The column containing the residue name information. If supplied, spin_id_col must be None.
@type res_name_col: int or None
@keyword res_num_col: The column containing the residue number information. If supplied, spin_id_col must be None.
@type res_num_col: int or None
@keyword spin_name_col: The column containing the spin name information. If supplied, spin_id_col must be None.
@type spin_name_col: int or None
@keyword spin_num_col: The column containing the spin number information. If supplied, spin_id_col must be None.
@type spin_num_col: int or None
@keyword data_col: The column containing the RDC data in Hz.
@type data_col: int or None
@keyword error_col: The column containing the RDC errors.
@type error_col: int or None
@keyword sep: The column separator which, if None, defaults to whitespace.
@type sep: str or None
@keyword spin_id: The spin ID string.
@type spin_id: None or str
"""
# Test if the current pipe exists.
check_pipe()
# Test if sequence data is loaded.
if not exists_mol_res_spin_data():
raise RelaxNoSequenceError
# Minimisation statistic flag.
min_stat = False
# Alias specific analysis API object method.
api = return_api()
return_value = api.return_value
# Specific set function.
set_fn = set
# Test data corresponding to param already exists.
for spin in spin_loop():
# Skip deselected spins.
if not spin.select:
continue
# Get the value and error.
value, error = return_value(spin, param)
# Data exists.
if value != None or error != None:
raise RelaxValueError(param)
# Loop over the data.
mol_names = []
res_nums = []
res_names = []
spin_nums = []
spin_names = []
values = []
errors = []
for data in read_spin_data(file=file, dir=dir, file_data=file_data, spin_id_col=spin_id_col, mol_name_col=mol_name_col, res_num_col=res_num_col, res_name_col=res_name_col, spin_num_col=spin_num_col, spin_name_col=spin_name_col, data_col=data_col, error_col=error_col, sep=sep, spin_id=spin_id):
# Unpack.
if data_col and error_col:
mol_name, res_num, res_name, spin_num, spin_name, value, error = data
elif data_col:
mol_name, res_num, res_name, spin_num, spin_name, value = data
error = None
else:
mol_name, res_num, res_name, spin_num, spin_name, error = data
value = None
# Set the value.
id = generate_spin_id_unique(mol_name=mol_name, res_num=res_num, res_name=res_name, spin_num=spin_num, spin_name=spin_name)
set_fn(val=value, error=error, param=param, spin_id=id)
# Append the data for printout.
mol_names.append(mol_name)
res_nums.append(res_num)
res_names.append(res_name)
spin_nums.append(spin_num)
spin_names.append(spin_name)
values.append(value)
errors.append(error)
# Print out.
write_spin_data(file=sys.stdout, mol_names=mol_names, res_nums=res_nums, res_names=res_names, spin_nums=spin_nums, spin_names=spin_names, data=values, data_name=param, error=errors, error_name='%s_error'%param)
# Reset the minimisation statistics.
if api.set(param) == 'min':
minimise.reset_min_stats()
def copy(pipe_from=None, pipe_to=None, param=None):
"""Copy spin specific data values from pipe_from to pipe_to.
@param pipe_from: The data pipe to copy the value from. This defaults to the current data
pipe.
@type pipe_from: str
@param pipe_to: The data pipe to copy the value to. This defaults to the current data pipe.
@type pipe_to: str
@param param: The name of the parameter to copy the values of.
@type param: str
"""
# The current data pipe.
if pipe_from == None:
pipe_from = pipes.cdp_name()
if pipe_to == None:
pipe_to = pipes.cdp_name()
pipe_orig = pipes.cdp_name()
# The second pipe does not exist.
pipes.test(pipe_to)
# Test if the sequence data for pipe_from is loaded.
if not exists_mol_res_spin_data(pipe_from):
raise RelaxNoSequenceError(pipe_from)
# Test if the sequence data for pipe_to is loaded.
if not exists_mol_res_spin_data(pipe_to):
raise RelaxNoSequenceError(pipe_to)
# Specific value and error returning function.
return_value = specific_analyses.setup.get_specific_fn('return_value', pipes.get_type(pipe_from))
# Test if the data exists for pipe_to.
for spin in spin_loop(pipe=pipe_to):
# Get the value and error for pipe_to.
value, error = return_value(spin, param)
# Data exists.
if value != None or error != None:
raise RelaxValueError(param, pipe_to)
# Switch to the data pipe to copy values to.
pipes.switch(pipe_to)
# Copy the values.
for spin, spin_id in spin_loop(pipe=pipe_from, return_id=True):
# Get the value and error from pipe_from.
value, error = return_value(spin, param)
# Set the values of pipe_to.
if value != None:
set(spin_id=spin_id, val=value, param=param, pipe=pipe_to)
if error != None:
set(spin_id=spin_id, val=error, param=param, pipe=pipe_to, error=True)
# Reset all minimisation statistics.
minimise.reset_min_stats(pipe_to)
# Switch back to the original current data pipe.
pipes.switch(pipe_orig)
