type Param_list

Known Subclasses:

• n_state_model.parameter_object.N_state_params
• , relax_disp.parameter_object.Relax_disp_params
• , jw_mapping.parameter_object.Jw_mapping_params
• , relax_fit.parameter_object.Relax_fit_params
• , frame_order.parameter_object.Frame_order_params
• , consistency_tests.parameter_object.Consistency_tests_params
• , noe.parameter_object.Noe_params
• , model_free.parameter_object.Model_free_params

A special object for handling global and spin parameters.

Instance Methods

__init__(self, spin_data=True)
Set up the class.

_add(self, name, scope=None, string=None, default=None, units=None, desc=None, py_type=None, set='all', conv_factor=None, scaling=1.0, grid_lower=None, grid_upper=None, grace_string=None, grace_units=None, err=False, sim=False)
Add a parameter to the list.

_add_align_data(self)
Add the PCS and RDC data.

_add_align_tensor(self)
Add the alignment tensor parameters.

_add_csa(self, default=None, set='fixed', err=False, sim=False)
Add the CSA parameter 'csa'.

_add_diffusion_params(self)
Add the Brownian rotational diffusion parameters to the list.

_add_min_data(self, min_stats_global=False, min_stats_spin=False)
Add minimisation specific objects.

_add_model_info(self, scope='spin', model_flag=True, equation_flag=False)
Add model specific objects 'model' and 'params'.

_add_peak_intensity(self)
Add the peak intensity structure 'peak_intensity'.

_add_sn_ratio(self)
Add the signal to noise ratio structure 'sn_ratio'.

_set_uf_title(self, title)
Set the title for the user function documentation.

Desc_container instance _uf_doc_loop(self, tables=None)
Generator method for looping over and yielding the user function parameter documentation.

Desc_container instance _uf_param_table(self, label=None, caption=None, scope='spin', sets=['params', 'fixed'], default=False, units=False, type=False)
"Create the parameter documentation for the user function docstrings.

str base_loop(self, set=None, scope=None)
An iterator method for looping over all the base parameters.

check_param(self, name)
Check if the parameter exists.

bool contains(self, name)
Determine if the given name is within the parameter list.

float conversion_factor(self, name)
Return the conversion factor.

list of str data_names(self, set='all', scope=None, error_names=False, sim_names=False)
Return a list of names of data structures.

None or str default_value(self, name)
Return the default value of the parameter.

None or str description(self, name)
Return the description of the parameter.

bool error_flag(self, name)
Return the error flag for the parameter.

str grace_string(self, name)
Return the Grace string for the parameter.

str grace_units(self, name)
Return the Grace units string for the parameter.

int grid_lower(self, name, incs=None, model_info=None)
Return the default lower grid bound for the parameter.

int grid_upper(self, name, incs=None, model_info=None)
Return the default upper grid bound for the parameter.

bool is_spin_param(self, name)
Determine whether the given parameter is spin specific.

str loop(self, set=None, scope=None, error_names=False, sim_names=False)
An iterator method for looping over all the parameters.

int scaling(self, name, model_info=None)
Return the scaling factor for the parameter.

str scope(self, name)
Return the parameter scope.

str set(self, name)
Return the parameter set that the parameter belongs to.

bool simulation_flag(self, name)
Return the Monte Carlo simulation flag for the parameter.

Python type object type(self, name)
Return the Python type for the parameter.

Python type object type_string(self, name)
Return the Python type for the parameter as a string representation.

Desc_container instance uf_doc(self, label=None, caption=None, scope='spin', default=False, units=False, type=False)
"Create the parameter documentation for the user function docstrings.

str units(self, name)
Return the units string for the parameter.

Static Methods

__new__(cls, *args, **kargs)
Replacement function for implementing the singleton design pattern.

Method Details

__init__(self, spin_data=True)
(Constructor)

Set up the class.

Parameters:

• spin_data (bool) - A flag which if True indicates that the specific analysis operates with spins.

Overrides: object.__init__

__new__(cls, *args, **kargs)
Static Method

Replacement function for implementing the singleton design pattern.

Overrides: object.__new__

_add(self, name, scope=None, string=None, default=None, units=None, desc=None, py_type=None, set='all', conv_factor=None, scaling=1.0, grid_lower=None, grid_upper=None, grace_string=None, grace_units=None, err=False, sim=False)

Add a parameter to the list.

Parameters:

• name (str) - The name of the parameter. This will be used as the variable name.
• scope (str) - The parameter scope. This can be set to 'global' for parameters located within the global scope of the current data pipe. Or set to 'spin' for spin specific parameters. Alternatively the value 'both' indicates that there are both global and specific versions of this parameter.
• string (None or str) - The string representation of the parameter.
• default (anything) - The default value of the parameter.
• units (None or str) - A string representing the parameters units.
• desc (None or str) - The text description of the parameter.
• py_type (Python type object) - The Python type that this parameter should be.
• set (str) - The set of object names. This can be set to 'all' for all names, to 'fixed' for parameter of the model which are permanently fixed, to 'params' for parameter of the model which are optimised or calculated, or to 'min' for minimisation specific object names.
• conv_factor (None, float or func) - The factor of conversion between different parameter units.
• scaling (float or function) - The diagonal scaling factor for optimisation.
• grid_lower (int or function) - The lower bound for the grid search.
• grid_upper (int or function) - The upper bound for the grid search.
• grace_string (None or str) - The string used for the axes in Grace plots of the data.
• grace_units (None or str) - A Grace string representing the parameters units.
• err (bool) - A flag which if True indicates that the parameter name + '_err' error data structure can exist.
• sim (bool) - A flag which if True indicates that the parameter name + '_sim' Monte Carlo simulation data structure can exist.

_add_csa(self, default=None, set='fixed', err=False, sim=False)

Add the CSA parameter 'csa'.

Parameters:

• default (float) - The default CSA value.
• set (str) - The set of object names. This can be set to 'all' for all names, to 'fixed' for parameter of the model which are permanently fixed, to 'params' for parameter of the model which are optimised or calculated, or to 'min' for minimisation specific object names.
• err (bool) - A flag which if True indicates that the 'csa_err' error data structure can exist.
• sim (bool) - A flag which if True indicates that the 'csa_sim' Monte Carlo simulation data structure can exist.

_add_min_data(self, min_stats_global=False, min_stats_spin=False)

Add minimisation specific objects.

The parameter scope is defined by the keyword arguments.

Parameters:

• min_stats_global (bool) - A flag which if True will cause the parameters to be global.
• min_stats_spin (bool) - A flag which if True will cause the parameters to be spin specific.

_add_model_info(self, scope='spin', model_flag=True, equation_flag=False)

Add model specific objects 'model' and 'params'.

Parameters:

• scope (str) - The parameter scope. This can be set to 'global' for parameters located within the global scope of the current data pipe. Or set to 'spin' for spin specific parameters. Alternatively the value 'both' indicates that there are both global and specific versions of this parameter.
• model_flag (bool) - A flag which if True will cause the 'model' structure to be added.

_set_uf_title(self, title)

Set the title for the user function documentation.

Parameters:

• title (str) - The title to use in the user function docstrings.

_uf_doc_loop(self, tables=None)

Generator method for looping over and yielding the user function parameter documentation.

Parameters:

• tables (list of str or None) - The list of tables to loop over. If None, then all tables will be yielded.

Returns: Desc_container instance

The user function documentation for each table.

_uf_param_table(self, label=None, caption=None, scope='spin', sets=['params', 'fixed'], default=False, units=False, type=False)

"Create the parameter documentation for the user function docstrings.

Parameters:

• label (str) - The label of the table. This is used to identify replicated tables, and is also used in the table referencing in the LaTeX compilation of the user manual. If this label is already used, the corresponding pre-constructed documentation object will be returned.
• caption (str) - The caption for the table.
• scope (str or None) - The parameter scope to restrict the table to, defaulting to 'spin'.
• sets (list of str) - The parameter sets to restrict the table to. If not given, then all parameters of the 'params' and 'fixed' sets will be added. This can be set to 'all' for all names, to 'fixed' for parameter of the model which are permanently fixed, to 'params' for parameter of the model which are optimised or calculated, or to 'min' for minimisation specific object names.
• default (bool) - A flag which if True will cause the default parameter value to be included in the table.
• units (bool) - A flag which if True will cause the units to be included in the table.
• type (bool) - A flag which if True will cause the parameter type to be included in the table.

Returns: Desc_container instance

The parameter documentation.

base_loop(self, set=None, scope=None)

An iterator method for looping over all the base parameters.

Parameters:

• set (str) - The set of object names. This can be set to 'all' for all names, to 'fixed' for parameter of the model which are permanently fixed, to 'params' for parameter of the model which are optimised or calculated, or to 'min' for minimisation specific object names.
• scope (str or None) - The scope of the parameter to return. If not set, then all will be returned. If set to 'global' or 'spin', then only the parameters within that scope will be returned.

Returns: str

The parameter names.

check_param(self, name)

Check if the parameter exists.

Parameters:

• name (str) - The name of the parameter to search for.

Raises:

• RelaxError - If the parameter does not exist.

contains(self, name)

Determine if the given name is within the parameter list.

Parameters:

• name (str) - The name of the parameter to search for.

Returns: bool

True if the parameter is within the list, False otherwise.

conversion_factor(self, name)

Return the conversion factor.

Parameters:

• name (str) - The name of the parameter.

Returns: float

The conversion factor.

data_names(self, set='all', scope=None, error_names=False, sim_names=False)

Return a list of names of data structures.

Parameters:

• set (str) - The set of object names. This can be set to 'all' for all names, to 'fixed' for parameter of the model which are permanently fixed, to 'params' for parameter of the model which are optimised or calculated, or to 'min' for minimisation specific object names.
• scope (str or None) - The scope of the parameter to return. If not set, then all will be returned. If set to 'global' or 'spin', then only the parameters within that scope will be returned.
• error_names (bool) - A flag which if True will add the error object names as well.
• sim_names (bool) - A flag which if True will add the Monte Carlo simulation object names as well.

Returns: list of str

The list of object names.

default_value(self, name)

Return the default value of the parameter.

Parameters:

• name (str) - The name of the parameter.

Returns: None or str

The default value.

description(self, name)

Return the description of the parameter.

Parameters:

• name (str) - The name of the parameter.

Returns: None or str

The description.

error_flag(self, name)

Return the error flag for the parameter.

Parameters:

• name (str) - The name of the parameter.

Returns: bool

The error flag for the parameter.

grace_string(self, name)

Return the Grace string for the parameter.

Parameters:

• name (str) - The name of the parameter.

Returns: str

The Grace string.

grace_units(self, name)

Return the Grace units string for the parameter.

Parameters:

• name (str) - The name of the parameter.

Returns: str

The Grace units string.

grid_lower(self, name, incs=None, model_info=None)

Return the default lower grid bound for the parameter.

Parameters:

• name (str) - The name of the parameter.
• incs (int) - The number of grid search increments. This is used by some of the bound determining functions.
• model_info (int) - The model information from the model_loop() specific API method. If the lower bound is a function, this information is sent into it.

Returns: int

The lower bound for the grid search.

grid_upper(self, name, incs=None, model_info=None)

Return the default upper grid bound for the parameter.

Parameters:

• name (str) - The name of the parameter.
• incs (int) - The number of grid search increments. This is used by some of the bound determining functions.
• model_info (int) - The model information from the model_loop() specific API method. If the upper bound is a function, this information is sent into it.

Returns: int

The upper bound for the grid search.

is_spin_param(self, name)

Determine whether the given parameter is spin specific.

Parameters:

• name (str) - The name of the parameter.

Returns: bool

True if the parameter is spin specific, False otherwise.

loop(self, set=None, scope=None, error_names=False, sim_names=False)

An iterator method for looping over all the parameters.

Parameters:

• set (str) - The set of object names. This can be set to 'all' for all names, to 'fixed' for parameter of the model which are permanently fixed, to 'params' for parameter of the model which are optimised or calculated, or to 'min' for minimisation specific object names.
• scope (str or None) - The scope of the parameter to return. If not set, then all will be returned. If set to 'global' or 'spin', then only the parameters within that scope will be returned.
• error_names (bool) - A flag which if True will add the error object names as well.
• sim_names (bool) - A flag which if True will add the Monte Carlo simulation object names as well.

Returns: str

The parameter names.

scaling(self, name, model_info=None)

Return the scaling factor for the parameter.

Parameters:

• model_info (int) - The model information from the model_loop() specific API method. If the scaling factor is a function, this information is sent into it.
• name (str) - The name of the parameter.

Returns: int

The scaling factor for optimisation.

scope(self, name)

Return the parameter scope.

Parameters:

• name (str) - The name of the parameter.

Returns: str

The scope. This is 'global' for parameters located within the global scope of the current data pipe. Or 'spin' for spin specific parameters. Alternatively the value 'both' indicates that there are both global and specific versions of this parameter.

set(self, name)

Return the parameter set that the parameter belongs to.

Parameters:

• name (str) - The name of the parameter.

Returns: str

The parameter set.

simulation_flag(self, name)

Return the Monte Carlo simulation flag for the parameter.

Parameters:

• name (str) - The name of the parameter.

Returns: bool

The Monte Carlo simulation flag for the parameter.

type(self, name)

Return the Python type for the parameter.

Parameters:

• name (str) - The name of the parameter.

Returns: Python type object

The Python type.

type_string(self, name)

Return the Python type for the parameter as a string representation.

Parameters:

• name (str) - The name of the parameter.

Returns: Python type object

The Python type.

uf_doc(self, label=None, caption=None, scope='spin', default=False, units=False, type=False)

"Create the parameter documentation for the user function docstrings.

Parameters:

• label (str) - The label of the table to return.

Returns: Desc_container instance

The parameter documentation.

units(self, name)

Return the units string for the parameter.

Parameters:

• name (str) - The name of the parameter.

Returns: str

The units string. If no unit is present, the empty string will be returned.