type N_state_model

Class containing functions for the N-state model.

Instance Methods

__init__(self)
Initialise the class by placing API_common methods into the API.

list of [SpinContainer instance, str, str] or [InteratomContainer instance, str, str] base_data_loop(self)
Loop over the base data of the spins - RDCs, PCSs, and NOESY data.

calculate(self, spin_id=None, scaling_matrix=None, verbosity=1, sim_index=None)
Calculation function.

list of floats create_mc_data(self, data_id=None)
Create the Monte Carlo data by back-calculation.

list of str get_param_names(self, model_info=None)
Return a vector of parameter names.

list of str get_param_values(self, model_info=None, sim_index=None)
Return a vector of parameter values.

grid_search(self, lower=None, upper=None, inc=None, scaling_matrix=None, constraints=False, verbosity=0, sim_index=None)
The grid search function.

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

list of float map_bounds(self, param, spin_id=None)
Create bounds for the OpenDX mapping function.

minimise(self, min_algor=None, min_options=None, func_tol=None, grad_tol=None, max_iterations=None, constraints=False, scaling_matrix=None, verbosity=0, sim_index=None, lower=None, upper=None, inc=None)
Minimisation function.

tuple of (int, int, float) model_statistics(self, model_info=None, spin_id=None, global_stats=None)
Return the k, n, and chi2 model statistics.

list of (float or None) return_data(self, data_id)
Return the base data for the given data ID.

list of float return_error(self, data_id=None)
Create and return the spin specific Monte Carlo Ri error structure.

set_error(self, index, error, model_info=None)
Set the parameter errors.

set_param_values(self, param=None, value=None, index=None, spin_id=None, error=False, force=True)
Set the N-state model parameter values.

sim_init_values(self)
Initialise the Monte Carlo parameter values.

sim_pack_data(self, data_id, sim_data)
Pack the Monte Carlo simulation data.

list of float sim_return_param(self, index, model_info=None)
Return the array of simulation parameter values.

Inherited from api_base.API_base: back_calc_ri, bmrb_read, bmrb_write, constraint_algorithm, covariance_matrix, data_init, data_names, data_type, default_value, deselect, duplicate_data, eliminate, get_model_container, has_errors, model_desc, model_loop, model_type, molmol_macro, num_instances, overfit_deselect, print_model_title, pymol_macro, return_conversion_factor, return_data_desc, return_error_red_chi2, return_grace_string, return_grace_units, return_units, return_value, set_selected_sim, set_update, sim_return_chi2, sim_return_selected, skip_function

Inherited from api_common.API_common (private): _base_data_loop_spin, _create_mc_relax_data, _data_init_dummy, _data_init_spin, _deselect_global, _eliminate_false, _get_model_container_cdp, _has_errors_spin, _is_spin_param_false, _is_spin_param_true, _model_loop_single_global, _model_loop_spin, _model_type_global, _model_type_local, _num_instances_spin, _overfit_deselect_dummy, _print_model_title_global, _print_model_title_spin, _return_data_relax_data, _return_error_relax_data, _return_no_conversion_factor, _return_value_general, _set_error_spin, _set_param_values_global, _set_param_values_spin, _set_selected_sim_global, _set_selected_sim_spin, _set_update, _sim_init_values_spin, _sim_pack_relax_data, _sim_return_chi2_spin, _sim_return_param_spin, _sim_return_selected_global, _sim_return_selected_spin

Static Methods

Inherited from api_base.API_base: __new__

Class Variables

instance = None

Method Details

__init__(self)
(Constructor)

Initialise the class by placing API_common methods into the API.

Overrides: object.__init__

base_data_loop(self)

Loop over the base data of the spins - RDCs, PCSs, and NOESY data.

This loop iterates for each data point (RDC, PCS, NOESY) for each spin or interatomic data container, returning the identification information.

Returns: list of [SpinContainer instance, str, str] or [InteratomContainer instance, str, str]

A list of the spin or interatomic data container, the data type ('rdc', 'pcs', 'noesy'), and the alignment ID if required.

Overrides: api_base.API_base.base_data_loop

calculate(self, spin_id=None, scaling_matrix=None, verbosity=1, sim_index=None)

Calculation function.

Currently this function simply calculates the NOESY flat-bottom quadratic energy potential, if NOE restraints are available.

Parameters:

• spin_id (None or str) - The spin identification string (unused).
• scaling_matrix (list of numpy rank-2, float64 array or list of None) - The per-model list of diagonal and square scaling matrices.
• verbosity (int) - The amount of information to print. The higher the value, the greater the verbosity.
• sim_index (None) - The MC simulation index (unused).

Overrides: api_base.API_base.calculate

create_mc_data(self, data_id=None)

Create the Monte Carlo data by back-calculation.

Parameters:

• data_id (str) - The list of spin ID, data type, and alignment ID, as yielded by the base_data_loop() generator method.

Returns: list of floats

The Monte Carlo Ri data.

Overrides: api_base.API_base.create_mc_data

get_param_names(self, model_info=None)

Return a vector of parameter names.

Parameters:

• model_info (None) - The model information from model_loop(). This is unused.

Returns: list of str

The vector of parameter names.

Overrides: api_base.API_base.get_param_names

get_param_values(self, model_info=None, sim_index=None)

Return a vector of parameter values.

Parameters:

• model_info (None) - The model information from model_loop(). This is unused.
• sim_index (int) - The optional Monte Carlo simulation index.

Returns: list of str

The vector of parameter values.

Overrides: api_base.API_base.get_param_values

grid_search(self, lower=None, upper=None, inc=None, scaling_matrix=None, constraints=False, verbosity=0, sim_index=None)

The grid search function.

Parameters:

• lower (list of lists of floats) - The lower bounds of the grid search which must be equal to the number of parameters in the model.
• upper (list of lists of floats) - The upper bounds of the grid search which must be equal to the number of parameters in the model.
• inc (list of lists of int) - The increments for each dimension of the space for the grid search. The number of elements in the array must equal to the number of parameters in the model.
• scaling_matrix (list of numpy rank-2, float64 array or list of None) - The per-model list of diagonal and square scaling matrices.
• constraints (bool) - If True, constraints are applied during the grid search (elinating parts of the grid). If False, no constraints are used.
• verbosity (int) - A flag specifying the amount of information to print. The higher the value, the greater the verbosity.

Overrides: api_base.API_base.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

False

Overrides: api_base.API_base.is_spin_param

map_bounds(self, param, spin_id=None)

Create bounds for the OpenDX mapping function.

Parameters:

• param (str) - The name of the parameter to return the lower and upper bounds of.
• spin_id (None) - The spin identification string (unused).

Returns: list of float

The upper and lower bounds of the parameter.

Overrides: api_base.API_base.map_bounds

minimise(self, min_algor=None, min_options=None, func_tol=None, grad_tol=None, max_iterations=None, constraints=False, scaling_matrix=None, verbosity=0, sim_index=None, lower=None, upper=None, inc=None)

Minimisation function.

Parameters:

• min_algor (str) - The minimisation algorithm to use.
• min_options (array of str) - An array of options to be used by the minimisation algorithm.
• func_tol (None or float) - The function tolerance which, when reached, terminates optimisation. Setting this to None turns of the check.
• grad_tol (None or float) - The gradient tolerance which, when reached, terminates optimisation. Setting this to None turns of the check.
• max_iterations (int) - The maximum number of iterations for the algorithm.
• constraints (bool) - If True, constraints are used during optimisation.
• scaling_matrix (list of numpy rank-2, float64 array or list of None) - The per-model list of diagonal and square scaling matrices.
• verbosity (int) - A flag specifying the amount of information to print. The higher the value, the greater the verbosity.
• sim_index (None or int) - The index of the simulation to optimise. This should be None if normal optimisation is desired.
• lower (list of lists of numbers) - The per-model lower bounds of the grid search which must be equal to the number of parameters in the model. This optional argument is only used when doing a grid search.
• upper (list of lists of numbers) - The per-model upper bounds of the grid search which must be equal to the number of parameters in the model. This optional argument is only used when doing a grid search.
• inc (list of lists of int) - The per-model increments for each dimension of the space for the grid search. The number of elements in the array must equal to the number of parameters in the model. This argument is only used when doing a grid search.

Overrides: api_base.API_base.minimise

model_statistics(self, model_info=None, spin_id=None, global_stats=None)

Return the k, n, and chi2 model statistics.

k - number of parameters. n - number of data points. chi2 - the chi-squared value.

Parameters:

• model_info (None) - The model information from model_loop(). This is unused.
• spin_id (None or str) - The spin identification string. This is ignored in the N-state model.
• global_stats (None or bool) - A parameter which determines if global or local statistics are returned. For the N-state model, this argument is ignored.

Returns: tuple of (int, int, float)

The optimisation statistics, in tuple format, of the number of parameters (k), the number of data points (n), and the chi-squared value (chi2).

Overrides: api_base.API_base.model_statistics

return_data(self, data_id)

Return the base data for the given data ID.

Parameters:

• data_id (list of str) - The list of spin ID, data type, and alignment ID, as yielded by the base_data_loop() generator method.

Returns: list of (float or None)

The base data.

Overrides: api_base.API_base.return_data

return_error(self, data_id=None)

Create and return the spin specific Monte Carlo Ri error structure.

Parameters:

• data_id (str) - The list of spin ID, data type, and alignment ID, as yielded by the base_data_loop() generator method.

Returns: list of float

The Monte Carlo simulation data errors.

Overrides: api_base.API_base.return_error

set_error(self, index, error, model_info=None)

Set the parameter errors.

Parameters:

• index (int) - The index of the parameter to set the errors for.
• error (float) - The error value.
• model_info (None) - The model information from model_loop(). This is unused.

Overrides: api_base.API_base.set_error

set_param_values(self, param=None, value=None, index=None, spin_id=None, error=False, force=True)

Set the N-state model parameter values.

Parameters:

• param (list of str) - The parameter name list.
• value (list) - The parameter value list.
• index (None or int) - The index for parameters which are of the list-type (probs, alpha, beta, and gamma). This is ignored for all other types.
• spin_id (None) - The spin identification string (unused).
• error (bool) - A flag which if True will allow the parameter errors to be set instead of the values.
• force (bool) - A flag which if True will cause current values to be overwritten. If False, a RelaxError will raised if the parameter value is already set.

Overrides: api_base.API_base.set_param_values

sim_init_values(self)

Initialise the Monte Carlo parameter values.

Overrides: api_base.API_base.sim_init_values

sim_pack_data(self, data_id, sim_data)

Pack the Monte Carlo simulation data.

Parameters:

• data_id (list of str) - The list of spin ID, data type, and alignment ID, as yielded by the base_data_loop() generator method.
• sim_data (list of float) - The Monte Carlo simulation data.

Overrides: api_base.API_base.sim_pack_data

sim_return_param(self, index, model_info=None)

Return the array of simulation parameter values.

Parameters:

• index (int) - The index of the parameter to return the array of values for.
• model_info (None) - The model information from model_loop(). This is unused.

Returns: list of float

The array of simulation parameter values.

Overrides: api_base.API_base.sim_return_param