Class Hybrid

Class containing function specific to hybrid models.

Instance Methods

_hybridise(self, hybrid=None, pipe_list=None)
Create the hybrid data pipe.

list of str data_names(self, set='all', scope=None, error_names=False, sim_names=False)
Return a list of nothing.

duplicate_data(self, pipe_from=None, pipe_to=None, model_info=None, global_stats=False, verbose=True)
Duplicate the data specific to a single hybrid data pipe.

str model_desc(self, model_info=None)
Return a description of the model.

model_loop(self)
Dummy generator method - this should be a global model!

model_type(self)
Method stating that this is a global model.

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 of the hybrid.

int num_instances(self)
Return the number of instances, which for hybrids is always 1.

bool skip_function(self, model_info=None)
Dummy function.

Method Details

_hybridise(self, hybrid=None, pipe_list=None)

Create the hybrid data pipe.

Parameters:

• hybrid (str) - The name of the new hybrid data pipe.
• pipe_list (list of str) - The list of data pipes that the hybrid is composed of.

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

Return a list of nothing.

Parameters:

• set (str) - The set of object names to return. This can be set to 'all' for all names, to 'generic' for generic object names, 'params' for analysis specific parameter names, 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.

duplicate_data(self, pipe_from=None, pipe_to=None, model_info=None, global_stats=False, verbose=True)

Duplicate the data specific to a single hybrid data pipe.

Parameters:

• pipe_from (str) - The data pipe to copy the data from.
• pipe_to (str) - The data pipe to copy the data to.
• model_info (unknown) - The model information from model_loop().
• global_stats (bool) - The global statistics flag.
• verbose (bool) - A flag which if True will cause info to be printed out.

model_desc(self, model_info=None)

Return a description of the model.

Parameters:

• model_info (unknown) - The model information from model_loop().

Returns: str

The model description.

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

Return the k, n, and chi2 model statistics of the hybrid.

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

Parameters:

• model_index (int) - The model index. This is zero for the global models or equal to the global spin index (which covers the molecule, residue, and spin indices). This originates from the model_loop().
• spin_id (None or str) - The spin identification string. Either this or the instance keyword argument must be supplied.
• global_stats (None or bool) - A parameter which determines if global or local statistics are returned. If None, then the appropriateness of global or local statistics is automatically determined.

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).

num_instances(self)

Return the number of instances, which for hybrids is always 1.

Returns: int

The number of instances.

skip_function(self, model_info=None)

Dummy function.

Parameters:

• model_info (unknown) - The model information from model_loop().

Returns: bool

True if the data should be skipped, False otherwise.