Class Disp_result_command

Class for processing the dispersion optimisation results.

This object will be sent from the slave back to the master to have its run() method executed.

Instance Methods

__init__(self, processor=None, memo_id=None, param_vector=None, chi2=None, iter_count=None, f_count=None, g_count=None, h_count=None, warning=None, missing=None, back_calc=None, completed=True)
Set up this class object on the slave, placing the minimisation results here.

run(self, processor=None, memo=None)
Disassemble the model-free optimisation results (on the master).

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

Instance Variables

Inherited from multi.misc.Result: completed, memo_id, rank

Properties

Inherited from object: __class__

Method Details

__init__(self, processor=None, memo_id=None, param_vector=None, chi2=None, iter_count=None, f_count=None, g_count=None, h_count=None, warning=None, missing=None, back_calc=None, completed=True)
(Constructor)

Set up this class object on the slave, placing the minimisation results here.

Parameters:

• processor (multi.processor.Processor instance) - The processor object.
• memo_id (str) - The memo identification string.
• param_vector (numpy rank-1 array) - The optimised parameter vector.
• chi2 (float) - The final target function value.
• iter_count (int) - The number of optimisation iterations.
• f_count (int) - The total function call count.
• g_count (int) - The total gradient call count.
• h_count (int) - The total Hessian call count.
• warning (str or None) - Any optimisation warnings.
• missing (numpy rank-3 array) - The data structure indicating which R2eff/R1rho' base data is missing.
• back_calc (numpy rank-3 array) - The back-calculated R2eff/R1rho' data structure from the target function class. This is will be transfered to the master to be stored in the r2eff_bc data structure.
• completed (bool) - A flag which if True signals that the optimisation successfully completed.

Overrides: object.__init__

run(self, processor=None, memo=None)

Disassemble the model-free optimisation results (on the master).

Parameters:

• processor (None) - Unused!
• memo (memo) - The dispersion memo. This holds a lot of the data and objects needed for processing the results from the slave.

Overrides: multi.result_commands.Result_command.run