fitbenchmarking.results_processing.local_min_table module¶

compare table

class fitbenchmarking.results_processing.local_min_table.LocalMinTable(results, best_results, options, group_dir, pp_locations, table_name)¶

Bases: fitbenchmarking.results_processing.base_table.Table

The local min results shows a True or False value together with $\frac{|| J^T r||}{||r||}$ . The True or False indicates whether the software finds a minimum with respect to the following criteria:

$||r|| \leq$ RES_TOL,
$|| J^T r|| \leq$ GRAD_TOL,
$\frac{|| J^T r||}{||r||} \leq$ GRAD_TOL,

where $J$ and $r$ are the Jacobian and residual of $f(x, p)$ , respectively. The tolerances can be found in the results object.

display_str(results)¶

Function that combines the True and False value from variable local_min with the normalised residual

Parameters:	results (tuple) – a dictionary containing true or false values whether the return parameters is a local minimizer and a dictionary containing $\frac{\|\| J^T r\|\|}{\|\|r\|\|}$ values
Returns:	dictionary containing the string representation of the values in the table.
Return type:	dict

get_colour(results)¶

Uses the local minimizer dictionary values to set the HTML colour

Parameters:	results (tuple) – a dictionary containing true or false values whether the return parameters is a local minimizer and a dictionary containing $\frac{\|\| J^T r\|\|}{\|\|r\|\|}$ values
Returns:	dictionary containing error codes from the minimizers
Return type:	dict

get_values(results_dict)¶

Gets the main values to be reported in the tables

Parameters:	results_dict (dictionary) – dictionary containing results where the keys are the problem sets and the values are lists of results objects
Returns:	a dictionary containing true or false values whether the return parameters is a local minimizer and a dictionary containing $\frac{\|\| J^T r\|\|}{\|\|r\|\|}$ values
Return type:	tuple(dict, dict)