conkit.misc.selectalg module

Energy function templates for restraint generation

class SubselectionAlgorithm

Bases: object

A class to collect all subselection algorithms

classmethod cutoff(data, cutoff=0.287)

A cutoff-defined subselection algorithm

This algorithm removes a decoy, if its score is less than the cutoff.

Parameters:

• data (list, tuple) – A 1D array of scores
• cutoff (float, optional) – The cutoff of keeping decoys

Returns:

• list – The decoy indices to keep
• list – The decoy indices to throw

classmethod ignore(data)

“A subselection algorithm to keep all

This algorithm doesn’t do anything except mimic others.

It will not discard any decoys and keep all!!

Parameters:data (list, tuple) – A 1D array of scores Returns:

• list – The decoy indices to keep
• list – The decoy indices to throw

classmethod linear(data, cutoff=0.5)

A linearly-defined subselection algorithm

This algorithm removes the worst x``% decoys, where ``x is defined by cutoff.

Parameters:

• data (list, tuple) – A 1D array of scores
• cutoff (float, optional) – The porportion of the total number of decoys to keep

Returns:

• list – The decoy indices to keep
• list – The decoy indices to throw

classmethod scaled(data, cutoff=0.5)

A scaling-defined subselection algorithm

This algorithm removes a decoy, if its scaled score is less than 0.5. The scaled score is calculated by dividing the precision score by the average of the set.

Parameters:

• data (list, tuple) – A 1D array of scores
• cutoff (float, optional) – The cutoff of keeping decoys

Returns:

• list – The decoy indices to keep
• list – The decoy indices to throw