You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: adapted_ranks.m
    path of file: ./repos/toolkit-legacy/analysis
    
    the code of the file until where you have to start completion: function adapted = adapted_ranks(ranks, different, mode)
% adapted_ranks Performs rank adaptation on a set of ranks
%
% Performs different types of rank adaptation on a set of ranks and a matrix of determined actual differences of ranked entities. 
%

    
function adapted = adapted_ranks(ranks, different, mode)
% adapted_ranks Performs rank adaptation on a set of ranks
%
% Performs different types of rank adaptation on a set of ranks and a matrix of determined actual differences of ranked entities. 
%
% The function looks for sets of entities that are considered equal according to the `different` matrix and adapts their ranks
% in one of the following ways:
% - none: no adaptation, keep the original ranks.
% - mean: a mean rank of a set is assigned to all trackers in the set.
% - median: a median rank of a set is assigned to all trackers in the set.
% - best: a minimum rank in a set is assigned to all trackers in the set.
%
% Input:
% - ranks (double vector): A vector of `N` ranks.
% - different (boolean matrix): A `N x N` matrix that denotes which entities should actually be equal and which not. 
% - mode (string): Type of rank adaptation.
%
% Output
% - adapted (double vector): Adapted ranks 

adapted = zeros(1, length(ranks)) ;

switch mode
	case 'none'
        adapted = ranks;
    
	case 'mean'

		for tracker = 1:length(ranks)
			adapted(tracker) = mean(ranks(find(~different(tracker,:)))) ; %#ok<FNDSB>
		end