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: replace_values.m
    path of file: ./repos/CanlabCore/CanlabCore/@canlab_dataset
    
    the code of the file until where you have to start completion: function D = replace_values(D, varname, function_handle, replace_with)
% Replace values identified with your custom input function with NaN
%
% D = replace_values(D, function_handle to select values to replace, replace_with, varname)
%
% function_handle is an anonymous function that selects values to replace.
% It should return a logical vector of true/false values. e.g.,  @(x) x <= 0
%
% e.g.,
% Take the variable 'ratings' in canlab_dataset object D
% Replace all ratings <= 0 with NaN
%
% D = replace_values(D, 'ratings', @(x) x <= 0, NaN)

[dat, datcell, wh_level, descrip, wh_indx] = get_var(D, varname);  % to list variables

switch wh_level
    case 1  % Subject
        
        wh = function_handle(dat); % select observations to replace, logical
        

    
function D = replace_values(D, varname, function_handle, replace_with)
% Replace values identified with your custom input function with NaN
%
% D = replace_values(D, function_handle to select values to replace, replace_with, varname)
%
% function_handle is an anonymous function that selects values to replace.
% It should return a logical vector of true/false values. e.g.,  @(x) x <= 0
%
% e.g.,
% Take the variable 'ratings' in canlab_dataset object D
% Replace all ratings <= 0 with NaN
%
% D = replace_values(D, 'ratings', @(x) x <= 0, NaN)

[dat, datcell, wh_level, descrip, wh_indx] = get_var(D, varname);  % to list variables

switch wh_level
    case 1  % Subject
        
        wh = function_handle(dat); % select observations to replace, logical
        
        dat(wh) = replace_with;
        
        D.Subj_Level.data(:, wh_indx) = dat;
        
    case 2  % Event
        
        n = length(datcell);  % for each subject
        
        for i = 1:n
            
            % Do not use datcell because NaNs are removed there
            
            mydat = D.Event_Level.data{i}(:, wh_indx);
            
            wh = function_handle(mydat); % select observations to replace, logical
            
            mydat(wh) = replace_with;
            
            D.Event_Level.data{i}(:, wh_indx) = mydat;
            
        end