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: TestBernoulli.m
    path of file: ./repos/MatlabStan/Tests
    
    the code of the file until where you have to start completion: % xUnit framework required
% http://www.mathworks.com/matlabcentral/fileexchange/22846-matlab-xunit-test-framework

% REF:
% https://github.com/stan-dev/pystan/blob/develop/pystan/tests/test_basic.py
classdef TestBernoulli < TestCase
   properties
      model
      fit
      code
      data
   end
   
   methods
      fu
    
function test_bernoulli_extract(self)
         fit = self.fit;
         extr = fit.extract('permuted',true);
         assertTrue((-7.4<mean(extr.lp__)) && (mean(extr.lp__)<-7.0));
         assertTrue((0.1<mean(extr.theta)) && (mean(extr.theta)<0.4));
         assertTrue((0.01<var(extr.theta)) && (var(extr.theta)<0.02));
         
         % permuted=false
         % CHECK:
         extr = fit.extract('permuted',false);
         
         % permuted=true
         extr = fit.extract('pars','lp__','permuted',true);
         assertTrue((-7.4<mean(extr.lp__)) && (mean(extr.lp__)<-7.0));
         extr = fit.extract('pars','theta','permuted',true);
         assertTrue((0.1<mean(extr.theta)) && (mean(extr.theta)<0.4));
         assertTrue((0.01<var(extr.theta)) && (var(extr.theta)<0.02));
      end
      
      function test_bernoulli_random_seed_consistency(self)
         for i = 1:2
            fit(i) = self.model.sampling('data',self.data,'seed',42,...
               'sample_file',['output_' num2str(i)]);
            fit(i).block();
            theta{i} = fit(i).extract('pars','theta','permuted',true).theta;
         end