[[PageOutline]]
= Analyzer = 
Analyzers are HeuristicLab 3.3 operators that implement the `IAnalyzer` interface. There are a couple of general purpose Analyzers, such as the `QualityAnalyzer` or the `MultiAnalyzer` as well as encoding and problem specific Analyzers. 

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== 1. General == 
[=#MultiAnalyzer]
=== 1.1 !MultiAnalyzer === 
An analyzer which applies arbitrary many other analyzers. It is used as a parameter in all currently implemented problems ([[Evolution Strategy]], [[Genetic Algorithm]] etc.) to ensure easy extendability. 

For example, if you open the [[UsersTSPSample#GATSP| GA for the ch130 problem]] sample on the Optimizer Start Page, navigate to the Parameters tab and click on the Analyzer property, you will see the following list of sub-Analyzers: 

[[Image(MultiAnalyzer_Example_TSP.png)]]

The `BestAverageWorstQualityAnalyzer` comes from the genetic algorithm and the `BestTSPSolutionAnalyzer` was provided by the TSP problem. This wiring also works if you configure your own algorithm in the Optimizer. Opening a new Evolution Strategy algorithm and loading a Griewank test function as problem will result in a `BestAverageWorstQualityAnalyzer` and a `BestSingleObjectiveTestFunctionSolutionAnalyzer`. You can of course add additional Analyzers via the GUI. 
 

'''Operator Parameters:'''

||= Parameter         =||= Description =||
|| !UpdateInterval || The interval in which the contained analyzers should be applied (Default: 1) ||
|| !UpdateCounter || The value which counts how many times the !MultiAnalyzer was called since the last update. ||

=== 1.2 !MinAverageMaxValueAnalyzer ===
An operator which analyzes the minimum, average and maximum of a value in the scope tree.
[=#BestAverageWorstQualityAnalyzer ]
=== 1.3 !BestAverageWorstQualityAnalyzer ===
An operator which analyzes the best, average and worst quality of solutions in the scope tree.

=== 1.4 !QualityAnalyzer ===
An operator which analyzes the quality of solutions in the scope tree.

=== 1.5 !ValueAnalyzer ===
An operator which analyzes a value in the scope tree.

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== 2. Tabu Search == 
=== 2.1 !TabuNeighborhoodAnalyzer === 

'''Operator Parameters:'''
||= Parameter         =||= Description =||
|| !IsTabu || A value that determines if a move is tabu or not. ||
|| !PercentTabu || Indicates how much of the neighborhood is tabu. ||
|| Results || The result collection where the value should be stored. ||

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== 3. Artificial Ant Problem ==
=== 3.1 !BestAntTrailAnalyzer ===  
An operator for analyzing the best ant trail of an [[Artificial Ant Problem]].


'''Operator Parameters:'''
||= Parameter         =||= Description =||
|| !BestSolution || The visual representation of the best ant trail. ||
|| !MaxTimeSteps || The maximal time steps that the artificial ant has available to collect all food items. ||
|| Quality || The qualities of the artificial ant solutions which should be visualized. ||
|| Results || The result collection where the best artificial ant solution should be stored. ||
|| !SymbolicExpressionTree || The artificial ant solutions from which the best solution should be visualized. ||
|| World || The world with food items for the artificial ant. ||

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== 4. Knapsack Problem ==
=== 4.1 !BestKnapsackSolutionAnalyzer ===
An operator for analyzing the best solution for a [[Knapsack Problem]].


'''Operator Parameters:'''
||= Parameter         =||= Description =||
|| !BestKnownQuality || The quality of the best known solution. ||
|| !BestKnownSolution || The best known solution. ||
|| !BestSolution || The best knapsack solution. ||
|| !BinaryVector || The knapsack solutions from which the best solution should be visualized. ||
|| !KnapsackCapacity || Capacity of the Knapsack. ||
|| Maximization || True if the problem is a maximization problem. ||
|| Quality || The qualities of the knapsack solutions which should be analyzed. ||
|| Results || The result collection where the knapsack solution should be stored. ||
|| Values || The values of the items. ||
|| Weights || The weights of the items. ||

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== 5. !OneMax Problem ==
=== 5.1 !BestOneMaxSolutionAnalyzer ===
An operator for analyzing the best solution for a [[OneMax Problem]].


'''Operator Parameters:'''
||= Parameter         =||= Description =||
|| !BestKnownQuality || The quality of the best known solution. ||
|| !BestKnownSolution || The best known solution. ||
|| !BinaryVector || The Onemax solutions from which the best solution should be visualized. ||
|| Maximization || True if the problem is a maximization problem. ||
|| Quality || The qualities of the Onemax solutions which should be analyzed. ||
|| Results || The result collection where the Onemax solution should be stored. ||

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== 6. Single Objective Test Function Problem ==
=== 6.1 !BestSingleObjectiveTestFunctionSolutionAnalyzer ===
An operator for analyzing the best solution for a [[Single Objective Test Function]] problem.

'''Problem Parameters:'''
||= Parameter         =||= Description =||
|| !BestKnownQuality   || The quality of the best known solution of this test function. ||
|| !BestKnownSolution  || The best known solution for this test function instance. ||
|| !BestSolution || The best !SingleObjectiveTestFunction solution. ||
|| Evaluator || The evaluator with which the solution is evaluated. ||  
|| Maximization || Set to false as most test functions are minimization problems. ||
|| Quality || The qualities of the test function solutions which should be analzed. ||
|| !RealVector || The !SingleObjectiveTestFunction solutions from which the best solution should be visualized. ||
|| Results || The result collection where the !SingleObjectiveTestFunction solution should be stored. ||

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== 7. Travelling Salesman Problem == 
=== 7.1 BestTSPSolutionAnalyzer ===
An operator for analyzing the best solution of a [[Travelling Salesman Problem]] given in path representation using city coordinates.

'''Operator Parameters:'''
||= Parameter         =||= Description =||
|| !BestKnownQuality || The quality of the best known solution of this TSP instance. ||
|| !BestKnownSolution || The best known solution of this TSP instance. ||
|| !BestSolution || The best TSP solution. ||
|| Coordinates || The x- and y-Coordinates of the cities. ||
|| Maximization || True if the problem is a maximization problem. ||
|| Permutation || The TSP solutions given in path representation from which the best solution should be analyzed. || 
|| Quality || The qualities of the TSP solutions which should be analzed. ||
|| Results || The result collection where the best TSP solution should be stored. ||