Update AlgLib to most recent version

[gkronber]

Script to test alglib changes (including persistence)

// use 'vars' to access variables in the script's variable store (e.g. vars.x = 5)
// use 'vars[string]' to access variables via runtime strings (e.g. vars["x"] = 5)
// use 'vars.Contains(string)' to check if a variable exists
// use 'vars.Clear()' to remove all variables
// use 'foreach (KeyValuePair<string, object> v in vars) { ... }' to iterate over all variables
// use 'variables' to work with IEnumerable<T> extension methods on the script's variable store

using System;
using System.Linq;
using System.Collections.Generic;
using System.Threading;

using HeuristicLab.Core;
using HeuristicLab.Common;
using HeuristicLab.Algorithms.DataAnalysis;
using HeuristicLab.Algorithms.OffspringSelectionGeneticAlgorithm;
using HeuristicLab.Problems.Instances.DataAnalysis;
using HeuristicLab.Optimization;
using HeuristicLab.Algorithms.CMAEvolutionStrategy;
using HeuristicLab.Algorithms.GradientDescent;
using HeuristicLab.Problems.TestFunctions;
using HeuristicLab.Problems.DataAnalysis;
using HeuristicLab.Problems.DataAnalysis.Symbolic;
using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
//using HeuristicLab.Collections;
using HeuristicLab.Data;
using HeuristicLab.ParallelEngine;

public class MyScript : HeuristicLab.Scripting.CSharpScriptBase {
  public override void Main() {
    TestRegressionTower();

    TestCMAES();
    TestLmbgfs();
    TestSymbReg();
  }
  
  public void TestRegressionTower() {
    // create tower problem
    var prov = new RegressionRealWorldInstanceProvider();
    var dd = prov.GetDataDescriptors().First(n=>n.Name.Contains("Tower"));
    var problemData = prov.LoadData(dd);
    var regProblem = new RegressionProblem();
    regProblem.Load(problemData);
    
    RunAlg("lr", new LinearRegression(), (IRegressionProblem)regProblem.Clone());
    RunAlg("rf", new RandomForestRegression(), (IRegressionProblem)regProblem.Clone());
       
    var smallProblem = (IRegressionProblem)regProblem.Clone();
    smallProblem.ProblemData.TrainingPartition.End = 300;
    RunAlg("gp", new GaussianProcessRegression(), smallProblem);
    
    RunAlg("nn", new NeuralNetworkRegression(), (IRegressionProblem)smallProblem.Clone());
    RunAlg("nne", new NeuralNetworkEnsembleRegression(), (IRegressionProblem)smallProblem.Clone());
    RunAlg("knn", new NearestNeighbourRegression(), (IRegressionProblem)regProblem.Clone());
  }
 
  
  public void TestCMAES() {   
    var cmaes = new CMAEvolutionStrategy();
    var prob = new SingleObjectiveTestFunctionProblem();
    prob.EvaluatorParameter.Value = new RosenbrockEvaluator();
    prob.ProblemSize = new IntValue(20);
    RunAlg("cmaes", cmaes, prob);
  }
  
  public void TestLmbgfs() {
    var lmbfgs = new LbfgsAlgorithm();
    var prob = new SingleObjectiveTestFunctionProblem();
    prob.EvaluatorParameter.Value = new RosenbrockEvaluator();
    prob.ProblemSize = new IntValue(20);
    lmbfgs.MaxIterations = 1000;
    RunAlg("lbfgs", lmbfgs, prob);
  }
  
  public void TestSymbReg() {
    // create tower problem
    var prov = new RegressionRealWorldInstanceProvider();
    var dd = prov.GetDataDescriptors().First(n=>n.Name.Contains("Tower"));
    var problemData = prov.LoadData(dd);
    var regProblem = new SymbolicRegressionSingleObjectiveProblem();
    regProblem.Load(problemData);
    regProblem.EvaluatorParameter.Value = new SymbolicRegressionConstantOptimizationEvaluator();
    regProblem.MaximumSymbolicExpressionTreeLength.Value = 100;
    regProblem.MaximumSymbolicExpressionTreeDepth.Value = 12;
    
    var gp = new OffspringSelectionGeneticAlgorithm();
    gp.Problem = regProblem;
    gp.MaximumGenerations.Value = 10;
    gp.ComparisonFactorLowerBound.Value = 1.0;
    gp.Mutator = gp.MutatorParameter.ValidValues.First(n => n.Name.Contains("TreeManipulator"));
    gp.Selector = gp.SelectorParameter.ValidValues.First(n => n.Name.Contains("GenderSpecific"));
    
    RunAlg("symbreg", gp, regProblem);
  }
  
  public void RunAlg(string name, IAlgorithm alg, IProblem prob) {
    alg.Problem = prob;
    var engineAlg = alg as EngineAlgorithm;
    if(engineAlg!=null) {
       engineAlg.Engine = new ParallelEngine();
    }
    vars[name] = alg;
    using(var wh = new AutoResetEvent(false)) {
      alg.ExceptionOccurred += (object sender, EventArgs<Exception> e) => { wh.Set(); };
      alg.Stopped += (object sender, EventArgs e) => { wh.Set(); };
      for(int i=0;i<10;i++) {
        alg.Prepare();
        alg.Start();
      
        wh.WaitOne();
      }
    }
  }
  // implement further classes and methods

}

[gkronber]

r12790: updated alglib to version 3.9.0 (reverse merge)

[gkronber]

r12791: updated alglib reference in test project (reverse merge)

[gkronber]

r12792: updated some of the alglib calls (we should only use the external API whenever possible) (reverse merge)

[gkronber]

r12796: updated alglib references to version 3.9.0 in FLA branch (reverse merge)

[gkronber]

r12798: quick fix for new result values in unit tests because of update to alglib 3.9 (reverse merge)

Version increment of HeuristicLab.Algorithms.DataAnalysis necessary? This would allow us to adjust the persistence code also.

[gkronber]

r12801: changed result value for gaussian process regression unit test because of changes of alglib version

[gkronber]

It seems there will be a new release soon. ​http://bugs.alglib.net/roadmap_page.php

[gkronber]

r12817: reverse merge of all trunk changes for updating to alglib version 3.9.0 (r12790:12792, r12798, r12801)

[gkronber]

r12818: reverse merge of r12796

[gkronber]

As discussed by architects it is necessary to increment the minor version of all dependent plugins if the alglib version increment would lead to a change in behavior.

[gkronber]

Results of evaluation of commercial version of alglib (including native implementation using Intel MKL)

1. The native implementation automatically detects wether it is running on x86 or x64 systems at runtime and simply works.
2. Native implementation is basically a C# wrapper to a compiled binary of C++ alglib that is statically linked to Intel MKL where useful. Thus, even the random forest implementation (even though it does not use MKL or parallelization) should be faster since it falls back to the native version.
3. In several places we use 'internal' classes of alglib instead of the standard API (e.g. alglib.dforest.dfbuild(...) instead of alglib.dfbuild(...)). This poses a problem because the native implementation only provides a C# wrapper for the user-facing API.
   • Code has to be rewritten to use 'official' alglib API calls. Especially for persistence (alglib now provides functions for serialization/deserialization of composed types)
   • Our LMBFGS uses internal API extensively. The code has to be completely rewritten when using the external API and possibly it is not possible to implement it in the same way as now.
   • We use a patched version of free alglib where we marked the PRNG as ThreadStatic. Alglib now has a different way of supporting multi-core parallel processing and thread-safety for the PRNG. Our code has to be adapted accordingly.
4. The native implementation might produce slightly different results than the managed implementation. Also, the native implementation might produce different results on different processors (especially x86 vs. x64 systems).
5. Updating alglib would lead to different algorithm results and therefore we need at least a minor version increment for all plugins that actually use alglib direcly or indirectly.
6. Updating the version would also be useful because we could completely update the persistence format for alglib types.

[gkronber]

• r14999: merged r12790,r12791,r12792,r12796,r12798,r12801, and r12817 (reverse merge of all previous) from trunk to stable. (only merge info is affected)
• r15000: merged r12818 from trunk to stable (which was a reverse merge of r12796, only merge info is affected)

Therefore, all changes in the ticket so far have been merged to stable.

[gkronber]

r16683: Created a new branch to add alglib version 3.15 as external library.

[gkronber]

r16684: added 3.15.0 version of alglib as external library (build from source)

[gkronber]

The branch is ready and can be merged to trunk. This would enable us to use the newer version for new developments in HL.

[mkommend]

r17034: Updated branch with most recent trunk changes.

[mkommend]

r17036: Changed rng in ALGLIB to have a separate instance per thread.

[mkommend]

r17037: Merged branch into trunk.

[mkommend]

r17038: Deleted branch.

[abeham]

We currently have alglib 3.7 and 3.15 side-by-side in HL. This creates problems for scripting and dependent plugins (programmable problem, external evaluation problem) which always load all assemblies in the appdomain.

The script cannot be compiled: "The type 'alglib' exists in both '...\ALGLIB-3.15.0.dll' and '...\ALGLIB-3.7.0.dll'".

I fixed that by checking for duplicate assemblies (by version-stripped filename) and using only the most recent version.

r17110: added filter to include only assemblies of most recent version in case multiple versions exist

[mkommend]

Reviewed r17110.

[gkronber]

r17158: merged r17037 and r17110 from trunk to stable