#region License Information
/* HeuristicLab
* Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Globalization;
using System.Linq;
using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
using HeuristicLab.Random;
using Microsoft.VisualStudio.TestTools.UnitTesting;
namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Tests {
[TestClass]
public class SymbolicDataAnalysisExpressionTreeInterpreterTest {
private const int N = 1000;
private const int Rows = 1000;
private const int Columns = 50;
private static Dataset ds = new Dataset(new string[] { "Y", "A", "B" }, new double[,] {
{ 1.0, 1.0, 1.0 },
{ 2.0, 2.0, 2.0 },
{ 3.0, 1.0, 2.0 },
{ 4.0, 1.0, 1.0 },
{ 5.0, 2.0, 2.0 },
{ 6.0, 1.0, 2.0 },
{ 7.0, 1.0, 1.0 },
{ 8.0, 2.0, 2.0 },
{ 9.0, 1.0, 2.0 },
{ 10.0, 1.0, 1.0 },
{ 11.0, 2.0, 2.0 },
{ 12.0, 1.0, 2.0 }
});
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void StandardInterpreterTestTypeCoherentGrammarPerformance() {
TestTypeCoherentGrammarPerformance(new SymbolicDataAnalysisExpressionTreeInterpreter(), 12.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void StandardInterpreterTestFullGrammarPerformance() {
TestFullGrammarPerformance(new SymbolicDataAnalysisExpressionTreeInterpreter(), 12.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void StandardInterpreterTestArithmeticGrammarPerformance() {
TestArithmeticGrammarPerformance(new SymbolicDataAnalysisExpressionTreeInterpreter(), 12.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void CompiledInterpreterTestTypeCoherentGrammarPerformance() {
TestTypeCoherentGrammarPerformance(new SymbolicDataAnalysisExpressionCompiledTreeInterpreter(), 12.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void CompiledInterpreterTestFullGrammarPerformance() {
TestFullGrammarPerformance(new SymbolicDataAnalysisExpressionCompiledTreeInterpreter(), 12.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void CompiledInterpreterTestArithmeticGrammarPerformance() {
TestArithmeticGrammarPerformance(new SymbolicDataAnalysisExpressionCompiledTreeInterpreter(), 12.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void ILEmittingInterpreterTestTypeCoherentGrammarPerformance() {
TestTypeCoherentGrammarPerformance(new SymbolicDataAnalysisExpressionTreeILEmittingInterpreter(), 7.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void ILEmittingInterpreterTestArithmeticGrammarPerformance() {
TestArithmeticGrammarPerformance(new SymbolicDataAnalysisExpressionTreeILEmittingInterpreter(), 7.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void LinearInterpreterTestTypeCoherentGrammarPerformance() {
TestTypeCoherentGrammarPerformance(new SymbolicDataAnalysisExpressionTreeLinearInterpreter(), 12.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void LinearInterpreterTestFullGrammarPerformance() {
TestFullGrammarPerformance(new SymbolicDataAnalysisExpressionTreeLinearInterpreter(), 12.5e6);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void LinearInterpreterTestArithmeticGrammarPerformance() {
TestArithmeticGrammarPerformance(new SymbolicDataAnalysisExpressionTreeLinearInterpreter(), 12.5e6);
}
private void TestTypeCoherentGrammarPerformance(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double nodesPerSecThreshold) {
var twister = new MersenneTwister(31415);
var dataset = Util.CreateRandomDataset(twister, Rows, Columns);
var grammar = new TypeCoherentExpressionGrammar();
grammar.ConfigureAsDefaultRegressionGrammar();
var randomTrees = Util.CreateRandomTrees(twister, dataset, grammar, N, 1, 100, 0, 0);
foreach (ISymbolicExpressionTree tree in randomTrees) {
Util.InitTree(tree, twister, new List(dataset.VariableNames));
}
double nodesPerSec = Util.CalculateEvaluatedNodesPerSec(randomTrees, interpreter, dataset, 3);
//mkommend: commented due to performance issues on the builder
// Assert.IsTrue(nodesPerSec > nodesPerSecThreshold); // evaluated nodes per seconds must be larger than 15mNodes/sec
}
private void TestFullGrammarPerformance(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double nodesPerSecThreshold) {
var twister = new MersenneTwister(31415);
var dataset = Util.CreateRandomDataset(twister, Rows, Columns);
var grammar = new FullFunctionalExpressionGrammar();
var randomTrees = Util.CreateRandomTrees(twister, dataset, grammar, N, 1, 100, 0, 0);
foreach (ISymbolicExpressionTree tree in randomTrees) {
Util.InitTree(tree, twister, new List(dataset.VariableNames));
}
double nodesPerSec = Util.CalculateEvaluatedNodesPerSec(randomTrees, interpreter, dataset, 3);
//mkommend: commented due to performance issues on the builder
//Assert.IsTrue(nodesPerSec > nodesPerSecThreshold); // evaluated nodes per seconds must be larger than 15mNodes/sec
}
private void TestArithmeticGrammarPerformance(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double nodesPerSecThreshold) {
var twister = new MersenneTwister(31415);
var dataset = Util.CreateRandomDataset(twister, Rows, Columns);
var grammar = new ArithmeticExpressionGrammar();
var randomTrees = Util.CreateRandomTrees(twister, dataset, grammar, N, 1, 100, 0, 0);
foreach (SymbolicExpressionTree tree in randomTrees) {
Util.InitTree(tree, twister, new List(dataset.VariableNames));
}
double nodesPerSec = Util.CalculateEvaluatedNodesPerSec(randomTrees, interpreter, dataset, 3);
//mkommend: commented due to performance issues on the builder
//Assert.IsTrue(nodesPerSec > nodesPerSecThreshold); // evaluated nodes per seconds must be larger than 15mNodes/sec
}
///
///A test for Evaluate
///
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "short")]
public void StandardInterpreterTestEvaluation() {
var interpreter = new SymbolicDataAnalysisExpressionTreeInterpreter();
EvaluateTerminals(interpreter, ds);
EvaluateOperations(interpreter, ds);
EvaluateLaggedOperations(interpreter, ds);
EvaluateSpecialFunctions(interpreter, ds);
EvaluateAdf(interpreter, ds);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "short")]
public void CompiledInterpreterTestEvaluation() {
var interpreter = new SymbolicDataAnalysisExpressionCompiledTreeInterpreter();
// ADFs are not supported by the compiled tree interpreter
EvaluateTerminals(interpreter, ds);
EvaluateOperations(interpreter, ds);
EvaluateSpecialFunctions(interpreter, ds);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "short")]
public void LinearInterpreterTestEvaluation() {
var interpreter = new SymbolicDataAnalysisExpressionTreeLinearInterpreter();
//ADFs are not supported by the linear interpreter
EvaluateTerminals(interpreter, ds);
EvaluateOperations(interpreter, ds);
EvaluateLaggedOperations(interpreter, ds);
EvaluateSpecialFunctions(interpreter, ds);
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void TestInterpretersEstimatedValuesConsistency() {
var twister = new MersenneTwister();
int seed = twister.Next(0, int.MaxValue);
twister.Seed((uint)seed);
const int numRows = 100;
var dataset = Util.CreateRandomDataset(twister, numRows, Columns);
var grammar = new TypeCoherentExpressionGrammar();
var interpreters = new ISymbolicDataAnalysisExpressionTreeInterpreter[] {
new SymbolicDataAnalysisExpressionTreeLinearInterpreter(),
new SymbolicDataAnalysisExpressionTreeInterpreter(),
};
var rows = Enumerable.Range(0, numRows).ToList();
var randomTrees = Util.CreateRandomTrees(twister, dataset, grammar, N, 1, 10, 0, 0);
foreach (ISymbolicExpressionTree tree in randomTrees) {
Util.InitTree(tree, twister, new List(dataset.VariableNames));
}
for (int i = 0; i < randomTrees.Length; ++i) {
var tree = randomTrees[i];
var valuesMatrix = interpreters.Select(x => x.GetSymbolicExpressionTreeValues(tree, dataset, rows)).ToList();
for (int m = 0; m < interpreters.Length - 1; ++m) {
var sum = valuesMatrix[m].Sum();
for (int n = m + 1; n < interpreters.Length; ++n) {
var s = valuesMatrix[n].Sum();
if (double.IsNaN(sum) && double.IsNaN(s)) continue;
string errorMessage = string.Format("Interpreters {0} and {1} do not agree on tree {2} (seed = {3}).", interpreters[m].Name, interpreters[n].Name, i, seed);
Assert.AreEqual(sum, s, 1e-12, errorMessage);
}
}
}
}
[TestMethod]
[TestCategory("Problems.DataAnalysis.Symbolic")]
[TestProperty("Time", "long")]
public void TestCompiledInterpreterEstimatedValuesConsistency() {
const double delta = 1e-12;
var twister = new MersenneTwister();
int seed = twister.Next(0, int.MaxValue);
twister.Seed((uint)seed);
Console.WriteLine(seed);
const int numRows = 100;
var dataset = Util.CreateRandomDataset(twister, numRows, Columns);
var grammar = new TypeCoherentExpressionGrammar();
grammar.ConfigureAsDefaultRegressionGrammar();
grammar.Symbols.First(x => x.Name == "Power Functions").Enabled = true;
var randomTrees = Util.CreateRandomTrees(twister, dataset, grammar, N, 1, 10, 0, 0);
foreach (ISymbolicExpressionTree tree in randomTrees) {
Util.InitTree(tree, twister, new List(dataset.VariableNames));
}
var interpreters = new ISymbolicDataAnalysisExpressionTreeInterpreter[] {
new SymbolicDataAnalysisExpressionCompiledTreeInterpreter(),
new SymbolicDataAnalysisExpressionTreeInterpreter(),
new SymbolicDataAnalysisExpressionTreeLinearInterpreter(),
};
var rows = Enumerable.Range(0, numRows).ToList();
var formatter = new SymbolicExpressionTreeHierarchicalFormatter();
for (int i = 0; i < randomTrees.Length; ++i) {
var tree = randomTrees[i];
var valuesMatrix = interpreters.Select(x => x.GetSymbolicExpressionTreeValues(tree, dataset, rows).ToList()).ToList();
for (int m = 0; m < interpreters.Length - 1; ++m) {
for (int n = m + 1; n < interpreters.Length; ++n) {
for (int row = 0; row < numRows; ++row) {
var v1 = valuesMatrix[m][row];
var v2 = valuesMatrix[n][row];
if (double.IsNaN(v1) && double.IsNaN(v2)) continue;
if (Math.Abs(v1 - v2) > delta) {
Console.WriteLine(formatter.Format(tree));
foreach (var node in tree.Root.GetSubtree(0).GetSubtree(0).IterateNodesPrefix().ToList()) {
var rootNode = (SymbolicExpressionTreeTopLevelNode)grammar.ProgramRootSymbol.CreateTreeNode();
if (rootNode.HasLocalParameters) rootNode.ResetLocalParameters(twister);
rootNode.SetGrammar(grammar.CreateExpressionTreeGrammar());
var startNode = (SymbolicExpressionTreeTopLevelNode)grammar.StartSymbol.CreateTreeNode();
if (startNode.HasLocalParameters) startNode.ResetLocalParameters(twister);
startNode.SetGrammar(grammar.CreateExpressionTreeGrammar());
rootNode.AddSubtree(startNode);
var t = new SymbolicExpressionTree(rootNode);
var start = t.Root.GetSubtree(0);
var p = node.Parent;
start.AddSubtree(node);
Console.WriteLine(node);
var y1 = interpreters[m].GetSymbolicExpressionTreeValues(t, dataset, new[] { row }).First();
var y2 = interpreters[n].GetSymbolicExpressionTreeValues(t, dataset, new[] { row }).First();
if (double.IsNaN(y1) && double.IsNaN(y2)) continue;
string prefix = Math.Abs(y1 - y2) > delta ? "++" : "==";
Console.WriteLine("\t{0} Row {1}: {2} {3}, Deviation = {4}", prefix, row, y1, y2, Math.Abs(y1 - y2));
node.Parent = p;
}
}
string errorMessage = string.Format("Interpreters {0} and {1} do not agree on tree {2} and row {3} (seed = {4}).", interpreters[m].Name, interpreters[n].Name, i, row, seed);
Assert.AreEqual(v1, v2, delta, errorMessage);
}
}
}
}
}
private void EvaluateTerminals(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataset ds) {
// constants
Evaluate(interpreter, ds, "(+ 1.5 3.5)", 0, 5.0);
// variables
Evaluate(interpreter, ds, "(variable 2.0 a)", 0, 2.0);
Evaluate(interpreter, ds, "(variable 2.0 a)", 1, 4.0);
}
private void EvaluateAdf(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataset ds) {
// ADF
Evaluate(interpreter, ds, @"(PROG
(MAIN
(CALL ADF0))
(defun ADF0 1.0))", 1, 1.0);
Evaluate(interpreter, ds, @"(PROG
(MAIN
(* (CALL ADF0) (CALL ADF0)))
(defun ADF0 2.0))", 1, 4.0);
Evaluate(interpreter, ds, @"(PROG
(MAIN
(CALL ADF0 2.0 3.0))
(defun ADF0
(+ (ARG 0) (ARG 1))))", 1, 5.0);
Evaluate(interpreter, ds, @"(PROG
(MAIN (CALL ADF1 2.0 3.0))
(defun ADF0
(- (ARG 1) (ARG 0)))
(defun ADF1
(+ (CALL ADF0 (ARG 1) (ARG 0))
(CALL ADF0 (ARG 0) (ARG 1)))))", 1, 0.0);
Evaluate(interpreter, ds, @"(PROG
(MAIN (CALL ADF1 (variable 2.0 a) 3.0))
(defun ADF0
(- (ARG 1) (ARG 0)))
(defun ADF1
(CALL ADF0 (ARG 1) (ARG 0))))", 1, 1.0);
Evaluate(interpreter, ds,
@"(PROG
(MAIN (CALL ADF1 (variable 2.0 a) 3.0))
(defun ADF0
(- (ARG 1) (ARG 0)))
(defun ADF1
(+ (CALL ADF0 (ARG 1) (ARG 0))
(CALL ADF0 (ARG 0) (ARG 1)))))", 1, 0.0);
}
private void EvaluateSpecialFunctions(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataset ds) {
// special functions
Action checkAiry = (x) => {
double ai, aip, bi, bip;
alglib.airy(x, out ai, out aip, out bi, out bip);
Evaluate(interpreter, ds, "(airya " + x + ")", 0, ai);
Evaluate(interpreter, ds, "(airyb " + x + ")", 0, bi);
};
Action checkBessel = (x) => {
Evaluate(interpreter, ds, "(bessel " + x + ")", 0, alglib.besseli0(x));
};
Action checkSinCosIntegrals = (x) => {
double si, ci;
alglib.sinecosineintegrals(x, out si, out ci);
Evaluate(interpreter, ds, "(cosint " + x + ")", 0, ci);
Evaluate(interpreter, ds, "(sinint " + x + ")", 0, si);
};
Action checkHypSinCosIntegrals = (x) => {
double shi, chi;
alglib.hyperbolicsinecosineintegrals(x, out shi, out chi);
Evaluate(interpreter, ds, "(hypcosint " + x + ")", 0, chi);
Evaluate(interpreter, ds, "(hypsinint " + x + ")", 0, shi);
};
Action checkFresnelSinCosIntegrals = (x) => {
double c = 0, s = 0;
alglib.fresnelintegral(x, ref c, ref s);
Evaluate(interpreter, ds, "(fresnelcosint " + x + ")", 0, c);
Evaluate(interpreter, ds, "(fresnelsinint " + x + ")", 0, s);
};
Action checkNormErf = (x) => {
Evaluate(interpreter, ds, "(norm " + x + ")", 0, alglib.normaldistribution(x));
Evaluate(interpreter, ds, "(erf " + x + ")", 0, alglib.errorfunction(x));
};
Action checkGamma = (x) => {
Evaluate(interpreter, ds, "(gamma " + x + ")", 0, alglib.gammafunction(x));
};
Action checkPsi = (x) => {
try {
Evaluate(interpreter, ds, "(psi " + x + ")", 0, alglib.psi(x));
}
catch (alglib.alglibexception) { // ignore cases where alglib throws an exception
}
};
Action checkDawson = (x) => {
Evaluate(interpreter, ds, "(dawson " + x + ")", 0, alglib.dawsonintegral(x));
};
Action checkExpInt = (x) => {
Evaluate(interpreter, ds, "(expint " + x + ")", 0, alglib.exponentialintegralei(x));
};
foreach (var e in new[] { -2.0, -1.0, 0.0, 1.0, 2.0 }) {
checkAiry(e);
checkBessel(e);
checkSinCosIntegrals(e);
checkGamma(e);
checkExpInt(e);
checkDawson(e);
checkPsi(e);
checkNormErf(e);
checkFresnelSinCosIntegrals(e);
checkHypSinCosIntegrals(e);
}
}
private void EvaluateLaggedOperations(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataset ds) {
// lag
Evaluate(interpreter, ds, "(lagVariable 1.0 a -1) ", 1, ds.GetDoubleValue("A", 0));
Evaluate(interpreter, ds, "(lagVariable 1.0 a -1) ", 2, ds.GetDoubleValue("A", 1));
Evaluate(interpreter, ds, "(lagVariable 1.0 a 0) ", 2, ds.GetDoubleValue("A", 2));
Evaluate(interpreter, ds, "(lagVariable 1.0 a 1) ", 0, ds.GetDoubleValue("A", 1));
// integral
Evaluate(interpreter, ds, "(integral -1.0 (variable 1.0 a)) ", 1, ds.GetDoubleValue("A", 0) + ds.GetDoubleValue("A", 1));
Evaluate(interpreter, ds, "(integral -1.0 (lagVariable 1.0 a 1)) ", 1, ds.GetDoubleValue("A", 1) + ds.GetDoubleValue("A", 2));
Evaluate(interpreter, ds, "(integral -2.0 (variable 1.0 a)) ", 2, ds.GetDoubleValue("A", 0) + ds.GetDoubleValue("A", 1) + ds.GetDoubleValue("A", 2));
Evaluate(interpreter, ds, "(integral -1.0 (* (variable 1.0 a) (variable 1.0 b)))", 1, ds.GetDoubleValue("A", 0) * ds.GetDoubleValue("B", 0) + ds.GetDoubleValue("A", 1) * ds.GetDoubleValue("B", 1));
Evaluate(interpreter, ds, "(integral -2.0 3.0)", 1, 9.0);
// derivative
// (f_0 + 2 * f_1 - 2 * f_3 - f_4) / 8; // h = 1
Evaluate(interpreter, ds, "(diff (variable 1.0 a)) ", 5, (ds.GetDoubleValue("A", 5) + 2 * ds.GetDoubleValue("A", 4) - 2 * ds.GetDoubleValue("A", 2) - ds.GetDoubleValue("A", 1)) / 8.0);
Evaluate(interpreter, ds, "(diff (variable 1.0 b)) ", 5, (ds.GetDoubleValue("B", 5) + 2 * ds.GetDoubleValue("B", 4) - 2 * ds.GetDoubleValue("B", 2) - ds.GetDoubleValue("B", 1)) / 8.0);
Evaluate(interpreter, ds, "(diff (* (variable 1.0 a) (variable 1.0 b)))", 5, +
(ds.GetDoubleValue("A", 5) * ds.GetDoubleValue("B", 5) +
2 * ds.GetDoubleValue("A", 4) * ds.GetDoubleValue("B", 4) -
2 * ds.GetDoubleValue("A", 2) * ds.GetDoubleValue("B", 2) -
ds.GetDoubleValue("A", 1) * ds.GetDoubleValue("B", 1)) / 8.0);
Evaluate(interpreter, ds, "(diff -2.0 3.0)", 5, 0.0);
// timelag
Evaluate(interpreter, ds, "(lag -1.0 (lagVariable 1.0 a 2)) ", 1, ds.GetDoubleValue("A", 2));
Evaluate(interpreter, ds, "(lag -2.0 (lagVariable 1.0 a 2)) ", 2, ds.GetDoubleValue("A", 2));
Evaluate(interpreter, ds, "(lag -1.0 (* (lagVariable 1.0 a 1) (lagVariable 1.0 b 2)))", 1, ds.GetDoubleValue("A", 1) * ds.GetDoubleValue("B", 2));
Evaluate(interpreter, ds, "(lag -2.0 3.0)", 1, 3.0);
}
private void EvaluateOperations(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataset ds) {
// addition
Evaluate(interpreter, ds, "(+ (variable 2.0 a ))", 1, 4.0);
Evaluate(interpreter, ds, "(+ (variable 2.0 a ) (variable 3.0 b ))", 0, 5.0);
Evaluate(interpreter, ds, "(+ (variable 2.0 a ) (variable 3.0 b ))", 1, 10.0);
Evaluate(interpreter, ds, "(+ (variable 2.0 a) (variable 3.0 b ))", 2, 8.0);
Evaluate(interpreter, ds, "(+ 8.0 2.0 2.0)", 0, 12.0);
// subtraction
Evaluate(interpreter, ds, "(- (variable 2.0 a ))", 1, -4.0);
Evaluate(interpreter, ds, "(- (variable 2.0 a ) (variable 3.0 b))", 0, -1.0);
Evaluate(interpreter, ds, "(- (variable 2.0 a ) (variable 3.0 b ))", 1, -2.0);
Evaluate(interpreter, ds, "(- (variable 2.0 a ) (variable 3.0 b ))", 2, -4.0);
Evaluate(interpreter, ds, "(- 8.0 2.0 2.0)", 0, 4.0);
// multiplication
Evaluate(interpreter, ds, "(* (variable 2.0 a ))", 0, 2.0);
Evaluate(interpreter, ds, "(* (variable 2.0 a ) (variable 3.0 b ))", 0, 6.0);
Evaluate(interpreter, ds, "(* (variable 2.0 a ) (variable 3.0 b ))", 1, 24.0);
Evaluate(interpreter, ds, "(* (variable 2.0 a ) (variable 3.0 b ))", 2, 12.0);
Evaluate(interpreter, ds, "(* 8.0 2.0 2.0)", 0, 32.0);
// division
Evaluate(interpreter, ds, "(/ (variable 2.0 a ))", 1, 1.0 / 4.0);
Evaluate(interpreter, ds, "(/ (variable 2.0 a ) 2.0)", 0, 1.0);
Evaluate(interpreter, ds, "(/ (variable 2.0 a ) 2.0)", 1, 2.0);
Evaluate(interpreter, ds, "(/ (variable 3.0 b ) 2.0)", 2, 3.0);
Evaluate(interpreter, ds, "(/ 8.0 2.0 2.0)", 0, 2.0);
// gt
Evaluate(interpreter, ds, "(> (variable 2.0 a) 2.0)", 0, -1.0);
Evaluate(interpreter, ds, "(> 2.0 (variable 2.0 a))", 0, -1.0);
Evaluate(interpreter, ds, "(> (variable 2.0 a) 1.9)", 0, 1.0);
Evaluate(interpreter, ds, "(> 1.9 (variable 2.0 a))", 0, -1.0);
Evaluate(interpreter, ds, "(> (log -1.0) (log -1.0))", 0, -1.0); // (> nan nan) should be false
// lt
Evaluate(interpreter, ds, "(< (variable 2.0 a) 2.0)", 0, -1.0);
Evaluate(interpreter, ds, "(< 2.0 (variable 2.0 a))", 0, -1.0);
Evaluate(interpreter, ds, "(< (variable 2.0 a) 1.9)", 0, -1.0);
Evaluate(interpreter, ds, "(< 1.9 (variable 2.0 a))", 0, 1.0);
Evaluate(interpreter, ds, "(< (log -1.0) (log -1.0))", 0, -1.0); // (< nan nan) should be false
// If
Evaluate(interpreter, ds, "(if -10.0 2.0 3.0)", 0, 3.0);
Evaluate(interpreter, ds, "(if -1.0 2.0 3.0)", 0, 3.0);
Evaluate(interpreter, ds, "(if 0.0 2.0 3.0)", 0, 3.0);
Evaluate(interpreter, ds, "(if 1.0 2.0 3.0)", 0, 2.0);
Evaluate(interpreter, ds, "(if 10.0 2.0 3.0)", 0, 2.0);
Evaluate(interpreter, ds, "(if (log -1.0) 2.0 3.0)", 0, 3.0); // if(nan) should return the else branch
// NOT
Evaluate(interpreter, ds, "(not -1.0)", 0, 1.0);
Evaluate(interpreter, ds, "(not -2.0)", 0, 1.0);
Evaluate(interpreter, ds, "(not 1.0)", 0, -1.0);
Evaluate(interpreter, ds, "(not 2.0)", 0, -1.0);
Evaluate(interpreter, ds, "(not 0.0)", 0, 1.0);
Evaluate(interpreter, ds, "(not (log -1.0))", 0, 1.0);
// AND
Evaluate(interpreter, ds, "(and -1.0 -2.0)", 0, -1.0);
Evaluate(interpreter, ds, "(and -1.0 2.0)", 0, -1.0);
Evaluate(interpreter, ds, "(and 1.0 -2.0)", 0, -1.0);
Evaluate(interpreter, ds, "(and 1.0 0.0)", 0, -1.0);
Evaluate(interpreter, ds, "(and 0.0 0.0)", 0, -1.0);
Evaluate(interpreter, ds, "(and 1.0 2.0)", 0, 1.0);
Evaluate(interpreter, ds, "(and 1.0 2.0 3.0)", 0, 1.0);
Evaluate(interpreter, ds, "(and 1.0 -2.0 3.0)", 0, -1.0);
Evaluate(interpreter, ds, "(and (log -1.0))", 0, -1.0); // (and NaN)
Evaluate(interpreter, ds, "(and (log -1.0) 1.0)", 0, -1.0); // (and NaN 1.0)
// OR
Evaluate(interpreter, ds, "(or -1.0 -2.0)", 0, -1.0);
Evaluate(interpreter, ds, "(or -1.0 2.0)", 0, 1.0);
Evaluate(interpreter, ds, "(or 1.0 -2.0)", 0, 1.0);
Evaluate(interpreter, ds, "(or 1.0 2.0)", 0, 1.0);
Evaluate(interpreter, ds, "(or 0.0 0.0)", 0, -1.0);
Evaluate(interpreter, ds, "(or -1.0 -2.0 -3.0)", 0, -1.0);
Evaluate(interpreter, ds, "(or -1.0 -2.0 3.0)", 0, 1.0);
Evaluate(interpreter, ds, "(or (log -1.0))", 0, -1.0); // (or NaN)
Evaluate(interpreter, ds, "(or (log -1.0) 1.0)", 0, -1.0); // (or NaN 1.0)
// XOR
Evaluate(interpreter, ds, "(xor -1.0 -2.0)", 0, -1.0);
Evaluate(interpreter, ds, "(xor -1.0 2.0)", 0, 1.0);
Evaluate(interpreter, ds, "(xor 1.0 -2.0)", 0, 1.0);
Evaluate(interpreter, ds, "(xor 1.0 2.0)", 0, -1.0);
Evaluate(interpreter, ds, "(xor 0.0 0.0)", 0, -1.0);
Evaluate(interpreter, ds, "(xor -1.0 -2.0 -3.0)", 0, -1.0);
Evaluate(interpreter, ds, "(xor -1.0 -2.0 3.0)", 0, 1.0);
Evaluate(interpreter, ds, "(xor -1.0 2.0 3.0)", 0, -1.0);
Evaluate(interpreter, ds, "(xor 1.0 2.0 3.0)", 0, 1.0);
Evaluate(interpreter, ds, "(xor (log -1.0))", 0, -1.0);
Evaluate(interpreter, ds, "(xor (log -1.0) 1.0)", 0, 1.0);
// sin, cos, tan
Evaluate(interpreter, ds, "(sin " + Math.PI.ToString(NumberFormatInfo.InvariantInfo) + ")", 0, 0.0);
Evaluate(interpreter, ds, "(sin 0.0)", 0, 0.0);
Evaluate(interpreter, ds, "(cos " + Math.PI.ToString(NumberFormatInfo.InvariantInfo) + ")", 0, -1.0);
Evaluate(interpreter, ds, "(cos 0.0)", 0, 1.0);
Evaluate(interpreter, ds, "(tan " + Math.PI.ToString(NumberFormatInfo.InvariantInfo) + ")", 0, Math.Tan(Math.PI));
Evaluate(interpreter, ds, "(tan 0.0)", 0, Math.Tan(Math.PI));
// exp, log
Evaluate(interpreter, ds, "(log (exp 7.0))", 0, Math.Log(Math.Exp(7)));
Evaluate(interpreter, ds, "(exp (log 7.0))", 0, Math.Exp(Math.Log(7)));
Evaluate(interpreter, ds, "(log -3.0)", 0, Math.Log(-3));
// power
Evaluate(interpreter, ds, "(pow 2.0 3.0)", 0, 8.0);
Evaluate(interpreter, ds, "(pow 4.0 0.5)", 0, 1.0); // interpreter should round to the nearest integer value value (.5 is rounded to the even number)
Evaluate(interpreter, ds, "(pow 4.0 2.5)", 0, 16.0); // interpreter should round to the nearest integer value value (.5 is rounded to the even number)
Evaluate(interpreter, ds, "(pow -2.0 3.0)", 0, -8.0);
Evaluate(interpreter, ds, "(pow 2.0 -3.0)", 0, 1.0 / 8.0);
Evaluate(interpreter, ds, "(pow -2.0 -3.0)", 0, -1.0 / 8.0);
// root
Evaluate(interpreter, ds, "(root 9.0 2.0)", 0, 3.0);
Evaluate(interpreter, ds, "(root 27.0 3.0)", 0, 3.0);
Evaluate(interpreter, ds, "(root 2.0 -3.0)", 0, Math.Pow(2.0, -1.0 / 3.0));
// mean
Evaluate(interpreter, ds, "(mean -1.0 1.0 -1.0)", 0, -1.0 / 3.0);
}
private void Evaluate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataset ds, string expr, int index, double expected) {
var importer = new SymbolicExpressionImporter();
ISymbolicExpressionTree tree = importer.Import(expr);
double actual = interpreter.GetSymbolicExpressionTreeValues(tree, ds, Enumerable.Range(index, 1)).First();
Assert.IsFalse(double.IsNaN(actual) && !double.IsNaN(expected));
Assert.IsFalse(!double.IsNaN(actual) && double.IsNaN(expected));
if (!double.IsNaN(actual) && !double.IsNaN(expected))
Assert.AreEqual(expected, actual, 1.0E-12, expr);
}
}
}