#region License Information /* HeuristicLab * Copyright (C) 2002-2012 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.Problems.DataAnalysis.Symbolic; using HeuristicLab.Random; using Microsoft.VisualStudio.TestTools.UnitTesting; namespace HeuristicLab.Problems.DataAnalysis.Symbolic_34.Tests { [TestClass()] public class SymbolicDataAnalysisExpressionTreeInterpreterTest { private const int N = 1000; private const int Rows = 1000; private const int Columns = 50; private TestContext testContextInstance; /// ///Gets or sets the test context which provides ///information about and functionality for the current test run. /// public TestContext TestContext { get { return testContextInstance; } set { testContextInstance = value; } } [TestMethod] public void SymbolicDataAnalysisExpressionTreeInterpreterTypeCoherentGrammarPerformanceTest() { TypeCoherentGrammarPerformanceTest(new SymbolicDataAnalysisExpressionTreeInterpreter(), 12.5e6); } [TestMethod] public void SymbolicDataAnalysisExpressionTreeInterpreterFullGrammarPerformanceTest() { FullGrammarPerformanceTest(new SymbolicDataAnalysisExpressionTreeInterpreter(), 12.5e6); } [TestMethod] public void SymbolicDataAnalysisExpressionTreeInterpreterArithmeticGrammarPerformanceTest() { ArithmeticGrammarPerformanceTest(new SymbolicDataAnalysisExpressionTreeInterpreter(), 12.5e6); } [TestMethod] public void SymbolicDataAnalysisExpressionTreeILEmittingInterpreterTypeCoherentGrammarPerformanceTest() { TypeCoherentGrammarPerformanceTest(new SymbolicDataAnalysisExpressionTreeILEmittingInterpreter(), 7.5e6); } [TestMethod] public void SymbolicDataAnalysisExpressionTreeILEmittingInterpreterFullGrammarPerformanceTest() { FullGrammarPerformanceTest(new SymbolicDataAnalysisExpressionTreeILEmittingInterpreter(), 7.5e6); } [TestMethod] public void SymbolicDataAnalysisExpressionTreeILEmittingInterpreterArithmeticGrammarPerformanceTest() { ArithmeticGrammarPerformanceTest(new SymbolicDataAnalysisExpressionTreeILEmittingInterpreter(), 7.5e6); } private void TypeCoherentGrammarPerformanceTest(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double nodesPerSecThreshold) { var twister = new MersenneTwister(31415); var dataset = Util.CreateRandomDataset(twister, Rows, Columns); var grammar = new TypeCoherentExpressionGrammar(); grammar.ConfigureAsDefaultRegressionGrammar(); grammar.MaximumFunctionArguments = 0; grammar.MaximumFunctionDefinitions = 0; grammar.MinimumFunctionArguments = 0; grammar.MinimumFunctionDefinitions = 0; 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); Assert.IsTrue(nodesPerSec > nodesPerSecThreshold); // evaluated nodes per seconds must be larger than 15mNodes/sec } private void FullGrammarPerformanceTest(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double nodesPerSecThreshold) { var twister = new MersenneTwister(31415); var dataset = Util.CreateRandomDataset(twister, Rows, Columns); var grammar = new FullFunctionalExpressionGrammar(); grammar.MaximumFunctionArguments = 0; grammar.MaximumFunctionDefinitions = 0; grammar.MinimumFunctionArguments = 0; grammar.MinimumFunctionDefinitions = 0; 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); Assert.IsTrue(nodesPerSec > nodesPerSecThreshold); // evaluated nodes per seconds must be larger than 15mNodes/sec } private void ArithmeticGrammarPerformanceTest(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, double nodesPerSecThreshold) { var twister = new MersenneTwister(31415); var dataset = Util.CreateRandomDataset(twister, Rows, Columns); var grammar = new ArithmeticExpressionGrammar(); grammar.MaximumFunctionArguments = 0; grammar.MaximumFunctionDefinitions = 0; grammar.MinimumFunctionArguments = 0; grammar.MinimumFunctionDefinitions = 0; 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); Assert.IsTrue(nodesPerSec > nodesPerSecThreshold); // evaluated nodes per seconds must be larger than 15mNodes/sec } /// ///A test for Evaluate /// [TestMethod] public void SymbolicDataAnalysisExpressionTreeInterpreterEvaluateTest() { 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 } }); var interpreter = new SymbolicDataAnalysisExpressionTreeInterpreter(); EvaluateTerminals(interpreter, ds); EvaluateOperations(interpreter, ds); EvaluateAdf(interpreter, ds); } [TestMethod] public void SymbolicDataAnalysisExpressionILEmittingTreeInterpreterEvaluateTest() { 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 } }); var interpreter = new SymbolicDataAnalysisExpressionTreeILEmittingInterpreter(); EvaluateTerminals(interpreter, ds); EvaluateOperations(interpreter, ds); } private void EvaluateTerminals(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, Dataset 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, Dataset 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 EvaluateOperations(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, Dataset 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) // 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); // 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); { // 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 Evaluate(ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, Dataset 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)); Assert.AreEqual(expected, actual, 1.0E-12, expr); } } }