csharpfftfsharpintegrationinterpolationlinear-algebramathdifferentiationmatrixnumericsrandomregressionstatisticsmathnet
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35 lines
1.3 KiB
35 lines
1.3 KiB
using System;
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using MathNet.Numerics.LinearAlgebra;
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using NUnit.Framework;
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namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
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{
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[TestFixture]
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public class VectorToStringTests
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{
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Vector<double> v1 = Vector<double>.Build.Dense(1, i => (i + 1)*Constants.Pi);
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Vector<double> v2 = Vector<double>.Build.Dense(2, i => (i + 1)*Constants.Pi);
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Vector<double> v100 = Vector<double>.Build.Dense(100, i => (i + 1)*Constants.Pi);
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readonly string NL = Environment.NewLine;
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[Test]
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public void MinimumLimits()
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{
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Assert.That(v1.ToVectorString(3, 16, "G6"), Is.EqualTo("3.14159" + NL));
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Assert.That(v2.ToVectorString(3, 16, "G6"), Is.EqualTo("3.14159" + NL + "6.28319" + NL));
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Assert.That(v100.ToVectorString(3, 16, "G6"), Is.EqualTo("3.14159" + NL + " .." + NL + "314.159" + NL));
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}
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[Test]
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public void GitHubIssue387()
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{
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Vector<double> v = Vector<double>.Build.DenseOfArray(new[]
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{
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0.607142857142857,
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1.17857142857143
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});
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Assert.That(v.ToVectorString(12, 12, "..", " ", "\n", x => x.ToString()), Is.EqualTo("0.607142857142857\n 1.17857142857143\n"));
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}
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}
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}
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