From fcc7598bf2fe8fc5747ec5996f3a15a654167bac Mon Sep 17 00:00:00 2001 From: Christoph Ruegg Date: Fri, 25 Feb 2011 14:18:33 +0100 Subject: [PATCH] Move Sampling/Sample to Signals/SignalGenerator to avoid confusion with statistical sampling --- src/Examples/Interpolation/AkimaSpline.cs | 4 ++-- src/Examples/Interpolation/LinearBetweenPoints.cs | 4 ++-- src/Examples/Interpolation/RationalWithPoles.cs | 4 ++-- src/Examples/Interpolation/RationalWithoutPoles.cs | 4 ++-- src/Examples/Sampling/Chebyshev.cs | 6 +++--- src/Examples/Sampling/Equidistant.cs | 10 +++++----- src/Examples/Sampling/Random.cs | 8 ++++---- src/Examples/SpecialFunctions/ErrorFunction.cs | 10 +++++----- src/Examples/Statistics.cs | 6 +++--- src/Numerics/Numerics.csproj | 6 +++--- .../SignalGenerator.Chebyshev.cs} | 6 +++--- .../SignalGenerator.Equidistant.cs} | 6 +++--- .../SignalGenerator.Random.cs} | 6 +++--- src/Silverlight/Silverlight.csproj | 12 ++++++------ src/UnitTests/IntegralTransformsTests/FourierTest.cs | 6 +++--- src/UnitTests/IntegralTransformsTests/HartleyTest.cs | 4 ++-- .../IntegralTransformsTests/InverseTransformTest.cs | 8 ++++---- .../MatchingNaiveTransformTest.cs | 12 ++++++------ .../IntegralTransformsTests/ParsevalTheoremTest.cs | 6 +++--- 19 files changed, 64 insertions(+), 64 deletions(-) rename src/Numerics/{Sampling/Sample.Chebyshev.cs => Signals/SignalGenerator.Chebyshev.cs} (97%) rename src/Numerics/{Sampling/Sample.Equidistant.cs => Signals/SignalGenerator.Equidistant.cs} (98%) rename src/Numerics/{Sampling/Sample.Random.cs => Signals/SignalGenerator.Random.cs} (97%) diff --git a/src/Examples/Interpolation/AkimaSpline.cs b/src/Examples/Interpolation/AkimaSpline.cs index 3b950b68..5732810b 100644 --- a/src/Examples/Interpolation/AkimaSpline.cs +++ b/src/Examples/Interpolation/AkimaSpline.cs @@ -30,7 +30,7 @@ namespace Examples.Interpolation using MathNet.Numerics.Interpolation; using MathNet.Numerics.Interpolation.Algorithms; using MathNet.Numerics.Random; - using MathNet.Numerics.Sampling; + using MathNet.Numerics.Signals; /// /// Interpolation example @@ -69,7 +69,7 @@ namespace Examples.Interpolation // 1. Generate 10 samples of the function x*x-2*x on interval [0, 10] Console.WriteLine(@"1. Generate 10 samples of the function x*x-2*x on interval [0, 10]"); double[] points; - var values = Sample.EquidistantInterval(TargetFunction, 0, 10, 10, out points); + var values = SignalGenerator.EquidistantInterval(TargetFunction, 0, 10, 10, out points); Console.WriteLine(); // 2. Create akima spline interpolation diff --git a/src/Examples/Interpolation/LinearBetweenPoints.cs b/src/Examples/Interpolation/LinearBetweenPoints.cs index f0cc3924..a835828c 100644 --- a/src/Examples/Interpolation/LinearBetweenPoints.cs +++ b/src/Examples/Interpolation/LinearBetweenPoints.cs @@ -29,7 +29,7 @@ namespace Examples.Interpolation using System; using MathNet.Numerics.Interpolation; using MathNet.Numerics.Random; - using MathNet.Numerics.Sampling; + using MathNet.Numerics.Signals; /// /// Interpolation example @@ -68,7 +68,7 @@ namespace Examples.Interpolation // 1. Generate 20 samples of the function x*x-2*x on interval [0, 10] Console.WriteLine(@"1. Generate 20 samples of the function x*x-2*x on interval [0, 10]"); double[] points; - var values = Sample.EquidistantInterval(TargetFunction, 0, 10, 20, out points); + var values = SignalGenerator.EquidistantInterval(TargetFunction, 0, 10, 20, out points); Console.WriteLine(); // 2. Create a linear spline interpolation based on arbitrary points diff --git a/src/Examples/Interpolation/RationalWithPoles.cs b/src/Examples/Interpolation/RationalWithPoles.cs index 6104818d..90f14618 100644 --- a/src/Examples/Interpolation/RationalWithPoles.cs +++ b/src/Examples/Interpolation/RationalWithPoles.cs @@ -29,7 +29,7 @@ namespace Examples.Interpolation using System; using MathNet.Numerics.Interpolation; using MathNet.Numerics.Random; - using MathNet.Numerics.Sampling; + using MathNet.Numerics.Signals; /// /// Interpolation example @@ -67,7 +67,7 @@ namespace Examples.Interpolation // 1. Generate 20 samples of the function f(x) = x on interval [-5, 5] Console.WriteLine(@"1. Generate 20 samples of the function f(x) = x on interval [-5, 5]"); double[] points; - var values = Sample.EquidistantInterval(TargetFunction, -5, 5, 20, out points); + var values = SignalGenerator.EquidistantInterval(TargetFunction, -5, 5, 20, out points); Console.WriteLine(); // 2. Create a burlish stoer rational interpolation based on arbitrary points diff --git a/src/Examples/Interpolation/RationalWithoutPoles.cs b/src/Examples/Interpolation/RationalWithoutPoles.cs index ffa1ebd8..e1dfde6f 100644 --- a/src/Examples/Interpolation/RationalWithoutPoles.cs +++ b/src/Examples/Interpolation/RationalWithoutPoles.cs @@ -29,7 +29,7 @@ namespace Examples.Interpolation using System; using MathNet.Numerics.Interpolation; using MathNet.Numerics.Random; - using MathNet.Numerics.Sampling; + using MathNet.Numerics.Signals; /// /// Interpolation example @@ -68,7 +68,7 @@ namespace Examples.Interpolation // 1. Generate 10 samples of the function 1/(1+x*x) on interval [-5, 5] Console.WriteLine(@"1. Generate 10 samples of the function 1/(1+x*x) on interval [-5, 5]"); double[] points; - var values = Sample.EquidistantInterval(TargetFunction, -5, 5, 10, out points); + var values = SignalGenerator.EquidistantInterval(TargetFunction, -5, 5, 10, out points); Console.WriteLine(); // 2. Create a floater hormann rational pole-free interpolation based on arbitrary points diff --git a/src/Examples/Sampling/Chebyshev.cs b/src/Examples/Sampling/Chebyshev.cs index 427614e5..f0f1f866 100644 --- a/src/Examples/Sampling/Chebyshev.cs +++ b/src/Examples/Sampling/Chebyshev.cs @@ -27,7 +27,7 @@ namespace Examples.Sampling { using System; - using MathNet.Numerics.Sampling; + using MathNet.Numerics.Signals; /// /// Example of generic function sampling and quantization provider @@ -62,7 +62,7 @@ namespace Examples.Sampling public void Run() { // 1. Get 20 samples of f(x) = (x * x) / 2 at the roots of the Chebyshev polynomial of the first kind within interval [0, 10] - var result = Sample.ChebyshevNodesFirstKind(Function, 0, 10, 20); + var result = SignalGenerator.ChebyshevNodesFirstKind(Function, 0, 10, 20); Console.WriteLine(@"1. Get 20 samples of f(x) = (x * x) / 2 at the roots of the Chebyshev polynomial of the first kind within interval [0, 10]"); for (var i = 0; i < result.Length; i++) { @@ -73,7 +73,7 @@ namespace Examples.Sampling Console.WriteLine(); // 2. Get 20 samples of f(x) = (x * x) / 2 at the roots of the Chebyshev polynomial of the second kind within interval [0, 10] - result = Sample.ChebyshevNodesSecondKind(Function, 0, 10, 20); + result = SignalGenerator.ChebyshevNodesSecondKind(Function, 0, 10, 20); Console.WriteLine(@"2. Get 20 samples of f(x) = (x * x) / 2 at the roots of the Chebyshev polynomial of the second kind within interval [0, 10]"); for (var i = 0; i < result.Length; i++) { diff --git a/src/Examples/Sampling/Equidistant.cs b/src/Examples/Sampling/Equidistant.cs index b0a6e3c8..dff33c22 100644 --- a/src/Examples/Sampling/Equidistant.cs +++ b/src/Examples/Sampling/Equidistant.cs @@ -27,7 +27,7 @@ namespace Examples.Sampling { using System; - using MathNet.Numerics.Sampling; + using MathNet.Numerics.Signals; /// /// Example of generic function sampling and quantization provider @@ -62,7 +62,7 @@ namespace Examples.Sampling public void Run() { // 1. Get 11 samples of f(x) = (x * x) / 2 equidistant within interval [-5, 5] - var result = Sample.EquidistantInterval(Function, -5, 5, 11); + var result = SignalGenerator.EquidistantInterval(Function, -5, 5, 11); Console.WriteLine(@"1. Get 11 samples of f(x) = (x * x) / 2 equidistant within interval [-5, 5]"); for (var i = 0; i < result.Length; i++) { @@ -74,7 +74,7 @@ namespace Examples.Sampling // 2. Get 10 samples of f(x) = (x * x) / 2 equidistant starting at x=1 with step = 0.5 and retrieve sample points double[] samplePoints; - result = Sample.EquidistantStartingAt(Function, 1, 0.5, 10, out samplePoints); + result = SignalGenerator.EquidistantStartingAt(Function, 1, 0.5, 10, out samplePoints); Console.WriteLine(@"2. Get 10 samples of f(x) = (x * x) / 2 equidistant starting at x=1 with step = 0.5 and retrieve sample points"); Console.Write(@"Points: "); for (var i = 0; i < samplePoints.Length; i++) @@ -93,7 +93,7 @@ namespace Examples.Sampling Console.WriteLine(); // 3. Get 10 samples of f(x) = (x * x) / 2 equidistant within period = 10 and period offset = 5 - result = Sample.EquidistantPeriodic(Function, 10, 5, 10); + result = SignalGenerator.EquidistantPeriodic(Function, 10, 5, 10); Console.WriteLine(@"3. Get 10 samples of f(x) = (x * x) / 2 equidistant within period = 10 and period offset = 5"); for (var i = 0; i < result.Length; i++) { @@ -104,7 +104,7 @@ namespace Examples.Sampling Console.WriteLine(); // 4. Sample f(x) = (x * x) / 2 equidistant to an integer-domain function starting at x = 0 and step = 2 - var equidistant = Sample.EquidistantToFunction(Function, 0, 2); + var equidistant = SignalGenerator.EquidistantToFunction(Function, 0, 2); Console.WriteLine(@" 4. Sample f(x) = (x * x) / 2 equidistant to an integer-domain function starting at x = 0 and step = 2"); for (var i = 0; i < 10; i++) { diff --git a/src/Examples/Sampling/Random.cs b/src/Examples/Sampling/Random.cs index c556e2ab..af43f93b 100644 --- a/src/Examples/Sampling/Random.cs +++ b/src/Examples/Sampling/Random.cs @@ -28,7 +28,7 @@ namespace Examples.Sampling { using System; using MathNet.Numerics.Distributions; - using MathNet.Numerics.Sampling; + using MathNet.Numerics.Signals; /// /// Example of generic function sampling and quantization provider @@ -64,7 +64,7 @@ namespace Examples.Sampling { // 1. Get 10 random samples of f(x) = (x * x) / 2 using continuous uniform distribution on [-10, 10] var uniform = new ContinuousUniform(-10, 10); - var result = Sample.Random(Function, uniform, 10); + var result = SignalGenerator.Random(Function, uniform, 10); Console.WriteLine(@" 1. Get 10 random samples of f(x) = (x * x) / 2 using continuous uniform distribution on [-10, 10]"); for (var i = 0; i < result.Length; i++) { @@ -77,7 +77,7 @@ namespace Examples.Sampling // 2. Get 10 random samples of f(x) = (x * x) / 2 using Exponential(1) distribution and retrieve sample points var exponential = new Exponential(1); double[] samplePoints; - result = Sample.Random(Function, exponential, 10, out samplePoints); + result = SignalGenerator.Random(Function, exponential, 10, out samplePoints); Console.WriteLine(@"2. Get 10 random samples of f(x) = (x * x) / 2 using Exponential(1) distribution and retrieve sample points"); Console.Write(@"Points: "); for (var i = 0; i < samplePoints.Length; i++) @@ -97,7 +97,7 @@ namespace Examples.Sampling // 3. Get 10 random samples of f(x, y) = (x * y) / 2 using ChiSquare(10) distribution var chiSquare = new ChiSquare(10); - result = Sample.Random(TwoDomainFunction, chiSquare, 10); + result = SignalGenerator.Random(TwoDomainFunction, chiSquare, 10); Console.WriteLine(@" 3. Get 10 random samples of f(x, y) = (x * y) / 2 using ChiSquare(10) distribution"); for (var i = 0; i < result.Length; i++) { diff --git a/src/Examples/SpecialFunctions/ErrorFunction.cs b/src/Examples/SpecialFunctions/ErrorFunction.cs index ae6537ce..503de8a6 100644 --- a/src/Examples/SpecialFunctions/ErrorFunction.cs +++ b/src/Examples/SpecialFunctions/ErrorFunction.cs @@ -27,7 +27,7 @@ namespace Examples.SpecialFunctions { using System; using MathNet.Numerics; - using MathNet.Numerics.Sampling; + using MathNet.Numerics.Signals; /// /// Special Functions: error functions @@ -69,7 +69,7 @@ namespace Examples.SpecialFunctions // 2. Sample 10 values of the error function in [-1.0; 1.0] Console.WriteLine(@"2. Sample 10 values of the error function in [-1.0; 1.0]"); - var data = Sample.EquidistantInterval(SpecialFunctions.Erf, -1.0, 1.0, 10); + var data = SignalGenerator.EquidistantInterval(SpecialFunctions.Erf, -1.0, 1.0, 10); for (var i = 0; i < data.Length; i++) { Console.Write(data[i].ToString("N") + @" "); @@ -85,7 +85,7 @@ namespace Examples.SpecialFunctions // 4. Sample 10 values of the complementary error function in [-1.0; 1.0] Console.WriteLine(@"4. Sample 10 values of the complementary error function in [-1.0; 1.0]"); - data = Sample.EquidistantInterval(SpecialFunctions.Erfc, -1.0, 1.0, 10); + data = SignalGenerator.EquidistantInterval(SpecialFunctions.Erfc, -1.0, 1.0, 10); for (var i = 0; i < data.Length; i++) { Console.Write(data[i].ToString("N") + @" "); @@ -101,7 +101,7 @@ namespace Examples.SpecialFunctions // 6. Sample 10 values of the inverse error function in [-1.0; 1.0] Console.WriteLine(@"6. Sample 10 values of the inverse error function in [-1.0; 1.0]"); - data = Sample.EquidistantInterval(SpecialFunctions.ErfInv, -1.0, 1.0, 10); + data = SignalGenerator.EquidistantInterval(SpecialFunctions.ErfInv, -1.0, 1.0, 10); for (var i = 0; i < data.Length; i++) { Console.Write(data[i].ToString("N") + @" "); @@ -117,7 +117,7 @@ namespace Examples.SpecialFunctions // 8. Sample 10 values of the complementary inverse error function in [-1.0; 1.0] Console.WriteLine(@"8. Sample 10 values of the complementary inverse error function in [-1.0; 1.0]"); - data = Sample.EquidistantInterval(SpecialFunctions.ErfcInv, -1.0, 1.0, 10); + data = SignalGenerator.EquidistantInterval(SpecialFunctions.ErfcInv, -1.0, 1.0, 10); for (var i = 0; i < data.Length; i++) { Console.Write(data[i].ToString("N") + @" "); diff --git a/src/Examples/Statistics.cs b/src/Examples/Statistics.cs index 40a10ea6..56c07968 100644 --- a/src/Examples/Statistics.cs +++ b/src/Examples/Statistics.cs @@ -28,7 +28,7 @@ namespace Examples { using System; using MathNet.Numerics.Distributions; - using MathNet.Numerics.Sampling; + using MathNet.Numerics.Signals; using MathNet.Numerics.Statistics; /// @@ -124,8 +124,8 @@ namespace Examples Console.WriteLine(); // 6. Correlation coefficient between 1000 samples of f(x) = x * 2 and f(x) = x * x - data = Sample.EquidistantInterval(x => x * 2, 0, 100, 1000); - dataB = Sample.EquidistantInterval(x => x * x, 0, 100, 1000); + data = SignalGenerator.EquidistantInterval(x => x * 2, 0, 100, 1000); + dataB = SignalGenerator.EquidistantInterval(x => x * x, 0, 100, 1000); Console.WriteLine(@"6. Correlation coefficient between 1000 samples of f(x) = x * 2 and f(x) = x * x is {0}", Correlation.Pearson(data, dataB).ToString("N04")); Console.WriteLine(); } diff --git a/src/Numerics/Numerics.csproj b/src/Numerics/Numerics.csproj index a15b2db4..e1153e2b 100644 --- a/src/Numerics/Numerics.csproj +++ b/src/Numerics/Numerics.csproj @@ -451,9 +451,9 @@ - - - + + + diff --git a/src/Numerics/Sampling/Sample.Chebyshev.cs b/src/Numerics/Signals/SignalGenerator.Chebyshev.cs similarity index 97% rename from src/Numerics/Sampling/Sample.Chebyshev.cs rename to src/Numerics/Signals/SignalGenerator.Chebyshev.cs index 62fdb39a..5b2049f0 100644 --- a/src/Numerics/Sampling/Sample.Chebyshev.cs +++ b/src/Numerics/Signals/SignalGenerator.Chebyshev.cs @@ -1,4 +1,4 @@ -// +// // Math.NET Numerics, part of the Math.NET Project // http://numerics.mathdotnet.com // http://github.com/mathnet/mathnet-numerics @@ -28,14 +28,14 @@ // OTHER DEALINGS IN THE SOFTWARE. // -namespace MathNet.Numerics.Sampling +namespace MathNet.Numerics.Signals { using System; /// /// Generic Function Sampling and Quantization Provider /// - public static partial class Sample + public static partial class SignalGenerator { /// /// Samples a function at the roots of the Chebyshev polynomial of the first kind. diff --git a/src/Numerics/Sampling/Sample.Equidistant.cs b/src/Numerics/Signals/SignalGenerator.Equidistant.cs similarity index 98% rename from src/Numerics/Sampling/Sample.Equidistant.cs rename to src/Numerics/Signals/SignalGenerator.Equidistant.cs index 5376f8ce..9fc8ee77 100644 --- a/src/Numerics/Sampling/Sample.Equidistant.cs +++ b/src/Numerics/Signals/SignalGenerator.Equidistant.cs @@ -1,4 +1,4 @@ -// +// // Math.NET Numerics, part of the Math.NET Project // http://numerics.mathdotnet.com // http://github.com/mathnet/mathnet-numerics @@ -28,7 +28,7 @@ // OTHER DEALINGS IN THE SOFTWARE. // -namespace MathNet.Numerics.Sampling +namespace MathNet.Numerics.Signals { using System; using System.Collections.Generic; @@ -36,7 +36,7 @@ namespace MathNet.Numerics.Sampling /// /// Generic Function Sampling and Quantization Provider /// - public static partial class Sample + public static partial class SignalGenerator { /// /// Samples a function equidistant within the provided interval. diff --git a/src/Numerics/Sampling/Sample.Random.cs b/src/Numerics/Signals/SignalGenerator.Random.cs similarity index 97% rename from src/Numerics/Sampling/Sample.Random.cs rename to src/Numerics/Signals/SignalGenerator.Random.cs index 63d78564..ff36c6c4 100644 --- a/src/Numerics/Sampling/Sample.Random.cs +++ b/src/Numerics/Signals/SignalGenerator.Random.cs @@ -1,4 +1,4 @@ -// +// // Math.NET Numerics, part of the Math.NET Project // http://numerics.mathdotnet.com // http://github.com/mathnet/mathnet-numerics @@ -28,7 +28,7 @@ // OTHER DEALINGS IN THE SOFTWARE. // -namespace MathNet.Numerics.Sampling +namespace MathNet.Numerics.Signals { using System; using Distributions; @@ -36,7 +36,7 @@ namespace MathNet.Numerics.Sampling /// /// Generic Function Sampling and Quantization Provider /// - public static partial class Sample + public static partial class SignalGenerator { /// /// Samples a function randomly with the provided distribution. diff --git a/src/Silverlight/Silverlight.csproj b/src/Silverlight/Silverlight.csproj index 27667cba..bc6446c8 100644 --- a/src/Silverlight/Silverlight.csproj +++ b/src/Silverlight/Silverlight.csproj @@ -933,14 +933,14 @@ Random\Xorshift.cs - - Sampling\Sample.Chebyshev.cs + + Signals\SignalGenerator.Chebyshev.cs - - Sampling\Sample.Equidistant.cs + + Signals\SignalGenerator.Equidistant.cs - - Sampling\Sample.Random.cs + + Signals\SignalGenerator.Random.cs Sorting.cs diff --git a/src/UnitTests/IntegralTransformsTests/FourierTest.cs b/src/UnitTests/IntegralTransformsTests/FourierTest.cs index 601e8887..416bd6fc 100644 --- a/src/UnitTests/IntegralTransformsTests/FourierTest.cs +++ b/src/UnitTests/IntegralTransformsTests/FourierTest.cs @@ -32,7 +32,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests using IntegralTransforms; using IntegralTransforms.Algorithms; using NUnit.Framework; - using Sampling; + using Signals; /// /// Fourier test. @@ -51,7 +51,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests [Test] public void NaiveTransformsRealSineCorrectly() { - var samples = Sample.EquidistantPeriodic(w => new Complex(Math.Sin(w), 0), Constants.Pi2, 0, 16); + var samples = SignalGenerator.EquidistantPeriodic(w => new Complex(Math.Sin(w), 0), Constants.Pi2, 0, 16); // real-odd transforms to imaginary odd var dft = new DiscreteFourierTransform(); @@ -87,7 +87,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests [Test] public void Radix2ThrowsWhenNotPowerOfTwo() { - var samples = Sample.Random((u, v) => new Complex(u, v), _uniform, 0x7F); + var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x7F); var dft = new DiscreteFourierTransform(); diff --git a/src/UnitTests/IntegralTransformsTests/HartleyTest.cs b/src/UnitTests/IntegralTransformsTests/HartleyTest.cs index b00d7203..ce336ede 100644 --- a/src/UnitTests/IntegralTransformsTests/HartleyTest.cs +++ b/src/UnitTests/IntegralTransformsTests/HartleyTest.cs @@ -32,7 +32,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests using IntegralTransforms; using IntegralTransforms.Algorithms; using NUnit.Framework; - using Sampling; + using Signals; /// /// Hartley tests. @@ -78,7 +78,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests public void NaiveMatchesDft([Values(HartleyOptions.Default, HartleyOptions.AsymmetricScaling, HartleyOptions.NoScaling)] HartleyOptions hartleyOptions, [Values(FourierOptions.Default, FourierOptions.AsymmetricScaling, FourierOptions.NoScaling)] FourierOptions fourierOptions) { var dht = new DiscreteHartleyTransform(); - var samples = Sample.Random(x => x, _uniform, 0x80); + var samples = SignalGenerator.Random(x => x, _uniform, 0x80); VerifyMatchesDft( samples, diff --git a/src/UnitTests/IntegralTransformsTests/InverseTransformTest.cs b/src/UnitTests/IntegralTransformsTests/InverseTransformTest.cs index 8a5529ab..dfda2531 100644 --- a/src/UnitTests/IntegralTransformsTests/InverseTransformTest.cs +++ b/src/UnitTests/IntegralTransformsTests/InverseTransformTest.cs @@ -32,7 +32,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests using IntegralTransforms; using IntegralTransforms.Algorithms; using NUnit.Framework; - using Sampling; + using Signals; /// /// Inverse Transform test. @@ -58,7 +58,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests Func forward, Func inverse) { - var samples = Sample.Random((u, v) => new Complex(u, v), _uniform, count); + var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, count); var work = new Complex[samples.Length]; samples.CopyTo(work, 0); @@ -84,7 +84,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests Func forward, Func inverse) { - var samples = Sample.Random(x => x, _uniform, count); + var samples = SignalGenerator.Random(x => x, _uniform, count); var work = new double[samples.Length]; samples.CopyTo(work, 0); @@ -183,7 +183,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests [Test] public void FourierDefaultTransformIsReversible() { - var samples = Sample.Random((u, v) => new Complex(u, v), _uniform, 0x7FFF); + var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x7FFF); var work = new Complex[samples.Length]; samples.CopyTo(work, 0); diff --git a/src/UnitTests/IntegralTransformsTests/MatchingNaiveTransformTest.cs b/src/UnitTests/IntegralTransformsTests/MatchingNaiveTransformTest.cs index 890d30a5..4f475bc9 100644 --- a/src/UnitTests/IntegralTransformsTests/MatchingNaiveTransformTest.cs +++ b/src/UnitTests/IntegralTransformsTests/MatchingNaiveTransformTest.cs @@ -32,7 +32,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests using IntegralTransforms; using IntegralTransforms.Algorithms; using NUnit.Framework; - using Sampling; + using Signals; /// /// Matching Naive transform tests. @@ -75,7 +75,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests public void FourierRadix2MatchesNaiveOnRealSine([Values(FourierOptions.Default, FourierOptions.Matlab, FourierOptions.NumericalRecipes)] FourierOptions options) { var dft = new DiscreteFourierTransform(); - var samples = Sample.EquidistantPeriodic(w => new Complex(Math.Sin(w), 0), Constants.Pi2, 0, 16); + var samples = SignalGenerator.EquidistantPeriodic(w => new Complex(Math.Sin(w), 0), Constants.Pi2, 0, 16); VerifyMatchesNaiveComplex( samples, @@ -98,7 +98,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests public void FourierRadix2MatchesNaiveOnRandom([Values(FourierOptions.Default, FourierOptions.Matlab, FourierOptions.NumericalRecipes)] FourierOptions options) { var dft = new DiscreteFourierTransform(); - var samples = Sample.Random((u, v) => new Complex(u, v), _uniform, 0x80); + var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x80); VerifyMatchesNaiveComplex( samples, @@ -121,7 +121,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests public void FourierBluesteinMatchesNaiveOnRealSineNonPowerOfTwo([Values(FourierOptions.Default, FourierOptions.Matlab, FourierOptions.NumericalRecipes)] FourierOptions options) { var dft = new DiscreteFourierTransform(); - var samples = Sample.EquidistantPeriodic(w => new Complex(Math.Sin(w), 0), Constants.Pi2, 0, 14); + var samples = SignalGenerator.EquidistantPeriodic(w => new Complex(Math.Sin(w), 0), Constants.Pi2, 0, 14); VerifyMatchesNaiveComplex( samples, @@ -144,7 +144,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests public void FourierBluesteinMatchesNaiveOnRandomPowerOfTwo([Values(FourierOptions.Default, FourierOptions.Matlab, FourierOptions.NumericalRecipes)] FourierOptions options) { var dft = new DiscreteFourierTransform(); - var samples = Sample.Random((u, v) => new Complex(u, v), _uniform, 0x80); + var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x80); VerifyMatchesNaiveComplex( samples, @@ -167,7 +167,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests public void FourierBluesteinMatchesNaiveOnRandomNonPowerOfTwo([Values(FourierOptions.Default, FourierOptions.Matlab, FourierOptions.NumericalRecipes)] FourierOptions options) { var dft = new DiscreteFourierTransform(); - var samples = Sample.Random((u, v) => new Complex(u, v), _uniform, 0x7F); + var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, 0x7F); VerifyMatchesNaiveComplex( samples, diff --git a/src/UnitTests/IntegralTransformsTests/ParsevalTheoremTest.cs b/src/UnitTests/IntegralTransformsTests/ParsevalTheoremTest.cs index fa504124..94a249c3 100644 --- a/src/UnitTests/IntegralTransformsTests/ParsevalTheoremTest.cs +++ b/src/UnitTests/IntegralTransformsTests/ParsevalTheoremTest.cs @@ -32,7 +32,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests using IntegralTransforms; using IntegralTransforms.Algorithms; using NUnit.Framework; - using Sampling; + using Signals; using Statistics; /// @@ -53,7 +53,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests [Test] public void FourierDefaultTransformSatisfiesParsevalsTheorem([Values(0x1000, 0x7FF)] int count) { - var samples = Sample.Random((u, v) => new Complex(u, v), _uniform, count); + var samples = SignalGenerator.Random((u, v) => new Complex(u, v), _uniform, count); var timeSpaceEnergy = (from s in samples select s.MagnitudeSquared()).Mean(); @@ -75,7 +75,7 @@ namespace MathNet.Numerics.UnitTests.IntegralTransformsTests [Test] public void HartleyDefaultNaiveSatisfiesParsevalsTheorem([Values(0x40, 0x1F)] int count) { - var samples = Sample.Random(x => x, _uniform, count); + var samples = SignalGenerator.Random(x => x, _uniform, count); var timeSpaceEnergy = (from s in samples select s * s).Mean();