Cleanup: remove obsolete code that has been scheduled for removal in v4 (breaking)

src/Numerics/Control.cs

@@ -103,24 +103,6 @@ namespace MathNet.Numerics
             FourierTransformControl.UseNativeMKL();
         }
 
-        /// <summary>
-        /// Use the Intel MKL native provider for linear algebra, with the specified configuration parameters.
-        /// Throws if it is not available or failed to initialize, in which case the previous provider is still active.
-        /// </summary>
-        [CLSCompliant(false)]
-        [Obsolete("Will be removed in the next major version. Use the enums in the Common namespace instead.")]
-        public static void UseNativeMKL(
-            Providers.LinearAlgebra.Mkl.MklConsistency consistency = Providers.LinearAlgebra.Mkl.MklConsistency.Auto,
-            Providers.LinearAlgebra.Mkl.MklPrecision precision = Providers.LinearAlgebra.Mkl.MklPrecision.Double,
-            Providers.LinearAlgebra.Mkl.MklAccuracy accuracy = Providers.LinearAlgebra.Mkl.MklAccuracy.High)
-        {
-            LinearAlgebraControl.UseNativeMKL(
-                (Providers.Common.Mkl.MklConsistency)consistency,
-                (Providers.Common.Mkl.MklPrecision)precision,
-                (Providers.Common.Mkl.MklAccuracy)accuracy);
-            FourierTransformControl.UseNativeMKL();
-        }
-
         /// <summary>
         /// Use the Intel MKL native provider for linear algebra, with the specified configuration parameters.
         /// Throws if it is not available or failed to initialize, in which case the previous provider is still active.

src/Numerics/Distributions/Erlang.cs

@@ -125,12 +125,6 @@ namespace MathNet.Numerics.Distributions
             return shape >= 0 && rate >= 0.0;
         }
 
-        [Obsolete("Use the variant that expects an int shape, or use Gamma instead. Will be dropped in v4.")]
-        public static bool IsValidParameterSet(double shape, double rate)
-        {
-            return IsValidParameterSet((int)shape, rate);
-        }
-
         /// <summary>
         /// Gets the shape (k) of the Erlang distribution. Range: k ≥ 0.
         /// </summary>
@@ -419,12 +413,6 @@ namespace MathNet.Numerics.Distributions
             return Math.Pow(rate, shape)*Math.Pow(x, shape - 1.0)*Math.Exp(-rate*x)/SpecialFunctions.Gamma(shape);
         }
 
-        [Obsolete("Use the variant that expects an int shape, or use Gamma instead. Will be dropped in v4.")]
-        public static double PDF(double shape, double rate, double x)
-        {
-            return PDF((int)shape, rate, x);
-        }
-
         /// <summary>
         /// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
         /// </summary>
@@ -458,12 +446,6 @@ namespace MathNet.Numerics.Distributions
             return (shape*Math.Log(rate)) + ((shape - 1.0)*Math.Log(x)) - (rate*x) - SpecialFunctions.GammaLn(shape);
         }
 
-        [Obsolete("Use the variant that expects an int shape, or use Gamma instead. Will be dropped in v4.")]
-        public static double PDFLn(double shape, double rate, double x)
-        {
-            return PDFLn((int)shape, rate, x);
-        }
-
         /// <summary>
         /// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
         /// </summary>
@@ -492,12 +474,6 @@ namespace MathNet.Numerics.Distributions
             return SpecialFunctions.GammaLowerRegularized(shape, x*rate);
         }
 
-        [Obsolete("Use the variant that expects an int shape, or use Gamma instead. Will be dropped in v4.")]
-        public static double CDF(double shape, double rate, double x)
-        {
-            return CDF((int)shape, rate, x);
-        }
-
         /// <summary>
         /// Generates a sample from the distribution.
         /// </summary>
@@ -510,12 +486,6 @@ namespace MathNet.Numerics.Distributions
             return Gamma.Sample(rnd, shape, rate);
         }
 
-        [Obsolete("Use the variant that expects an int shape, or use Gamma instead. Will be dropped in v4.")]
-        public static double Sample(System.Random rnd, double shape, double rate)
-        {
-            return Sample(rnd, (int)shape, rate);
-        }
-
         /// <summary>
         /// Generates a sequence of samples from the distribution.
         /// </summary>
@@ -528,12 +498,6 @@ namespace MathNet.Numerics.Distributions
             return Gamma.Samples(rnd, shape, rate);
         }
 
-        [Obsolete("Use the variant that expects an int shape, or use Gamma instead. Will be dropped in v4.")]
-        public static IEnumerable<double> Samples(System.Random rnd, double shape, double rate)
-        {
-            return Samples(rnd, (int)shape, rate);
-        }
-
         /// <summary>
         /// Fills an array with samples generated from the distribution.
         /// </summary>
@@ -558,12 +522,6 @@ namespace MathNet.Numerics.Distributions
             return Gamma.Sample(shape, rate);
         }
 
-        [Obsolete("Use the variant that expects an int shape, or use Gamma instead. Will be dropped in v4.")]
-        public static double Sample(double shape, double rate)
-        {
-            return Sample((int)shape, rate);
-        }
-
         /// <summary>
         /// Generates a sequence of samples from the distribution.
         /// </summary>
@@ -575,12 +533,6 @@ namespace MathNet.Numerics.Distributions
             return Gamma.Samples(shape, rate);
         }
 
-        [Obsolete("Use the variant that expects an int shape, or use Gamma instead. Will be dropped in v4.")]
-        public static IEnumerable<double> Samples(double shape, double rate)
-        {
-            return Samples((int)shape, rate);
-        }
-
         /// <summary>
         /// Fills an array with samples generated from the distribution.
         /// </summary>

src/Numerics/Financial/AbsoluteReturnMeasures.cs

@@ -36,12 +36,6 @@ namespace MathNet.Numerics.Financial
 {
     public static class AbsoluteReturnMeasures
     {
-        [Obsolete("Use CompoundReturn instead, will be removed in v4.0")]
-        public static double CompoundMonthlyReturn(this IEnumerable<double> data)
-        {
-            return CompoundReturn(data);
-        }
-
         /// <summary>
         /// Compound Monthly Return or Geometric Return or Annualized Return
         /// </summary>

src/Numerics/Generate.cs

@@ -970,58 +970,6 @@ namespace MathNet.Numerics
             return Distributions.Normal.Samples(SystemRandomSource.Default, mean, standardDeviation);
         }
 
-        /// <summary>
-        /// Create samples with independent amplitudes of normal distribution and a flat spectral density.
-        /// </summary>
-        [Obsolete("Use Normal instead. Will be removed in v4.")]
-        public static double[] Gaussian(int length, double mean, double standardDeviation)
-        {
-            return Normal(length, mean, standardDeviation);
-        }
-
-        /// <summary>
-        /// Create an infinite sample sequence with independent amplitudes of normal distribution and a flat spectral density.
-        /// </summary>
-        [Obsolete("Use NormalSequence instead. Will be removed in v4.")]
-        public static IEnumerable<double> GaussianSequence(double mean, double standardDeviation)
-        {
-            return NormalSequence(mean, standardDeviation);
-        }
-
-        /// <summary>
-        /// Create skew alpha stable samples.
-        /// </summary>
-        /// <param name="length">The number of samples to generate.</param>
-        /// <param name="alpha">Stability alpha-parameter of the stable distribution</param>
-        /// <param name="beta">Skewness beta-parameter of the stable distribution</param>
-        /// <param name="scale">Scale c-parameter of the stable distribution</param>
-        /// <param name="location">Location mu-parameter of the stable distribution</param>
-        [Obsolete("Will be removed in v4.")]
-        public static double[] Stable(int length, double alpha, double beta, double scale, double location)
-        {
-            if (length < 0)
-            {
-                throw new ArgumentOutOfRangeException("length");
-            }
-
-            var samples = new double[length];
-            Distributions.Stable.Samples(SystemRandomSource.Default, samples, alpha, beta, scale, location);
-            return samples;
-        }
-
-        /// <summary>
-        /// Create skew alpha stable samples.
-        /// </summary>
-        /// <param name="alpha">Stability alpha-parameter of the stable distribution</param>
-        /// <param name="beta">Skewness beta-parameter of the stable distribution</param>
-        /// <param name="scale">Scale c-parameter of the stable distribution</param>
-        /// <param name="location">Location mu-parameter of the stable distribution</param>
-        [Obsolete("Will be removed in v4.")]
-        public static IEnumerable<double> StableSequence(double alpha, double beta, double scale, double location)
-        {
-            return Distributions.Stable.Samples(SystemRandomSource.Default, alpha, beta, scale, location);
-        }
-
         /// <summary>
         /// Create random samples.
         /// </summary>
@@ -1147,7 +1095,5 @@ namespace MathNet.Numerics
         {
             return distribution.Samples().Zip(distribution.Samples(), map);
         }
-
-
     }
 }

src/Numerics/Interpolate.cs

@@ -180,12 +180,6 @@ namespace MathNet.Numerics
             return Interpolation.LogLinear.Interpolate(points, values);
         }
 
-        [Obsolete("Use Linear instead. Will be removed in the next major version.")]
-        public static IInterpolation LinearSpline(IEnumerable<double> points, IEnumerable<double> values)
-        {
-            return Interpolation.LinearSpline.Interpolate(points, values);
-        }
-
         /// <summary>
         /// Create an piecewise natural cubic spline interpolation based on arbitrary points,
         /// with zero secondary derivatives at the boundaries.

src/Numerics/LinearAlgebra/Matrix.cs

@@ -1282,15 +1282,6 @@ namespace MathNet.Numerics.LinearAlgebra
         /// </summary>
         public abstract bool IsHermitian();
 
-        /// <summary>
-        /// Evaluates whether this matrix is conjugate symmetric.
-        /// </summary>
-        [Obsolete("Use IsHermitian instead. Will be removed in v4.")]
-        public bool IsConjugateSymmetric()
-        {
-            return IsHermitian();
-        }
-
         /// <summary>
         /// Returns this matrix as a multidimensional array.
         /// The returned array will be independent from this matrix.
@@ -1320,12 +1311,6 @@ namespace MathNet.Numerics.LinearAlgebra
             return Storage.ToColumnMajorArray();
         }
 
-        [Obsolete("Use ToColumnMajorArray instead. Will be removed in v4.")]
-        public T[] ToColumnWiseArray()
-        {
-            return ToColumnMajorArray();
-        }
-
         /// <summary>
         /// Returns the matrix's elements as an array with the data laid row by row (row major).
         /// The returned array will be independent from this matrix.
@@ -1344,13 +1329,6 @@ namespace MathNet.Numerics.LinearAlgebra
             return Storage.ToRowMajorArray();
         }
 
-
-        [Obsolete("Use ToRowMajorArray instead. Will be removed in v4.")]
-        public T[] ToRowWiseArray()
-        {
-            return ToRowMajorArray();
-        }
-
         /// <summary>
         /// Returns this matrix as array of row arrays.
         /// The returned arrays will be independent from this matrix.
@@ -1499,32 +1477,6 @@ namespace MathNet.Numerics.LinearAlgebra
             }
         }
 
-        /// <summary>
-        /// Returns an IEnumerable that can be used to iterate through all non-zero values of the matrix.
-        /// </summary>
-        /// <remarks>
-        /// The enumerator will skip all elements with a zero value.
-        /// </remarks>
-        [Obsolete("Use Enumerate(Zeros.AllowSkip) instead. Will be removed in v4.")]
-        public IEnumerable<T> EnumerateNonZero()
-        {
-            return Storage.EnumerateNonZero();
-        }
-
-        /// <summary>
-        /// Returns an IEnumerable that can be used to iterate through all non-zero values of the matrix and their index.
-        /// </summary>
-        /// <remarks>
-        /// The enumerator returns a Tuple with the first two values being the row and column index
-        /// and the third value being the value of the element at that index.
-        /// The enumerator will skip all elements with a zero value.
-        /// </remarks>
-        [Obsolete("Use EnumerateIndexed(Zeros.AllowSkip) instead. Will be removed in v4.")]
-        public IEnumerable<Tuple<int, int, T>> EnumerateNonZeroIndexed()
-        {
-            return Storage.EnumerateNonZeroIndexed();
-        }
-
         /// <summary>
         /// Returns an IEnumerable that can be used to iterate through all columns of the matrix.
         /// </summary>

src/Numerics/LinearAlgebra/Options.cs

@@ -77,9 +77,6 @@ namespace MathNet.Numerics.LinearAlgebra
         /// </summary>
         Hermitian = 2,
 
-        [Obsolete("Use Hermitian instead. Will be removed in v4.")]
-        ConjugateSymmetric = 2,
-
         /// <summary>
         /// A matrix is not symmetric
         /// </summary>

src/Numerics/LinearAlgebra/Vector.cs

@@ -343,32 +343,6 @@ namespace MathNet.Numerics.LinearAlgebra
             }
         }
 
-        /// <summary>
-        /// Returns an IEnumerable that can be used to iterate through all non-zero values of the vector.
-        /// </summary>
-        /// <remarks>
-        /// The enumerator will skip all elements with a zero value.
-        /// </remarks>
-        [Obsolete("Use Enumerate(Zeros.AllowSkip) instead. Will be removed in v4.")]
-        public IEnumerable<T> EnumerateNonZero()
-        {
-            return Storage.EnumerateNonZero();
-        }
-
-        /// <summary>
-        /// Returns an IEnumerable that can be used to iterate through all non-zero values of the vector and their index.
-        /// </summary>
-        /// <remarks>
-        /// The enumerator returns a Tuple with the first value being the element index
-        /// and the second value being the value of the element at that index.
-        /// The enumerator will skip all elements with a zero value.
-        /// </remarks>
-        [Obsolete("Use EnumerateIndexed(Zeros.AllowSkip) instead. Will be removed in v4.")]
-        public IEnumerable<Tuple<int, T>> EnumerateNonZeroIndexed()
-        {
-            return Storage.EnumerateNonZeroIndexed();
-        }
-
         /// <summary>
         /// Applies a function to each value of this vector and replaces the value with its result.
         /// If forceMapZero is not set to true, zero values may or may not be skipped depending

src/Numerics/Providers/LinearAlgebra/Mkl/MklLinearAlgebraProvider.cs

@@ -37,7 +37,7 @@ namespace MathNet.Numerics.Providers.LinearAlgebra.Mkl
     /// <summary>
     /// Error codes return from the MKL provider.
     /// </summary>
-    public enum MklError : int
+    internal enum MklError : int
     {
         /// <summary>
         /// Unable to allocate memory.
@@ -45,50 +45,14 @@ namespace MathNet.Numerics.Providers.LinearAlgebra.Mkl
         MemoryAllocation = -999999
     }
 
-    /// <summary>
-    /// Consistency vs. performance trade-off between runs on different machines.
-    /// </summary>
-    [Obsolete("Will be removed in the next major version. Use the enums in the Common namespace instead.")]
-    public enum MklConsistency : int
-    {
-        /// <summary>Consistent on the same CPU only (maximum performance)</summary>
-        Auto = 2,
-        /// <summary>Consistent on Intel and compatible CPUs with SSE2 support (maximum compatibility)</summary>
-        Compatible = 3,
-        /// <summary>Consistent on Intel CPUs supporting SSE2 or later</summary>
-        SSE2 = 4,
-        /// <summary>Consistent on Intel CPUs supporting SSE4.2 or later</summary>
-        SSE4_2 = 8,
-        /// <summary>Consistent on Intel CPUs supporting AVX or later</summary>
-        AVX = 9,
-        /// <summary>Consistent on Intel CPUs supporting AVX2 or later</summary>
-        AVX2 = 10
-    }
-
-    [CLSCompliant(false)]
-    [Obsolete("Will be removed in the next major version. Use the enums in the Common namespace instead.")]
-    public enum MklAccuracy : uint
-    {
-        Low = 0x1,
-        High = 0x2
-    }
-
-    [CLSCompliant(false)]
-    [Obsolete("Will be removed in the next major version. Use the enums in the Common namespace instead.")]
-    public enum MklPrecision : uint
-    {
-        Single = 0x10,
-        Double = 0x20
-    }
-
     /// <summary>
     /// Intel's Math Kernel Library (MKL) linear algebra provider.
     /// </summary>
     public partial class MklLinearAlgebraProvider : ManagedLinearAlgebraProvider
     {
-        readonly Common.Mkl.MklConsistency _consistency;
+        readonly MklConsistency _consistency;
-        readonly Common.Mkl.MklPrecision _precision;
+        readonly MklPrecision _precision;
-        readonly Common.Mkl.MklAccuracy _accuracy;
+        readonly MklAccuracy _accuracy;
 
         int _linearAlgebraMajor;
         int _linearAlgebraMinor;
@@ -102,28 +66,10 @@ namespace MathNet.Numerics.Providers.LinearAlgebra.Mkl
         /// <param name="precision">VML optimal precision and rounding.</param>
         /// <param name="accuracy">VML accuracy mode.</param>
         [CLSCompliant(false)]
-        [Obsolete("Will be removed in the next major version. Use the enums in the Common namespace instead.")]
         public MklLinearAlgebraProvider(
             MklConsistency consistency = MklConsistency.Auto,
             MklPrecision precision = MklPrecision.Double,
             MklAccuracy accuracy = MklAccuracy.High)
-        {
-            _consistency = (Common.Mkl.MklConsistency)consistency;
-            _precision = (Common.Mkl.MklPrecision)precision;
-            _accuracy = (Common.Mkl.MklAccuracy)accuracy;
-        }
-
-        /// <param name="consistency">
-        /// Sets the desired bit consistency on repeated identical computations on varying CPU architectures,
-        /// as a trade-off with performance.
-        /// </param>
-        /// <param name="precision">VML optimal precision and rounding.</param>
-        /// <param name="accuracy">VML accuracy mode.</param>
-        [CLSCompliant(false)]
-        public MklLinearAlgebraProvider(
-            Common.Mkl.MklConsistency consistency = Common.Mkl.MklConsistency.Auto,
-            Common.Mkl.MklPrecision precision = Common.Mkl.MklPrecision.Double,
-            Common.Mkl.MklAccuracy accuracy = Common.Mkl.MklAccuracy.High)
         {
             _consistency = consistency;
             _precision = precision;
@@ -132,9 +78,9 @@ namespace MathNet.Numerics.Providers.LinearAlgebra.Mkl
 
         public MklLinearAlgebraProvider()
         {
-            _consistency = Common.Mkl.MklConsistency.Auto;
+            _consistency = MklConsistency.Auto;
-            _precision = Common.Mkl.MklPrecision.Double;
+            _precision = MklPrecision.Double;
-            _accuracy = Common.Mkl.MklAccuracy.High;
+            _accuracy = MklAccuracy.High;
         }
 
         /// <summary>