add JsonInclude for Polynomial and DescriptiveStatistics

Author: jetersen

src/Numerics.Tests/PolynomialTests.cs

@@ -444,7 +444,7 @@ public void EvaluateTest(double[] c, double z, double expected)
             }
 
             // static Complex Evaluate(Complex, double[])
-            {                
+            {
                 var actual = Polynomial.Evaluate(zComplex, c);
                 Assert.AreEqual(expectedComplex, actual);
             }
@@ -466,8 +466,21 @@ public void EvaluateTest(double[] c, double z, double expected)
                 var actual = p.Evaluate(zComplex);
                 Assert.AreEqual(expectedComplex, actual);
             }
-                        
+
+        }
+
+#if NET5_0_OR_GREATER
+        [Test]
+        public void JsonDeserializationTest()
+        {
+            var polynomial = new Polynomial(0, 1, 2);
+            var json = System.Text.Json.JsonSerializer.Serialize(polynomial);
+            var deserialize = System.Text.Json.JsonSerializer.Deserialize<Polynomial>(json);
+            Assert.NotNull(deserialize);
+            Assert.AreEqual(polynomial.Coefficients.Length, deserialize.Coefficients.Length);
+            Assert.IsTrue(polynomial.Coefficients.SequenceEqual(deserialize.Coefficients));
         }
+#endif
 
     }
 

src/Numerics.Tests/StatisticsTests/DescriptiveStatisticsTests.cs

@@ -29,6 +29,10 @@
 
 using System;
 using System.Collections.Generic;
+#if NET5_0_OR_GREATER
+using System.Text.Json;
+using System.Text.Json.Serialization;
+#endif
 using NUnit.Framework;
 using MathNet.Numerics.Statistics;
 
@@ -301,5 +305,47 @@ public void ZeroVarianceSequence()
             Assert.That(stats.Skewness, Is.NaN);
             Assert.That(stats.Kurtosis, Is.NaN);
         }
+
+#if NET5_0_OR_GREATER
+        /// <summary>
+        /// <c>IEnumerable</c> Double.
+        /// </summary>
+        /// <param name="dataSet">Dataset name.</param>
+        /// <param name="digits">Digits count.</param>
+        /// <param name="skewness">Skewness value.</param>
+        /// <param name="kurtosis">Kurtosis value.</param>
+        /// <param name="median">Median value.</param>
+        /// <param name="min">Min value.</param>
+        /// <param name="max">Max value.</param>
+        /// <param name="count">Count value.</param>
+        [TestCase("lottery", 12, -0.09333165310779, -1.19256091074856, 522.5, 4, 999, 218)]
+        [TestCase("lew", 12, -0.050606638756334, -1.49604979214447, -162, -579, 300, 200)]
+        [TestCase("mavro", 11, 0.64492948110824, -0.82052379677456, 2.0018, 2.0013, 2.0027, 50)]
+        [TestCase("michelso", 11, -0.0185388637725746, 0.33968459842539, 299.85, 299.62, 300.07, 100)]
+        [TestCase("numacc1", 15, 0, double.NaN, 10000002, 10000001, 10000003, 3)]
+        [TestCase("numacc2", 13, 0, -2.003003003003, 1.2, 1.1, 1.3, 1001)]
+        [TestCase("numacc3", 9, 0, -2.003003003003, 1000000.2, 1000000.1, 1000000.3, 1001)]
+        [TestCase("numacc4", 7, 0, -2.00300300299913, 10000000.2, 10000000.1, 10000000.3, 1001)]
+        [TestCase("meixner", 8, -0.016649617280859657, 0.8171318629552635, -0.002042931016531602, -4.825626912281697, 5.3018298664184913, 10000)]
+        public void JsonDeserializationTest(string dataSet, int digits, double skewness, double kurtosis, double median, double min, double max, int count)
+        {
+            var data = _data[dataSet];
+            var serialize = new DescriptiveStatistics(data.Data, false);
+            var jsonSerializerOptions = new JsonSerializerOptions
+            {
+                NumberHandling = JsonNumberHandling.AllowNamedFloatingPointLiterals,
+            };
+            var json = JsonSerializer.Serialize(serialize, jsonSerializerOptions);
+            var stats = JsonSerializer.Deserialize<DescriptiveStatistics>(json, jsonSerializerOptions);
+            Assert.NotNull(stats);
+            AssertHelpers.AlmostEqualRelative(data.Mean, stats.Mean, 10);
+            AssertHelpers.AlmostEqualRelative(data.StandardDeviation, stats.StandardDeviation, digits);
+            AssertHelpers.AlmostEqualRelative(skewness, stats.Skewness, 8);
+            AssertHelpers.AlmostEqualRelative(kurtosis, stats.Kurtosis, 8);
+            Assert.AreEqual(stats.Minimum, min);
+            Assert.AreEqual(stats.Maximum, max);
+            Assert.AreEqual(stats.Count, count);
+        }
+#endif
     }
 }

src/Numerics/Polynomial.cs

@@ -5,6 +5,9 @@
 using System.Linq;
 using Complex = System.Numerics.Complex;
 using System.Text;
+#if NET5_0_OR_GREATER
+using System.Text.Json.Serialization;
+#endif
 using MathNet.Numerics.LinearAlgebra;
 using MathNet.Numerics.LinearAlgebra.Double;
 using MathNet.Numerics.LinearRegression;
@@ -24,6 +27,9 @@ public class Polynomial : IFormattable, IEquatable<Polynomial>, ICloneable
         /// The coefficients of the polynomial in a
         /// </summary>
         [DataMember(Order = 1)]
+#if NET5_0_OR_GREATER
+        [JsonInclude]
+#endif
         public double[] Coefficients { get; private set; }
 
         /// <summary>

src/Numerics/Statistics/DescriptiveStatistics.cs

@@ -30,6 +30,9 @@
 using System;
 using System.Collections.Generic;
 using System.Runtime.Serialization;
+#if NET5_0_OR_GREATER
+using System.Text.Json.Serialization;
+#endif
 
 namespace MathNet.Numerics.Statistics
 {
@@ -107,32 +110,56 @@ public DescriptiveStatistics(IEnumerable<double?> data, bool increasedAccuracy =
             }
         }
 
+#if NET5_0_OR_GREATER
+        /// <summary>
+        /// Initializes a new instance of the <see cref="DescriptiveStatistics"/> class.
+        /// </summary>
+        /// <remarks>
+        /// Used for Json serialization
+        /// </remarks>
+        public DescriptiveStatistics()
+        {
+        }
+#endif
+
         /// <summary>
         /// Gets the size of the sample.
         /// </summary>
         /// <value>The size of the sample.</value>
         [DataMember(Order = 1)]
+#if NET5_0_OR_GREATER
+        [JsonInclude]
+#endif
         public long Count { get; private set; }
 
         /// <summary>
         /// Gets the sample mean.
         /// </summary>
         /// <value>The sample mean.</value>
         [DataMember(Order = 2)]
+#if NET5_0_OR_GREATER
+        [JsonInclude]
+#endif
         public double Mean { get; private set; }
 
         /// <summary>
         /// Gets the unbiased population variance estimator (on a dataset of size N will use an N-1 normalizer).
         /// </summary>
         /// <value>The sample variance.</value>
         [DataMember(Order = 3)]
+#if NET5_0_OR_GREATER
+        [JsonInclude]
+#endif
         public double Variance { get; private set; }
 
         /// <summary>
         /// Gets the unbiased population standard deviation (on a dataset of size N will use an N-1 normalizer).
         /// </summary>
         /// <value>The sample standard deviation.</value>
         [DataMember(Order = 4)]
+#if NET5_0_OR_GREATER
+        [JsonInclude]
+#endif
         public double StandardDeviation { get; private set; }
 
         /// <summary>
@@ -141,6 +168,9 @@ public DescriptiveStatistics(IEnumerable<double?> data, bool increasedAccuracy =
         /// <value>The sample skewness.</value>
         /// <remarks>Returns zero if <see cref="Count"/> is less than three. </remarks>
         [DataMember(Order = 5)]
+#if NET5_0_OR_GREATER
+        [JsonInclude]
+#endif
         public double Skewness { get; private set; }
 
         /// <summary>
@@ -149,20 +179,29 @@ public DescriptiveStatistics(IEnumerable<double?> data, bool increasedAccuracy =
         /// <value>The sample kurtosis.</value>
         /// <remarks>Returns zero if <see cref="Count"/> is less than four. </remarks>
         [DataMember(Order = 6)]
+#if NET5_0_OR_GREATER
+        [JsonInclude]
+#endif
         public double Kurtosis { get; private set; }
 
         /// <summary>
         /// Gets the maximum sample value.
         /// </summary>
         /// <value>The maximum sample value.</value>
         [DataMember(Order = 7)]
+#if NET5_0_OR_GREATER
+        [JsonInclude]
+#endif
         public double Maximum { get; private set; }
 
         /// <summary>
         /// Gets the minimum sample value.
         /// </summary>
         /// <value>The minimum sample value.</value>
         [DataMember(Order = 8)]
+#if NET5_0_OR_GREATER
+        [JsonInclude]
+#endif
         public double Minimum { get; private set; }
 
         /// <summary>