fix: add [NotInParallel] to random tests to prevent race conditions

Random tests using np.random.seed() share global RNG state. When run in
parallel, multiple tests can interfere with each other causing:
- IndexOutOfRangeException in MT19937 (race on _pos/_key access)
- Non-reproducible test results

Added [NotInParallel] attribute to 27 random test classes to ensure
sequential execution of tests sharing the global RNG.

Author: Nucs

test/NumSharp.UnitTest/OpenBugs.Random.cs

@@ -20,6 +20,7 @@ namespace NumSharp.UnitTest
     ///     </code>
     /// </summary>
     [OpenBugs]
+    [NotInParallel]
     public class OpenBugsRandom : TestClass
     {
         // ===== CRITICAL: RNG Algorithm Mismatch =====

test/NumSharp.UnitTest/RandomSampling/np.random.dirichlet.Test.cs

@@ -6,6 +6,7 @@ namespace NumSharp.UnitTest.RandomSampling
     /// <summary>
     /// Tests for np.random.dirichlet (Dirichlet distribution)
     /// </summary>
+    [NotInParallel]
     public class NpRandomDirichletTests : TestClass
     {
         [Test]

test/NumSharp.UnitTest/RandomSampling/np.random.f.Test.cs

@@ -4,6 +4,7 @@
 
 namespace NumSharp.UnitTest.RandomSampling
 {
+    [NotInParallel]
     public class NpRandomFTest : TestClass
     {
         [Test]

test/NumSharp.UnitTest/RandomSampling/np.random.gumbel.Test.cs

@@ -6,6 +6,7 @@ namespace NumSharp.UnitTest.RandomSampling
     /// <summary>
     /// Tests for np.random.gumbel (Gumbel/extreme value type I distribution)
     /// </summary>
+    [NotInParallel]
     public class NpRandomGumbelTests : TestClass
     {
         // Euler-Mascheroni constant

test/NumSharp.UnitTest/RandomSampling/np.random.hypergeometric.Test.cs

@@ -9,7 +9,8 @@ namespace NumSharp.UnitTest.RandomSampling;
 /// Samples from hypergeometric distribution without replacement.
 /// Mean = nsample * ngood / (ngood + nbad)
 /// </summary>
-public class RandomHypergeometricTests : TestClass
+[NotInParallel]
+    public class RandomHypergeometricTests : TestClass
 {
     [Test]
     public void Hypergeometric_ScalarCall_ReturnsLong()

test/NumSharp.UnitTest/RandomSampling/np.random.laplace.Test.cs

@@ -6,6 +6,7 @@ namespace NumSharp.UnitTest.RandomSampling
     /// <summary>
     /// Tests for np.random.laplace (Laplace/double exponential distribution)
     /// </summary>
+    [NotInParallel]
     public class NpRandomLaplaceTests : TestClass
     {
         [Test]

test/NumSharp.UnitTest/RandomSampling/np.random.logistic.Test.cs

@@ -8,7 +8,8 @@ namespace NumSharp.UnitTest.RandomSampling;
 /// Tests for np.random.logistic following NumPy 2.4.2 behavior.
 /// Mean = loc, Variance = scale^2 * pi^2 / 3
 /// </summary>
-public class RandomLogisticTests : TestClass
+[NotInParallel]
+    public class RandomLogisticTests : TestClass
 {
     [Test]
     public void Logistic_DefaultParameters_ReturnsScalar()

test/NumSharp.UnitTest/RandomSampling/np.random.logseries.Test.cs

@@ -11,6 +11,7 @@ namespace NumSharp.UnitTest.RandomSampling
     /// Tests for np.random.logseries (logarithmic series distribution).
     /// Based on NumPy 2.4.2 behavior.
     /// </summary>
+    [NotInParallel]
     public class np_random_logseries_Tests
     {
         #region Basic Functionality

test/NumSharp.UnitTest/RandomSampling/np.random.multinomial.Test.cs

@@ -5,6 +5,7 @@
 
 namespace NumSharp.UnitTest.RandomSampling
 {
+    [NotInParallel]
     public class MultinomialTests
     {
         private static readonly double[] DicePvals = { 1.0 / 6, 1.0 / 6, 1.0 / 6, 1.0 / 6, 1.0 / 6, 1.0 / 6 };

test/NumSharp.UnitTest/RandomSampling/np.random.multivariate_normal.Test.cs

@@ -7,6 +7,7 @@ namespace NumSharp.UnitTest.RandomSampling
     /// Tests for np.random.multivariate_normal
     /// Reference: https://numpy.org/doc/stable/reference/random/generated/numpy.random.multivariate_normal.html
     /// </summary>
+    [NotInParallel]
     public class NpRandomMultivariateNormalTests : TestClass
     {
         [Test]