Release version 2.0.0.

Author: Novacta

.gitignore

@@ -2,7 +2,7 @@
 ## files generated by popular Visual Studio add-ons.
 
 # macOS files
-/.DS_Store
+.DS_Store
 
 # Novacta.Analytics.CodeExamples
 **/Novacta.Analytics.CodeExamples/*.txt

README.md

@@ -1,175 +1,192 @@
 # Novacta.Analytics
 
 The **Novacta.Analytics** library
-provides functionality for data analysis. 
+provides functionality for data analysis.
 
-The project targets all platforms implementing
-the [.NET Standard](https://github.com/dotnet/standard), 
-version 2.0, and supports the
-[x86 architecture](https://en.wikipedia.org/wiki/X86):
-64 bit is supported on all platforms, 32 bit on Windows only.
+The project targets
+[.NET 6](https://github.com/dotnet/core/blob/main/release-notes/6.0/README.md),
+and supports the
+[x86-64 architecture](https://en.wikipedia.org/wiki/X86-64)
+on Windows, Linux, and macOS platforms.
 
 Installation can be performed via [NuGet](https://www.nuget.org/packages/Novacta.Analytics).
 
-# Features
+## Features
 
-## Matrix algebra operations
+### Matrix algebra operations
 
-* [Read only](http://novacta.github.io/analytics/html/T_Novacta_Analytics_ReadOnlyDoubleMatrix.htm)
+* Matrices of 
+  [Double](https://docs.microsoft.com/dotnet/api/system.double) 
   or
-  [writable](http://novacta.github.io/analytics/html/T_Novacta_Analytics_DoubleMatrix.htm)
-  matrices, supporting
-  [Sparse](http://novacta.github.io/analytics/html/M_Novacta_Analytics_DoubleMatrix_Sparse.htm)
-  and
-  [Dense](http://novacta.github.io/analytics/html/M_Novacta_Analytics_DoubleMatrix_Dense_1.htm)
-  storage schemes.
-* [Overloaded operators](http://novacta.github.io/analytics/html/Operators_T_Novacta_Analytics_DoubleMatrix.htm)
+  [Complex](https://docs.microsoft.com/dotnet/api/system.numerics.complex)
+  numbers, represented through types
+  [DoubleMatrix](https://novacta.github.io/analytics/html/1DED9EB1.htm) and
+  [ComplexMatrix](https://novacta.github.io/analytics/html/AFDA21E4.htm),
+  respectively.
+* Support for both dense
+  and 
+  [Compressed sparse row](https://en.wikipedia.org/wiki/Sparse_matrix#Compressed_sparse_row_(CSR,_CRS_or_Yale_format))
+  storage 
+  [schemes](https://novacta.github.io/analytics/html/6274B7FA.htm).
+* Matrices exposed as read-only objects, see types
+  [ReadOnlyDoubleMatrix](https://novacta.github.io/analytics/html/9FFC4131.htm)
+  and 
+  [ReadOnlyComplexMatrix](https://novacta.github.io/analytics/html/E2E3D527.htm).
+* Overloaded operators
   supporting sums, subtractions, multiplications, and divisions whose operands 
-  are matrices or scalars.
+  are (writable or read-only) matrices or scalars, eventually mixing Complex or 
+  Double based operands.
 * Matrix slicing where rows or columns are referred to
   using integers, strings, or
-  [collections of indexes](http://novacta.github.io/analytics/html/T_Novacta_Analytics_IndexCollection.htm),
-  possibly avoiding dense allocations via specialized
-  [indexers](http://novacta.github.io/analytics/html/P_Novacta_Analytics_DoubleMatrix_Item_1.htm).
-* [Out-](http://novacta.github.io/analytics/html/M_Novacta_Analytics_DoubleMatrix_Apply.htm)
+  [collections of indexes](https://novacta.github.io/analytics/html/9B3BDFD7.htm).
+* Out- or In- place application
+  of operations to matrix entries (for examples, see methods
+  [Apply](https://novacta.github.io/analytics/html/4A64A4C1.htm)
   or
-  [In-](http://novacta.github.io/analytics/html/M_Novacta_Analytics_DoubleMatrix_InPlaceApply.htm)
-  place application of operations to matrix entries.
+  [InPlaceApply](https://novacta.github.io/analytics/html/7887E503.htm)).
+* Matrix
+  [Singular Value Decompositions](https://novacta.github.io/analytics/html/D334409A.htm)
+  and
+  [Spectral Decompositions](https://novacta.github.io/analytics/html/17359C6B.htm)
+  of symmetric/Hermitian matrices.
+
 
-## Matrix data presentation and interaction in application UI
+### Matrix data presentation and interaction in application UI
 
 * Matrices can be exploited as
   [binding sources](https://docs.microsoft.com/en-us/dotnet/desktop-wpf/data/data-binding-overview#basic-data-binding-concepts)
   by interpreting them as
-  [collections](http://novacta.github.io/analytics/html/T_Novacta_Analytics_DoubleMatrixRowCollection.htm)
+  [collections](https://novacta.github.io/analytics/html/CF178F79.htm)
   of
-  [rows](http://novacta.github.io/analytics/html/T_Novacta_Analytics_DoubleMatrixRow.htm).
+  [rows](https://novacta.github.io/analytics/html/8C5BBFE.htm).
   See the
   [BindingToRowCollection](https://github.com/novacta/analytics/blob/master/samples/BindingToRowCollection)
   sample for further details.
 
-## Summary statistics
+### Summary statistics
 
-* [Descriptive statistical functions](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Stat.htm),
+* [Descriptive statistical functions](https://novacta.github.io/analytics/html/ADDA5F5.htm),
   operating on rows, columns, or all matrix entries.
 
-## Multivariate data analysis
+### Multivariate data analysis
 
 * Represent multi-dimensional, weighted points by taking
   their coordinates with respect to whatever
-  [basis](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_Basis.htm)
+  [basis](https://novacta.github.io/analytics/html/59623234.htm)
   using
-  [cloud](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_Cloud.htm)
+  [cloud](https://novacta.github.io/analytics/html/781E2F6F.htm)
   instances.
 * Project clouds along their
-  [principal](http://novacta.github.io/analytics/html/T_Novacta_Analytics_PrincipalProjections.htm)
+  [principal](https://novacta.github.io/analytics/html/3ADFD77D.htm)
   directions by identifying new, uncorrelated variables
   whose variances enhance our comprehension of the overall cloud
   variability, possibly approximating the cloud in a lower dimensional space.
 * Compute the
-  [principal components](http://novacta.github.io/analytics/html/T_Novacta_Analytics_PrincipalComponents.htm)
+  [principal components](https://novacta.github.io/analytics/html/3ADC7B56.htm)
   of a matrix, an application of principal projections
   to the classical context in which matrix rows are
   interpreted as point coordinates taken with respect to
   bases depending on specific coefficients assigned to the
   observed variables.
-* [Correspondence](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Correspondence.htm)
+* [Correspondence](https://novacta.github.io/analytics/html/8945AB1F.htm)
   analysis of a contingency table.
 * Cluster Analysis
-  * [Discover](http://novacta.github.io/analytics/html/M_Novacta_Analytics_Clusters_Discover.htm)
+  * [Discover](https://novacta.github.io/analytics/html/32B0ECC0.htm)
     optimal clusters in a data set by minimizing the sum of
     intra-cluster squared deviations.
-  * [Explain](http://novacta.github.io/analytics/html/M_Novacta_Analytics_Clusters_Explain.htm)
+  * [Explain](https://novacta.github.io/analytics/html/76A18A84.htm)
     existing clusters selecting features by minimizing the
-    [Davies-Bouldin index](http://novacta.github.io/analytics/html/M_Novacta_Analytics_IndexPartition_DaviesBouldinIndex.htm).
+    [Davies-Bouldin index](https://novacta.github.io/analytics/html/40CF1518.htm).
 
-## Categorical data sets
+### Categorical data sets
 
 * Create
-  [categorical data sets](http://novacta.github.io/analytics/html/T_Novacta_Analytics_CategoricalDataSet.htm)
+  [categorical data sets](https://novacta.github.io/analytics/html/B39F799B.htm)
   by
-  [encoding](http://novacta.github.io/analytics/html/M_Novacta_Analytics_CategoricalDataSet_Encode_1.htm)
+  [encoding](https://novacta.github.io/analytics/html/CBC7240B.htm)
   categorical or numerical data from a stream.
 * Categorize continuous data
-  [by entropy minimization](http://novacta.github.io/analytics/html/M_Novacta_Analytics_CategoricalDataSet_CategorizeByEntropyMinimization.htm).
-* [Multiple Correspondence](http://novacta.github.io/analytics/html/T_Novacta_Analytics_MultipleCorrespondence.htm)
+  [by entropy minimization](https://novacta.github.io/analytics/html/5D736549.htm).
+* [Multiple Correspondence](https://novacta.github.io/analytics/html/C792CEE0.htm)
   analysis of a categorical data set.
 * Classify items from a feature space via
-  [ensembles](http://novacta.github.io/analytics/html/T_Novacta_Analytics_CategoricalEntailmentEnsembleClassifier.htm)
+  [ensembles](https://novacta.github.io/analytics/html/401D2F27.htm)
   of
-  [categorical entailments](http://novacta.github.io/analytics/html/T_Novacta_Analytics_CategoricalEntailment.htm).
+  [categorical entailments](https://novacta.github.io/analytics/html/39D67B46.htm).
 
-## Randomization
+### Randomization
 
 * Use Mersenne Twister
-  [random number generators](http://novacta.github.io/analytics/html/T_Novacta_Analytics_RandomNumberGenerator.htm)
+  [random number generators](https://novacta.github.io/analytics/html/E076C0AC.htm)
   to draw samples from basic statistical distributions.
 * Represent additional
-  [probability distributions](http://novacta.github.io/analytics/html/T_Novacta_Analytics_ProbabilityDistribution.htm)
+  [probability distributions](https://novacta.github.io/analytics/html/1984D730.htm)
   to compute and sample from specific cumulative or probability density
   functions.
 * Select
-  [random samples](http://novacta.github.io/analytics/html/T_Novacta_Analytics_RandomSampling.htm)
+  [random samples](https://novacta.github.io/analytics/html/FCF45A04.htm)
   from a finite population, with
-  [equal](http://novacta.github.io/analytics/html/T_Novacta_Analytics_SimpleRandomSampling.htm)
+  [equal](https://novacta.github.io/analytics/html/37F088DE.htm)
   or
-  [unequal](http://novacta.github.io/analytics/html/T_Novacta_Analytics_UnequalProbabilityRandomSampling.htm)
+  [unequal](https://novacta.github.io/analytics/html/EC35632C.htm)
   probabilities of being inserted in a sample.
-* [Permute randomly](http://novacta.github.io/analytics/html/T_Novacta_Analytics_RandomIndexPermutation.htm)
+* [Permute randomly](https://novacta.github.io/analytics/html/C0371263.htm)
   a given collection of integers.
 
-## Optimization
+### Optimization
 
-* [Optimize continuous functions](http://novacta.github.io/analytics/html/T_Novacta_Analytics_ContinuousOptimization.htm)
+* [Optimize continuous functions](https://novacta.github.io/analytics/html/3D985383.htm)
   having multiple arguments ranging over the real line.
 * Apply the Cross-Entropy method to
   represent continuous or combinatorial optimization problems via 
-  [Cross-Entropy contexts for optimization](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_SystemPerformanceOptimizationContext.htm),
+  [Cross-Entropy contexts for optimization](https://novacta.github.io/analytics/html/1C32368C.htm),
   and solve them using a
-  [Cross-Entropy optimizer](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_SystemPerformanceOptimizer.htm).
+  [Cross-Entropy optimizer](https://novacta.github.io/analytics/html/E252E84.htm).
 * Take advantage of specialized Cross-Entropy contexts to
   optimize functions having as arguments
-  [continuous variables](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_ContinuousOptimizationContext.htm),
-  [combinations](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_CombinationOptimizationContext.htm),
-  [partitions](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_PartitionOptimizationContext.htm),
+  [continuous variables](https://novacta.github.io/analytics/html/A8203153.htm),
+  [combinations](https://novacta.github.io/analytics/html/236BBBCF.htm),
+  [partitions](https://novacta.github.io/analytics/html/240B10D.htm),
   or
-  [ensembles of categorical entailments](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_CategoricalEntailmentEnsembleOptimizationContext.htm).
+  [ensembles of categorical entailments](https://novacta.github.io/analytics/html/EB7894F3.htm).
 
-## Rare event simulation
+### Rare event simulation
 
 * Express the problem of estimating the probability of
-  rare events via 
-  [Cross-Entropy contexts for rare event simulation](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_RareEventProbabilityEstimationContext.htm),
+  rare events via
+  [Cross-Entropy contexts for rare event simulation](https://novacta.github.io/analytics/html/F877CA6A.htm),
   solvable using a
-  [Cross-Entropy estimator](http://novacta.github.io/analytics/html/T_Novacta_Analytics_Advanced_RareEventProbabilityEstimator.htm).
+  [Cross-Entropy estimator](https://novacta.github.io/analytics/html/463F9A03.htm).
 
 ## Documentation
 
 The current documentation includes the following topics.
 
-* [Novacta.Analytics release notes](http://novacta.github.io/analytics/html/41221eed-891e-4925-a654-ecf8b2d38c65.htm).
-* [Testing environment](http://novacta.github.io/analytics/html/07a926cb-9c3c-432d-998b-0af7eea037f6.htm)
+* [Novacta.Analytics release notes](https://novacta.github.io/analytics/html/e6a1e4b5-02ef-4f97-9bd4-3bf049441535.htm).
+* [Build and test](https://novacta.github.io/analytics/html/07a926cb-9c3c-432d-998b-0af7eea037f6.htm)
   instructs about the setup required
-  to test the assembly.
-* [Novacta.Analytics namespaces](http://novacta.github.io/analytics/html/G_Novacta_Analytics.htm)
-  contains reference information about library
-  types by namespace.
+  to build and test the assembly.
+* Namespaces [Novacta.Analytics](https://novacta.github.io/analytics/html/2406EB43.htm)
+  and [Novacta.Analytics.Advanced](https://novacta.github.io/analytics/html/F249DE1E.htm)
+  contain reference information about assembly types.
 
 ## Versioning
 
-We use [SemVer](http://semver.org/) for versioning. 
-For available versions, see the 
-[tags on this repository](https://github.com/novacta/analytics/tags). 
+We use [SemVer](http://semver.org/) for versioning.
+For available versions, see the
+[tags on this repository](https://github.com/novacta/analytics/tags).
 
 ## Copyrights and Licenses
 
-All source code is Copyright (c) 2020 Giovanni Lafratta.
+All source code is Copyright (c) 2018 Giovanni Lafratta.
 
-**Novacta.Analytics** is licensed under the 
-[MIT License](https://github.com/novacta/analytics/blob/master/LICENSE.md). 
+**Novacta.Analytics** is licensed under the
+[MIT License](https://github.com/novacta/analytics/blob/master/LICENSE.md).
 
-This project relies on native dynamic-link libraries obtained via the Intel® MKL custom DLL builder.
-[MKL](https://software.intel.com/en-us/mkl) is Copyright (c) 2018 Intel Corporation and
+This project relies on native dynamic-link libraries obtained
+via the Intel® oneAPI Math Kernel Library customDLL builder.
+[oneAPI MKL](https://www.intel.com/content/www/us/en/developer/tools/oneapi/onemkl.html) is 
+Copyright (c) 2021 Intel® Corporation and
 licensed under the
 [ISSL](https://software.intel.com/en-us/license/intel-simplified-software-license)
-terms.
+terms.