Added functionality includes:

• Upgraded to Intel MKL 11.3 Update 2 with resulting performance increases.
• Updated NMath Premium GPU code to CUDA 7.5.
• Added classes for performing Discrete Wavelet Transforms (DWTs) using most common wavelet families, including Harr, Daubechies, Symlet, Best Localized, and Coiflet.
• Added classes for solving stiff ordinary differential equations. The algorithm uses higher order methods and smaller step size when the solution varies rapidly.
• Added classes for performing two-way ANOVA with unbalanced designs.
• Added classes for performing Partial Least Squares Discriminant Analysis (PLS-DA), a variant of PLS used when the response variable is categorical.

For more complete changelogs, see:

• NMath changelog
• NMath Stats changelog

Upgrades are provided free of charge to customers with current annual maintenance contracts. To request an upgrade, please visit our upgrade page, or contact sales@centerspace.net. Maintenance contracts are available through our webstore.

The post Announcing NMath 6.2 and NMath Stats 4.2 appeared first on CenterSpace.

Added functionality includes:

• Upgraded to Intel MKL 11.2 Update 2 with resulting performance increases.
• Updated NMath Premium GPU code to CUDA 6.
• Added classes for solving linear and nonlinear programming problems with integer or binary constraints.
• Added class SpecialFunctions containing special functions such as factorial, binomial, the gamma function and related functions, Bessel functions, elliptic integrals, and many more. (Prior versions of a few of these functions, such as StatsFunctions.IncompleteGamma, are now deprecated.)
• Added a new native library, nmath_sf_x86.dll and nmath_sf_x64.dll, with high-performance C language implementations of the special functions.
• Added single-precision versions of general sparse matrix and vector types.

For more complete changelogs, see here and here.

Upgrades are provided free of charge to customers with current annual maintenance contracts. To request an upgrade, please visit our upgrade page, or contact sales@centerspace.net. Maintenance contracts are available through our webstore.

The post Announcing NMath 6.1 and NMath Stats 4.1 appeared first on CenterSpace.

Added functionality includes:

• Upgraded to Intel MKL 11.1 Update 3 with resulting performance increases.
• Added Adaptive Bridge™ technology to NMath Premium edition, with support for multiple GPUs, per-thread control for binding threads to GPUs, and automatic performance tuning of individual CPU–GPU routing to insure optimal hardware usage.
• NMath linear programming, nonlinear programming, and quadratic programming classes are now built on the Microsoft Solver Foundation (MSF). The Standard Edition of MSF is included with NMath.
• Added classes for solving nonlinear programming problems using the Stochastic Hill Climbing algorithm, for solving quadratic programming problems using an interior point algorithm, and for solving constrained least squares problems using quadratic programming methods.
• Added support for MKL Conditional Numerical Reproducibility (CNR).

For more complete changelogs, see here and here.

Upgrades are provided free of charge to customers with current annual maintenance contracts. To request an upgrade, please contact sales@centerspace.net. Maintenance contracts are available through our webstore.

The post Announcing NMath 6.0 and NMath Stats 4.0 appeared first on CenterSpace.

Version 5.3 of NMath adds:

• IEnumerable<T> support for matrix classes, facilitating their use with LINQ.
• An in-place solve option for LU factorization.
• Improved support for NMath configuration within ASP.NET web applications.
• Matrix and vector visualizers for debugging in Visual Studio 2012.
• Performance increases in several areas, due to an upgrade to Intel MKL 11.0 Update 3.
• Here is a complete changelog.

Version 3.6 of NMath Stats adds:

• New LogisticRegression and related classes for performing binomial logistic regression.
• New classes for process control statistics, such as Cp, Cpm, Cp, Pp, and Ppk.
• Here is a complete changelog.

Upgrades are provided free of charge to customers with current annual maintenance contracts. Maintenance contracts are available through our webstore.

We will shortly also be announcing the general availability of the new Premium Edition of NMath and NMath Stats, which provides GPU acceleration of linear algebra (dense systems) and 1D and 2D FFT. We’ve gotten great feedback from users in our beta program, and are excited to make this option available to everyone. We think you will be too, when you see how easy it is to add GPU acceleration to your existing NMath applications. Check out our whitepaper, NMath Premium: GPU-Accelerated Math Libraries for .NET, and watch this space for more information soon.

The post Announcing NMath 5.3 and NMath Stats 3.6 appeared first on CenterSpace.

• IEnumerable<T> support for matrix classes, facilitating their use with LINQ.
• An in-place solve option for LU factorization.
• Improved support for NMath configuration within ASP.NET web applications.
• Matrix and vector visualizers for debugging in Visual Studio 2012.
• Performance increases in several areas, due to an upgrade to Intel MKL 10.3 Update 12.
• A variety of new options, performance improvements, and bug fixes.

And new Stats capabilities:

• New LogisticRegression and related classes for performing binomial logistic regression.
• New classes for process control statistics, such as Cp, Cpm, Cp, Pp, and Ppk.

In addition, NMath Premium edition offers GPU acceleration of linear algebra and 1D and 2D FFT.  Check out the NMath Premium page on our website for more information, or download our detailed whitepaper, “NMath Premium: GPU-Accelerated Math Libraries for .NET.”

Upgrades will be available free of charge for customers with current annual maintenance contracts, so it’s a great time to check that your maintenance is up to date. Since new product licenses include a one year Maintenance Contract, anyone purchasing new licenses now will receive the upgrades free.

Product licenses and maintenance contract renewals are available through our web store, or feel free to contact sales@centerspace.net with any questions.

The post NMath 5.3, NMath Stats 3.6 are coming appeared first on CenterSpace.

If no license key is found at runtime, a default evaluation license key is used which provides a free 30-day evaluation period for NMath on the current machine.

Three mechanisms are supported for setting your NMath license key:

• by setting the NMATH_LICENSE_KEY environment variable
• by setting the NMathLicenseKey configuration app setting
• by programmatically setting the LicenseKey property on class NMathConfiguration

Settings are applied in that order, and resetting the license key takes precedent over any earlier values. For example, here the environment variable is used:

 > set NMATH_LICENSE_KEY="<your key here>"

This code uses an app config file:

<?xml version="1.0" encoding="utf-8" ?>
<configuration>
  <appSettings>
    <add key="NMathLicenseKey" value="<your key here>" />
  </appSettings>
</configuration>

And this code accomplishes the same thing programmatically:

NMathConfiguration.LicenseKey = "<your key here>";

Note 1: Setting your license key works the same way for development and deployment machines.

Note 2: If you forget to set your license key on a machine, your code NMath code will work initially, using the default evaluation license, but this license will expire in 30 days.

The post Setting the NMath License Key appeared first on CenterSpace.

Changes for version 5.2 of NMath include:

• Upgraded to Intel MKL 10.3 Update 11 with resulting performance increases.
• Added class NMathConfiguration for controlling the loading of the NMath
  license key, kernel assembly, and native library. Logging can be enabled for debugging configuration issues.
  License files are no longer used. See here for more information.
• Replaced all custom NMath delegate types in the API with Func or Action
  equivalents, and deprecated the older signatures.
• Added support for postive and negative strided signals in all FFT classes.

A complete changelog is located here.

Version 3.5 of NMath Stats adds:

• Classes DoubleFactorAnalysis, FactorAnalysisCorrelation, FactorAnalysisCovariance, and supporting types for performing factor analysis.
• Class OneSampleAndersonDarlingTest for performing an Anderson-Darling test of the distribution of one sample.
• Class ShapiroWilkTest for testing the null hypothesis that a sample comes from a normally distributed population.
• Method NMathFunctions.FishersExactTest() for computing the Fisher’s Exact Test p-value for a specified 2 x 2 contingency table.

A complete changelog is located here.

The new release is build-compatible with the prior release. Upgrades are provided free of charge to customers with current annual maintenance contracts. Maintenance contracts are available through our webstore.

The post New Versions of NMath Libraries Released appeared first on CenterSpace.

An NMath license file is no longer used.

NMath License Key

NMath license information is stored in a license key which must be found at runtime. The license key governs the properties of your NMath installation. If no license key is found, a default evaluation license key is used which provides a free 30-day evaluation period for NMath on the current machine.

When you purchase one or more developer seats of NMath, you will be issued a license key describing the terms of your license. To enter your license key:

1. Open CenterSpace Software | License NMath from your Start menu.
2. Enter your name, email, and license key, and click OK.

The license key will be written to the registry. You can also specify your license key using various other mechanisms: by environment variable, by configuration app setting, and programmatically. These mechanisms may be preferable in group development environments, and at deployment. (See below.)

NMath Configuration

NMath configuration settings govern the loading of the NMath license key, kernel assembly, and native library. Property values can be set three ways:

• by environment variable
• by configuration app setting
• by programmatically setting properties on class NMathConfiguration

Settings are applied in that order, and resetting a property takes precedent over any earlier values. For example, here an environment variable is used:

 > set NMATH_NATIVE_LOCATION="C:\tmp"

This code uses an app config file:

<?xml version="1.0" encoding="utf-8" ?>
<configuration>
  <appSettings>
    <add key="NMathNativeLocation" value="C:\tmp" />
  </appSettings>
</configuration>

And this code accomplishes the same thing programmatically:

NMathConfiguration.NativeLocation = @"C:\tmp";

Also, all paths can be specified relative to the executable. So to place the natives in an existing directory named resources adjacent to the executable one would
write:

NMathConfiguration.NativeLocation = @"..\resources";

The supported environment variables, configuration app setting keys, and property names are show below.

Environment Variable
Configuration Setting
Property


NMATH_LOG_LOCATION
NMathLogLocation
LogLocation


NMATH_LICENSE_KEY
NMathLicenseKey
LicenseKey


NMATH_NATIVE_LOCATION
NMathNativeLocation
NativeLocation


NMATH_USE_SEQUENTIAL_THREADING
NMathUseSequentialThreading
UseSequentialThreading


NMATH_USE_EXTERNAL_THREADING
NMathUseExternalThreading
UseExternalThreading

NOTE- Assembly loading and license checking is normally performed the first time you make an NMath call. If you wish to explicitly control when these operations occur–at application start-up, for example–use the static NMathConfiguration.Init() method.

For example, when using Mono on a Mac, to configured NMath with a sequentially threaded library set the environmental variable as follows.

 > export NMATH_USE_SEQUENTIAL_THREADING="True" 

Logging

To debug configuration issues, specify a log file location. For example, setting the property programmatically to place the NMath log file in the same directory as the executable one would write:

NMathConfiguration.LogLocation = @".";

Or if you prefer to use a global temporary directory you could specify an absolute path.

NMathConfiguration.LogLocation = @"C:\temp\logs";

This creates a file named NMathConfiguration.log at the specified location containing log output. The specified location must exist. To turn off logging, set the log location to null.

License Key

You can specify your NMath license key using the LicenseKey property, or the equivalent environment variable or app config setting. If so, any keys in the registry are ignored.

Native Location

The NMath native assembly must be found at runtime. Failure to locate this file is one of the most common configuration issues, especially in deployment. The search order is determined by your PATH (on Windows systems). Some standard locations are automatically prepended to your (process-specific) PATH. You can also use the NativeLocation property, or the equivalent environment variable or app config setting, to prepend another location.

Alternative Kernel and Native Assemblies

The names of the NMath kernel and native assemblies are determined by your platform (x86 or x64), and the values of the UseSequentialThreading and UseExternalThreading properties, as shown below:

Standard
     Kernel
          NMathKernelx86.dll
          NMathKernelx64.dll
     Native
          nmath_native_x86.dll
          nmath_native_x64.dll

Sequentially-Threaded
     Kernel
          NMathKernelx86Sequential.dll
          NMathKernelx64Sequential.dll
     Native
          nmath_native_x86_seq.dll
          nmath_native_x64_seq.dll

Externally-Threaded
     Kernel
          NMathKernelx86External.dll
          NMathKernelx64External.dll
     Native
          nmath_native_x86_ext.dll
          nmath_native_x64_ext.dll

Sequentially-threaded and externally-threaded kernel and native assemblies are available upon request from CenterSpace Software:

• Sequentially-Threaded: MKL contains highly optimized, extensively threaded math routines. In rare cases, these can cause conflicts between the Intel OMP threading library (libiomp.dll) and the .NET threading model. If your .NET application is itself highly multi-threaded, you may wish to use the sequentially-threaded version of MKL.
• Externally-Threaded: NMath normally statically links in the Intel OMP threading library described above. Sometimes this can cause collisions with libraries from other vendors that also use OMP. The externally-threaded version of NMath dynamically-links in OMP.

To trigger loading of these assemblies, use properties UseSequentialThreading and UseExternalThreading on class NMathConfiguration, or the equivalent environment variables or app config settings. Both properties default to false.

UseSequentialThreading and UseExternalThreading are mutually exclusive, and UseSequentialThreading takes precedence; UseExternalThreading only has an effect if UseSequentialThreading is false.

The post NMath Configuration appeared first on CenterSpace.

For those not familiar with the usage and definition of Func<> types within .NET there is a short primer at the end of this post.

Compiler Warning for [Obsolete] NMath defined delegates

All of our NMath delegate types have been deprecated using the .NET [Obsolete()] attribute. The generated compiler warnings will provide the suggested Func type replacement.

Warning 52 'CenterSpace.NMath.Core.NMathFunctions.FloatUnaryFunction'
   is obsolete: 'Use Func< float, float >'   ...

To further clarify, the following table lists the deprecated NMath float delegate types side by side with their replacements. All NMath delegates should be redefined in your code using the generic Func types.

 List of float-precision deprecated NMath delegate types


Old NMath delegates
Replacement


float FloatFunction()
Func< float >


float FloatUnaryFunction( float x )
Func< float, float >


float FloatBinaryFunction( float x, float y )
Func< float, float, float >


float FloatIntFunction( float x, int y )
Func< float, int, float >


float FloatVectorFloatFunction( FloatVector v )
Func< FloatVector, float >


FloatVector
  FloatVectorFloatVectorFunction( FloatVector x )
Func< FloatVector, FloatVector >

There are many other deprecated NMath delegates that should be similarly replaced in your code.

Code examples for updating your code

Where previously you might have created a delegate that takes a double argument and returns a double like this:

NMathFunctions.DoubleUnaryFunction soln =
   delegate(double x) {return (x*x*x) / 3.0 + y0; };

you should now do it like this:

Func soln =
   new Func< double, double >(  x => (x*x*x) / 3.0 + y0 );

All methods in NMath and NMath Stats now take Func<> type delegates. If you use the old NMath delegates types to call a NMath method, an obsolescence warning will be issued by the compiler.

NMath and NMath Stats contain many functors that have now been obsolesced and redefined using a generic Func<> type. The new functor naming convention simply drops the “tion” from “Function” to make the new name. For example, the delegate NMathFunctions.AtanFunction should now be replaced with NMathFunctions.AtanFunc. The old delegate has a type of NMathFunctions.DoubleUnaryFunction, and the new delegate has a type of Func< double, double >. This kind of replacement can be done safely with a global search and replace operation to rid yourself of compiler obsolescence warnings. The table below list a few functor redefinitions that demonstrate the renaming pattern that was applied across the API.

 Sampling of deprecated NMath functors


Old NMath functor
Replacement


DoubleUnaryFunction AbsFunction
Func< double, double > AbsFunc


DoubleUnaryFunction AcosFunction
Func< double, double > AcosFunc


DoubleUnaryFunction AsinFunction
Func< double, double > AsinFunc


DoubleBinaryFunction PowFunction
Func< double, double, double > PowFunc


DoubleIntFunction RoundFunction
Func< double, int, double > RoundFunc


DoubleVectorDoubleFunction
  DoubleNaNMedianFunction
Func< DoubleVector, double > DoubleNaNMedianFunc

Potential Issues

The deprecation process requires us to maintain the old custom delegate defintions in the API methods while introducing the new Func<> based API. As a result, every method call in our API which previously consumed a custom NMath delgate type, a functionally identical signature was added which consumes a Func<> based delegate. This duplication can cause an easy-to-fix compiler error in situations when an anonymous delegate was used instead of a NMath delegate type. Consider the follow line of code which inverts the singular values of a SVD.

      DoubleVector wInverse =
         svDecomp.SingularValues.Apply(
              delegate( double w )
                 { return w < eps ? 0.0 : 1.0 / w; }
         );

Written this way will now cause the following compiler error.

Error	43
The call is ambiguous between the following methods or properties:
'CenterSpace.NMath.Core.DoubleVector.Apply(
    CenterSpace.NMath.Core.NMathFunctions.DoubleUnaryFunction )'
and
'CenterSpace.NMath.Core.DoubleVector.Apply( System.Func )' ....

In this error message, the first Apply() is the old method signature and the second Apply() is the new Func<> based signature. The C# compiler can't choose between the two when provided an anonymous delegate. Exactly why this ambiguity error is generated by the compiler is carefully explained by Eric Lippert over on stackoverflow. Briefly, the ambiguity error arises because both methods equally satisfy the Apply() method signature and the C# standard does not provide a way to judge which would be 'better', and so reports an error. The fix is simple, we just specified explicitly that we want to use the method that takes a generic Func<>.

      DoubleVector wInverse =
         svDecomp.SingularValues.Apply(
              new Func< double, double >
                 ( delegate( double w )
                    { return w < eps ? 0.0 : 1.0 / w; }
                 )
         );

Or, somewhat more concisely using a lamda expression.

      DoubleVector wInverse =
         svDecomp.SingularValues.Apply(
              new Func< double, double >
                 ( w => w < eps ? 0.0 : 1.0 / w  )
         );

A brief Func<> & Action<> primer

The generic delegate types, Func<> and Action<>, were introduced with the .NET 3.5 framework to unify delegate types across various .NET libraries. This allows a .NET library developer like CenterSpace to create an API that accepts generic delegates that are defined elsewhere in client code. The Func and Action are differentiated by their return values: Actions have no return value, Funcs always have a single return value of type TResult. For each of them, the .NET framework defines a type signature that takes between 0 and 16 generically typed arguments.

 .NET Func<> and Action<> definitions


Func
Action


TResult Func()
void Action<>()


TResult Func( T arg )
void Action( T arg )


...
...


TResult Func(
	T1 arg1,
	T2 arg2,
	...
	T15 arg15,
	T16 arg16 )
void Action(
	T1 arg1,
	T2 arg2,
	...
	T15 arg15,
	T16 arg16 )

This is still all abstract. Here's how we create a Func using a lambda expression.

Func mySquaringFunc =
   new Func< double, double> ( x =>  x*x ); 

double xSquared = mySquaringFunc( 45 );  // xSquared = 2025

This Func delegate takes single double value and returns a double value. Lamda expressions are commonly used today to generate delegates, however an anonymous delegate could also be used for the same purpose.

Func mySquaringFunc =
   new Func< double, double> ( delegate( double x ) { return x*x; } ); 

double xSquared = mySquaringFunc( 45 );  // xSquared = 2025

I find the lambda syntax to be more expressive and succinct. From the table above, T1 = double, and TResult = double.

Action types are not used within the NMath API because we are always dealing with functions and return values. However, Actions are similarly defined, and may be used for example in queuing code where a queue manager takes work in the form of Action delegates.

Action< DoubleVector > FFTWorker =
   new Action< DoubleVector >( v =>
      {
         DoubleComplexForward1DFFT fft = new DoubleComplexForward1DFFT( v.Length );
         fft.FFTInPlace( v );
       } );
...
QueueManager.AddWork( FFTWorker, bigDataVector );

The Action above computes the in-place FFT, and the QueueManager can now generically schedule this work on the queue.

Happy Computing,
Paul Shirkey

The post NMath API updated with .NET Func<> delegates appeared first on CenterSpace.

A follow-up whitepaper and adapter code extends these capabilities to NMath Stats.  This paper details how to:

• Use the NMathStatsChart adapter to create and customize Essential Chart ChartControl instances easily.
• Plot vectors, matrices, functions, fitted functions, function peaks, least squares classes, and histograms using a variety of chart types.
• Plot NMath Stats data structures such as data frames, probability distributions, linear regressions, goodness of fit, principal component analyses, and cluster analyses.

Click here to download the free adapter code and detailed instructions.

The post NMath Stats integration with Essential Chart appeared first on CenterSpace.