mirror of
https://github.com/hanzoai/jube-fork.git
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richard-churchman
cc0a2bee21
Included open-source Accord.net library code natively to the solution given the deprecated state of that project. Accord.net will be supported inside Jube for own needs (such as upgrading to .Net 7+). Accord.net libraries modified to compile to .Net 6. Modified Accord.net libraries to better support Newtonsoft Json.net serialisation. Included annotations in the Accord.net libraries to house important dependency statistics. Serialised json can be used independently of Jube to recall a Neural Network. Removal of Binary Serializer totally as a precursor to the projects support of .Net 7+. Extensive bug fixing in crucial functions of Neural Network training and recall. While this part of the system remains in Alpha, it is substantially more fit for purpose.
302 lines
12 KiB
C#
302 lines
12 KiB
C#
// Accord Statistics Library
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// The Accord.NET Framework
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// http://accord-framework.net
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//
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// Copyright © César Souza, 2009-2017
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// cesarsouza at gmail.com
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//
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// This library is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 2.1 of the License, or (at your option) any later version.
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//
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// This library is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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// Lesser General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License along with this library; if not, write to the Free Software
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// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
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//
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namespace Accord.Statistics.Distributions.Reflection
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{
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using Accord.Statistics.Distributions.Fitting;
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using Accord.Statistics.Distributions.Multivariate;
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using Accord.Statistics.Distributions.Univariate;
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using System;
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using System.Collections.Generic;
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using System.ComponentModel;
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using System.ComponentModel.DataAnnotations;
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using System.Linq;
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using System.Reflection;
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using System.Text;
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using Accord.Compat;
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using System.Threading.Tasks;
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/// <summary>
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/// Discovers the parameters of a <see cref="IDistribution">probability distribution</see>
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/// and helps determine their range and whether then can be constructed automatically from
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/// their indicated parameter ranges.
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/// </summary>
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///
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public class DistributionInfo
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{
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private bool? isBuildable;
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/// <summary>
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/// Gets the distribution's type information.
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/// </summary>
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///
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public Type DistributionType { get; protected set; }
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/// <summary>
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/// Gets the name of this distribution in a more human-readable form.
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/// </summary>
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///
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public string Name { get; protected set; }
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/// <summary>
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/// Gets a value indicating whether it is possible to discover enough
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/// information about this constructor such that the distribution can
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/// be constructed using reflection.
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/// </summary>
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///
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/// <value><c>true</c> if this instance is buildable; otherwise, <c>false</c>.</value>
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///
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public bool IsBuildable
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{
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get
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{
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if (isBuildable == null)
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isBuildable = GetConstructors().Any(x => x.IsBuildable);
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return isBuildable.Value;
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}
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}
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/// <summary>
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/// Gets a value indicating whether the distribution modeled by <see cref="DistributionType"/> is a discrete-valued distribution.
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/// Discrete distributions are assumed to inherit from <see cref="UnivariateDiscreteDistribution"/> or
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/// <see cref="MultivariateDiscreteDistribution"/>.
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/// </summary>
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///
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public bool IsDiscrete
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{
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get
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{
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#if NETSTANDARD
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var distributionTypeInfo = DistributionType.GetTypeInfo();
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return typeof(UnivariateDiscreteDistribution).GetTypeInfo().IsAssignableFrom(distributionTypeInfo)
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|| typeof(MultivariateDiscreteDistribution).GetTypeInfo().IsAssignableFrom(distributionTypeInfo);
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#else
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return typeof(UnivariateDiscreteDistribution).IsAssignableFrom(DistributionType)
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|| typeof(MultivariateDiscreteDistribution).IsAssignableFrom(DistributionType);
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#endif
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}
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}
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/// <summary>
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/// Gets a value indicating whether the distribution modeled by <see cref="DistributionType"/> is a continuous-valued distribution.
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/// Discrete distributions are assumed to inherit from <see cref="UnivariateContinuousDistribution"/> or
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/// <see cref="MultivariateContinuousDistribution"/>.
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/// </summary>
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///
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public bool IsContinuous
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{
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get
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{
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#if NETSTANDARD
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var distributionTypeInfo = DistributionType.GetTypeInfo();
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return typeof(UnivariateContinuousDistribution).GetTypeInfo().IsAssignableFrom(distributionTypeInfo)
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|| typeof(MultivariateContinuousDistribution).GetTypeInfo().IsAssignableFrom(distributionTypeInfo);
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#else
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return typeof(UnivariateContinuousDistribution).IsAssignableFrom(DistributionType)
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|| typeof(MultivariateContinuousDistribution).IsAssignableFrom(DistributionType);
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#endif
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}
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}
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/// <summary>
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/// Gets a value indicating whether the distribution modeled by <see cref="DistributionType"/> is univariate.
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/// A distribution is assumed to be univariate if it implements the <see cref="IUnivariateDistribution"/> interface.
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/// </summary>
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///
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public bool IsUnivariate
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{
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#if NETSTANDARD
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get { return typeof(IUnivariateDistribution).GetTypeInfo().IsAssignableFrom(DistributionType.GetTypeInfo()); }
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#else
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get { return typeof(IUnivariateDistribution).IsAssignableFrom(DistributionType); }
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#endif
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}
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/// <summary>
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/// Gets a value indicating whether the distribution modeled by <see cref="DistributionType"/> is multivariate.
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/// A distribution is assumed to be univariate if it implements the <see cref="IMultivariateDistribution"/> interface.
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/// </summary>
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///
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public bool IsMultivariate
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{
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#if NETSTANDARD
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get { return typeof(IMultivariateDistribution).GetTypeInfo().IsAssignableFrom(DistributionType.GetTypeInfo()); }
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#else
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get { return typeof(IMultivariateDistribution).IsAssignableFrom(DistributionType); }
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#endif
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}
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/// <summary>
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/// Initializes a new instance of the <see cref="DistributionInfo" /> class.
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/// </summary>
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///
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/// <param name="type">The type for the distribution.</param>
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///
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public DistributionInfo(Type type)
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{
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Type baseType = typeof(IDistribution);
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#if NETSTANDARD
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var typeDesc = type.GetTypeInfo();
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if (!baseType.GetTypeInfo().IsAssignableFrom(typeDesc) || typeDesc.IsAbstract || typeDesc.IsInterface)
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throw new ArgumentException("type");
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#else
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if (!baseType.IsAssignableFrom(type) || type.IsAbstract || type.IsInterface)
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throw new ArgumentException("type");
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#endif
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this.DistributionType = type;
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this.Name = GetDistributionName(type);
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}
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/// <summary>
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/// Gets the public constructors of the distribution.
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/// </summary>
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///
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public DistributionConstructorInfo[] GetConstructors()
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{
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#if NETSTANDARD
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var constructors = new List<DistributionConstructorInfo>();
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var typeInfo = DistributionType.GetTypeInfo();
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var declaredConstructors = typeInfo.DeclaredConstructors;
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foreach (ConstructorInfo ctor in declaredConstructors)
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if (ctor.IsPublic)
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constructors.Add(new DistributionConstructorInfo(ctor));
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#else
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var constructors = new List<DistributionConstructorInfo>();
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foreach (ConstructorInfo ctor in DistributionType.GetConstructors())
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constructors.Add(new DistributionConstructorInfo(ctor));
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#endif
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return constructors.ToArray();
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}
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/// <summary>
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/// Gets the fitting options object that are expected by the distribution, if any. An
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/// Accord.NET distribution object can be fitted to a set of observed values. However,
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/// some distributions have different settings on how this fitting can be done. This
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/// function creates an object that contains those possible settings that can be configured
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/// for a given distribution type.
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/// </summary>
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///
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public IFittingOptions GetFittingOptions()
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{
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return GetFittingOptions(DistributionType);
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}
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/// <summary>
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/// Gets the name of the distribution modeled by a given Accord.NET type.
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/// The name is returned in a normalized form (i.e. given a type whose name
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/// is NormalDistribution, the function would return "Normal").
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/// </summary>
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///
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public static string GetDistributionName(Type type)
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{
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// Extract the real distribution name from the class name
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string name = type.Name;
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if (name.Contains('`'))
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name = name.Remove(name.IndexOf("`"));
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// Remove the trailing "Distribution" from the name
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if (name.EndsWith("Distribution"))
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name = name.Remove(name.IndexOf("Distribution"));
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return name.Trim();
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}
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/// <summary>
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/// Gets the fitting options object that are expected by one distribution, if any. An
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/// Accord.NET distribution object can be fit to a set of observed values. However,
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/// some distributions have different settings on how this fitting can be done. This
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/// function creates an object that contains those possible settings that can be configured
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/// for a given distribution type.
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/// </summary>
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///
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public static IFittingOptions GetFittingOptions(Type type)
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{
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// Try to create a fitting options object
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var fittingOptions = typeof(IFittingOptions);
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#if NETSTANDARD
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var interfaces = type.GetTypeInfo().ImplementedInterfaces.Select(t => t.GetTypeInfo())
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.Where(i => i.IsGenericType && i.GetGenericTypeDefinition() == typeof(IFittableDistribution<,>));
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var fittingOptionsInfo = fittingOptions.GetTypeInfo();
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foreach (TypeInfo i in interfaces)
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foreach (Type arg in i.GenericTypeArguments)
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if (fittingOptionsInfo.IsAssignableFrom(arg.GetTypeInfo()) && arg != fittingOptions)
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return (IFittingOptions)Activator.CreateInstance(arg);
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#else
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var interfaces = type.GetInterfaces()
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.Where(i => i.IsGenericType && i.GetGenericTypeDefinition() == typeof(IFittableDistribution<,>));
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foreach (Type i in interfaces)
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foreach (Type arg in i.GetGenericArguments())
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if (fittingOptions.IsAssignableFrom(arg) && arg != fittingOptions)
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return (IFittingOptions)Activator.CreateInstance(arg);
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#endif
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return null;
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}
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/// <summary>
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/// Gets the fitting options object that are expected by one distribution, if any. An
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/// Accord.NET distribution object can be fit to a set of observed values. However,
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/// some distributions have different settings on how this fitting can be done. This
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/// function creates an object that contains those possible settings that can be configured
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/// for a given distribution type.
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/// </summary>
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///
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public static IFittingOptions GetFittingOptions<T>()
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{
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return GetFittingOptions(typeof(T));
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}
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internal static Type[] GetDistributionsInheritingFromBaseType(Type baseType)
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{
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// This function iterates the Accord.Statistics assembly looking for
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// classes that are concrete (not abstract) and that implement the
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// given interface.
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// Get all univariate distributions in Accord.NET:
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#if NETSTANDARD1_4
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var baseInfo = baseType.GetTypeInfo();
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var distributions = baseInfo.Assembly.DefinedTypes
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.Where(p => baseInfo.IsAssignableFrom(p) && !p.IsAbstract && !p.IsInterface)
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.Select(p => p.AsType());
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#else
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var distributions = Assembly.GetAssembly(baseType).GetTypes().Where(p =>
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baseType.IsAssignableFrom(p) && !p.IsAbstract && !p.IsInterface);
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#endif
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return distributions.ToArray();
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}
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/// <summary>
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/// Returns a <see cref="System.String" /> that represents this instance.
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/// </summary>
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/// <returns>A <see cref="System.String" /> that represents this instance.</returns>
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public override string ToString()
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{
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return Name;
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}
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}
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}
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