public void Execute(IExampleInterface app)
{
// build the bayesian network structure
BayesianNetwork network = new BayesianNetwork();
BayesianEvent BlueTaxi = network.CreateEvent("blue_taxi");
BayesianEvent WitnessSawBlue = network.CreateEvent("saw_blue");
network.CreateDependency(BlueTaxi, WitnessSawBlue);
network.FinalizeStructure();
// build the truth tales
BlueTaxi.Table.AddLine(0.85, true);
WitnessSawBlue.Table.AddLine(0.80, true, true);
WitnessSawBlue.Table.AddLine(0.20, true, false);
// validate the network
network.Validate();
// display basic stats
Console.WriteLine(network.ToString());
Console.WriteLine("Parameter count: " + network.CalculateParameterCount());
EnumerationQuery query = new EnumerationQuery(network);
//SamplingQuery query = new SamplingQuery(network);
query.DefineEventType(WitnessSawBlue, EventType.Evidence);
query.DefineEventType(BlueTaxi, EventType.Outcome);
query.SetEventValue(WitnessSawBlue, false);
query.SetEventValue(BlueTaxi, false);
query.Execute();
Console.WriteLine(query.ToString());
}
/// <summary>
/// Calculate G.
/// </summary>
/// <param name="network">The network to calculate for.</param>
/// <param name="e">The event to calculate for.</param>
/// <param name="parents">The parents.</param>
/// <returns>The value for G.</returns>
public double CalculateG(BayesianNetwork network,
BayesianEvent e, IList <BayesianEvent> parents)
{
double result = 1.0;
int r = e.Choices.Count;
var args = new int[parents.Count];
do
{
double n = EncogMath.Factorial(r - 1);
double d = EncogMath.Factorial(CalculateN(network, e,
parents, args) + r - 1);
double p1 = n / d;
double p2 = 1;
for (int k = 0; k < e.Choices.Count; k++)
{
p2 *= EncogMath.Factorial(CalculateN(network, e, parents, args, k));
}
result *= p1 * p2;
} while (EnumerationQuery.Roll(parents, args));
return(result);
}
static EnumerationQuery BuildEnumerationQuery()
{
Console.WriteLine("Building enumeration query");
EnumerationQuery ret = new EnumerationQuery();
return(ret);
}
static void Enumerate()
{
// Search(string indexName, SearchQuery query, out SearchResult result)
string indexName = InputString("Index name:", null, true);
if (String.IsNullOrEmpty(indexName))
{
return;
}
EnumerationQuery eq = new EnumerationQuery();
string filename = InputString("Enumeration filename:", "", true);
if (!String.IsNullOrEmpty(filename))
{
eq = DeserializeJson <EnumerationQuery>(File.ReadAllBytes(filename));
}
EnumerationResult result = _Sdk.Enumerate(indexName, eq).Result;
if (result != null)
{
Console.WriteLine(SerializeJson(result, true));
}
}
public void Execute(IExampleInterface app)
{
// Create a Bayesian network
BayesianNetwork network = new BayesianNetwork();
// Create the Uber driver event
BayesianEvent UberDriver = network.CreateEvent("uber_driver");
// create the witness event
BayesianEvent WitnessSawUberDriver = network.CreateEvent("saw_uber_driver");
// Attach the two
network.CreateDependency(UberDriver, WitnessSawUberDriver);
network.FinalizeStructure();
// build the truth tables
UberDriver?.Table?.AddLine(0.85, true);
WitnessSawUberDriver?.Table?.AddLine(0.80, true, true);
WitnessSawUberDriver?.Table?.AddLine(0.20, true, false);
network.Validate();
Console.WriteLine(network.ToString());
Console.WriteLine($"Parameter count: {network.CalculateParameterCount()}");
EnumerationQuery query = new EnumerationQuery(network);
// The evidence is that someone saw the Uber driver hit the car
query.DefineEventType(WitnessSawUberDriver, EventType.Evidence);
// The result was the Uber driver did it
query.DefineEventType(UberDriver, EventType.Outcome);
query.SetEventValue(WitnessSawUberDriver, false);
query.SetEventValue(UberDriver, false);
query.Execute();
Console.WriteLine(query.ToString());
}
static void TestCase2()
{
List <string> docsToIndex = DocumentsToIndex("./TestCases/2/");
List <string> queriesToProcess = QueriesToProcess("./TestCases/2/");
ParseOptions options = new ParseOptions();
// load documents
foreach (string curr in docsToIndex)
{
byte[] data = Common.ReadBinaryFile(curr);
SourceDocument src = new SourceDocument("test", "test", curr, curr, null, DocType.Json, null, "application/json", data.Length, Common.Md5(data));
IndexResult result = _IndexClient.Add(src, data, options, true).Result;
Console.WriteLine("");
Console.WriteLine("Add: " + curr);
Console.WriteLine(Common.SerializeJson(result, true));
}
Console.WriteLine("");
Console.WriteLine("Press ENTER to continue");
Console.ReadLine();
// execute queries
foreach (string curr in queriesToProcess)
{
EnumerationQuery query = Common.DeserializeJson <EnumerationQuery>(Common.ReadBinaryFile(curr));
EnumerationResult result = _IndexClient.Enumerate(query);
Console.WriteLine("");
Console.WriteLine("Query: " + curr);
Console.WriteLine(Common.SerializeJson(result, true));
}
}
public void TestEnumeration2()
{
BayesianNetwork network = new BayesianNetwork();
BayesianEvent a = network.CreateEvent("a");
BayesianEvent x1 = network.CreateEvent("x1");
BayesianEvent x2 = network.CreateEvent("x2");
BayesianEvent x3 = network.CreateEvent("x3");
network.CreateDependency(a, x1, x2, x3);
network.FinalizeStructure();
a.Table.AddLine(0.5, true); // P(A) = 0.5
x1.Table.AddLine(0.2, true, true); // p(x1|a) = 0.2
x1.Table.AddLine(0.6, true, false); // p(x1|~a) = 0.6
x2.Table.AddLine(0.2, true, true); // p(x2|a) = 0.2
x2.Table.AddLine(0.6, true, false); // p(x2|~a) = 0.6
x3.Table.AddLine(0.2, true, true); // p(x3|a) = 0.2
x3.Table.AddLine(0.6, true, false); // p(x3|~a) = 0.6
network.Validate();
EnumerationQuery query = new EnumerationQuery(network);
query.DefineEventType(x1, EventType.Evidence);
query.DefineEventType(x2, EventType.Evidence);
query.DefineEventType(x3, EventType.Evidence);
query.DefineEventType(a, EventType.Outcome);
query.SetEventValue(a, true);
query.SetEventValue(x1, true);
query.SetEventValue(x2, true);
query.SetEventValue(x3, false);
query.Execute();
TestPercent(query.Probability, 18);
}
private static async Task PutEnumerateIndex(RequestMetadata md)
{
string header = "[Komodo.Server] " + md.Http.Request.Source.IpAddress + ":" + md.Http.Request.Source.Port + " PutEnumerateIndex ";
if (md.Http.Request.Data == null || md.Http.Request.ContentLength < 1)
{
md.Http.Response.StatusCode = 400;
md.Http.Response.ContentType = "application/json";
await md.Http.Response.Send(new ErrorResponse(400, "No request body.", null, null).ToJson(true));
return;
}
string indexName = md.Http.Request.Url.Elements[0];
if (!_Daemon.IndexExists(indexName))
{
_Logging.Warn(header + "index " + indexName + " does not exist");
md.Http.Response.StatusCode = 404;
md.Http.Response.ContentType = "application/json";
await md.Http.Response.Send(new ErrorResponse(404, "Unknown index.", null, null).ToJson(true));
return;
}
EnumerationQuery query = Common.DeserializeJson <EnumerationQuery>(Common.StreamToBytes(md.Http.Request.Data));
if (query.Filters == null)
{
query.Filters = new List <SearchFilter>();
}
EnumerationResult result = _Daemon.Enumerate(indexName, query);
if (!result.Success)
{
_Logging.Warn(header + "failed to execute enumeration in index " + indexName);
md.Http.Response.StatusCode = 500;
md.Http.Response.ContentType = "application/json";
await md.Http.Response.Send(new ErrorResponse(500, "Unable to enumerate index '" + indexName + "'.", null, result).ToJson(true));
return;
}
md.Http.Response.StatusCode = 200;
md.Http.Response.ContentType = "application/json";
await md.Http.Response.Send(Common.SerializeJson(result, md.Params.Pretty));
return;
}
/// <summary>
/// Enumerate the index.
/// </summary>
/// <param name="indexName">Name of the index.</param>
/// <param name="query">Enumeration query.</param>
/// <returns>Enumeraiton result.</returns>
public EnumerationResult Enumerate(string indexName, EnumerationQuery query)
{
if (String.IsNullOrEmpty(indexName))
{
throw new ArgumentNullException(nameof(indexName));
}
if (query == null)
{
throw new ArgumentNullException(nameof(query));
}
KomodoIndex idx = GetIndexClient(indexName);
return(idx.Enumerate(query));
}
static void Enumerate()
{
string indexName = Common.InputString("Index name :", null, false);
EnumerationQuery query = BuildEnumerationQuery();
EnumerationResult result = _Komodo.Enumerate(indexName, query);
if (result == null)
{
Console.WriteLine("(none)");
}
else
{
Console.WriteLine(Common.SerializeJson(result, true));
}
}
/// <summary>
/// Enumerate source documents in the specified index.
/// </summary>
/// <param name="indexName">Name of the index.</param>
/// <param name="query">Enumeration query.</param>
/// <param name="token">Cancellation token used to cancel the request.</param>
/// <returns>Enumeration result.</returns>
public async Task <EnumerationResult> Enumerate(string indexName, EnumerationQuery query, CancellationToken token = default)
{
if (String.IsNullOrEmpty(indexName))
{
throw new ArgumentNullException(nameof(indexName));
}
if (query == null)
{
throw new ArgumentNullException(nameof(query));
}
try
{
string url = indexName + "?enumerate";
RestRequest req = new RestRequest(
_Endpoint + url,
HttpMethod.PUT,
_AuthHeaders,
"application/json");
req.IgnoreCertificateErrors = AcceptInvalidCertificates;
RestResponse resp = await req.SendAsync(KomodoCommon.SerializeJson(query, true), token).ConfigureAwait(false);
KomodoException e = KomodoException.FromRestResponse(resp);
if (e != null)
{
throw e;
}
if (resp.Data != null && resp.ContentLength > 0)
{
byte[] respData = KomodoCommon.StreamToBytes(resp.Data);
return(KomodoCommon.DeserializeJson <EnumerationResult>(respData));
}
return(null);
}
catch (TaskCanceledException)
{
return(null);
}
catch (OperationCanceledException)
{
return(null);
}
}
/// <summary>
/// Reset the truth table to zero.
/// </summary>
public void Reset()
{
_lines.Clear();
IList <BayesianEvent> parents = _event.Parents;
int l = parents.Count;
int[] args = new int[l];
do
{
for (int k = 0; k < _event.Choices.Count; k++)
{
AddLine(0, k, args);
}
} while (EnumerationQuery.Roll(parents, args));
}
static void Main(string[] args)
{
/*Przykład 4.2.3 Teoria Bayesa - Zakłady Produkcyjne Etap Manualny
* Lesson 1 - Machine Learning in C# for Amazon ML Group created by me :-)
* PS. Kill me I use polish :-)
*/
BayesianNetwork network = new BayesianNetwork();
BayesianEvent WadliwyElement = network.CreateEvent("wadliwy_element");
BayesianEvent A1 = network.CreateEvent("wadliwy_element_zaklad_A1");
BayesianEvent A2 = network.CreateEvent("wadliwy_element_zaklad_A2");
BayesianEvent A3 = network.CreateEvent("wadliwy_element_zaklad_A3");
BayesianEvent A4 = network.CreateEvent("wadliwy_element_zaklad_A4");
network.CreateDependency(WadliwyElement, A1, A2, A3, A4);
network.FinalizeStructure();
WadliwyElement?.Table?.AddLine(0.1083, true);
A1?.Table.AddLine(0.069, true, true);
A1?.Table.AddLine(1 - 0.069, true, false);
A2?.Table.AddLine(0.277, true, true);
A2?.Table.AddLine(1 - 0.277, true, false);
A3?.Table.AddLine(0.007, true, true);
A3?.Table.AddLine(1 - 0.007, true, false);
A4?.Table.AddLine(0.646, true, true);
A4?.Table.AddLine(1 - 0.646, true, false);
network.Validate();
Console.WriteLine(network.ToString() + "\n");
Console.WriteLine($"Liczba parametrów: {network.CalculateParameterCount()}");
EnumerationQuery query = new EnumerationQuery(network);
query.DefineEventType(WadliwyElement, EventType.Evidence);
query.DefineEventType(A1, EventType.Outcome);
query.DefineEventType(A2, EventType.Evidence);
query.DefineEventType(A3, EventType.Evidence);
query.DefineEventType(A4, EventType.Evidence);
query.SetEventValue(WadliwyElement, false);
query.SetEventValue(A1, false);
query.SetEventValue(A2, false);
query.SetEventValue(A3, false);
query.SetEventValue(A4, false);
query.Execute();
Console.WriteLine(query.ToString());
}
public void Execute(IExampleInterface app)
{
BayesianNetwork network = new BayesianNetwork();
BayesianEvent grass = network.CreateEvent("grass");
BayesianEvent sprinkler = network.CreateEvent("sprinkler");
BayesianEvent rain = network.CreateEvent("rain");
BayesianEvent DidRain = network.CreateEvent("did_rain");
BayesianEvent SprinklerOn = network.CreateEvent("sprinkler_on");
network.CreateDependency(rain, DidRain);
network.CreateDependency(sprinkler, SprinklerOn);
network.FinalizeStructure();
// build the truth tales
rain.Table.AddLine(0.35, true);
// 80% of the time they were right
DidRain.Table.AddLine(0.80, false, true);
// 20% of the time they were wrong
DidRain.Table.AddLine(0.20, true, true);
sprinkler.Table.AddLine(.65, true);
// 60% of the time they were right
SprinklerOn.Table.AddLine(.40, true, true);
// 40% of the time they were wrong
SprinklerOn.Table.AddLine(.60, false, true);
// validate the network
network.Validate();
// display basic stats
Console.WriteLine(network.ToString());
Console.WriteLine("Parameter count: " + network.CalculateParameterCount());
EnumerationQuery query = new EnumerationQuery(network);
//SamplingQuery query = new SamplingQuery(network);
query.DefineEventType(SprinklerOn, EventType.Evidence);
query.DefineEventType(sprinkler, EventType.Outcome);
query.DefineEventType(DidRain, EventType.Evidence);
query.DefineEventType(rain, EventType.Outcome);
query.Execute();
Console.WriteLine(query.ToString());
}
public void TestEnumeration1()
{
BayesianNetwork network = new BayesianNetwork();
BayesianEvent a = network.CreateEvent("a");
BayesianEvent b = network.CreateEvent("b");
network.CreateDependency(a, b);
network.FinalizeStructure();
a.Table.AddLine(0.5, true); // P(A) = 0.5
b.Table.AddLine(0.2, true, true); // p(b|a) = 0.2
b.Table.AddLine(0.8, true, false); // p(b|~a) = 0.8
network.Validate();
EnumerationQuery query = new EnumerationQuery(network);
query.DefineEventType(a, EventType.Evidence);
query.DefineEventType(b, EventType.Outcome);
query.SetEventValue(b, true);
query.SetEventValue(a, true);
query.Execute();
TestPercent(query.Probability, 20);
}
/// <summary>
/// Construct a Bayesian network.
/// </summary>
public BayesianNetwork()
{
Query = new EnumerationQuery(this);
}
/// <inheritdoc/>
public Object Read(Stream istream)
{
BayesianNetwork result = new BayesianNetwork();
EncogReadHelper input = new EncogReadHelper(istream);
EncogFileSection section;
String queryType = "";
String queryStr = "";
String contentsStr = "";
while ((section = input.ReadNextSection()) != null)
{
if (section.SectionName.Equals("BAYES-NETWORK") &&
section.SubSectionName.Equals("BAYES-PARAM"))
{
IDictionary <String, String> p = section.ParseParams();
queryType = p["queryType"];
queryStr = p["query"];
contentsStr = p["contents"];
}
if (section.SectionName.Equals("BAYES-NETWORK") &&
section.SubSectionName.Equals("BAYES-TABLE"))
{
result.Contents = contentsStr;
// first, define relationships (1st pass)
foreach (String line in section.Lines)
{
result.DefineRelationship(line);
}
result.FinalizeStructure();
// now define the probabilities (2nd pass)
foreach (String line in section.Lines)
{
result.DefineProbability(line);
}
}
if (section.SectionName.Equals("BAYES-NETWORK") &&
section.SubSectionName.Equals("BAYES-PROPERTIES"))
{
IDictionary <String, String> paras = section.ParseParams();
EngineArray.PutAll(paras, result.Properties);
}
}
// define query, if it exists
if (queryType.Length > 0)
{
IBayesianQuery query = null;
if (queryType.Equals("EnumerationQuery"))
{
query = new EnumerationQuery(result);
}
else
{
query = new SamplingQuery(result);
}
if (query != null && queryStr.Length > 0)
{
result.Query = query;
result.DefineClassificationStructure(queryStr);
}
}
return(result);
}
