public ItemAverageRecommender(IDataModel dataModel) : base(dataModel)
{
this.itemAverages = new FastByIDMap <IRunningAverage>();
this.refreshHelper = new RefreshHelper(() => {
buildAverageDiffs();
});
refreshHelper.AddDependency(dataModel);
buildAverageDiffs();
}
public AbstractUserNeighborhood(UserSimilarity userSimilarity, DataModel dataModel, double samplingRate)
{
this.userSimilarity = userSimilarity;
this.dataModel = dataModel;
this.samplingRate = samplingRate;
this.refreshHelper = new RefreshHelper(null);
this.refreshHelper.addDependency(this.dataModel);
this.refreshHelper.addDependency(this.userSimilarity);
}
private void DoRefreshColumns()
{
var list = NodesTableColumns = new ObservableCollection <NodeDbTableColumnsToExcel>();
RefreshHelper.RefreshTableColumns(eventAgg, root, ref list);
NodesTableColumns = list;
// slow?? :-)
SetDescShown(AreDescsShown);
}
public SupplierManagementCtrl(IManagementService managemntService) : base()
{
_managementService = managemntService;
InitializeComponent();
this.Dock = DockStyle.Fill;
this.gridControl1.DataSource = _managementService.GetAllSuppliers();
colId.Visible = false;
_refreshHelper = new RefreshHelper(gridView1, nameof(parentModel.Id).ToString());
}
/// Creates this on top of the given {@link UserSimilarity}.
/// The cache size is capped by the given size.
public CachingUserSimilarity(IUserSimilarity similarity, int maxCacheSize)
{
//Preconditions.checkArgument(similarity != null, "similarity is null");
this.similarity = similarity;
this.similarityCache = new Cache <Tuple <long, long>, Double>(new SimilarityRetriever(similarity), maxCacheSize);
this.refreshHelper = new RefreshHelper(() => {
similarityCache.Clear();
});
refreshHelper.AddDependency(similarity);
}
public AbstractUserNeighborhood(IUserSimilarity userSimilarity, IDataModel dataModel, double samplingRate)
{
//Preconditions.checkArgument(userSimilarity != null, "userSimilarity is null");
//Preconditions.checkArgument(dataModel != null, "dataModel is null");
//Preconditions.checkArgument(samplingRate > 0.0 && samplingRate <= 1.0, "samplingRate must be in (0,1]");
this.userSimilarity = userSimilarity;
this.dataModel = dataModel;
this.samplingRate = samplingRate;
this.refreshHelper = new RefreshHelper(null);
this.refreshHelper.AddDependency(this.dataModel);
this.refreshHelper.AddDependency(this.userSimilarity);
}
public ItemUserAverageRecommender(IDataModel dataModel) : base(dataModel)
{
this.itemAverages = new FastByIDMap <IRunningAverage>();
this.userAverages = new FastByIDMap <IRunningAverage>();
this.overallAveragePrefValue = new FullRunningAverage();
//this.buildAveragesLock = new ReentrantReadWriteLock();
this.refreshHelper = new RefreshHelper(() => {
buildAverageDiffs();
});
refreshHelper.AddDependency(dataModel);
buildAverageDiffs();
}
/// <p>
/// Creates a possibly weighted {@link AbstractSimilarity}.
/// </p>
public AbstractSimilarity(IDataModel dataModel, Weighting weighting, bool centerData) : base(dataModel)
{
this.weighted = weighting == Weighting.WEIGHTED;
this.centerData = centerData;
this.cachedNumItems = dataModel.GetNumItems();
this.cachedNumUsers = dataModel.GetNumUsers();
this.refreshHelper = new RefreshHelper(() => {
cachedNumItems = dataModel.GetNumItems();
cachedNumUsers = dataModel.GetNumUsers();
}
);
}
public ContractManagementCtrl(IManagementService managemntService)
{
_managemntService = managemntService;
InitializeComponent();
this.Dock = DockStyle.Fill;
this.gridControl1.DataSource = _managemntService.GetAllPoNumbers();
colPOId.Visible = false;
RenderCommonHelper.SetColNotEditable(colCreateDate);
RenderCommonHelper.SetColNotEditable(colUpdateDate);
_refreshHelper = new RefreshHelper(gridView1, nameof(parentModel.PoNumber).ToString());
}
public CachingUserSimilarity(UserSimilarity similarity, int maxCacheSize)
{
Action refreshRunnable = null;
this.similarity = similarity;
this.similarityCache = new Cache <Tuple <long, long>, double>(new SimilarityRetriever(similarity), maxCacheSize);
if (refreshRunnable == null)
{
refreshRunnable = () => this.similarityCache.clear();
}
this.refreshHelper = new RefreshHelper(refreshRunnable);
this.refreshHelper.addDependency(similarity);
}
private void DoRefresh()
{
var list = NodesTable = new ObservableCollection <NodeDbTableToExcel>();
RefreshHelper.RefreshTables(eventAgg, root, ref list);
NodesTable = list;
// slow?? :-)
SetDescShown(AreDescsShown);
//third tree view... (Tables-Columns -> Excels -> Sheets)
DoRefreshColumns();
}
protected AbstractFactorizer(DataModel dataModel)
{
Action refreshRunnable = null;
this.dataModel = dataModel;
this.buildMappings();
if (refreshRunnable == null)
{
refreshRunnable = () => this.buildMappings();
}
this.refreshHelper = new RefreshHelper(refreshRunnable);
this.refreshHelper.addDependency(dataModel);
}
public ItemAverageRecommender(DataModel dataModel)
: base(dataModel)
{
Action refreshRunnable = null;
this.itemAverages = new FastByIDMap <RunningAverage>();
if (refreshRunnable == null)
{
refreshRunnable = () => this.buildAverageDiffs();
}
this.refreshHelper = new RefreshHelper(refreshRunnable);
this.refreshHelper.addDependency(dataModel);
this.buildAverageDiffs();
}
private async Task <bool> DisableRefresh(IDocumentStore store)
{
var config = new RefreshConfiguration
{
Disabled = true,
RefreshFrequencyInSec = 100,
};
await RefreshHelper.SetupExpiration(store, Server.ServerStore, config);
var database = await Databases.GetDocumentDatabaseInstanceFor(store);
return(database.ExpiredDocumentsCleaner != null);
}
public InDeliveryCtrl(IStockService stockService)
{
_stockService = stockService;
_refreshHelper = new RefreshHelper(gridView1, nameof(parentModel.OutStockNumber).ToString());
InitializeComponent();
this.Dock = DockStyle.Fill;
//this.gridControl1.DataSource = _stockService.GetAllOutInstock();
RenderCommonHelper.SetColNotEditable(colOutStockCategory);
RenderCommonHelper.SetColNotEditable(colRequestNumber);
RenderCommonHelper.SetColNotEditable(colAddress);
RenderCommonHelper.SetColNotEditable(colContractNumber);
}
private void Form1_Load(object sender, System.EventArgs e)
{
helper = new RefreshHelper(gridView1, "ID");
DataSet dataSet11 = new DataSet();
dataSet11.Tables.Add(GetCustomerDataTable());
dataSet11.Tables.Add(GetPersonDataTable());
DataColumn keyColumn = dataSet11.Tables["Customers"].Columns["ID"];
DataColumn foreignKeyColumn = dataSet11.Tables["Persons"].Columns["ID"];
dataSet11.Relations.Add("CustomersPersons", keyColumn, foreignKeyColumn);
gridControl1.DataSource = dataSet11.Tables["Customers"];
gridControl1.ForceInitialize();
}
public GenericUserBasedRecommender(IDataModel dataModel,
IUserNeighborhood neighborhood,
IUserSimilarity similarity) : base(dataModel)
{
//Preconditions.checkArgument(neighborhood != null, "neighborhood is null");
this.neighborhood = neighborhood;
this.similarity = similarity;
this.refreshHelper = new RefreshHelper(() => {
capper = buildCapper();
});
refreshHelper.AddDependency(dataModel);
refreshHelper.AddDependency(similarity);
refreshHelper.AddDependency(neighborhood);
capper = buildCapper();
}
public CachingRecommender(IRecommender recommender)
{
//Preconditions.checkArgument(recommender != null, "recommender is null");
this.recommender = recommender;
maxHowMany = new int[] { 1 };
// Use "num users" as an upper limit on cache size. Rough guess.
int numUsers = recommender.GetDataModel().GetNumUsers();
recommendationsRetriever = new RecommendationRetriever(this);
recommendationCache = new Cache <long, Recommendations>(recommendationsRetriever, numUsers);
estimatedPrefCache = new Cache <Tuple <long, long>, float>(new EstimatedPrefRetriever(this), numUsers);
refreshHelper = new RefreshHelper(() => {
clear();
});
refreshHelper.AddDependency(recommender);
}
public GenericUserBasedRecommender(DataModel dataModel, UserNeighborhood neighborhood, UserSimilarity similarity)
: base(dataModel)
{
Action refreshRunnable = null;
this.neighborhood = neighborhood;
this.similarity = similarity;
if (refreshRunnable == null)
{
refreshRunnable = () => this.capper = this.buildCapper();
}
this.refreshHelper = new RefreshHelper(refreshRunnable);
this.refreshHelper.addDependency(dataModel);
this.refreshHelper.addDependency(similarity);
this.refreshHelper.addDependency(neighborhood);
this.capper = this.buildCapper();
}
/**
* @param dataModel
* {@link DataModel} which provides users
* @param clusterSimilarity
* {@link ClusterSimilarity} used to compute cluster similarity
* @param numClusters
* desired number of clusters to create
* @throws IllegalArgumentException
* if arguments are {@code null}, or {@code numClusters} is less than 2
*/
public TreeClusteringRecommender2(DataModel dataModel, ClusterSimilarity clusterSimilarity, int numClusters)
: base(dataModel)
{
if (numClusters < 2)
{
throw new Exception("numClusters must be at least 2");
}
//Preconditions.checkArgument(numClusters >= 2, "numClusters must be at least 2");
this.clusterSimilarity = clusterSimilarity;//Preconditions.checkNotNull(clusterSimilarity);
this.numClusters = numClusters;
this.clusteringThreshold = Double.NaN;
this.clusteringByThreshold = false;
this.refreshHelper = new RefreshHelper(buildClusters);
refreshHelper.addDependency(dataModel);
refreshHelper.addDependency(clusterSimilarity);
buildClusters();
}
public CachingRecommender(Recommender recommender)
{
Action refreshRunnable = null;
this.recommender = recommender;
this.maxHowMany = new int[] { 1 };
int maxEntries = recommender.getDataModel().getNumUsers();
this.recommendationsRetriever = new RecommendationRetriever(this);
this.recommendationCache = new Cache <long, Recommendations>(this.recommendationsRetriever, maxEntries);
this.estimatedPrefCache = new Cache <Tuple <long, long>, float>(new EstimatedPrefRetriever(this), maxEntries);
if (refreshRunnable == null)
{
refreshRunnable = () => this.clear();
}
this.refreshHelper = new RefreshHelper(refreshRunnable);
this.refreshHelper.addDependency(recommender);
}
public GenericItemBasedRecommender(DataModel dataModel, ItemSimilarity similarity, CandidateItemsStrategy candidateItemsStrategy, MostSimilarItemsCandidateItemsStrategy mostSimilarItemsCandidateItemsStrategy)
: base(dataModel, candidateItemsStrategy)
{
Action refreshRunnable = null;
this.similarity = similarity;
this.mostSimilarItemsCandidateItemsStrategy = mostSimilarItemsCandidateItemsStrategy;
if (refreshRunnable == null)
{
refreshRunnable = () => this.capper = this.buildCapper();
}
this.refreshHelper = new RefreshHelper(refreshRunnable);
this.refreshHelper.addDependency(dataModel);
this.refreshHelper.addDependency(similarity);
this.refreshHelper.addDependency(candidateItemsStrategy);
this.refreshHelper.addDependency(mostSimilarItemsCandidateItemsStrategy);
this.capper = this.buildCapper();
}
public MemoryDiffStorage(DataModel dataModel,
Weighting stdDevWeighted,
long maxEntries)
{
//Preconditions.checkArgument(dataModel != null, "dataModel is null");
//Preconditions.checkArgument(dataModel.getNumItems() >= 1, "dataModel has no items");
//Preconditions.checkArgument(maxEntries > 0L, "maxEntries must be positive");
this.dataModel = dataModel;
this.stdDevWeighted = stdDevWeighted == Weighting.WEIGHTED;
this.maxEntries = maxEntries;
this.averageDiffs = new FastByIDMap <FastByIDMap <RunningAverage> >();
this.averageItemPref = new FastByIDMap <RunningAverage>();
this.buildAverageDiffsLock = new ReaderWriterLockSlim();
this.allRecommendableItemIDs = new FastIDSet(dataModel.getNumItems());
this.refreshHelper = new RefreshHelper(buildAverageDiffs);
refreshHelper.addDependency(dataModel);
buildAverageDiffs();
}
public InStockCtrl(IStockService stockService)
{
_stockService = stockService;
_refreshHelper = new RefreshHelper(gridView1, nameof(parentModel.InStockNumber).ToString());
InitializeComponent();
this.Dock = DockStyle.Fill;
//this.gridControl1.DataSource = _stockService.GetAllInstock();
RenderCommonHelper.SetColNotEditable(colInStockNumber);
RenderCommonHelper.SetColNotEditable(colPoNumber);
RenderCommonHelper.SetColNotEditable(colPurchaseNumber);
RenderCommonHelper.SetColNotEditable(colRequestNumber);
RenderCommonHelper.SetColNotEditable(colContractNumber);
RenderCommonHelper.SetColNotEditable(colSupplierName);
RenderCommonHelper.SetColNotEditable(colInStockCategory);
RenderCommonHelper.SetColNotEditable(colCreateDate);
}
public AbstractSimilarity(DataModel dataModel, Weighting weighting, bool centerData)
: base(dataModel)
{
Action refreshRunnable = null;
this.weighted = weighting == Weighting.WEIGHTED;
this.centerData = centerData;
this.cachedNumItems = dataModel.getNumItems();
this.cachedNumUsers = dataModel.getNumUsers();
if (refreshRunnable == null)
{
refreshRunnable = delegate
{
this.cachedNumItems = dataModel.getNumItems();
this.cachedNumUsers = dataModel.getNumUsers();
};
}
this.refreshHelper = new RefreshHelper(refreshRunnable);
}
/**
* @param dataModel
* {@link DataModel} which provides users
* @param clusterSimilarity
* {@link ClusterSimilarity} used to compute cluster
* similarity
* @param clusteringThreshold
* clustering similarity threshold; clusters will be aggregated into larger clusters until the next
* two nearest clusters' similarity drops below this threshold
* @throws IllegalArgumentException
* if arguments are {@code null}, or {@code clusteringThreshold} is {@link Double#NaN}
*/
public TreeClusteringRecommender2(DataModel dataModel,
ClusterSimilarity clusterSimilarity,
double clusteringThreshold)
: base(dataModel)
{
// Preconditions.checkArgument(!Double.isNaN(clusteringThreshold), "clusteringThreshold must not be NaN");
if (Double.IsNaN(clusteringThreshold))
{
throw new Exception("clusteringThreshold must not be NaN");
}
this.clusterSimilarity = clusterSimilarity; //Preconditions.checkNotNull(clusterSimilarity);
this.numClusters = int.MinValue; // Integer.MIN_VALUE;
this.clusteringThreshold = clusteringThreshold;
this.clusteringByThreshold = true;
this.refreshHelper = new RefreshHelper(buildClusters);
refreshHelper.addDependency(dataModel);
refreshHelper.addDependency(clusterSimilarity);
buildClusters();
}
/**
* @param dataModel
* {@link DataModel} which provides users
* @param clusterSimilarity
* {@link ClusterSimilarity} used to compute cluster similarity
* @param clusteringThreshold
* clustering similarity threshold; clusters will be aggregated into larger clusters until the next
* two nearest clusters' similarity drops below this threshold
* @param samplingRate
* percentage of all cluster-cluster pairs to consider when finding next-most-similar clusters.
* Decreasing this value from 1.0 can increase performance at the cost of accuracy
* @throws IllegalArgumentException
* if arguments are {@code null}, or {@code clusteringThreshold} is {@link Double#NaN},
* or samplingRate is {@link Double#NaN} or nonpositive or greater than 1.0
*/
public TreeClusteringRecommender(DataModel dataModel,
ClusterSimilarity clusterSimilarity,
double clusteringThreshold,
double samplingRate)
: base(dataModel)
{
//Preconditions.checkArgument(!Double.IsNaN(clusteringThreshold), "clusteringThreshold must not be NaN");
//Preconditions.checkArgument(samplingRate > 0.0 && samplingRate <= 1.0, "samplingRate is invalid: %f", samplingRate);
random = RandomUtils.getRandom();
this.clusterSimilarity = clusterSimilarity; //Preconditions.checkNotNull(clusterSimilarity);
this.numClusters = int.MinValue; //Integer.MIN_VALUE;
this.clusteringThreshold = clusteringThreshold;
this.clusteringByThreshold = true;
this.samplingRate = samplingRate;
this.refreshHelper = new RefreshHelper(buildClusters);
refreshHelper.addDependency(dataModel);
refreshHelper.addDependency(clusterSimilarity);
buildClusters();
}
public GenericItemBasedRecommender(IDataModel dataModel,
IItemSimilarity similarity,
ICandidateItemsStrategy candidateItemsStrategy,
IMostSimilarItemsCandidateItemsStrategy mostSimilarItemsCandidateItemsStrategy) :
base(dataModel, candidateItemsStrategy)
{
//Preconditions.checkArgument(similarity != null, "similarity is null");
this.similarity = similarity;
//Preconditions.checkArgument(mostSimilarItemsCandidateItemsStrategy != null,
// "mostSimilarItemsCandidateItemsStrategy is null");
this.mostSimilarItemsCandidateItemsStrategy = mostSimilarItemsCandidateItemsStrategy;
this.refreshHelper = new RefreshHelper(() => {
capper = buildCapper();
});
refreshHelper.AddDependency(dataModel);
refreshHelper.AddDependency(similarity);
refreshHelper.AddDependency(candidateItemsStrategy);
refreshHelper.AddDependency(mostSimilarItemsCandidateItemsStrategy);
capper = buildCapper();
}
/**
* @param dataModel
* {@link DataModel} which provdes users
* @param clusterSimilarity
* {@link ClusterSimilarity} used to compute cluster similarity
* @param numClusters
* desired number of clusters to create
* @param samplingRate
* percentage of all cluster-cluster pairs to consider when finding next-most-similar clusters.
* Decreasing this value from 1.0 can increase performance at the cost of accuracy
* @throws IllegalArgumentException
* if arguments are {@code null}, or {@code numClusters} is less than 2, or samplingRate
* is {@link Double#NaN} or nonpositive or greater than 1.0
*/
public TreeClusteringRecommender(DataModel dataModel,
ClusterSimilarity clusterSimilarity,
int numClusters,
double samplingRate)
: base(dataModel)
{
//Preconditions.checkArgument(numClusters >= 2, "numClusters must be at least 2");
//Preconditions.checkArgument(samplingRate > 0.0 && samplingRate <= 1.0,
// "samplingRate is invalid: %f", samplingRate);
random = RandomUtils.getRandom();
this.clusterSimilarity = clusterSimilarity;//Preconditions.checkNotNull(clusterSimilarity);
this.numClusters = numClusters;
this.clusteringThreshold = Double.NaN;
this.clusteringByThreshold = false;
this.samplingRate = samplingRate;
this.refreshHelper = new RefreshHelper(buildClusters);
refreshHelper.addDependency(dataModel);
refreshHelper.addDependency(clusterSimilarity);
buildClusters();
}
public PurchaseApplicationCtrl(IPurchaseService purchaseService, IManagementService managementService)
{
_purchaseService = purchaseService;
_managementService = managementService;
InitializeComponent();
this.Dock = DockStyle.Fill;
SetCurrentRequestCategory(RequestCategoriesEnum.材料需求);
RenderCommonHelper.SetColNotEditable(colApplicationNumber);
RenderCommonHelper.SetColNotEditable(colRequestHeaderNumber);
RenderCommonHelper.SetColNotEditable(colPoNumber);
RenderCommonHelper.SetColNotEditable(colTotalApplied);
RenderCommonHelper.SetColNotEditable(colTotalConfirmed);
RenderCommonHelper.SetColNotEditable(colAuditStatus);
RenderCommonHelper.SetColNotEditable(colStatus);
RenderCommonHelper.SetColNotEditable(colCompletePercentage);
RenderCommonHelper.SetColNotEditable(colCreateDate);
RenderCommonHelper.SetColNotEditable(colUpdateDate);
colCompletePercentage.DisplayFormat.FormatType = FormatType.Numeric; colCompletePercentage.DisplayFormat.FormatString = "P";
_refreshHelper = new RefreshHelper(gridView1, nameof(parentModel.ApplicationNumber));
}
