private void BestConfiguration(ILearner <TSample> learner) { var predictions = _cache.ContainsKey(learner.UniqueId) ? _cache[learner.UniqueId] : (_cache[learner.UniqueId] = GetPredictions(learner)); var best = new LayerHolder(float.PositiveInfinity, null, null); var sampleCount = predictions.Count; var samplesProcessed = 0; foreach (var p in predictions) { best = BestLayerSetup(learner.WithConfiguration(p.Key), p.Value, best); SetBest(best); if (_cancellation.IsCancellationRequested) { return; } if (_progress != null) { samplesProcessed++; _progress.Report(Tuple.Create("Finding best setup for \"" + learner.UniqueId + "\"", samplesProcessed * 100 / sampleCount)); } } //Parallel.ForEach( // predictions, // () => new LayerHolder(float.PositiveInfinity, null, null), // (p, s, best) => BestLayerSetup(learner.WithConfiguration(p.Key), p.Value, best), // SetBest //); }
/// <summary> /// Determines whether [is valid with employment support] [the specified candidate]. /// </summary> /// <param name="candidate">The candidate.</param> /// <returns> /// <c>true</c> if [is valid with employment support] [the specified candidate]; otherwise, <c>false</c>. /// </returns> public bool IsValidWithEmploymentSupport(ILearner candidate) { var lds = candidate.LearningDeliveries.AsSafeReadOnlyList(); var les = candidate.LearnerEmploymentStatuses.AsSafeReadOnlyList(); return(lds.Any(d => IsAdultSkills(d) && IsValidWithEmploymentSupport(les, d))); }
public LearnerView(ILearner learner) { ///if (learner == null) throw new ArgumentNullException(); ///if (learner.UserName == null) throw new ArgumentNullException(); this.learner = learner; }
/// <summary> /// Determines whether [is adult funded unemployed with other state benefits] [the specified candidate]. /// </summary> /// <param name="candidate">The candidate.</param> /// <returns> /// <c>true</c> if [is adult funded unemployed with other state benefits] [the specified candidate]; otherwise, <c>false</c>. /// </returns> public bool IsAdultFundedUnemployedWithOtherStateBenefits(ILearner candidate) { It.IsNull(candidate) .AsGuard <ArgumentNullException>(nameof(candidate)); var lds = candidate.LearningDeliveries.AsSafeReadOnlyList(); var les = candidate.LearnerEmploymentStatuses.AsSafeReadOnlyList(); /* * if * // is adult skills * LearningDelivery.FundModel = 35 * * // is umemployed (not employed, seeking and available or otherwise) * and LearnerEmploymentStatus.EmpStat = 11 or 12 for the latest Employment Status on (or before) the LearningDelivery.LearnStartDate * * // in receipt of another benefit. * and ((Monitoring.EmploymentStatus.ESMType = BSI and Monitoring.EmploymentStatus.ESMCode = 3) * or * // in receipt of universal credit. * (Monitoring.EmploymentStatus.ESMType = BSI and Monitoring.EmploymentStatus.ESMCode = 4 * // is learning delivery monitored * and LearningDeliveryFAM.LearnDelFAMType = LDM * // and not mandated to skills training * and LearningDeliveryFAM.LearnDelFAMCode <> 318)) * * set to Y, * otherwise set to N */ return(lds.Any(d => IsAdultSkills(d) && IsNotEmployed(les, d, () => ConfirmMonitoringAndMandation(d.LearningDeliveryFAMs.AsSafeReadOnlyList())))); }
internal Layer(ILearner <TSample> learner, float coefPos, float coefNeg, float threshold) { _learner = learner; CoefPos = coefPos; CoefNeg = coefNeg; Threshold = threshold; }
/// <summary> /// Determines whether [is adult skills unemployed with benefits] [the specified candidate]. /// </summary> /// <param name="candidate">The candidate.</param> /// <returns> /// <c>true</c> if [is adult skills unemployed with benefits] [the specified candidate]; otherwise, <c>false</c>. /// </returns> public bool IsAdultFundedUnemployedWithBenefits(ILearner candidate) { It.IsNull(candidate) .AsGuard <ArgumentNullException>(nameof(candidate)); /* * if * // is adult skills * LearningDelivery.FundModel = 35 * // and has valid employment status * and LearnerEmploymentStatus.EmpStat = 10, 11, 12 or 98 * // and in receipt of support at the time of starting the learning aim * and (EmploymentStatusMonitoring.ESMType = BSI and EmploymentStatusMonitoring.ESMCode = 1 or 2) * (for the learner's Employment status on the LearningDelivery.LearnStartDate of the learning aim) * or * // or is not employed, and in receipt of benefits * LearnerEmploymentStatus.EmpStat = 11 or 12 * and (EmploymentStatusMonitoring.ESMType = BSI and EmploymentStatusMonitoring.ESMCode = 3 or 4) * or * // or is employed with workng short hours and in receipt of support * LearnerEmploymentStatus.EmpStat = 10 * and (EmploymentStatusMonitoring.ESMType = EII and EmploymentStatusMonitoring.ESMCode = 2, 5 or 6) * and (EmploymentStatusMonitoring.ESMType = BSI and EmploymentStatusMonitoring.ESMCode = 3 or 4) * set to Y, * otherwise set to N */ return(IsValidWithEmploymentSupport(candidate) || IsNotEmployedWithBenefits(candidate) || IsEmployedWithSupport(candidate)); }
public LearningDeliveryHE BuildLearningDeliveryHERecord(int ukprn, ILearner learner, ILearningDelivery learningDelivery) { return(new LearningDeliveryHE { AimSeqNumber = learningDelivery.AimSeqNumber, UKPRN = ukprn, LearnRefNumber = learner.LearnRefNumber, DOMICILE = learningDelivery.LearningDeliveryHEEntity.DOMICILE, ELQ = learningDelivery.LearningDeliveryHEEntity.ELQNullable, FUNDCOMP = learningDelivery.LearningDeliveryHEEntity.FUNDCOMP, FUNDLEV = learningDelivery.LearningDeliveryHEEntity.FUNDLEV, GROSSFEE = learningDelivery.LearningDeliveryHEEntity.GROSSFEENullable, HEPostCode = learningDelivery.LearningDeliveryHEEntity.HEPostCode, MODESTUD = learningDelivery.LearningDeliveryHEEntity.MODESTUD, MSTUFEE = learningDelivery.LearningDeliveryHEEntity.MSTUFEE, NETFEE = learningDelivery.LearningDeliveryHEEntity.NETFEENullable, NUMHUS = learningDelivery.LearningDeliveryHEEntity.NUMHUS, PCFLDCS = learningDelivery.LearningDeliveryHEEntity.PCFLDCSNullable, PCOLAB = learningDelivery.LearningDeliveryHEEntity.PCOLABNullable, PCSLDCS = learningDelivery.LearningDeliveryHEEntity.PCSLDCSNullable, PCTLDCS = learningDelivery.LearningDeliveryHEEntity.PCTLDCSNullable, QUALENT3 = learningDelivery.LearningDeliveryHEEntity.QUALENT3, SEC = learningDelivery.LearningDeliveryHEEntity.SECNullable, SOC2000 = learningDelivery.LearningDeliveryHEEntity.SOC2000Nullable, SPECFEE = learningDelivery.LearningDeliveryHEEntity.SPECFEE, SSN = learningDelivery.LearningDeliveryHEEntity.SSN, STULOAD = learningDelivery.LearningDeliveryHEEntity.STULOADNullable, TYPEYR = learningDelivery.LearningDeliveryHEEntity.TYPEYR, UCASAPPID = learningDelivery.LearningDeliveryHEEntity.UCASAPPID, YEARSTU = learningDelivery.LearningDeliveryHEEntity.YEARSTU }); }
public static LearningDelivery BuildValidLearningDelivery(int ukprn, ILearner learner, ILearningDelivery learningDelivery) { return(new LearningDelivery { UKPRN = ukprn, LearnRefNumber = learner.LearnRefNumber, LearnAimRef = learningDelivery.LearnAimRef, AimSeqNumber = learningDelivery.AimSeqNumber, AchDate = learningDelivery.AchDateNullable, AddHours = learningDelivery.AddHoursNullable, AimType = learningDelivery.AimType, CompStatus = learningDelivery.CompStatus, ConRefNumber = learningDelivery.ConRefNumber, DelLocPostCode = learningDelivery.DelLocPostCode, EmpOutcome = learningDelivery.EmpOutcomeNullable, EPAOrgID = learningDelivery.EPAOrgID, FundModel = learningDelivery.FundModel, FworkCode = learningDelivery.FworkCodeNullable, LearnActEndDate = learningDelivery.LearnActEndDateNullable, LearnPlanEndDate = learningDelivery.LearnPlanEndDate, LearnStartDate = learningDelivery.LearnStartDate, OrigLearnStartDate = learningDelivery.OrigLearnStartDateNullable, OtherFundAdj = learningDelivery.OtherFundAdjNullable, OutGrade = learningDelivery.OutGrade, Outcome = learningDelivery.OutcomeNullable, PartnerUKPRN = learningDelivery.PartnerUKPRNNullable, PriorLearnFundAdj = learningDelivery.PriorLearnFundAdjNullable, ProgType = learningDelivery.ProgTypeNullable, PwayCode = learningDelivery.PwayCodeNullable, StdCode = learningDelivery.StdCodeNullable, SWSupAimId = learningDelivery.SWSupAimId, WithdrawReason = learningDelivery.WithdrawReasonNullable }); }
public SharpML(MACHINE_TYPE t, string path) { LoadModel(path); // create new type = t; switch (type) { case MACHINE_TYPE.PLAYER: learner = null; break; case MACHINE_TYPE.DECISION_TREE: learner = new RegressionDecisionTreeLearner(); break; case MACHINE_TYPE.RANDOM_FOREST: learner = new RegressionRandomForestLearner(); break; case MACHINE_TYPE.EXTRA_TREES: learner = new RegressionExtremelyRandomizedTreesLearner(); break; case MACHINE_TYPE.ADABOOST: learner = new RegressionAdaBoostLearner(); break; case MACHINE_TYPE.GRAD_SQUARE: learner = new RegressionSquareLossGradientBoostLearner(); break; case MACHINE_TYPE.GRAD_ABSOLUTE: learner = new RegressionAbsoluteLossGradientBoostLearner(); break; case MACHINE_TYPE.GRAD_HUBER: learner = new RegressionHuberLossGradientBoostLearner(); break; case MACHINE_TYPE.GRAD_QUANTILE: learner = new RegressionQuantileLossGradientBoostLearner(); break; case MACHINE_TYPE.NEURAL_NETWORK: NeuralNet net = new NeuralNet(); net.Add(new InputLayer(inputUnits: 4)); net.Add(new DenseLayer(9, Activation.Relu)); net.Add(new DenseLayer(9, Activation.Relu)); net.Add(new SquaredErrorRegressionLayer()); learner = new RegressionNeuralNetLearner(net , loss: new SquareLoss() , iterations: 100 , learningRate: 0.002 , batchSize: 128 ); break; } }
public virtual bool Filter(ILearner learner, FM25Learner fm25Learner) { return(learner != null && fm25Learner != null && FilterStartFund(fm25Learner.StartFund) && FilterFundLine(fm25Learner.FundLine) && learner?.LearningDeliveries?.Any(ld => ld?.LearningDeliveryFAMs?.Any(FilterSOF) == true) == true); }
public Learner BuildValidLearner(int ukprn, ILearner ilrLearner) { return(new Learner { LearnRefNumber = ilrLearner.LearnRefNumber, UKPRN = ukprn, Accom = ilrLearner.AccomNullable, AddLine1 = ilrLearner.AddLine1, AddLine2 = ilrLearner.AddLine2, AddLine3 = ilrLearner.AddLine3, AddLine4 = ilrLearner.AddLine4, ALSCost = ilrLearner.ALSCostNullable, CampId = ilrLearner.CampId, DateOfBirth = ilrLearner.DateOfBirthNullable, Email = ilrLearner.Email, EngGrade = ilrLearner.EngGrade, Ethnicity = ilrLearner.Ethnicity, FamilyName = ilrLearner.FamilyName, GivenNames = ilrLearner.GivenNames, LLDDHealthProb = ilrLearner.LLDDHealthProb, MathGrade = ilrLearner.MathGrade, NINumber = ilrLearner.NINumber, PlanEEPHours = ilrLearner.PlanEEPHoursNullable, PlanLearnHours = ilrLearner.PlanLearnHoursNullable, PMUKPRN = ilrLearner.PMUKPRNNullable, Postcode = ilrLearner.Postcode, PostcodePrior = ilrLearner.PostcodePrior, PrevLearnRefNumber = ilrLearner.PrevLearnRefNumber, PrevUKPRN = ilrLearner.PrevUKPRNNullable, PriorAttain = ilrLearner.PriorAttainNullable, Sex = ilrLearner.Sex, TelNo = ilrLearner.TelNo, ULN = ilrLearner.ULN }); }
public AppsDataMatchMonthEndModel BuildModel(ILearner learner) { return(new AppsDataMatchMonthEndModel() { LearnerReferenceNumber = learner.LearnRefNumber, UniqueLearnerNumber = learner.ULN }); }
private int TLevelPlannedHours(ILearner learner) { return(learner.LearningDeliveries? .Where(ld => ld.AimType == ProgrammeAim && ld.ProgTypeNullable == TLevel) .OrderByDescending(ld => ld.LearnStartDate) .FirstOrDefault() ?.PHoursNullable ?? 0); }
public AppsMonthlyPaymentModel BuildModel(ILearner learner, FM36Learner learnerData) { return(new AppsMonthlyPaymentModel() { LearnerReferenceNumber = learner.LearnRefNumber, UniqueLearnerNumber = learner.ULN }); }
/// <summary> /// Stacking Regression Ensemble Learner. /// Combines several models into a single ensemble model using a top or meta level model to combine the models. /// The bottom level models generates output for the top level model using cross validation. /// Default is 5-fold RandomCrossValidation. /// </summary> /// <param name="learners">Learners in the ensemble</param> /// <param name="metaLearner">Meta learner or top level model for combining the ensemble models</param> /// <param name="includeOriginalFeaturesForMetaLearner">True; the meta learner also receives the original features. /// False; the meta learner only receives the output of the ensemble models as features. Default is true</param> public RegressionStackingEnsembleLearner( IIndexedLearner <double>[] learners, ILearner <double> metaLearner, bool includeOriginalFeaturesForMetaLearner = true) : this(learners, (obs, targets) => metaLearner.Learn(obs, targets), new RandomCrossValidation <double>(5, 42), includeOriginalFeaturesForMetaLearner) { }
public Tld(IObjectModel objectModel, ITracker tracker, ILearner learner, IDetector detector, IOutputStrategy outputStrategy) { _objectModel = objectModel; _tracker = tracker; _learner = learner; _detector = detector; _outputStrategy = outputStrategy; }
public AppsIndicativeEarningsReportModel BuildLineModel( ILearner learner, ILearningDelivery learningDelivery, LearningDelivery fm36DeliveryAttribute, PriceEpisode fm36EpisodeAttribute, LARSLearningDelivery larsLearningDelivery, string notionalEndLevel, bool earliestEpisode, bool hasPriceEpisodes) { DateTime employmentStatusDate = learner.LearnerEmploymentStatuses? .Where(x => x.DateEmpStatApp <= learningDelivery.LearnStartDate).Select(x => x.DateEmpStatApp) .DefaultIfEmpty(DateTime.MinValue).Max() ?? DateTime.MinValue; var model = new AppsIndicativeEarningsReportModel { Learner = learner, ProviderSpecLearnerMonitoring = _ilrModelMapper.MapProviderSpecLearnerMonitorings(learner.ProviderSpecLearnerMonitorings), ProviderSpecDeliveryMonitoring = _ilrModelMapper.MapProviderSpecDeliveryMonitorings(learningDelivery .ProviderSpecDeliveryMonitorings), LearningDeliveryFAMs = _ilrModelMapper.MapLearningDeliveryFAMs(learningDelivery.LearningDeliveryFAMs), LearningDelivery = learningDelivery, LarsLearningDelivery = larsLearningDelivery, EmploymentStatus = learner.LearnerEmploymentStatuses?.SingleOrDefault(x => x.DateEmpStatApp == employmentStatusDate), PriceEpisodeValues = fm36EpisodeAttribute?.PriceEpisodeValues, StandardNotionalEndLevel = notionalEndLevel }; model.EmpStatusMonitoringSmallEmployer = model.EmploymentStatus?.EmploymentStatusMonitorings ?.FirstOrDefault(x => string.Equals(x.ESMType, ReportingConstants.EmploymentStatusMonitoringTypeSEM, StringComparison.OrdinalIgnoreCase))?.ESMCode; model.FundingLineType = GetFundingType(fm36DeliveryAttribute?.LearningDeliveryValues, fm36EpisodeAttribute?.PriceEpisodeValues); model.Fm36LearningDelivery = fm36DeliveryAttribute?.LearningDeliveryValues; if (learningDelivery?.LearningDeliveryFAMs != null) { CalculateApprenticeshipContractTypeFields( learningDelivery, model, fm36DeliveryAttribute, fm36EpisodeAttribute, hasPriceEpisodes); } if (earliestEpisode || !hasPriceEpisodes) { CalculateAppFinTotals(model, learningDelivery); } var isMathsEngLearningDelivery = fm36DeliveryAttribute?.LearningDeliveryValues?.LearnDelMathEng ?? false; model.PeriodisedValues = BuildPeriodisedValuesModel(fm36EpisodeAttribute?.PriceEpisodePeriodisedValues, fm36DeliveryAttribute?.LearningDeliveryPeriodisedValues, isMathsEngLearningDelivery); return(model); }
/// <summary> /// Main static method /// </summary> /// <param name="args">arguments list</param> static void Main(string[] args) { LearnerService learnerService = new LearnerService(); ILearner learner = learnerService.GetCurrentLearner(); LearnerView learnerView = new LearnerView(learner); learnerView.RenderView(); }
public ILearnedImage Learn(ILearner learner, Action <ILearnerConfiguration> configuration) { LearnerConfiguration learnerConfiguration; configuration(learnerConfiguration = new LearnerConfiguration(learner)); _learnedImage = learnerConfiguration.Learn(_exportedImage, learnerConfiguration.Alphabet, learnerConfiguration.Options); return(_learnedImage); }
public override bool Filter(ILearner learner, FM25Learner fm25Learner) { return(learner != null && fm25Learner != null && FilterFundLine(fm25Learner.FundLine) && learner.LearningDeliveries?.Any(ld => ld.FundModel == FundModelConstants.FM25 && ld.LearningDeliveryFAMs?.Any(FilterSOF) == true) == true); }
public void DoStuff() { LearnerService learnerService = new LearnerService(); ILearner learner = learnerService.GetCurrenLearner(); LearnerView view = new LearnerView(learner); view.RenderView(); }
/// <summary> /// Stacking Classification Ensemble Learner. /// Combines several models into a single ensemble model using a top or meta level model to combine the models. /// The bottom level models generates output for the top level model using cross validation. /// </summary> /// <param name="learners">Learners in the ensemble</param> /// <param name="metaLearner">Meta learner or top level model for combining the ensemble models</param> /// <param name="crossValidation">Cross validation method</param> /// <param name="includeOriginalFeaturesForMetaLearner">True; the meta learner also receives the original features. /// False; the meta learner only receives the output of the ensemble models as features. Default is true</param> public ClassificationStackingEnsembleLearner( IIndexedLearner <ProbabilityPrediction>[] learners, ILearner <ProbabilityPrediction> metaLearner, ICrossValidation <ProbabilityPrediction> crossValidation, bool includeOriginalFeaturesForMetaLearner = true) : this(learners, (obs, targets) => metaLearner.Learn(obs, targets), crossValidation, includeOriginalFeaturesForMetaLearner) { }
public bool HasQualifyingOutcome(ILearner learner, IMessage message) { var dps = GetDAndP(learner.LearnRefNumber, message); var delivery = GetLastDelivery(learner); return dps != null && delivery != null && dps.DPOutcomes.NullSafeAny(x => HasQualifyingOutcome(x, delivery.LearnActEndDateNullable.Value)); }
public MainOccupancyModel BuildFm25Model( ILearner learner, ILearningDelivery learningDelivery, FM25Learner fm25Data) { var onProgPayment = fm25Data?.LearnerPeriodisedValues?.SingleOrDefault(attr => string.Equals(attr.AttributeName, Constants.Fm25OnProgrammeAttributeName, StringComparison.OrdinalIgnoreCase)); var onProgPaymentTotal = onProgPayment?.Period1 + onProgPayment?.Period2 + onProgPayment?.Period3 + onProgPayment?.Period4 + onProgPayment?.Period5 + onProgPayment?.Period6 + onProgPayment?.Period7 + onProgPayment?.Period8 + onProgPayment?.Period9 + onProgPayment?.Period10 + onProgPayment?.Period11 + onProgPayment?.Period12; return(new MainOccupancyModel { LearnRefNumber = learner.LearnRefNumber, Uln = learner.ULN, AimSeqNumber = learningDelivery.AimSeqNumber, DateOfBirth = learner.DateOfBirthNullable?.ToString("dd/MM/yyyy"), PostcodePrior = learner.PostcodePrior, PmUkprn = learner.PMUKPRNNullable, CampId = learner.CampId, ProvSpecLearnMonA = learner.ProviderSpecLearnerMonitorings ?.SingleOrDefault(x => string.Equals(x.ProvSpecLearnMonOccur, "A", StringComparison.OrdinalIgnoreCase))?.ProvSpecLearnMon, ProvSpecLearnMonB = learner.ProviderSpecLearnerMonitorings ?.SingleOrDefault(x => string.Equals(x.ProvSpecLearnMonOccur, "B", StringComparison.OrdinalIgnoreCase))?.ProvSpecLearnMon, ApplicWeightFundRate = fm25Data?.NatRate, FundModel = learningDelivery.FundModel, LearnStartDate = fm25Data?.LearnerStartDate?.ToString("dd/MM/yyyy"), LearnPlanEndDate = fm25Data?.LearnerPlanEndDate?.ToString("dd/MM/yyyy"), LearnActEndDate = fm25Data?.LearnerActEndDate?.ToString("dd/MM/yyyy"), FundLine = fm25Data?.FundLine, Period1OnProgPayment = onProgPayment?.Period1, Period2OnProgPayment = onProgPayment?.Period2, Period3OnProgPayment = onProgPayment?.Period3, Period4OnProgPayment = onProgPayment?.Period4, Period5OnProgPayment = onProgPayment?.Period5, Period6OnProgPayment = onProgPayment?.Period6, Period7OnProgPayment = onProgPayment?.Period7, Period8OnProgPayment = onProgPayment?.Period8, Period9OnProgPayment = onProgPayment?.Period9, Period10OnProgPayment = onProgPayment?.Period10, Period11OnProgPayment = onProgPayment?.Period11, Period12OnProgPayment = onProgPayment?.Period12, TotalOnProgPayment = onProgPaymentTotal, TotalEarnedCash = onProgPaymentTotal }); }
public ILearner GetLearner(int result) { ILearner learner = null; switch (result) { case 1: learner = new DownloadWinForm(); break; case 2: learner = new Threads(); break; case 3: learner = new ThreadSafety(); break; case 4: learner = new EasyPools(); break; case 5: learner = new SignalManualReset(); break; case 6: learner = new AsyncIO(); break; case 7: learner = new TPLDemo(); break; case 8: learner = new AsyncAndAwait(); break; case 9: learner = new ConcurrentQueueDemo(); break; case 10: learner = new ConcurrentDictionaryDemo(); break; case 11: learner = new ProduceConsumer(); break; default: learner = new DownloadWinForm(); break; } return(learner); }
/// <summary> /// Raises the validation message. /// </summary> /// <param name="learner">The learner.</param> /// <param name="dAndP">The destination and progression.</param> public void RaiseValidationMessage(ILearner learner, ILearnerDestinationAndProgression dAndP) { var parameters = Collection.Empty <IErrorMessageParameter>(); parameters.Add(_messageHandler.BuildErrorMessageParameter(nameof(learner.ULN), learner.ULN)); parameters.Add(_messageHandler.BuildErrorMessageParameter(PropertyNameConstants.LearningDestinationAndProgressionULN, dAndP.ULN)); parameters.Add(_messageHandler.BuildErrorMessageParameter(PropertyNameConstants.LearningDestinationAndProgressionLearnRefNumber, dAndP.LearnRefNumber)); _messageHandler.Handle(RuleName, learner.LearnRefNumber, null, parameters); }
public ContactPreference BuildContactPreference(int ukprn, ILearner learner, IContactPreference contactPreference) { return(new ContactPreference { UKPRN = ukprn, LearnRefNumber = learner.LearnRefNumber, ContPrefCode = contactPreference.ContPrefCode, ContPrefType = contactPreference.ContPrefType }); }
public LearnerFAM BuildLearnerFAM(int ukprn, ILearner learner, ILearnerFAM fam) { return(new LearnerFAM { UKPRN = ukprn, LearnRefNumber = learner.LearnRefNumber, LearnFAMCode = fam.LearnFAMCode, LearnFAMType = fam.LearnFAMType }); }
public LearnerHE BuildLearnerHE(int ukprn, ILearner learner) { return(new LearnerHE { LearnRefNumber = learner.LearnRefNumber, TTACCOM = learner.LearnerHEEntity.TTACCOMNullable, UKPRN = ukprn, UCASPERID = learner.LearnerHEEntity.UCASPERID }); }
public LearnerHEFinancialSupport BuildLearnerHEFinancialSupport(int ukprn, ILearner learner, ILearnerHEFinancialSupport support) { return(new LearnerHEFinancialSupport { FINAMOUNT = support.FINAMOUNT, FINTYPE = support.FINTYPE, LearnRefNumber = learner.LearnRefNumber, UKPRN = ukprn }); }