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
});
}
