/// <summary>
/// Delete a trained model.
/// Documentation https://developers.google.com/prediction/v1.6/reference/trainedmodels/delete
/// Generation Note: This does not always build corectly. Google needs to standardise things I need to figuer out which ones are wrong.
/// </summary>
/// <param name="service">Authenticated Prediction service.</param>
/// <param name="project">The project associated with the model.</param>
/// <param name="id">The unique name for the predictive model.</param>
public static void Delete(PredictionService service, string project, string id)
{
try
{
// Initial validation.
if (service == null)
{
throw new ArgumentNullException("service");
}
if (project == null)
{
throw new ArgumentNullException(project);
}
if (id == null)
{
throw new ArgumentNullException(id);
}
// Make the request.
service.Trainedmodels.Delete(project, id).Execute();
}
catch (Exception ex)
{
throw new Exception("Request Trainedmodels.Delete failed.", ex);
}
}
private async void Save()
{
try
{
DialogService.ShowLoading("Saving...");
var result = await PredictionService.SavePredictionAsync(new SavePredictionModel()
{
PredictionId = Prediction.PredictionId,
WeekId = Prediction.WeekId,
GameId = Prediction.GameId,
AwayPrediction = AwayPredictedScore.AsInt(0),
HomePrediction = HomePredictedScore.AsInt(0)
});
if (result != null && Prediction != null)
{
MessageBus.Publish(new RefreshPredictionsMessage(result.PredictionId,
Prediction.HomeTeam, Prediction.AwayTeam,
AwayPredictedScore.AsInt(0), HomePredictedScore.AsInt(0)));
await Navigation.PopModalAsync(true);
}
}
catch (Exception ex)
{
DialogService.Alert("Failed to save Prediction");
}
finally
{
DialogService.HideLoading();
}
}
private async Task LoadPredictionsAsync()
{
_predictions = await PredictionService.GetCurrentWeekPredictions();
OnPropertyChanged(nameof(PredictionGroups));
OnPropertyChanged(nameof(NoGames));
}
/// <summary>
/// Submit input and request an output against a hosted model.
/// Documentation https://developers.google.com/prediction/v1.6/reference/hostedmodels/predict
/// Generation Note: This does not always build corectly. Google needs to standardise things I need to figuer out which ones are wrong.
/// </summary>
/// <param name="service">Authenticated Prediction service.</param>
/// <param name="project">The project associated with the model.</param>
/// <param name="hostedModelName">The name of a hosted model.</param>
/// <param name="body">A valid Prediction v1.6 body.</param>
/// <returns>OutputResponse</returns>
public static Output Predict(PredictionService service, string project, string hostedModelName, Input body)
{
try
{
// Initial validation.
if (service == null)
{
throw new ArgumentNullException("service");
}
if (body == null)
{
throw new ArgumentNullException("body");
}
if (project == null)
{
throw new ArgumentNullException(project);
}
if (hostedModelName == null)
{
throw new ArgumentNullException(hostedModelName);
}
// Make the request.
return(service.Hostedmodels.Predict(body, project, hostedModelName).Execute());
}
catch (Exception ex)
{
throw new Exception("Request Hostedmodels.Predict failed.", ex);
}
}
public double getForecastCow(int idCow)
{
predictionService = new PredictionService();
double forecastValue = predictionService.ForecastYieldCow(idCow);
return(forecastValue);
}
/// <summary>
/// Begin training your model
/// Documentation https://developers.google.com/prediction/v1.2/reference/training/insert
/// Generation Note: This does not always build corectly. Google needs to standardise things I need to figuer out which ones are wrong.
/// </summary>
/// <param name="service">Authenticated Prediction service.</param>
/// <param name="body">A valid Prediction v1.2 body.</param>
/// <param name="optional">Optional paramaters.</param>
/// <returns>TrainingResponse</returns>
public static Training Insert(PredictionService service, Training body, TrainingInsertOptionalParms optional = null)
{
try
{
// Initial validation.
if (service == null)
{
throw new ArgumentNullException("service");
}
if (body == null)
{
throw new ArgumentNullException("body");
}
// Building the initial request.
var request = service.Training.Insert(body);
// Applying optional parameters to the request.
request = (TrainingResource.InsertRequest)SampleHelpers.ApplyOptionalParms(request, optional);
// Requesting data.
return(request.Execute());
}
catch (Exception ex)
{
throw new Exception("Request Training.Insert failed.", ex);
}
}
/// <summary>
/// Add new data to a trained model
/// Documentation https://developers.google.com/prediction/v1.2/reference/training/update
/// Generation Note: This does not always build corectly. Google needs to standardise things I need to figuer out which ones are wrong.
/// </summary>
/// <param name="service">Authenticated Prediction service.</param>
/// <param name="data">mybucket/mydata resource in Google Storage</param>
/// <param name="body">A valid Prediction v1.2 body.</param>
/// <returns>TrainingResponse</returns>
public static Training Update(PredictionService service, string data, Update body)
{
try
{
// Initial validation.
if (service == null)
{
throw new ArgumentNullException("service");
}
if (body == null)
{
throw new ArgumentNullException("body");
}
if (data == null)
{
throw new ArgumentNullException(data);
}
// Make the request.
return(service.Training.Update(body, data).Execute());
}
catch (Exception ex)
{
throw new Exception("Request Training.Update failed.", ex);
}
}
/// <summary>
/// Add new data to a trained model.
/// Documentation https://developers.google.com/prediction/v1.6/reference/trainedmodels/update
/// Generation Note: This does not always build corectly. Google needs to standardise things I need to figuer out which ones are wrong.
/// </summary>
/// <param name="service">Authenticated Prediction service.</param>
/// <param name="project">The project associated with the model.</param>
/// <param name="id">The unique name for the predictive model.</param>
/// <param name="body">A valid Prediction v1.6 body.</param>
/// <returns>Insert2Response</returns>
public static Insert2 Update(PredictionService service, string project, string id, Update body)
{
try
{
// Initial validation.
if (service == null)
{
throw new ArgumentNullException("service");
}
if (body == null)
{
throw new ArgumentNullException("body");
}
if (project == null)
{
throw new ArgumentNullException(project);
}
if (id == null)
{
throw new ArgumentNullException(id);
}
// Make the request.
return(service.Trainedmodels.Update(body, project, id).Execute());
}
catch (Exception ex)
{
throw new Exception("Request Trainedmodels.Update failed.", ex);
}
}
public void WhenRunWithAllPossibleMapping_ShouldHavePredictResult()
{
var scores = new Score[]
{
Score.Dragon,
Score.Dragon,
Score.Dragon,
Score.Tiger,
Score.Dragon,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Dragon,
Score.Tiger,
//Score.Tiger,
};
var predictors = new IPredictor[]
{
new SameDifferentPredictor(),
new Anti12Predictor(),
new Anti2Predictor()
};
var resultPredictor = new DummyPredictor();
var predictService = new PredictionService(predictors, resultPredictor);
var tableSize = 8;
var result = predictService.Predict(scores.Select(x => new GameStateInput(x, None)), tableSize, 15)
.GameStatesWithScorePrediction
.ToList();
Assert.AreEqual((int)Math.Pow(2, tableSize), result.Count());
Assert.AreEqual(scores.Count() + 1, result.First().GameStates.Count());
}
public void MakePredictionFromSample_NullArgument_ThrowArgumentException()
{
var predictionService = new PredictionService(_openExchangeClient.Object, _cache.Object);
Assert.Throws <ArgumentException>(() =>
predictionService.MakePredictionFromSample("USD", "VND", DateTime.Today, null));
}
/// <summary>
/// List available models.
/// Documentation https://developers.google.com/prediction/v1.6/reference/trainedmodels/list
/// Generation Note: This does not always build corectly. Google needs to standardise things I need to figuer out which ones are wrong.
/// </summary>
/// <param name="service">Authenticated Prediction service.</param>
/// <param name="project">The project associated with the model.</param>
/// <param name="optional">Optional paramaters.</param>
/// <returns>ListResponse</returns>
public static List List(PredictionService service, string project, TrainedmodelsListOptionalParms optional = null)
{
try
{
// Initial validation.
if (service == null)
{
throw new ArgumentNullException("service");
}
if (project == null)
{
throw new ArgumentNullException(project);
}
// Building the initial request.
var request = service.Trainedmodels.List(project);
// Applying optional parameters to the request.
request = (TrainedmodelsResource.ListRequest)SampleHelpers.ApplyOptionalParms(request, optional);
// Requesting data.
return(request.Execute());
}
catch (Exception ex)
{
throw new Exception("Request Trainedmodels.List failed.", ex);
}
}
public GetExpertStatsHandler(PredictionsContext context, IMapper mapper)
{
_context = context;
_mapper = mapper;
_statService = new StatService();
_predictionService = new PredictionService();
}
/// <summary>
/// Submit model id and request a prediction.
/// Documentation https://developers.google.com/prediction/v1.5/reference/trainedmodels/predict
/// Generation Note: This does not always build corectly. Google needs to standardise things I need to figuer out which ones are wrong.
/// </summary>
/// <param name="service">Authenticated Prediction service.</param>
/// <param name="id">The unique name for the predictive model.</param>
/// <param name="body">A valid Prediction v1.5 body.</param>
/// <returns>OutputResponse</returns>
public static Output Predict(PredictionService service, string id, Input body)
{
try
{
// Initial validation.
if (service == null)
{
throw new ArgumentNullException("service");
}
if (body == null)
{
throw new ArgumentNullException("body");
}
if (id == null)
{
throw new ArgumentNullException(id);
}
// Make the request.
return(service.Trainedmodels.Predict(body, id).Execute());
}
catch (Exception ex)
{
throw new Exception("Request Trainedmodels.Predict failed.", ex);
}
}
public PredictionsController()
{
_context = new PredictionsContext();
_expertService = new ExpertService(_context);
_tourService = new TourService(_context);
_predictionService = new PredictionService(_context);
_matchService = new MatchService(_context);
}
public void GetAmlPredictions_case1()
{
var storedDemand = DataSource.GetSalesHistory();
var singleProductHistory = storedDemand.Where(d => d.Plu == 2480).Take(10).ToArray();
var predictionService = new PredictionService(MlSettings.Endpoint, MlSettings.Key);
var actual = predictionService.GetAmlPredictions(singleProductHistory).Result;
}
public PredictionGradeViewModel(Student s)
{
student = s;
PredictCommand = new Command(async() =>
{
var grade = await PredictionService.PredictGrade(student);
G3 = grade;
});
}
//public PredictionServiceTests()
//{
// var predictionRepository = new Mock<IPredictionRepository>();
// predictionRepository.Setup(x => x.CheckTypeResult(It.IsAny<string>())).ReturnsAsync((string result) =>
// {
// if (Convert.ToInt32(result.Substring(0, 1)) > Convert.ToInt32(result.Substring(2, 1))) return TypeResult.WinTeam1;
// else if (Convert.ToInt32(result.Substring(0, 1)) < Convert.ToInt32(result.Substring(2, 1))) return TypeResult.WinTeam2;
// else if (Convert.ToInt32(result.Substring(0, 1)) == Convert.ToInt32(result.Substring(2, 1))) return TypeResult.Draw;
// else return TypeResult.NNB;
// });
// predictionRepository.Setup(x => x.CompareResultsAsync(It.IsAny<Game>(), It.IsAny<Prediction>())).ReturnsAsync((Game z, Prediction y) =>
// {
// if (y.PredictedResult == z.Result)
// return 3;
// else if (y.PredictedTypeResult == z.typeResult)
// return 1;
// else
// return 0;
// });
// _predictionService = new PredictionService(predictionRepository.Object);
//}
public async Task CreateDb()
{
var options = new DbContextOptionsBuilder <StrikeNetDbContext>()
.UseInMemoryDatabase(databaseName: "StrikeNetTestDb")
.EnableSensitiveDataLogging()
.UseQueryTrackingBehavior(QueryTrackingBehavior.NoTracking)
.Options;
var dbContext = new StrikeNetDbContext(options);
if (await dbContext.Predictions.CountAsync() <= 0)
{
Prediction p1 = new Prediction()
{
Id = 1,
GameId = 1,
UserId = User1,
PredictedResult = "3-0",
PredictedTypeResult = TypeResult.WinTeam1
};
Prediction p2 = new Prediction()
{
Id = 2,
GameId = 3,
UserId = User2,
PredictedResult = "2-0",
PredictedTypeResult = TypeResult.WinTeam1
};
Prediction p3 = new Prediction()
{
Id = 3,
GameId = 3,
UserId = User3,
PredictedResult = "0-1",
PredictedTypeResult = TypeResult.WinTeam2
};
Prediction p4 = new Prediction()
{
Id = 4,
GameId = 4,
UserId = User4,
PredictedResult = "1-1",
PredictedTypeResult = TypeResult.Draw
};
dbContext.Predictions.Add(p1);
dbContext.Predictions.Add(p2);
dbContext.Predictions.Add(p3);
dbContext.Predictions.Add(p4);
await dbContext.SaveChangesAsync();
}
var identityRepository = new IdentityRepository(_userManager, _roleManager, _signInManager);
var predictionRepository = new PredictionRepository(identityRepository, dbContext);
_predictionService2 = new PredictionService(predictionRepository);
}
async Task LoadPredictionHistoryAsync()
{
var predictions = await PredictionService.GetPredictionsForYearAsync(Year);
Predictions = new ObservableCollection <SummaryPredictionGroup>(
predictions.GroupBy(x => x.WeekNumber)
.OrderBy(x => x.Key)
.Select(x => new SummaryPredictionGroup(x.Key.ToString(), x.ToList()))
);
}
private async Task EvaluateImage()
{
IsBusy = true;
await Task.Run(() =>
{
PredictionDetailsViewModel.PredictionResult = PredictionService.Predict(PredictionDetailsViewModel.Path);
});
IsBusy = false;
}
public void WhenRunWithAllTiger_ShouldHave100PercentPredictResult()
{
var scores = new Score[]
{
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger
};
var predictors = new IPredictor[]
{
new SameDifferentPredictor(),
new Anti12Predictor(),
new Anti2Predictor()
};
var resultPredictor = new DummyPredictor();
var predictService = new PredictionService(predictors, resultPredictor);
var mappingScores = new Score[]
{
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger
};
var gameStates = scores.Select(s => new GameStateInput(s, None));
var result = predictService.PredictScore(gameStates, mappingScores)
.ToList();
Assert.AreEqual(scores.Count() + 1, result.Count());
var sdResult = result
.Select(r => r.ScorePredictions.Find(Constants.SameDiffPredictionName).Bind(p => p.Result))
.Where(r => r.IsSome)
.Map(r => r.IfNone(Result.Lose));
var stat = StatService.Calculate(
Constants.SameDiffPredictionName,
sdResult);
Assert.AreEqual(100, stat.WinRate);
}
public void WhenRunWithSpecificMapping_ShouldHavePredictResult()
{
var scores = new Score[]
{
Score.Dragon,
Score.Dragon,
Score.Dragon,
Score.Tiger,
Score.Dragon,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Dragon,
Score.Tiger,
};
var predictors = new IPredictor[]
{
new SameDifferentPredictor(),
new Anti12Predictor(),
new Anti2Predictor()
};
var resultPredictor = new DummyPredictor();
var predictService = new PredictionService(predictors, resultPredictor);
var mappingScores = new Score[]
{
Score.Tiger,
Score.Dragon,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger,
Score.Tiger
};
var gameStates = scores.Select(s => new GameStateInput(s, None));
var result = predictService.PredictScore(gameStates, mappingScores)
.ToList();
Assert.AreEqual(scores.Count() + 1, result.Count());
var predictResult = result.Last();
Assert.AreEqual(Score.Dragon, predictResult.ScorePredictions.Find(Constants.MappingTablePredctionName).Map(x => x.Score));
Assert.AreEqual(Score.Dragon, predictResult.ScorePredictions.Find(Constants.SameDiffPredictionName).Map(x => x.Score));
Assert.AreEqual(Score.Tiger, predictResult.ScorePredictions.Find(Constants.Anti12PredictionName).Map(x => x.Score));
Assert.AreEqual(Score.Dragon, predictResult.ScorePredictions.Find(Constants.Anti2PredictionName).Map(x => x.Score));
}
static void Main(string[] args)
{
var imgFile = @"C:\Users\ch489gt\Pictures\Snag-Auto\TestSnag.png";
var predictService = new PredictionService();
var predictRes = predictService.Predict(imgFile);
var ocrService = new OcrService();
var ocrRes = ocrService.DoOcr(imgFile);
var analyzer = new VisionAnalyzer();
var result = analyzer.GetResult(imgFile, predictRes.Data);
}
//private readonly IMapper _mapper;
public CurrentTournamentToursController(IPredictionsContext context, IMapper mapper)
{
_expertService = new ExpertService(context);
_tourService = new TourService(context);
_predictionService = new PredictionService(context);
_matchService = new MatchService(context, mapper);
_teamService = new TeamService(context);
_tournamentService = new TournamentService(context);
_context = context;
// _mapper = mapper;
_fileService = new FileService();
}
public async Task GetServiceAsync()
{
var trainingService = new PredictionService();
var response = await trainingService.PredictProfile(new UserInteraction()
{
Tier = 2,
Picture = 1,
Summary = 1,
Specs = 1,
Reviews = 1,
Comments = 1,
Share = 1,
Buy = 0,
Related = 0
});
}
public void CreatePredictionService(string authJsonFile)
{
Environment.SetEnvironmentVariable("GOOGLE_APPLICATION_CREDENTIALS", authJsonFile);
var credentials = Google.Apis.Auth.OAuth2.GoogleCredential.GetApplicationDefaultAsync().Result;
if (credentials.IsCreateScopedRequired)
{
credentials = credentials.CreateScoped(PredictionService.Scope.DevstorageFullControl, PredictionService.Scope.Prediction);
}
var serviceInitializer = new BaseClientService.Initializer()
{
ApplicationName = "Prediction Sample",
HttpClientInitializer = credentials
};
PredictionService = new PredictionService(serviceInitializer);
}
public void MakePredictionFromSample_DoesNotHaveToCurrencyInSample_ThrowCurrencyNotFoundException()
{
var predictionService = new PredictionService(_openExchangeClient.Object, _cache.Object);
Assert.Throws <CurrencyNotFoundException>(() =>
predictionService.MakePredictionFromSample("USD", "VND", new DateTime(2019, 12, 31),
new List <OpenExchangeRateResult>
{
new OpenExchangeRateResult
{
Base = "USD",
Rates = new Dictionary <string, double>(),
TimeStamp = 123234
}
}));
}
public void CreatePredictionService(string authJsonFile)
{
Environment.SetEnvironmentVariable("GOOGLE_APPLICATION_CREDENTIALS", authJsonFile);
var credentials = Google.Apis.Auth.OAuth2.GoogleCredential.GetApplicationDefaultAsync().Result;
if (credentials.IsCreateScopedRequired)
{
credentials = credentials.CreateScoped(PredictionService.Scope.DevstorageFullControl, PredictionService.Scope.Prediction);
}
var serviceInitializer = new BaseClientService.Initializer()
{
ApplicationName = "Prediction Sample",
HttpClientInitializer = credentials
};
PredictionService = new PredictionService(serviceInitializer);
}
private async Task Predict()
{
Trip = new TaxiTrip()
{
FareAmount = FareAmount,
PassengerCount = PassengerCount,
PaymentType = PaymentType,
RateCode = RateCode,
TripDistance = TripDistance,
TripTime = TripTime,
VendorId = VendorId
};
var amount = await PredictionService.Predict(Trip);
await App.Current.MainPage.DisplayAlert("Prediction", $"Trip Fare: {amount:C2}", "OK");
}
static void Main(string[] args)
{
// Display the header and initialize the sample.
CommandLine.EnableExceptionHandling();
CommandLine.DisplayGoogleSampleHeader("Prediction API");
CommandLine.WriteLine();
// Register the authenticator.
var provider = new NativeApplicationClient(GoogleAuthenticationServer.Description);
provider.ClientIdentifier = ClientCredentials.ClientID;
provider.ClientSecret = ClientCredentials.ClientSecret;
var auth = new OAuth2Authenticator<NativeApplicationClient>(provider, GetAuthentication);
// Create the service.
var service = new PredictionService(auth);
RunPrediction(service);
CommandLine.PressAnyKeyToExit();
}
private static void RunPrediction(PredictionService service)
{
// Make a prediction.
CommandLine.WriteAction("Performing a prediction...");
string text = "mucho bueno";
CommandLine.RequestUserInput("Text to analyze", ref text);
var input = new Input {
InputValue = new Input.InputData {
CsvInstance = new List <string> {
text
}
}
};
Output result = service.Hostedmodels.Predict(input, "sample.languageid").Fetch();
CommandLine.WriteResult("Language", result.OutputLabel);
}
public void MakePredictionFromSample_HaveCorrectNoneUSDSample_ReturnCorrectResultFromConvertedRates()
{
var predictionService = new PredictionService(_openExchangeClient.Object, _cache.Object);
var result = predictionService.MakePredictionFromSample("CNY", "VND",
DateTimeOffset.FromUnixTimeSeconds(40).UtcDateTime,
new List <OpenExchangeRateResult>
{
new OpenExchangeRateResult
{
Base = "USD",
Rates = new Dictionary <string, double>()
{
{ "VND", 23050 },
{ "CNY", 6.5434 }
},
TimeStamp = 10
},
new OpenExchangeRateResult
{
Base = "USD",
Rates = new Dictionary <string, double>()
{
{ "VND", 23100 },
{ "CNY", 6.6434 }
},
TimeStamp = 20
},
new OpenExchangeRateResult
{
Base = "USD",
Rates = new Dictionary <string, double>()
{
{ "VND", 23150 },
{ "CNY", 6.7434 }
},
TimeStamp = 30
}
});
//Assert.Equal(3387.9378, result);
}
public async Task CreateDbWithMockIdentity()
{
var options = new DbContextOptionsBuilder <StrikeNetDbContext>()
.UseInMemoryDatabase(databaseName: "StrikeNetTestDb")
.EnableSensitiveDataLogging()
.UseQueryTrackingBehavior(QueryTrackingBehavior.NoTracking)
.Options;
var _dbContext = new StrikeNetDbContext(options);
TestUser = new UserIdentity {
Score = 0
};
var identityRepository = new Mock <IIdentityRepository>();
identityRepository.Setup(x => x.GetUserAsync(It.IsAny <Guid?>())).ReturnsAsync(TestUser);
var predictionRepository = new PredictionRepository(identityRepository.Object, _dbContext);
_predictionService = new PredictionService(predictionRepository);
}
private static void RunPrediction(PredictionService service)
{
// Make a prediction.
CommandLine.WriteAction("Performing a prediction...");
string text = "mucho bueno";
CommandLine.RequestUserInput("Text to analyze", ref text);
var input = new Input { InputValue = new Input.InputData { CsvInstance = new List<string> { text } } };
Output result = service.Hostedmodels.Predict(input, "sample.languageid").Fetch();
CommandLine.WriteResult("Language", result.OutputLabel);
}
private static void RunPrediction(PredictionService service)
{
// Train the service with the existing bucket data.
string id = ClientCredentials.BucketPath;
CommandLine.WriteAction("Performing training of the service ...");
CommandLine.WriteResult("Bucket", id);
Training training = new Training { Id = id };
training = service.Training.Insert(training).Fetch();
// Wait until the training is complete.
while (training.TrainingStatus == "RUNNING")
{
CommandLine.Write("..");
Thread.Sleep(1000);
training = service.Training.Get(id).Fetch();
}
CommandLine.WriteLine();
CommandLine.WriteAction("Training complete!");
CommandLine.WriteLine();
// Make a prediction.
CommandLine.WriteAction("Performing a prediction...");
string text = "mucho bueno";
CommandLine.RequestUserInput("Text to analyze", ref text);
var input = new Input { InputValue = new Input.InputData { CsvInstance = new List<string> { text } } };
Output result = service.Training.Predict(input, id).Fetch();
CommandLine.WriteResult("Language", result.OutputLabel);
}