AnomalyDetectorClient.DetectUnivariateLastPointAsync メソッド

Source:

AnomalyDetectorClient.cs

public virtual System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.UnivariateLastDetectionResult>> DetectUnivariateLastPointAsync (Azure.AI.AnomalyDetector.UnivariateDetectionOptions options, System.Threading.CancellationToken cancellationToken = default);

abstract member DetectUnivariateLastPointAsync : Azure.AI.AnomalyDetector.UnivariateDetectionOptions * System.Threading.CancellationToken -> System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.UnivariateLastDetectionResult>>
override this.DetectUnivariateLastPointAsync : Azure.AI.AnomalyDetector.UnivariateDetectionOptions * System.Threading.CancellationToken -> System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.UnivariateLastDetectionResult>>

Public Overridable Function DetectUnivariateLastPointAsync (options As UnivariateDetectionOptions, Optional cancellationToken As CancellationToken = Nothing) As Task(Of Response(Of UnivariateLastDetectionResult))

パラメーター

戻り値

例外

例

このサンプルでは、必要なパラメーターを使用して DetectUnivariateLastPointAsync を呼び出す方法を示します。

var credential = new AzureKeyCredential("<key>");
var endpoint = new Uri("<https://my-service.azure.com>");
var client = new AnomalyDetectorClient(endpoint, credential);

var options = new UnivariateDetectionOptions(new TimeSeriesPoint[] 
{
    new TimeSeriesPoint(3.14f)
{
        Timestamp = DateTimeOffset.UtcNow,
    }
})
{
    Granularity = TimeGranularity.Yearly,
    CustomInterval = 1234,
    Period = 1234,
    MaxAnomalyRatio = 3.14f,
    Sensitivity = 1234,
    ImputeMode = ImputeMode.Auto,
    ImputeFixedValue = 3.14f,
};
var result = await client.DetectUnivariateLastPointAsync(options);

注釈

この操作では、API に送信したポイントを使用し、すべてのデータに基づいて、最後のポイントが異常かどうかを判断することでモデルを生成します。

Source:

AnomalyDetectorClient.cs

public virtual System.Threading.Tasks.Task<Azure.Response> DetectUnivariateLastPointAsync (Azure.Core.RequestContent content, Azure.RequestContext context = default);

abstract member DetectUnivariateLastPointAsync : Azure.Core.RequestContent * Azure.RequestContext -> System.Threading.Tasks.Task<Azure.Response>
override this.DetectUnivariateLastPointAsync : Azure.Core.RequestContent * Azure.RequestContext -> System.Threading.Tasks.Task<Azure.Response>

Public Overridable Function DetectUnivariateLastPointAsync (content As RequestContent, Optional context As RequestContext = Nothing) As Task(Of Response)

パラメーター

戻り値

サービスから返された応答。

例外

例

このサンプルでは、必要な要求コンテンツを使用して DetectUnivariateLastPointAsync を呼び出す方法と、結果を解析する方法を示します。

var credential = new AzureKeyCredential("<key>");
var endpoint = new Uri("<https://my-service.azure.com>");
var client = new AnomalyDetectorClient(endpoint, credential);

var data = new {
    series = new[] {
        new {
            value = 123.45f,
        }
    },
};

Response response = await client.DetectUnivariateLastPointAsync(RequestContent.Create(data));

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("period").ToString());
Console.WriteLine(result.GetProperty("suggestedWindow").ToString());
Console.WriteLine(result.GetProperty("expectedValue").ToString());
Console.WriteLine(result.GetProperty("upperMargin").ToString());
Console.WriteLine(result.GetProperty("lowerMargin").ToString());
Console.WriteLine(result.GetProperty("isAnomaly").ToString());
Console.WriteLine(result.GetProperty("isNegativeAnomaly").ToString());
Console.WriteLine(result.GetProperty("isPositiveAnomaly").ToString());

このサンプルでは、すべての要求コンテンツで DetectUnivariateLastPointAsync を呼び出す方法と、結果を解析する方法を示します。

var credential = new AzureKeyCredential("<key>");
var endpoint = new Uri("<https://my-service.azure.com>");
var client = new AnomalyDetectorClient(endpoint, credential);

var data = new {
    series = new[] {
        new {
            timestamp = "2022-05-10T14:57:31.2311892-04:00",
            value = 123.45f,
        }
    },
    granularity = "yearly",
    customInterval = 1234,
    period = 1234,
    maxAnomalyRatio = 123.45f,
    sensitivity = 1234,
    imputeMode = "auto",
    imputeFixedValue = 123.45f,
};

Response response = await client.DetectUnivariateLastPointAsync(RequestContent.Create(data), new RequestContext());

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("period").ToString());
Console.WriteLine(result.GetProperty("suggestedWindow").ToString());
Console.WriteLine(result.GetProperty("expectedValue").ToString());
Console.WriteLine(result.GetProperty("upperMargin").ToString());
Console.WriteLine(result.GetProperty("lowerMargin").ToString());
Console.WriteLine(result.GetProperty("isAnomaly").ToString());
Console.WriteLine(result.GetProperty("isNegativeAnomaly").ToString());
Console.WriteLine(result.GetProperty("isPositiveAnomaly").ToString());
Console.WriteLine(result.GetProperty("severity").ToString());

注釈

この操作では、API に送信したポイントを使用してモデルを生成し、すべてのデータに基づいて、最後のポイントが異常かどうかを判断します。

要求と応答のペイロードの JSON スキーマを次に示します。

要求本文:

の UnivariateDetectionOptionsスキーマ:

{
  series: [
    {
      timestamp: string (date & time), # Optional.
      value: number, # Required.
    }
  ], # Required.
  granularity: "yearly" | "monthly" | "weekly" | "daily" | "hourly" | "minutely" | "secondly" | "microsecond" | "none", # Optional.
  customInterval: number, # Optional.
  period: number, # Optional.
  maxAnomalyRatio: number, # Optional.
  sensitivity: number, # Optional.
  imputeMode: "auto" | "previous" | "linear" | "fixed" | "zero" | "notFill", # Optional.
  imputeFixedValue: number, # Optional.
}

応答本文:

の UnivariateLastDetectionResultスキーマ:

{
  period: number, # Required.
  suggestedWindow: number, # Required.
  expectedValue: number, # Required.
  upperMargin: number, # Required.
  lowerMargin: number, # Required.
  isAnomaly: boolean, # Required.
  isNegativeAnomaly: boolean, # Required.
  isPositiveAnomaly: boolean, # Required.
  severity: number, # Optional.
}