AnomalyDetectorClient.DetectMultivariateLastAnomalyAsync Method

Definition

Namespace:

Azure.AI.AnomalyDetector

Assembly:

Azure.AI.AnomalyDetector.dll

Package:

Azure.AI.AnomalyDetector v3.0.0-preview.7

Overloads

DetectMultivariateLastAnomalyAsync(String, MultivariateLastDetectionOptions, CancellationToken)	Detect anomalies in the last point of the request body.
DetectMultivariateLastAnomalyAsync(String, RequestContent, RequestContext)	[Protocol Method] Detect anomalies in the last point of the request body This protocol method allows explicit creation of the request and processing of the response for advanced scenarios. Please try the simpler DetectMultivariateLastAnomalyAsync(String, MultivariateLastDetectionOptions, CancellationToken) convenience overload with strongly typed models first.

DetectMultivariateLastAnomalyAsync(String, MultivariateLastDetectionOptions, CancellationToken)

Source:

AnomalyDetectorClient.cs

Detect anomalies in the last point of the request body.

public virtual System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.MultivariateLastDetectionResult>> DetectMultivariateLastAnomalyAsync (string modelId, Azure.AI.AnomalyDetector.MultivariateLastDetectionOptions options, System.Threading.CancellationToken cancellationToken = default);

abstract member DetectMultivariateLastAnomalyAsync : string * Azure.AI.AnomalyDetector.MultivariateLastDetectionOptions * System.Threading.CancellationToken -> System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.MultivariateLastDetectionResult>>
override this.DetectMultivariateLastAnomalyAsync : string * Azure.AI.AnomalyDetector.MultivariateLastDetectionOptions * System.Threading.CancellationToken -> System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.MultivariateLastDetectionResult>>

Public Overridable Function DetectMultivariateLastAnomalyAsync (modelId As String, options As MultivariateLastDetectionOptions, Optional cancellationToken As CancellationToken = Nothing) As Task(Of Response(Of MultivariateLastDetectionResult))

Parameters

modelId

String

Model identifier.

options

MultivariateLastDetectionOptions

Request of the last detection.

cancellationToken

CancellationToken

The cancellation token to use.

Returns

Task<Response<MultivariateLastDetectionResult>>

Exceptions

ArgumentNullException

modelId or options is null.

ArgumentException

modelId is an empty string, and was expected to be non-empty.

Examples

This sample shows how to call DetectMultivariateLastAnomalyAsync with required parameters.

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

var options = new MultivariateLastDetectionOptions(new VariableValues[] 
{
    new VariableValues("<variable>", new string[] 
{
        "<null>"
    }, new float[] 
{
        3.14f
    })
})
{
    TopContributorCount = 1234,
};
var result = await client.DetectMultivariateLastAnomalyAsync("<modelId>", options);

Remarks

Submit a multivariate anomaly detection task with the modelId value of a trained model and inference data. The inference data should be put into the request body in JSON format. The request will finish synchronously and return the detection immediately in the response body.

DetectMultivariateLastAnomalyAsync(String, RequestContent, RequestContext)

Source:

AnomalyDetectorClient.cs

[Protocol Method] Detect anomalies in the last point of the request body

• This protocol method allows explicit creation of the request and processing of the response for advanced scenarios.
• Please try the simpler DetectMultivariateLastAnomalyAsync(String, MultivariateLastDetectionOptions, CancellationToken) convenience overload with strongly typed models first.

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

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

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

Parameters

modelId

String

Model identifier.

content

RequestContent

The content to send as the body of the request.

context

RequestContext

The request context, which can override default behaviors of the client pipeline on a per-call basis.

Returns

Task<Response>

The response returned from the service.

Exceptions

ArgumentNullException

modelId or content is null.

ArgumentException

modelId is an empty string, and was expected to be non-empty.

RequestFailedException

Service returned a non-success status code.

Examples

This sample shows how to call DetectMultivariateLastAnomalyAsync with required parameters and request content, and how to parse the result.

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

var data = new {
    variables = new[] {
        new {
            variable = "<variable>",
            timestamps = new[] {
                "<String>"
            },
            values = new[] {
                123.45f
            },
        }
    },
};

Response response = await client.DetectMultivariateLastAnomalyAsync("<modelId>", RequestContent.Create(data));

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.ToString());

This sample shows how to call DetectMultivariateLastAnomalyAsync with all parameters and request content, and how to parse the result.

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

var data = new {
    variables = new[] {
        new {
            variable = "<variable>",
            timestamps = new[] {
                "<String>"
            },
            values = new[] {
                123.45f
            },
        }
    },
    topContributorCount = 1234,
};

Response response = await client.DetectMultivariateLastAnomalyAsync("<modelId>", RequestContent.Create(data), new RequestContext());

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("variableStates")[0].GetProperty("variable").ToString());
Console.WriteLine(result.GetProperty("variableStates")[0].GetProperty("filledNARatio").ToString());
Console.WriteLine(result.GetProperty("variableStates")[0].GetProperty("effectiveCount").ToString());
Console.WriteLine(result.GetProperty("variableStates")[0].GetProperty("firstTimestamp").ToString());
Console.WriteLine(result.GetProperty("variableStates")[0].GetProperty("lastTimestamp").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("timestamp").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("isAnomaly").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("severity").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("score").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("interpretation")[0].GetProperty("variable").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("interpretation")[0].GetProperty("contributionScore").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("value").GetProperty("interpretation")[0].GetProperty("correlationChanges").GetProperty("changedVariables")[0].ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("errors")[0].GetProperty("code").ToString());
Console.WriteLine(result.GetProperty("results")[0].GetProperty("errors")[0].GetProperty("message").ToString());

Remarks

Submit multivariate anomaly detection task with the modelId of trained model and inference data, and the inference data should be put into request body in a JSON format. The request will complete synchronously and return the detection immediately in the response body.

Below is the JSON schema for the request and response payloads.

Request Body:

Schema for MultivariateLastDetectionOptions:

{
  variables: [
    {
      variable: string, # Required.
      timestamps: [string], # Required.
      values: [number], # Required.
    }
  ], # Required.
  topContributorCount: number, # Required.
}

Response Body:

Schema for MultivariateLastDetectionResult:

{
  variableStates: [
    {
      variable: string, # Optional.
      filledNARatio: number, # Optional.
      effectiveCount: number, # Optional.
      firstTimestamp: string (date & time), # Optional.
      lastTimestamp: string (date & time), # Optional.
    }
  ], # Optional.
  results: [AnomalyState], # Optional.
}