AnomalyDetectorClient.GetMultivariateModelAsync Method

Definition

Namespace:

Azure.AI.AnomalyDetector

Assembly:

Azure.AI.AnomalyDetector.dll

Package:

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

Overloads

GetMultivariateModelAsync(String, RequestContext)	[Protocol Method] Get Multivariate Model This protocol method allows explicit creation of the request and processing of the response for advanced scenarios. Please try the simpler GetMultivariateModelAsync(String, CancellationToken) convenience overload with strongly typed models first.
GetMultivariateModelAsync(String, CancellationToken)	Get Multivariate Model.

GetMultivariateModelAsync(String, RequestContext)

Source:

AnomalyDetectorClient.cs

[Protocol Method] Get Multivariate Model

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

public virtual System.Threading.Tasks.Task<Azure.Response> GetMultivariateModelAsync (string modelId, Azure.RequestContext context);

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

Public Overridable Function GetMultivariateModelAsync (modelId As String, context As RequestContext) As Task(Of Response)

Parameters

modelId

String

Model identifier.

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 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 GetMultivariateModelAsync with required parameters and parse the result.

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

Response response = await client.GetMultivariateModelAsync("<modelId>", new RequestContext());

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("modelId").ToString());
Console.WriteLine(result.GetProperty("createdTime").ToString());
Console.WriteLine(result.GetProperty("lastUpdatedTime").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("dataSource").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("dataSchema").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("startTime").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("endTime").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("displayName").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("slidingWindow").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("alignPolicy").GetProperty("alignMode").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("alignPolicy").GetProperty("fillNAMethod").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("alignPolicy").GetProperty("paddingValue").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("status").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("errors")[0].GetProperty("code").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("errors")[0].GetProperty("message").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("diagnosticsInfo").GetProperty("modelState").GetProperty("epochIds")[0].ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("diagnosticsInfo").GetProperty("modelState").GetProperty("trainLosses")[0].ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("diagnosticsInfo").GetProperty("modelState").GetProperty("validationLosses")[0].ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("diagnosticsInfo").GetProperty("modelState").GetProperty("latenciesInSeconds")[0].ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("diagnosticsInfo").GetProperty("variableStates")[0].GetProperty("variable").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("diagnosticsInfo").GetProperty("variableStates")[0].GetProperty("filledNARatio").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("diagnosticsInfo").GetProperty("variableStates")[0].GetProperty("effectiveCount").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("diagnosticsInfo").GetProperty("variableStates")[0].GetProperty("firstTimestamp").ToString());
Console.WriteLine(result.GetProperty("modelInfo").GetProperty("diagnosticsInfo").GetProperty("variableStates")[0].GetProperty("lastTimestamp").ToString());

Remarks

Get detailed information of multivariate model, including the training status and variables used in the model.

Below is the JSON schema for the response payload.

Response Body:

Schema for AnomalyDetectionModel:

{
  modelId: string, # Required.
  createdTime: string (date & time), # Required.
  lastUpdatedTime: string (date & time), # Required.
  modelInfo: {
    dataSource: string, # Required.
    dataSchema: "OneTable" | "MultiTable", # Optional.
    startTime: string (date & time), # Required.
    endTime: string (date & time), # Required.
    displayName: string, # Optional.
    slidingWindow: number, # Optional.
    alignPolicy: {
      alignMode: "Inner" | "Outer", # Optional.
      fillNAMethod: "Previous" | "Subsequent" | "Linear" | "Zero" | "Fixed", # Optional.
      paddingValue: number, # Optional.
    }, # Optional.
    status: "CREATED" | "RUNNING" | "READY" | "FAILED", # Optional.
    errors: [
      {
        code: string, # Required.
        message: string, # Required.
      }
    ], # Optional.
    diagnosticsInfo: {
      modelState: {
        epochIds: [number], # Optional.
        trainLosses: [number], # Optional.
        validationLosses: [number], # Optional.
        latenciesInSeconds: [number], # Optional.
      }, # Optional.
      variableStates: [VariableState], # Optional.
    }, # Optional.
  }, # Optional.
}

GetMultivariateModelAsync(String, CancellationToken)

Source:

AnomalyDetectorClient.cs

Get Multivariate Model.

public virtual System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.AnomalyDetectionModel>> GetMultivariateModelAsync (string modelId, System.Threading.CancellationToken cancellationToken = default);

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

Public Overridable Function GetMultivariateModelAsync (modelId As String, Optional cancellationToken As CancellationToken = Nothing) As Task(Of Response(Of AnomalyDetectionModel))

Parameters

modelId

String

Model identifier.

cancellationToken

CancellationToken

The cancellation token to use.

Returns

Task<Response<AnomalyDetectionModel>>

Exceptions

ArgumentNullException

modelId is null.

ArgumentException

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

Examples

This sample shows how to call GetMultivariateModelAsync with required parameters.

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

var result = await client.GetMultivariateModelAsync("<modelId>");

Remarks

Get detailed information about the multivariate model, including the training status and variables used in the model.