diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorAsyncClient.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorAsyncClient.java
index 40e17f4d59a9..99d05eef9069 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorAsyncClient.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorAsyncClient.java
@@ -13,7 +13,6 @@
import com.azure.ai.anomalydetector.models.UnivariateChangePointDetectionOptions;
import com.azure.ai.anomalydetector.models.UnivariateChangePointDetectionResult;
import com.azure.ai.anomalydetector.models.UnivariateDetectionOptions;
-import com.azure.ai.anomalydetector.models.UnivariateEntireDetectionResult;
import com.azure.ai.anomalydetector.models.UnivariateLastDetectionResult;
import com.azure.core.annotation.Generated;
import com.azure.core.annotation.ReturnType;
@@ -53,9 +52,9 @@ public final class AnomalyDetectorAsyncClient {
/**
* Detect anomalies for the entire series in batch.
*
- * This operation generates a model with an entire series, each point is detected with the same model. With this
- * method, points before and after a certain point are used to determine whether it is an anomaly. The entire
- * detection can give user an overall status of the time series.
+ *
This operation generates a model with an entire series. Each point is detected with the same model. With this
+ * method, points before and after a certain point are used to determine whether it's an anomaly. The entire
+ * detection can give the user an overall status of the time series.
*
*
Request Body Schema
*
@@ -112,7 +111,7 @@ public final class AnomalyDetectorAsyncClient {
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of entire anomaly detection along with {@link Response} on successful completion of {@link
+ * @return response of the entire anomaly detection along with {@link Response} on successful completion of {@link
* Mono}.
*/
@Generated
@@ -125,7 +124,7 @@ public Mono> detectUnivariateEntireSeriesWithResponse(
/**
* Detect anomaly status of the latest point in time series.
*
- * This operation generates a model using the points that you sent into the API, and based on all data to
+ *
This operation generates a model by using the points that you sent in to the API and based on all data to
* determine whether the last point is anomalous.
*
*
Request Body Schema
@@ -170,7 +169,7 @@ public Mono> detectUnivariateEntireSeriesWithResponse(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of last anomaly detection along with {@link Response} on successful completion of {@link
+ * @return response of the last anomaly detection along with {@link Response} on successful completion of {@link
* Mono}.
*/
@Generated
@@ -183,7 +182,7 @@ public Mono> detectUnivariateLastPointWithResponse(
/**
* Detect change point for the entire series
*
- * Evaluate change point score of every series point.
+ *
Evaluate the change point score of every series point.
*
*
Request Body Schema
*
@@ -223,8 +222,7 @@ public Mono> detectUnivariateLastPointWithResponse(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of change point detection along with {@link Response} on successful completion of {@link
- * Mono}.
+ * @return response of change point detection along with {@link Response} on successful completion of {@link Mono}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -236,8 +234,8 @@ public Mono> detectUnivariateChangePointWithResponse(
/**
* Get Multivariate Anomaly Detection Result
*
- * For asynchronous inference, get multivariate anomaly detection result based on resultId returned by the
- * BatchDetectAnomaly api.
+ *
For asynchronous inference, get a multivariate anomaly detection result based on the resultId value that the
+ * BatchDetectAnomaly API returns.
*
*
Response Body Schema
*
@@ -263,7 +261,7 @@ public Mono> detectUnivariateChangePointWithResponse(
* ]
* setupInfo (Required): {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -301,7 +299,7 @@ public Mono> detectUnivariateChangePointWithResponse(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detection results for the given resultId along with {@link Response} on successful completion of {@link
+ * @return detection results for the resultId value along with {@link Response} on successful completion of {@link
* Mono}.
*/
@Generated
@@ -315,10 +313,12 @@ public Mono> getMultivariateBatchDetectionResultWithRespons
* Train a Multivariate Anomaly Detection Model
*
* Create and train a multivariate anomaly detection model. The request must include a source parameter to
- * indicate an externally accessible Azure blob storage URI.There are two types of data input: An URI pointed to an
- * Azure blob storage folder which contains multiple CSV files, and each CSV file contains two columns, timestamp
- * and variable. Another type of input is an URI pointed to a CSV file in Azure blob storage, which contains all the
- * variables and a timestamp column.
+ * indicate an Azure Blob Storage URI that's accessible to the service. There are two types of data input. The Blob
+ * Storage URI can point to an Azure Blob Storage folder that contains multiple CSV files, where each CSV file has
+ * two columns, time stamp and variable. Or the Blob Storage URI can point to a single blob that contains a CSV file
+ * that has all the variables and a time stamp column. The model object will be created and returned in the
+ * response, but the training process happens asynchronously. To check the training status, call
+ * GetMultivariateModel with the modelId value and check the status field in the modelInfo object.
*
*
Request Body Schema
*
@@ -450,8 +450,8 @@ public Mono> trainMultivariateModelWithResponse(
*
* Query Parameters
* | Name | Type | Required | Description |
|---|
- * | skip | Integer | No | Skip indicates how many models will be skipped. |
- * | top | Integer | No | Top indicates how many models will be fetched. |
+ * | skip | Integer | No | The number of result items to skip. |
+ * | top | Integer | No | The number of result items to return. |
*
*
* You can add these to a request with {@link RequestOptions#addQueryParam}
@@ -527,7 +527,7 @@ public PagedFlux listMultivariateModels(RequestOptions requestOption
/**
* Delete Multivariate Model
*
- * Delete an existing multivariate model according to the modelId.
+ *
Delete an existing multivariate model according to the modelId value.
*
* @param modelId Model identifier.
* @param requestOptions The options to configure the HTTP request before HTTP client sends it.
@@ -546,7 +546,8 @@ public Mono> deleteMultivariateModelWithResponse(String modelId,
/**
* Get Multivariate Model
*
- * Get detailed information of multivariate model, including the training status and variables used in the model.
+ *
Get detailed information about the multivariate model, including the training status and variables used in the
+ * model.
*
*
Response Body Schema
*
@@ -609,8 +610,8 @@ public Mono> deleteMultivariateModelWithResponse(String modelId,
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detailed information of multivariate model, including the training status and variables used in the model
- * along with {@link Response} on successful completion of {@link Mono}.
+ * @return detailed information about the multivariate model, including the training status and variables used in
+ * the model along with {@link Response} on successful completion of {@link Mono}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -621,18 +622,18 @@ public Mono> getMultivariateModelWithResponse(String modelI
/**
* Detect Multivariate Anomaly
*
- * Submit multivariate anomaly detection task with the modelId of trained model and inference data, the input
- * schema should be the same with the training request. The request will complete asynchronously and return a
- * resultId to query the detection result.The request should be a source link to indicate an externally accessible
- * Azure storage Uri, either pointed to an Azure blob storage folder, or pointed to a CSV file in Azure blob
- * storage.
+ *
Submit a multivariate anomaly detection task with the modelId value of a trained model and inference data. The
+ * input schema should be the same with the training request. The request will finish asynchronously and return a
+ * resultId value to query the detection result. The request should be a source link to indicate an externally
+ * accessible Azure Storage URI that either points to an Azure Blob Storage folder or points to a CSV file in Azure
+ * Blob Storage.
*
*
Request Body Schema
*
*
{@code
* {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -662,7 +663,7 @@ public Mono> getMultivariateModelWithResponse(String modelI
* ]
* setupInfo (Required): {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -701,7 +702,7 @@ public Mono> getMultivariateModelWithResponse(String modelI
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detection results for the given resultId along with {@link Response} on successful completion of {@link
+ * @return detection results for the resultId value along with {@link Response} on successful completion of {@link
* Mono}.
*/
@Generated
@@ -714,8 +715,8 @@ public Mono> detectMultivariateBatchAnomalyWithResponse(
/**
* Detect anomalies in the last point of the request body
*
- * 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
+ *
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.
*
*
Request Body Schema
@@ -733,7 +734,7 @@ public Mono> detectMultivariateBatchAnomalyWithResponse(
* ]
* }
* ]
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* }
* }
*
@@ -781,13 +782,13 @@ public Mono> detectMultivariateBatchAnomalyWithResponse(
* }
*
* @param modelId Model identifier.
- * @param options Request of last detection.
+ * @param options Request of the last detection.
* @param requestOptions The options to configure the HTTP request before HTTP client sends it.
* @throws HttpResponseException thrown if the request is rejected by server.
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return results of last detection along with {@link Response} on successful completion of {@link Mono}.
+ * @return results of the last detection along with {@link Response} on successful completion of {@link Mono}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -796,36 +797,10 @@ public Mono> detectMultivariateLastAnomalyWithResponse(
return this.serviceClient.detectMultivariateLastAnomalyWithResponseAsync(modelId, options, requestOptions);
}
- /**
- * Detect anomalies for the entire series in batch.
- *
- * This operation generates a model with an entire series, each point is detected with the same model. With this
- * method, points before and after a certain point are used to determine whether it is an anomaly. The entire
- * detection can give user an overall status of the time series.
- *
- * @param options Method of univariate anomaly detection.
- * @throws IllegalArgumentException thrown if parameters fail the validation.
- * @throws HttpResponseException thrown if the request is rejected by server.
- * @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
- * @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
- * @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return the response of entire anomaly detection on successful completion of {@link Mono}.
- */
- @Generated
- @ServiceMethod(returns = ReturnType.SINGLE)
- public Mono detectUnivariateEntireSeries(UnivariateDetectionOptions options) {
- // Generated convenience method for detectUnivariateEntireSeriesWithResponse
- RequestOptions requestOptions = new RequestOptions();
- return detectUnivariateEntireSeriesWithResponse(BinaryData.fromObject(options), requestOptions)
- .flatMap(FluxUtil::toMono)
- .map(protocolMethodData -> protocolMethodData.toObject(UnivariateEntireDetectionResult.class));
- }
-
/**
* Detect anomaly status of the latest point in time series.
*
- * This operation generates a model using the points that you sent into the API, and based on all data to
+ *
This operation generates a model by using the points that you sent in to the API and based on all data to
* determine whether the last point is anomalous.
*
* @param options Method of univariate anomaly detection.
@@ -835,7 +810,7 @@ public Mono detectUnivariateEntireSeries(Univar
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return the response of last anomaly detection on successful completion of {@link Mono}.
+ * @return response of the last anomaly detection on successful completion of {@link Mono}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -850,7 +825,7 @@ public Mono detectUnivariateLastPoint(UnivariateD
/**
* Detect change point for the entire series
*
- * Evaluate change point score of every series point.
+ *
Evaluate the change point score of every series point.
*
* @param options Method of univariate anomaly detection.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -859,7 +834,7 @@ public Mono detectUnivariateLastPoint(UnivariateD
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return the response of change point detection on successful completion of {@link Mono}.
+ * @return response of change point detection on successful completion of {@link Mono}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -875,8 +850,8 @@ public Mono detectUnivariateChangePoint(
/**
* Get Multivariate Anomaly Detection Result
*
- * For asynchronous inference, get multivariate anomaly detection result based on resultId returned by the
- * BatchDetectAnomaly api.
+ *
For asynchronous inference, get a multivariate anomaly detection result based on the resultId value that the
+ * BatchDetectAnomaly API returns.
*
* @param resultId ID of a batch detection result.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -885,7 +860,7 @@ public Mono detectUnivariateChangePoint(
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return detection results for the given resultId on successful completion of {@link Mono}.
+ * @return detection results for the resultId value on successful completion of {@link Mono}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -901,10 +876,12 @@ public Mono getMultivariateBatchDetectionResult(Str
* Train a Multivariate Anomaly Detection Model
*
* Create and train a multivariate anomaly detection model. The request must include a source parameter to
- * indicate an externally accessible Azure blob storage URI.There are two types of data input: An URI pointed to an
- * Azure blob storage folder which contains multiple CSV files, and each CSV file contains two columns, timestamp
- * and variable. Another type of input is an URI pointed to a CSV file in Azure blob storage, which contains all the
- * variables and a timestamp column.
+ * indicate an Azure Blob Storage URI that's accessible to the service. There are two types of data input. The Blob
+ * Storage URI can point to an Azure Blob Storage folder that contains multiple CSV files, where each CSV file has
+ * two columns, time stamp and variable. Or the Blob Storage URI can point to a single blob that contains a CSV file
+ * that has all the variables and a time stamp column. The model object will be created and returned in the
+ * response, but the training process happens asynchronously. To check the training status, call
+ * GetMultivariateModel with the modelId value and check the status field in the modelInfo object.
*
* @param modelInfo Model information.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -1020,7 +997,7 @@ public PagedFlux listMultivariateModels() {
/**
* Delete Multivariate Model
*
- * Delete an existing multivariate model according to the modelId.
+ *
Delete an existing multivariate model according to the modelId value.
*
* @param modelId Model identifier.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -1042,7 +1019,8 @@ public Mono deleteMultivariateModel(String modelId) {
/**
* Get Multivariate Model
*
- * Get detailed information of multivariate model, including the training status and variables used in the model.
+ *
Get detailed information about the multivariate model, including the training status and variables used in the
+ * model.
*
* @param modelId Model identifier.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -1051,8 +1029,8 @@ public Mono deleteMultivariateModel(String modelId) {
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return detailed information of multivariate model, including the training status and variables used in the model
- * on successful completion of {@link Mono}.
+ * @return detailed information about the multivariate model, including the training status and variables used in
+ * the model on successful completion of {@link Mono}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -1067,11 +1045,11 @@ public Mono getMultivariateModel(String modelId) {
/**
* Detect Multivariate Anomaly
*
- * Submit multivariate anomaly detection task with the modelId of trained model and inference data, the input
- * schema should be the same with the training request. The request will complete asynchronously and return a
- * resultId to query the detection result.The request should be a source link to indicate an externally accessible
- * Azure storage Uri, either pointed to an Azure blob storage folder, or pointed to a CSV file in Azure blob
- * storage.
+ *
Submit a multivariate anomaly detection task with the modelId value of a trained model and inference data. The
+ * input schema should be the same with the training request. The request will finish asynchronously and return a
+ * resultId value to query the detection result. The request should be a source link to indicate an externally
+ * accessible Azure Storage URI that either points to an Azure Blob Storage folder or points to a CSV file in Azure
+ * Blob Storage.
*
* @param modelId Model identifier.
* @param options Request of multivariate anomaly detection.
@@ -1081,7 +1059,7 @@ public Mono getMultivariateModel(String modelId) {
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return detection results for the given resultId on successful completion of {@link Mono}.
+ * @return detection results for the resultId value on successful completion of {@link Mono}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -1097,19 +1075,19 @@ public Mono detectMultivariateBatchAnomaly(
/**
* Detect anomalies in the last point of the request body
*
- * 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
+ *
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.
*
* @param modelId Model identifier.
- * @param options Request of last detection.
+ * @param options Request of the last detection.
* @throws IllegalArgumentException thrown if parameters fail the validation.
* @throws HttpResponseException thrown if the request is rejected by server.
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return results of last detection on successful completion of {@link Mono}.
+ * @return results of the last detection on successful completion of {@link Mono}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorClient.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorClient.java
index 3b37c4eeb688..8b0950f870ff 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorClient.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorClient.java
@@ -12,7 +12,6 @@
import com.azure.ai.anomalydetector.models.UnivariateChangePointDetectionOptions;
import com.azure.ai.anomalydetector.models.UnivariateChangePointDetectionResult;
import com.azure.ai.anomalydetector.models.UnivariateDetectionOptions;
-import com.azure.ai.anomalydetector.models.UnivariateEntireDetectionResult;
import com.azure.ai.anomalydetector.models.UnivariateLastDetectionResult;
import com.azure.core.annotation.Generated;
import com.azure.core.annotation.ReturnType;
@@ -46,9 +45,9 @@ public final class AnomalyDetectorClient {
/**
* Detect anomalies for the entire series in batch.
*
- *
This operation generates a model with an entire series, each point is detected with the same model. With this
- * method, points before and after a certain point are used to determine whether it is an anomaly. The entire
- * detection can give user an overall status of the time series.
+ *
This operation generates a model with an entire series. Each point is detected with the same model. With this
+ * method, points before and after a certain point are used to determine whether it's an anomaly. The entire
+ * detection can give the user an overall status of the time series.
*
*
Request Body Schema
*
@@ -105,7 +104,7 @@ public final class AnomalyDetectorClient {
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of entire anomaly detection along with {@link Response}.
+ * @return response of the entire anomaly detection along with {@link Response}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -117,7 +116,7 @@ public Response detectUnivariateEntireSeriesWithResponse(
/**
* Detect anomaly status of the latest point in time series.
*
- * This operation generates a model using the points that you sent into the API, and based on all data to
+ *
This operation generates a model by using the points that you sent in to the API and based on all data to
* determine whether the last point is anomalous.
*
*
Request Body Schema
@@ -162,7 +161,7 @@ public Response detectUnivariateEntireSeriesWithResponse(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of last anomaly detection along with {@link Response}.
+ * @return response of the last anomaly detection along with {@link Response}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -174,7 +173,7 @@ public Response detectUnivariateLastPointWithResponse(
/**
* Detect change point for the entire series
*
- * Evaluate change point score of every series point.
+ *
Evaluate the change point score of every series point.
*
*
Request Body Schema
*
@@ -214,7 +213,7 @@ public Response detectUnivariateLastPointWithResponse(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of change point detection along with {@link Response}.
+ * @return response of change point detection along with {@link Response}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -226,8 +225,8 @@ public Response detectUnivariateChangePointWithResponse(
/**
* Get Multivariate Anomaly Detection Result
*
- * For asynchronous inference, get multivariate anomaly detection result based on resultId returned by the
- * BatchDetectAnomaly api.
+ *
For asynchronous inference, get a multivariate anomaly detection result based on the resultId value that the
+ * BatchDetectAnomaly API returns.
*
*
Response Body Schema
*
@@ -253,7 +252,7 @@ public Response detectUnivariateChangePointWithResponse(
* ]
* setupInfo (Required): {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -291,7 +290,7 @@ public Response detectUnivariateChangePointWithResponse(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detection results for the given resultId along with {@link Response}.
+ * @return detection results for the resultId value along with {@link Response}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -304,10 +303,12 @@ public Response getMultivariateBatchDetectionResultWithResponse(
* Train a Multivariate Anomaly Detection Model
*
* Create and train a multivariate anomaly detection model. The request must include a source parameter to
- * indicate an externally accessible Azure blob storage URI.There are two types of data input: An URI pointed to an
- * Azure blob storage folder which contains multiple CSV files, and each CSV file contains two columns, timestamp
- * and variable. Another type of input is an URI pointed to a CSV file in Azure blob storage, which contains all the
- * variables and a timestamp column.
+ * indicate an Azure Blob Storage URI that's accessible to the service. There are two types of data input. The Blob
+ * Storage URI can point to an Azure Blob Storage folder that contains multiple CSV files, where each CSV file has
+ * two columns, time stamp and variable. Or the Blob Storage URI can point to a single blob that contains a CSV file
+ * that has all the variables and a time stamp column. The model object will be created and returned in the
+ * response, but the training process happens asynchronously. To check the training status, call
+ * GetMultivariateModel with the modelId value and check the status field in the modelInfo object.
*
*
Request Body Schema
*
@@ -439,8 +440,8 @@ public Response trainMultivariateModelWithResponse(
*
* Query Parameters
* | Name | Type | Required | Description |
|---|
- * | skip | Integer | No | Skip indicates how many models will be skipped. |
- * | top | Integer | No | Top indicates how many models will be fetched. |
+ * | skip | Integer | No | The number of result items to skip. |
+ * | top | Integer | No | The number of result items to return. |
*
*
* You can add these to a request with {@link RequestOptions#addQueryParam}
@@ -516,7 +517,7 @@ public PagedIterable listMultivariateModels(RequestOptions requestOp
/**
* Delete Multivariate Model
*
- * Delete an existing multivariate model according to the modelId.
+ *
Delete an existing multivariate model according to the modelId value.
*
* @param modelId Model identifier.
* @param requestOptions The options to configure the HTTP request before HTTP client sends it.
@@ -535,7 +536,8 @@ public Response deleteMultivariateModelWithResponse(String modelId, Reques
/**
* Get Multivariate Model
*
- * Get detailed information of multivariate model, including the training status and variables used in the model.
+ *
Get detailed information about the multivariate model, including the training status and variables used in the
+ * model.
*
*
Response Body Schema
*
@@ -598,8 +600,8 @@ public Response deleteMultivariateModelWithResponse(String modelId, Reques
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detailed information of multivariate model, including the training status and variables used in the model
- * along with {@link Response}.
+ * @return detailed information about the multivariate model, including the training status and variables used in
+ * the model along with {@link Response}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -610,18 +612,18 @@ public Response getMultivariateModelWithResponse(String modelId, Req
/**
* Detect Multivariate Anomaly
*
- * Submit multivariate anomaly detection task with the modelId of trained model and inference data, the input
- * schema should be the same with the training request. The request will complete asynchronously and return a
- * resultId to query the detection result.The request should be a source link to indicate an externally accessible
- * Azure storage Uri, either pointed to an Azure blob storage folder, or pointed to a CSV file in Azure blob
- * storage.
+ *
Submit a multivariate anomaly detection task with the modelId value of a trained model and inference data. The
+ * input schema should be the same with the training request. The request will finish asynchronously and return a
+ * resultId value to query the detection result. The request should be a source link to indicate an externally
+ * accessible Azure Storage URI that either points to an Azure Blob Storage folder or points to a CSV file in Azure
+ * Blob Storage.
*
*
Request Body Schema
*
*
{@code
* {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -651,7 +653,7 @@ public Response getMultivariateModelWithResponse(String modelId, Req
* ]
* setupInfo (Required): {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -690,7 +692,7 @@ public Response getMultivariateModelWithResponse(String modelId, Req
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detection results for the given resultId along with {@link Response}.
+ * @return detection results for the resultId value along with {@link Response}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -702,8 +704,8 @@ public Response detectMultivariateBatchAnomalyWithResponse(
/**
* Detect anomalies in the last point of the request body
*
- * 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
+ *
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.
*
*
Request Body Schema
@@ -721,7 +723,7 @@ public Response detectMultivariateBatchAnomalyWithResponse(
* ]
* }
* ]
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* }
* }
*
@@ -769,13 +771,13 @@ public Response detectMultivariateBatchAnomalyWithResponse(
* }
*
* @param modelId Model identifier.
- * @param options Request of last detection.
+ * @param options Request of the last detection.
* @param requestOptions The options to configure the HTTP request before HTTP client sends it.
* @throws HttpResponseException thrown if the request is rejected by server.
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return results of last detection along with {@link Response}.
+ * @return results of the last detection along with {@link Response}.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -784,36 +786,10 @@ public Response detectMultivariateLastAnomalyWithResponse(
return this.client.detectMultivariateLastAnomalyWithResponse(modelId, options, requestOptions).block();
}
- /**
- * Detect anomalies for the entire series in batch.
- *
- * This operation generates a model with an entire series, each point is detected with the same model. With this
- * method, points before and after a certain point are used to determine whether it is an anomaly. The entire
- * detection can give user an overall status of the time series.
- *
- * @param options Method of univariate anomaly detection.
- * @throws IllegalArgumentException thrown if parameters fail the validation.
- * @throws HttpResponseException thrown if the request is rejected by server.
- * @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
- * @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
- * @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return the response of entire anomaly detection.
- */
- @Generated
- @ServiceMethod(returns = ReturnType.SINGLE)
- public UnivariateEntireDetectionResult detectUnivariateEntireSeries(UnivariateDetectionOptions options) {
- // Generated convenience method for detectUnivariateEntireSeriesWithResponse
- RequestOptions requestOptions = new RequestOptions();
- return detectUnivariateEntireSeriesWithResponse(BinaryData.fromObject(options), requestOptions)
- .getValue()
- .toObject(UnivariateEntireDetectionResult.class);
- }
-
/**
* Detect anomaly status of the latest point in time series.
*
- *
This operation generates a model using the points that you sent into the API, and based on all data to
+ *
This operation generates a model by using the points that you sent in to the API and based on all data to
* determine whether the last point is anomalous.
*
* @param options Method of univariate anomaly detection.
@@ -823,7 +799,7 @@ public UnivariateEntireDetectionResult detectUnivariateEntireSeries(UnivariateDe
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return the response of last anomaly detection.
+ * @return response of the last anomaly detection.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -838,7 +814,7 @@ public UnivariateLastDetectionResult detectUnivariateLastPoint(UnivariateDetecti
/**
* Detect change point for the entire series
*
- *
Evaluate change point score of every series point.
+ *
Evaluate the change point score of every series point.
*
* @param options Method of univariate anomaly detection.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -847,7 +823,7 @@ public UnivariateLastDetectionResult detectUnivariateLastPoint(UnivariateDetecti
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return the response of change point detection.
+ * @return response of change point detection.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -863,8 +839,8 @@ public UnivariateChangePointDetectionResult detectUnivariateChangePoint(
/**
* Get Multivariate Anomaly Detection Result
*
- *
For asynchronous inference, get multivariate anomaly detection result based on resultId returned by the
- * BatchDetectAnomaly api.
+ *
For asynchronous inference, get a multivariate anomaly detection result based on the resultId value that the
+ * BatchDetectAnomaly API returns.
*
* @param resultId ID of a batch detection result.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -873,7 +849,7 @@ public UnivariateChangePointDetectionResult detectUnivariateChangePoint(
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return detection results for the given resultId.
+ * @return detection results for the resultId value.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -889,10 +865,12 @@ public MultivariateDetectionResult getMultivariateBatchDetectionResult(String re
* Train a Multivariate Anomaly Detection Model
*
*
Create and train a multivariate anomaly detection model. The request must include a source parameter to
- * indicate an externally accessible Azure blob storage URI.There are two types of data input: An URI pointed to an
- * Azure blob storage folder which contains multiple CSV files, and each CSV file contains two columns, timestamp
- * and variable. Another type of input is an URI pointed to a CSV file in Azure blob storage, which contains all the
- * variables and a timestamp column.
+ * indicate an Azure Blob Storage URI that's accessible to the service. There are two types of data input. The Blob
+ * Storage URI can point to an Azure Blob Storage folder that contains multiple CSV files, where each CSV file has
+ * two columns, time stamp and variable. Or the Blob Storage URI can point to a single blob that contains a CSV file
+ * that has all the variables and a time stamp column. The model object will be created and returned in the
+ * response, but the training process happens asynchronously. To check the training status, call
+ * GetMultivariateModel with the modelId value and check the status field in the modelInfo object.
*
* @param modelInfo Model information.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -956,7 +934,7 @@ public PagedIterable listMultivariateModels() {
/**
* Delete Multivariate Model
*
- * Delete an existing multivariate model according to the modelId.
+ *
Delete an existing multivariate model according to the modelId value.
*
* @param modelId Model identifier.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -977,7 +955,8 @@ public void deleteMultivariateModel(String modelId) {
/**
* Get Multivariate Model
*
- *
Get detailed information of multivariate model, including the training status and variables used in the model.
+ *
Get detailed information about the multivariate model, including the training status and variables used in the
+ * model.
*
* @param modelId Model identifier.
* @throws IllegalArgumentException thrown if parameters fail the validation.
@@ -986,8 +965,8 @@ public void deleteMultivariateModel(String modelId) {
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return detailed information of multivariate model, including the training status and variables used in the
- * model.
+ * @return detailed information about the multivariate model, including the training status and variables used in
+ * the model.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -1002,11 +981,11 @@ public AnomalyDetectionModel getMultivariateModel(String modelId) {
/**
* Detect Multivariate Anomaly
*
- *
Submit multivariate anomaly detection task with the modelId of trained model and inference data, the input
- * schema should be the same with the training request. The request will complete asynchronously and return a
- * resultId to query the detection result.The request should be a source link to indicate an externally accessible
- * Azure storage Uri, either pointed to an Azure blob storage folder, or pointed to a CSV file in Azure blob
- * storage.
+ *
Submit a multivariate anomaly detection task with the modelId value of a trained model and inference data. The
+ * input schema should be the same with the training request. The request will finish asynchronously and return a
+ * resultId value to query the detection result. The request should be a source link to indicate an externally
+ * accessible Azure Storage URI that either points to an Azure Blob Storage folder or points to a CSV file in Azure
+ * Blob Storage.
*
* @param modelId Model identifier.
* @param options Request of multivariate anomaly detection.
@@ -1016,7 +995,7 @@ public AnomalyDetectionModel getMultivariateModel(String modelId) {
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return detection results for the given resultId.
+ * @return detection results for the resultId value.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -1032,19 +1011,19 @@ public MultivariateDetectionResult detectMultivariateBatchAnomaly(
/**
* Detect anomalies in the last point of the request body
*
- *
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
+ *
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.
*
* @param modelId Model identifier.
- * @param options Request of last detection.
+ * @param options Request of the last detection.
* @throws IllegalArgumentException thrown if parameters fail the validation.
* @throws HttpResponseException thrown if the request is rejected by server.
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
* @throws RuntimeException all other wrapped checked exceptions if the request fails to be sent.
- * @return results of last detection.
+ * @return results of the last detection.
*/
@Generated
@ServiceMethod(returns = ReturnType.SINGLE)
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorClientBuilder.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorClientBuilder.java
index 8b7440be2953..bdb1f0821858 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorClientBuilder.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/AnomalyDetectorClientBuilder.java
@@ -33,6 +33,7 @@
import com.azure.core.util.Configuration;
import com.azure.core.util.CoreUtils;
import com.azure.core.util.builder.ClientBuilderUtil;
+import com.azure.core.util.logging.ClientLogger;
import com.azure.core.util.serializer.JacksonAdapter;
import java.util.ArrayList;
import java.util.List;
@@ -72,6 +73,9 @@ public AnomalyDetectorClientBuilder() {
@Generated
@Override
public AnomalyDetectorClientBuilder pipeline(HttpPipeline pipeline) {
+ if (this.pipeline != null && pipeline == null) {
+ LOGGER.info("HttpPipeline is being set to 'null' when it was previously configured.");
+ }
this.pipeline = pipeline;
return this;
}
@@ -287,4 +291,6 @@ public AnomalyDetectorAsyncClient buildAsyncClient() {
public AnomalyDetectorClient buildClient() {
return new AnomalyDetectorClient(new AnomalyDetectorAsyncClient(buildInnerClient()));
}
+
+ private static final ClientLogger LOGGER = new ClientLogger(AnomalyDetectorClientBuilder.class);
}
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/implementation/AnomalyDetectorClientImpl.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/implementation/AnomalyDetectorClientImpl.java
index c691ab0a7989..10df3cec6861 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/implementation/AnomalyDetectorClientImpl.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/implementation/AnomalyDetectorClientImpl.java
@@ -50,13 +50,13 @@ public final class AnomalyDetectorClientImpl {
private final AnomalyDetectorClientService service;
/**
- * Supported Cognitive Services endpoints (protocol and hostname, for example:
+ * Supported Azure Cognitive Services endpoints (protocol and host name, such as
* https://westus2.api.cognitive.microsoft.com).
*/
private final String endpoint;
/**
- * Gets Supported Cognitive Services endpoints (protocol and hostname, for example:
+ * Gets Supported Azure Cognitive Services endpoints (protocol and host name, such as
* https://westus2.api.cognitive.microsoft.com).
*
* @return the endpoint value.
@@ -104,7 +104,7 @@ public SerializerAdapter getSerializerAdapter() {
/**
* Initializes an instance of AnomalyDetectorClient client.
*
- * @param endpoint Supported Cognitive Services endpoints (protocol and hostname, for example:
+ * @param endpoint Supported Azure Cognitive Services endpoints (protocol and host name, such as
* https://westus2.api.cognitive.microsoft.com).
* @param serviceVersion Service version.
*/
@@ -122,7 +122,7 @@ public AnomalyDetectorClientImpl(String endpoint, AnomalyDetectorServiceVersion
* Initializes an instance of AnomalyDetectorClient client.
*
* @param httpPipeline The HTTP pipeline to send requests through.
- * @param endpoint Supported Cognitive Services endpoints (protocol and hostname, for example:
+ * @param endpoint Supported Azure Cognitive Services endpoints (protocol and host name, such as
* https://westus2.api.cognitive.microsoft.com).
* @param serviceVersion Service version.
*/
@@ -136,7 +136,7 @@ public AnomalyDetectorClientImpl(
*
* @param httpPipeline The HTTP pipeline to send requests through.
* @param serializerAdapter The serializer to serialize an object into a string.
- * @param endpoint Supported Cognitive Services endpoints (protocol and hostname, for example:
+ * @param endpoint Supported Azure Cognitive Services endpoints (protocol and host name, such as
* https://westus2.api.cognitive.microsoft.com).
* @param serviceVersion Service version.
*/
@@ -385,9 +385,9 @@ Mono> listMultivariateModelsNext(
/**
* Detect anomalies for the entire series in batch.
*
- * This operation generates a model with an entire series, each point is detected with the same model. With this
- * method, points before and after a certain point are used to determine whether it is an anomaly. The entire
- * detection can give user an overall status of the time series.
+ *
This operation generates a model with an entire series. Each point is detected with the same model. With this
+ * method, points before and after a certain point are used to determine whether it's an anomaly. The entire
+ * detection can give the user an overall status of the time series.
*
*
Request Body Schema
*
@@ -444,7 +444,7 @@ Mono> listMultivariateModelsNext(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of entire anomaly detection along with {@link Response} on successful completion of {@link
+ * @return response of the entire anomaly detection along with {@link Response} on successful completion of {@link
* Mono}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -465,9 +465,9 @@ public Mono> detectUnivariateEntireSeriesWithResponseAsync(
/**
* Detect anomalies for the entire series in batch.
*
- * This operation generates a model with an entire series, each point is detected with the same model. With this
- * method, points before and after a certain point are used to determine whether it is an anomaly. The entire
- * detection can give user an overall status of the time series.
+ *
This operation generates a model with an entire series. Each point is detected with the same model. With this
+ * method, points before and after a certain point are used to determine whether it's an anomaly. The entire
+ * detection can give the user an overall status of the time series.
*
*
Request Body Schema
*
@@ -524,7 +524,7 @@ public Mono> detectUnivariateEntireSeriesWithResponseAsync(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of entire anomaly detection along with {@link Response}.
+ * @return response of the entire anomaly detection along with {@link Response}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Response detectUnivariateEntireSeriesWithResponse(
@@ -535,7 +535,7 @@ public Response detectUnivariateEntireSeriesWithResponse(
/**
* Detect anomaly status of the latest point in time series.
*
- * This operation generates a model using the points that you sent into the API, and based on all data to
+ *
This operation generates a model by using the points that you sent in to the API and based on all data to
* determine whether the last point is anomalous.
*
*
Request Body Schema
@@ -580,7 +580,7 @@ public Response detectUnivariateEntireSeriesWithResponse(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of last anomaly detection along with {@link Response} on successful completion of {@link
+ * @return response of the last anomaly detection along with {@link Response} on successful completion of {@link
* Mono}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -601,7 +601,7 @@ public Mono> detectUnivariateLastPointWithResponseAsync(
/**
* Detect anomaly status of the latest point in time series.
*
- * This operation generates a model using the points that you sent into the API, and based on all data to
+ *
This operation generates a model by using the points that you sent in to the API and based on all data to
* determine whether the last point is anomalous.
*
*
Request Body Schema
@@ -646,7 +646,7 @@ public Mono> detectUnivariateLastPointWithResponseAsync(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of last anomaly detection along with {@link Response}.
+ * @return response of the last anomaly detection along with {@link Response}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Response detectUnivariateLastPointWithResponse(
@@ -657,7 +657,7 @@ public Response detectUnivariateLastPointWithResponse(
/**
* Detect change point for the entire series
*
- * Evaluate change point score of every series point.
+ *
Evaluate the change point score of every series point.
*
*
Request Body Schema
*
@@ -697,8 +697,7 @@ public Response detectUnivariateLastPointWithResponse(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of change point detection along with {@link Response} on successful completion of {@link
- * Mono}.
+ * @return response of change point detection along with {@link Response} on successful completion of {@link Mono}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Mono> detectUnivariateChangePointWithResponseAsync(
@@ -718,7 +717,7 @@ public Mono> detectUnivariateChangePointWithResponseAsync(
/**
* Detect change point for the entire series
*
- * Evaluate change point score of every series point.
+ *
Evaluate the change point score of every series point.
*
*
Request Body Schema
*
@@ -758,7 +757,7 @@ public Mono> detectUnivariateChangePointWithResponseAsync(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return the response of change point detection along with {@link Response}.
+ * @return response of change point detection along with {@link Response}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Response detectUnivariateChangePointWithResponse(
@@ -769,8 +768,8 @@ public Response detectUnivariateChangePointWithResponse(
/**
* Get Multivariate Anomaly Detection Result
*
- * For asynchronous inference, get multivariate anomaly detection result based on resultId returned by the
- * BatchDetectAnomaly api.
+ *
For asynchronous inference, get a multivariate anomaly detection result based on the resultId value that the
+ * BatchDetectAnomaly API returns.
*
*
Response Body Schema
*
@@ -796,7 +795,7 @@ public Response detectUnivariateChangePointWithResponse(
* ]
* setupInfo (Required): {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -834,7 +833,7 @@ public Response detectUnivariateChangePointWithResponse(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detection results for the given resultId along with {@link Response} on successful completion of {@link
+ * @return detection results for the resultId value along with {@link Response} on successful completion of {@link
* Mono}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -855,8 +854,8 @@ public Mono> getMultivariateBatchDetectionResultWithRespons
/**
* Get Multivariate Anomaly Detection Result
*
- * For asynchronous inference, get multivariate anomaly detection result based on resultId returned by the
- * BatchDetectAnomaly api.
+ *
For asynchronous inference, get a multivariate anomaly detection result based on the resultId value that the
+ * BatchDetectAnomaly API returns.
*
*
Response Body Schema
*
@@ -882,7 +881,7 @@ public Mono> getMultivariateBatchDetectionResultWithRespons
* ]
* setupInfo (Required): {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -920,7 +919,7 @@ public Mono> getMultivariateBatchDetectionResultWithRespons
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detection results for the given resultId along with {@link Response}.
+ * @return detection results for the resultId value along with {@link Response}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Response getMultivariateBatchDetectionResultWithResponse(
@@ -932,10 +931,12 @@ public Response getMultivariateBatchDetectionResultWithResponse(
* Train a Multivariate Anomaly Detection Model
*
* Create and train a multivariate anomaly detection model. The request must include a source parameter to
- * indicate an externally accessible Azure blob storage URI.There are two types of data input: An URI pointed to an
- * Azure blob storage folder which contains multiple CSV files, and each CSV file contains two columns, timestamp
- * and variable. Another type of input is an URI pointed to a CSV file in Azure blob storage, which contains all the
- * variables and a timestamp column.
+ * indicate an Azure Blob Storage URI that's accessible to the service. There are two types of data input. The Blob
+ * Storage URI can point to an Azure Blob Storage folder that contains multiple CSV files, where each CSV file has
+ * two columns, time stamp and variable. Or the Blob Storage URI can point to a single blob that contains a CSV file
+ * that has all the variables and a time stamp column. The model object will be created and returned in the
+ * response, but the training process happens asynchronously. To check the training status, call
+ * GetMultivariateModel with the modelId value and check the status field in the modelInfo object.
*
*
Request Body Schema
*
@@ -1069,10 +1070,12 @@ public Mono> trainMultivariateModelWithResponseAsync(
* Train a Multivariate Anomaly Detection Model
*
* Create and train a multivariate anomaly detection model. The request must include a source parameter to
- * indicate an externally accessible Azure blob storage URI.There are two types of data input: An URI pointed to an
- * Azure blob storage folder which contains multiple CSV files, and each CSV file contains two columns, timestamp
- * and variable. Another type of input is an URI pointed to a CSV file in Azure blob storage, which contains all the
- * variables and a timestamp column.
+ * indicate an Azure Blob Storage URI that's accessible to the service. There are two types of data input. The Blob
+ * Storage URI can point to an Azure Blob Storage folder that contains multiple CSV files, where each CSV file has
+ * two columns, time stamp and variable. Or the Blob Storage URI can point to a single blob that contains a CSV file
+ * that has all the variables and a time stamp column. The model object will be created and returned in the
+ * response, but the training process happens asynchronously. To check the training status, call
+ * GetMultivariateModel with the modelId value and check the status field in the modelInfo object.
*
*
Request Body Schema
*
@@ -1203,8 +1206,8 @@ public Response trainMultivariateModelWithResponse(
*
* Query Parameters
* | Name | Type | Required | Description |
|---|
- * | skip | Integer | No | Skip indicates how many models will be skipped. |
- * | top | Integer | No | Top indicates how many models will be fetched. |
+ * | skip | Integer | No | The number of result items to skip. |
+ * | top | Integer | No | The number of result items to return. |
*
*
* You can add these to a request with {@link RequestOptions#addQueryParam}
@@ -1303,8 +1306,8 @@ private Mono> listMultivariateModelsSinglePageAsync(Re
*
* Query Parameters
* | Name | Type | Required | Description |
|---|
- * | skip | Integer | No | Skip indicates how many models will be skipped. |
- * | top | Integer | No | Top indicates how many models will be fetched. |
+ * | skip | Integer | No | The number of result items to skip. |
+ * | top | Integer | No | The number of result items to return. |
*
*
* You can add these to a request with {@link RequestOptions#addQueryParam}
@@ -1393,8 +1396,8 @@ public PagedFlux listMultivariateModelsAsync(RequestOptions requestO
*
* Query Parameters
* | Name | Type | Required | Description |
|---|
- * | skip | Integer | No | Skip indicates how many models will be skipped. |
- * | top | Integer | No | Top indicates how many models will be fetched. |
+ * | skip | Integer | No | The number of result items to skip. |
+ * | top | Integer | No | The number of result items to return. |
*
*
* You can add these to a request with {@link RequestOptions#addQueryParam}
@@ -1469,7 +1472,7 @@ public PagedIterable listMultivariateModels(RequestOptions requestOp
/**
* Delete Multivariate Model
*
- * Delete an existing multivariate model according to the modelId.
+ *
Delete an existing multivariate model according to the modelId value.
*
* @param modelId Model identifier.
* @param requestOptions The options to configure the HTTP request before HTTP client sends it.
@@ -1497,7 +1500,7 @@ public Mono> deleteMultivariateModelWithResponseAsync(
/**
* Delete Multivariate Model
*
- * Delete an existing multivariate model according to the modelId.
+ *
Delete an existing multivariate model according to the modelId value.
*
* @param modelId Model identifier.
* @param requestOptions The options to configure the HTTP request before HTTP client sends it.
@@ -1515,7 +1518,8 @@ public Response deleteMultivariateModelWithResponse(String modelId, Reques
/**
* Get Multivariate Model
*
- * Get detailed information of multivariate model, including the training status and variables used in the model.
+ *
Get detailed information about the multivariate model, including the training status and variables used in the
+ * model.
*
*
Response Body Schema
*
@@ -1578,8 +1582,8 @@ public Response deleteMultivariateModelWithResponse(String modelId, Reques
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detailed information of multivariate model, including the training status and variables used in the model
- * along with {@link Response} on successful completion of {@link Mono}.
+ * @return detailed information about the multivariate model, including the training status and variables used in
+ * the model along with {@link Response} on successful completion of {@link Mono}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Mono> getMultivariateModelWithResponseAsync(
@@ -1599,7 +1603,8 @@ public Mono> getMultivariateModelWithResponseAsync(
/**
* Get Multivariate Model
*
- * Get detailed information of multivariate model, including the training status and variables used in the model.
+ *
Get detailed information about the multivariate model, including the training status and variables used in the
+ * model.
*
*
Response Body Schema
*
@@ -1662,8 +1667,8 @@ public Mono> getMultivariateModelWithResponseAsync(
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detailed information of multivariate model, including the training status and variables used in the model
- * along with {@link Response}.
+ * @return detailed information about the multivariate model, including the training status and variables used in
+ * the model along with {@link Response}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Response getMultivariateModelWithResponse(String modelId, RequestOptions requestOptions) {
@@ -1673,18 +1678,18 @@ public Response getMultivariateModelWithResponse(String modelId, Req
/**
* Detect Multivariate Anomaly
*
- * Submit multivariate anomaly detection task with the modelId of trained model and inference data, the input
- * schema should be the same with the training request. The request will complete asynchronously and return a
- * resultId to query the detection result.The request should be a source link to indicate an externally accessible
- * Azure storage Uri, either pointed to an Azure blob storage folder, or pointed to a CSV file in Azure blob
- * storage.
+ *
Submit a multivariate anomaly detection task with the modelId value of a trained model and inference data. The
+ * input schema should be the same with the training request. The request will finish asynchronously and return a
+ * resultId value to query the detection result. The request should be a source link to indicate an externally
+ * accessible Azure Storage URI that either points to an Azure Blob Storage folder or points to a CSV file in Azure
+ * Blob Storage.
*
*
Request Body Schema
*
*
{@code
* {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -1714,7 +1719,7 @@ public Response getMultivariateModelWithResponse(String modelId, Req
* ]
* setupInfo (Required): {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -1753,7 +1758,7 @@ public Response getMultivariateModelWithResponse(String modelId, Req
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detection results for the given resultId along with {@link Response} on successful completion of {@link
+ * @return detection results for the resultId value along with {@link Response} on successful completion of {@link
* Mono}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
@@ -1775,18 +1780,18 @@ public Mono> detectMultivariateBatchAnomalyWithResponseAsyn
/**
* Detect Multivariate Anomaly
*
- * Submit multivariate anomaly detection task with the modelId of trained model and inference data, the input
- * schema should be the same with the training request. The request will complete asynchronously and return a
- * resultId to query the detection result.The request should be a source link to indicate an externally accessible
- * Azure storage Uri, either pointed to an Azure blob storage folder, or pointed to a CSV file in Azure blob
- * storage.
+ *
Submit a multivariate anomaly detection task with the modelId value of a trained model and inference data. The
+ * input schema should be the same with the training request. The request will finish asynchronously and return a
+ * resultId value to query the detection result. The request should be a source link to indicate an externally
+ * accessible Azure Storage URI that either points to an Azure Blob Storage folder or points to a CSV file in Azure
+ * Blob Storage.
*
*
Request Body Schema
*
*
{@code
* {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -1816,7 +1821,7 @@ public Mono> detectMultivariateBatchAnomalyWithResponseAsyn
* ]
* setupInfo (Required): {
* dataSource: String (Required)
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* startTime: OffsetDateTime (Required)
* endTime: OffsetDateTime (Required)
* }
@@ -1855,7 +1860,7 @@ public Mono> detectMultivariateBatchAnomalyWithResponseAsyn
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return detection results for the given resultId along with {@link Response}.
+ * @return detection results for the resultId value along with {@link Response}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Response detectMultivariateBatchAnomalyWithResponse(
@@ -1866,8 +1871,8 @@ public Response detectMultivariateBatchAnomalyWithResponse(
/**
* Detect anomalies in the last point of the request body
*
- * 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
+ *
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.
*
*
Request Body Schema
@@ -1885,7 +1890,7 @@ public Response detectMultivariateBatchAnomalyWithResponse(
* ]
* }
* ]
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* }
* }
*
@@ -1933,13 +1938,13 @@ public Response detectMultivariateBatchAnomalyWithResponse(
* }
*
* @param modelId Model identifier.
- * @param options Request of last detection.
+ * @param options Request of the last detection.
* @param requestOptions The options to configure the HTTP request before HTTP client sends it.
* @throws HttpResponseException thrown if the request is rejected by server.
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return results of last detection along with {@link Response} on successful completion of {@link Mono}.
+ * @return results of the last detection along with {@link Response} on successful completion of {@link Mono}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Mono> detectMultivariateLastAnomalyWithResponseAsync(
@@ -1960,8 +1965,8 @@ public Mono> detectMultivariateLastAnomalyWithResponseAsync
/**
* Detect anomalies in the last point of the request body
*
- * 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
+ *
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.
*
*
Request Body Schema
@@ -1979,7 +1984,7 @@ public Mono> detectMultivariateLastAnomalyWithResponseAsync
* ]
* }
* ]
- * topContributorCount: int (Required)
+ * topContributorCount: Integer (Optional)
* }
* }
*
@@ -2027,13 +2032,13 @@ public Mono> detectMultivariateLastAnomalyWithResponseAsync
* }
*
* @param modelId Model identifier.
- * @param options Request of last detection.
+ * @param options Request of the last detection.
* @param requestOptions The options to configure the HTTP request before HTTP client sends it.
* @throws HttpResponseException thrown if the request is rejected by server.
* @throws ClientAuthenticationException thrown if the request is rejected by server on status code 401.
* @throws ResourceNotFoundException thrown if the request is rejected by server on status code 404.
* @throws ResourceModifiedException thrown if the request is rejected by server on status code 409.
- * @return results of last detection along with {@link Response}.
+ * @return results of the last detection along with {@link Response}.
*/
@ServiceMethod(returns = ReturnType.SINGLE)
public Response detectMultivariateLastAnomalyWithResponse(
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/implementation/package-info.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/implementation/package-info.java
index 7460f62ca500..1675f0d766a8 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/implementation/package-info.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/implementation/package-info.java
@@ -4,16 +4,16 @@
/**
* Package containing the implementations for AnomalyDetector. The Anomaly Detector API detects anomalies automatically
- * in time series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In
- * stateless mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained
- * by the time series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is
- * for detecting trend changes in time series. In stateful mode, user can store time series, the stored time series will
- * be used for detection anomalies. Under this mode, user can still use the above three functionalities by only giving a
- * time range without preparing time series in client side. Besides the above three functionalities, stateful model also
- * provide group based detection and labeling service. By leveraging labeling service user can provide labels for each
- * detection result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is
- * a kind of group based detection, this detection will find inconsistency ones in a set of time series. By using
- * anomaly detector service, business customers can discover incidents and establish a logic flow for root cause
- * analysis.
+ * in time series data. It supports both a stateless detection mode and a stateful detection mode. In stateless mode,
+ * there are three functionalities. Entire Detect is for detecting the whole series, with the model trained by the time
+ * series. Last Detect is for detecting the last point, with the model trained by points before. ChangePoint Detect is
+ * for detecting trend changes in the time series. In stateful mode, the user can store time series. The stored time
+ * series will be used for detection anomalies. In this mode, the user can still use the preceding three functionalities
+ * by only giving a time range without preparing time series on the client side. Besides the preceding three
+ * functionalities, the stateful model provides group-based detection and labeling services. By using the labeling
+ * service, the user can provide labels for each detection result. These labels will be used for retuning or
+ * regenerating detection models. Inconsistency detection is a kind of group-based detection that finds inconsistencies
+ * in a set of time series. By using the anomaly detector service, business customers can discover incidents and
+ * establish a logic flow for root cause analysis.
*/
package com.azure.ai.anomalydetector.implementation;
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AlignMode.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AlignMode.java
index 0f3275035816..a6a404067a77 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AlignMode.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AlignMode.java
@@ -4,48 +4,47 @@
package com.azure.ai.anomalydetector.models;
+import com.azure.core.annotation.Generated;
+import com.azure.core.util.ExpandableStringEnum;
import com.fasterxml.jackson.annotation.JsonCreator;
-import com.fasterxml.jackson.annotation.JsonValue;
+import java.util.Collection;
/** Defines values for AlignMode. */
-public enum AlignMode {
- /** Enum value Inner. */
- INNER("Inner"),
+public final class AlignMode extends ExpandableStringEnum {
+ /** Static value Inner for AlignMode. */
+ @Generated public static final AlignMode INNER = fromString("Inner");
- /** Enum value Outer. */
- OUTER("Outer");
+ /** Static value Outer for AlignMode. */
+ @Generated public static final AlignMode OUTER = fromString("Outer");
- /** The actual serialized value for a AlignMode instance. */
- private final String value;
-
- AlignMode(String value) {
- this.value = value;
- }
+ /**
+ * Creates a new instance of AlignMode value.
+ *
+ * @deprecated Use the {@link #fromString(String)} factory method.
+ */
+ @Generated
+ @Deprecated
+ public AlignMode() {}
/**
- * Parses a serialized value to a AlignMode instance.
+ * Creates or finds a AlignMode from its string representation.
*
- * @param value the serialized value to parse.
- * @return the parsed AlignMode object, or null if unable to parse.
+ * @param name a name to look for.
+ * @return the corresponding AlignMode.
*/
+ @Generated
@JsonCreator
- public static AlignMode fromString(String value) {
- if (value == null) {
- return null;
- }
- AlignMode[] items = AlignMode.values();
- for (AlignMode item : items) {
- if (item.toString().equalsIgnoreCase(value)) {
- return item;
- }
- }
- return null;
+ public static AlignMode fromString(String name) {
+ return fromString(name, AlignMode.class);
}
- /** {@inheritDoc} */
- @JsonValue
- @Override
- public String toString() {
- return this.value;
+ /**
+ * Gets known AlignMode values.
+ *
+ * @return known AlignMode values.
+ */
+ @Generated
+ public static Collection values() {
+ return values(AlignMode.class);
}
}
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AlignPolicy.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AlignPolicy.java
index a6cbbab5fa48..a1494dd1efc6 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AlignPolicy.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AlignPolicy.java
@@ -1,15 +1,15 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Fluent;
import com.fasterxml.jackson.annotation.JsonProperty;
-/** An optional field, indicating the manner to align multiple variables. */
+/** Manner of aligning multiple variables. */
@Fluent
public final class AlignPolicy {
+
/*
* An optional field, indicating how to align different variables to the same
* time-range. Either Inner or Outer.
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyDetectionModel.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyDetectionModel.java
index c488f04619ca..59e5271bd0a4 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyDetectionModel.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyDetectionModel.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
@@ -12,6 +11,7 @@
/** Response of getting a model. */
@Immutable
public final class AnomalyDetectionModel {
+
/*
* Model identifier.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyInterpretation.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyInterpretation.java
index e2a9fce56f69..8c2a71789d59 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyInterpretation.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyInterpretation.java
@@ -1,15 +1,15 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
import com.fasterxml.jackson.annotation.JsonProperty;
-/** Interpretation of the anomalous timestamp. */
+/** Interpretation of the anomalous time stamp. */
@Immutable
public final class AnomalyInterpretation {
+
/*
* Variable.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyState.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyState.java
index 78caad875798..f73e31de0322 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyState.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyState.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
@@ -13,6 +12,7 @@
/** Anomaly status and information. */
@Immutable
public final class AnomalyState {
+
/*
* The timestamp for this anomaly.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyValue.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyValue.java
index 61a03c2f7636..752c2c0cdcfb 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyValue.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/AnomalyValue.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
@@ -9,9 +8,10 @@
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
-/** Detailed information of the anomalous timestamp. */
+/** Detailed information of the anomalous time stamp. */
@Immutable
public final class AnomalyValue {
+
/*
* True if an anomaly is detected at the current timestamp.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/CorrelationChanges.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/CorrelationChanges.java
index 941641457de2..fe72b77beb8a 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/CorrelationChanges.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/CorrelationChanges.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
@@ -11,6 +10,7 @@
/** Correlation changes among the anomalous variables. */
@Immutable
public final class CorrelationChanges {
+
/*
* The correlated variables that have correlation changes under an anomaly.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/DataSchema.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/DataSchema.java
index b996f1595862..393d6a5e6787 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/DataSchema.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/DataSchema.java
@@ -1,15 +1,15 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.util.ExpandableStringEnum;
import com.fasterxml.jackson.annotation.JsonCreator;
import java.util.Collection;
-/** Data schema of input data source: OneTable or MultiTable. The default DataSchema is OneTable. */
+/** Data schema of the input data source. The default is OneTable. */
public final class DataSchema extends ExpandableStringEnum {
+
/**
* OneTable means that your input data are all in one CSV file, which contains one 'timestamp' column and several
* variable columns. The default DataSchema is OneTable.
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/DiagnosticsInfo.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/DiagnosticsInfo.java
index 7746d0fbcaa4..8f120714f557 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/DiagnosticsInfo.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/DiagnosticsInfo.java
@@ -1,16 +1,16 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
-import com.azure.core.annotation.Fluent;
+import com.azure.core.annotation.Immutable;
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
-/** Diagnostics information to help inspect the states of model or variable. */
-@Fluent
+/** Diagnostics information to help inspect the states of a model or variable. */
+@Immutable
public final class DiagnosticsInfo {
+
/*
* Model status.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ErrorResponse.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ErrorResponse.java
index f3b26161746d..67f4e17ce771 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ErrorResponse.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ErrorResponse.java
@@ -1,16 +1,16 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
import com.fasterxml.jackson.annotation.JsonCreator;
import com.fasterxml.jackson.annotation.JsonProperty;
-/** ErrorResponse contains code and message that shows the error information. */
+/** Error information that the API returned. */
@Immutable
public final class ErrorResponse {
+
/*
* The error code.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/FillNAMethod.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/FillNAMethod.java
index 136f6221d31d..4e10952371e4 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/FillNAMethod.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/FillNAMethod.java
@@ -1,17 +1,15 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.util.ExpandableStringEnum;
import com.fasterxml.jackson.annotation.JsonCreator;
import java.util.Collection;
-/**
- * An optional field, indicating how missing values will be filled. One of Previous, Subsequent, Linear, Zero, Fixed.
- */
+/** Field that indicates how missing values will be filled. */
public final class FillNAMethod extends ExpandableStringEnum {
+
/** Static value Previous for FillNAMethod. */
public static final FillNAMethod PREVIOUS = fromString("Previous");
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ImputeMode.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ImputeMode.java
index f1b4891086cb..2a2e1bf90451 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ImputeMode.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ImputeMode.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.util.ExpandableStringEnum;
@@ -10,6 +9,7 @@
/** Defines values for ImputeMode. */
public final class ImputeMode extends ExpandableStringEnum {
+
/** Static value auto for ImputeMode. */
public static final ImputeMode AUTO = fromString("auto");
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelInfo.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelInfo.java
index 0155a4c77ad0..5a30ccb1eef9 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelInfo.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelInfo.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Fluent;
@@ -10,9 +9,10 @@
import java.time.OffsetDateTime;
import java.util.List;
-/** Training result of a model including its status, errors and diagnostics information. */
+/** Training result of a model, including its status, errors, and diagnostics information. */
@Fluent
public final class ModelInfo {
+
/*
* Source link to the input data to indicate an accessible Azure storage Uri,
* either pointed to an Azure blob storage folder, or pointed to a CSV file in
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelState.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelState.java
index fcf914eb63b8..dd6d9941f669 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelState.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelState.java
@@ -1,16 +1,16 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
-import com.azure.core.annotation.Fluent;
+import com.azure.core.annotation.Immutable;
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
/** Model status. */
-@Fluent
+@Immutable
public final class ModelState {
+
/*
* This indicates the number of passes of the entire training dataset the
* algorithm has completed.
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelStatus.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelStatus.java
index 2ff7519fd5d9..0b3460b8e8b9 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelStatus.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/ModelStatus.java
@@ -4,54 +4,53 @@
package com.azure.ai.anomalydetector.models;
+import com.azure.core.annotation.Generated;
+import com.azure.core.util.ExpandableStringEnum;
import com.fasterxml.jackson.annotation.JsonCreator;
-import com.fasterxml.jackson.annotation.JsonValue;
+import java.util.Collection;
/** Defines values for ModelStatus. */
-public enum ModelStatus {
- /** Enum value CREATED. */
- CREATED("CREATED"),
+public final class ModelStatus extends ExpandableStringEnum {
+ /** The model has been created. Training has been scheduled but not yet started. */
+ @Generated public static final ModelStatus CREATED = fromString("CREATED");
- /** Enum value RUNNING. */
- RUNNING("RUNNING"),
+ /** The model is being trained. */
+ @Generated public static final ModelStatus RUNNING = fromString("RUNNING");
- /** Enum value READY. */
- READY("READY"),
+ /** The model has been trained and is ready to be used for anomaly detection. */
+ @Generated public static final ModelStatus READY = fromString("READY");
- /** Enum value FAILED. */
- FAILED("FAILED");
+ /** The model training failed. */
+ @Generated public static final ModelStatus FAILED = fromString("FAILED");
- /** The actual serialized value for a ModelStatus instance. */
- private final String value;
-
- ModelStatus(String value) {
- this.value = value;
- }
+ /**
+ * Creates a new instance of ModelStatus value.
+ *
+ * @deprecated Use the {@link #fromString(String)} factory method.
+ */
+ @Generated
+ @Deprecated
+ public ModelStatus() {}
/**
- * Parses a serialized value to a ModelStatus instance.
+ * Creates or finds a ModelStatus from its string representation.
*
- * @param value the serialized value to parse.
- * @return the parsed ModelStatus object, or null if unable to parse.
+ * @param name a name to look for.
+ * @return the corresponding ModelStatus.
*/
+ @Generated
@JsonCreator
- public static ModelStatus fromString(String value) {
- if (value == null) {
- return null;
- }
- ModelStatus[] items = ModelStatus.values();
- for (ModelStatus item : items) {
- if (item.toString().equalsIgnoreCase(value)) {
- return item;
- }
- }
- return null;
+ public static ModelStatus fromString(String name) {
+ return fromString(name, ModelStatus.class);
}
- /** {@inheritDoc} */
- @JsonValue
- @Override
- public String toString() {
- return this.value;
+ /**
+ * Gets known ModelStatus values.
+ *
+ * @return known ModelStatus values.
+ */
+ @Generated
+ public static Collection values() {
+ return values(ModelStatus.class);
}
}
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionOptions.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionOptions.java
index 040382c0f001..e4c05444efd5 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionOptions.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionOptions.java
@@ -1,20 +1,21 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
-import com.azure.core.annotation.Immutable;
+import com.azure.core.annotation.Fluent;
+import com.azure.core.annotation.Generated;
import com.fasterxml.jackson.annotation.JsonCreator;
import com.fasterxml.jackson.annotation.JsonProperty;
import java.time.OffsetDateTime;
/**
- * Detection request for batch inference. This is an asynchronous inference which will need another API to get detection
+ * Detection request for batch inference. This is an asynchronous inference that will need another API to get detection
* results.
*/
-@Immutable
+@Fluent
public final class MultivariateBatchDetectionOptions {
+
/*
* Source link to the input data to indicate an accessible Azure storage Uri,
* either pointed to an Azure blob storage folder, or pointed to a CSV file in
@@ -106,4 +107,17 @@ public OffsetDateTime getStartTime() {
public OffsetDateTime getEndTime() {
return this.endTime;
}
+
+ /**
+ * Set the topContributorCount property: Number of top contributed variables for one anomalous time stamp in the
+ * response.
+ *
+ * @param topContributorCount the topContributorCount value to set.
+ * @return the MultivariateBatchDetectionOptions object itself.
+ */
+ @Generated
+ public MultivariateBatchDetectionOptions setTopContributorCount(Integer topContributorCount) {
+ this.topContributorCount = topContributorCount;
+ return this;
+ }
}
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionResultSummary.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionResultSummary.java
index 10b62cc16da5..a2a88690890f 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionResultSummary.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionResultSummary.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
@@ -12,6 +11,7 @@
/** Multivariate anomaly detection status. */
@Immutable
public final class MultivariateBatchDetectionResultSummary {
+
/*
* Status of detection results. One of CREATED, RUNNING, READY, and FAILED.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionStatus.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionStatus.java
index c3f17996f22c..56b1acc45967 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionStatus.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateBatchDetectionStatus.java
@@ -4,54 +4,53 @@
package com.azure.ai.anomalydetector.models;
+import com.azure.core.annotation.Generated;
+import com.azure.core.util.ExpandableStringEnum;
import com.fasterxml.jackson.annotation.JsonCreator;
-import com.fasterxml.jackson.annotation.JsonValue;
+import java.util.Collection;
/** Defines values for MultivariateBatchDetectionStatus. */
-public enum MultivariateBatchDetectionStatus {
- /** Enum value CREATED. */
- CREATED("CREATED"),
+public final class MultivariateBatchDetectionStatus extends ExpandableStringEnum {
+ /** Static value CREATED for MultivariateBatchDetectionStatus. */
+ @Generated public static final MultivariateBatchDetectionStatus CREATED = fromString("CREATED");
- /** Enum value RUNNING. */
- RUNNING("RUNNING"),
+ /** Static value RUNNING for MultivariateBatchDetectionStatus. */
+ @Generated public static final MultivariateBatchDetectionStatus RUNNING = fromString("RUNNING");
- /** Enum value READY. */
- READY("READY"),
+ /** Static value READY for MultivariateBatchDetectionStatus. */
+ @Generated public static final MultivariateBatchDetectionStatus READY = fromString("READY");
- /** Enum value FAILED. */
- FAILED("FAILED");
+ /** Static value FAILED for MultivariateBatchDetectionStatus. */
+ @Generated public static final MultivariateBatchDetectionStatus FAILED = fromString("FAILED");
- /** The actual serialized value for a MultivariateBatchDetectionStatus instance. */
- private final String value;
-
- MultivariateBatchDetectionStatus(String value) {
- this.value = value;
- }
+ /**
+ * Creates a new instance of MultivariateBatchDetectionStatus value.
+ *
+ * @deprecated Use the {@link #fromString(String)} factory method.
+ */
+ @Generated
+ @Deprecated
+ public MultivariateBatchDetectionStatus() {}
/**
- * Parses a serialized value to a MultivariateBatchDetectionStatus instance.
+ * Creates or finds a MultivariateBatchDetectionStatus from its string representation.
*
- * @param value the serialized value to parse.
- * @return the parsed MultivariateBatchDetectionStatus object, or null if unable to parse.
+ * @param name a name to look for.
+ * @return the corresponding MultivariateBatchDetectionStatus.
*/
+ @Generated
@JsonCreator
- public static MultivariateBatchDetectionStatus fromString(String value) {
- if (value == null) {
- return null;
- }
- MultivariateBatchDetectionStatus[] items = MultivariateBatchDetectionStatus.values();
- for (MultivariateBatchDetectionStatus item : items) {
- if (item.toString().equalsIgnoreCase(value)) {
- return item;
- }
- }
- return null;
+ public static MultivariateBatchDetectionStatus fromString(String name) {
+ return fromString(name, MultivariateBatchDetectionStatus.class);
}
- /** {@inheritDoc} */
- @JsonValue
- @Override
- public String toString() {
- return this.value;
+ /**
+ * Gets known MultivariateBatchDetectionStatus values.
+ *
+ * @return known MultivariateBatchDetectionStatus values.
+ */
+ @Generated
+ public static Collection values() {
+ return values(MultivariateBatchDetectionStatus.class);
}
}
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateDetectionResult.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateDetectionResult.java
index aa2938743296..f36ebd936757 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateDetectionResult.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateDetectionResult.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
@@ -9,9 +8,10 @@
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
-/** Detection results for the given resultId. */
+/** Detection results for the resultId value. */
@Immutable
public final class MultivariateDetectionResult {
+
/*
* Result identifier, which is used to fetch the results of an inference call.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateLastDetectionOptions.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateLastDetectionOptions.java
index faf9d874b8fb..8eab220543db 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateLastDetectionOptions.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateLastDetectionOptions.java
@@ -1,17 +1,18 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
-import com.azure.core.annotation.Immutable;
+import com.azure.core.annotation.Fluent;
+import com.azure.core.annotation.Generated;
import com.fasterxml.jackson.annotation.JsonCreator;
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
-/** Request of last detection. */
-@Immutable
+/** Request of the last detection. */
+@Fluent
public final class MultivariateLastDetectionOptions {
+
/*
* This contains the inference data, including the name, timestamps(ISO 8601) and
* values of variables.
@@ -60,4 +61,17 @@ public List getVariables() {
public int getTopContributorCount() {
return this.topContributorCount;
}
+
+ /**
+ * Set the topContributorCount property: Number of top contributed variables for one anomalous time stamp in the
+ * response. The default is 10.
+ *
+ * @param topContributorCount the topContributorCount value to set.
+ * @return the MultivariateLastDetectionOptions object itself.
+ */
+ @Generated
+ public MultivariateLastDetectionOptions setTopContributorCount(Integer topContributorCount) {
+ this.topContributorCount = topContributorCount;
+ return this;
+ }
}
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateLastDetectionResult.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateLastDetectionResult.java
index 356567313ae6..0d2518d01229 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateLastDetectionResult.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/MultivariateLastDetectionResult.java
@@ -1,16 +1,16 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
-/** Results of last detection. */
+/** Results of the last detection. */
@Immutable
public final class MultivariateLastDetectionResult {
+
/*
* Variable Status.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/TimeGranularity.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/TimeGranularity.java
index fea416ba0eca..bdfcdc71e3a3 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/TimeGranularity.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/TimeGranularity.java
@@ -4,69 +4,68 @@
package com.azure.ai.anomalydetector.models;
+import com.azure.core.annotation.Generated;
+import com.azure.core.util.ExpandableStringEnum;
import com.fasterxml.jackson.annotation.JsonCreator;
-import com.fasterxml.jackson.annotation.JsonValue;
+import java.util.Collection;
/** Defines values for TimeGranularity. */
-public enum TimeGranularity {
- /** Enum value yearly. */
- YEARLY("yearly"),
+public final class TimeGranularity extends ExpandableStringEnum {
+ /** Static value yearly for TimeGranularity. */
+ @Generated public static final TimeGranularity YEARLY = fromString("yearly");
- /** Enum value monthly. */
- MONTHLY("monthly"),
+ /** Static value monthly for TimeGranularity. */
+ @Generated public static final TimeGranularity MONTHLY = fromString("monthly");
- /** Enum value weekly. */
- WEEKLY("weekly"),
+ /** Static value weekly for TimeGranularity. */
+ @Generated public static final TimeGranularity WEEKLY = fromString("weekly");
- /** Enum value daily. */
- DAILY("daily"),
+ /** Static value daily for TimeGranularity. */
+ @Generated public static final TimeGranularity DAILY = fromString("daily");
- /** Enum value hourly. */
- HOURLY("hourly"),
+ /** Static value hourly for TimeGranularity. */
+ @Generated public static final TimeGranularity HOURLY = fromString("hourly");
- /** Enum value minutely. */
- PER_MINUTE("minutely"),
+ /** Static value minutely for TimeGranularity. */
+ @Generated public static final TimeGranularity PER_MINUTE = fromString("minutely");
- /** Enum value secondly. */
- PER_SECOND("secondly"),
+ /** Static value secondly for TimeGranularity. */
+ @Generated public static final TimeGranularity PER_SECOND = fromString("secondly");
- /** Enum value microsecond. */
- MICROSECOND("microsecond"),
+ /** Static value microsecond for TimeGranularity. */
+ @Generated public static final TimeGranularity MICROSECOND = fromString("microsecond");
- /** Enum value none. */
- NONE("none");
+ /** Static value none for TimeGranularity. */
+ @Generated public static final TimeGranularity NONE = fromString("none");
- /** The actual serialized value for a TimeGranularity instance. */
- private final String value;
-
- TimeGranularity(String value) {
- this.value = value;
- }
+ /**
+ * Creates a new instance of TimeGranularity value.
+ *
+ * @deprecated Use the {@link #fromString(String)} factory method.
+ */
+ @Generated
+ @Deprecated
+ public TimeGranularity() {}
/**
- * Parses a serialized value to a TimeGranularity instance.
+ * Creates or finds a TimeGranularity from its string representation.
*
- * @param value the serialized value to parse.
- * @return the parsed TimeGranularity object, or null if unable to parse.
+ * @param name a name to look for.
+ * @return the corresponding TimeGranularity.
*/
+ @Generated
@JsonCreator
- public static TimeGranularity fromString(String value) {
- if (value == null) {
- return null;
- }
- TimeGranularity[] items = TimeGranularity.values();
- for (TimeGranularity item : items) {
- if (item.toString().equalsIgnoreCase(value)) {
- return item;
- }
- }
- return null;
+ public static TimeGranularity fromString(String name) {
+ return fromString(name, TimeGranularity.class);
}
- /** {@inheritDoc} */
- @JsonValue
- @Override
- public String toString() {
- return this.value;
+ /**
+ * Gets known TimeGranularity values.
+ *
+ * @return known TimeGranularity values.
+ */
+ @Generated
+ public static Collection values() {
+ return values(TimeGranularity.class);
}
}
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/TimeSeriesPoint.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/TimeSeriesPoint.java
index e4cf70e77a62..57ef242c4508 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/TimeSeriesPoint.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/TimeSeriesPoint.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Fluent;
@@ -9,9 +8,10 @@
import com.fasterxml.jackson.annotation.JsonProperty;
import java.time.OffsetDateTime;
-/** The definition of input timeseries points. */
+/** Definition of input time series points. */
@Fluent
public final class TimeSeriesPoint {
+
/*
* Optional argument, timestamp of a data point (ISO8601 format).
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateChangePointDetectionOptions.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateChangePointDetectionOptions.java
index 1d3103748d65..42580b6b1540 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateChangePointDetectionOptions.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateChangePointDetectionOptions.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Fluent;
@@ -9,9 +8,10 @@
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
-/** The request of change point detection. */
+/** Request of change point detection. */
@Fluent
public final class UnivariateChangePointDetectionOptions {
+
/*
* Time series data points. Points should be sorted by timestamp in ascending
* order to match the change point detection result.
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateChangePointDetectionResult.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateChangePointDetectionResult.java
index 0d8774223073..08470aee5306 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateChangePointDetectionResult.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateChangePointDetectionResult.java
@@ -1,16 +1,16 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
-/** The response of change point detection. */
+/** Response of change point detection. */
@Immutable
public final class UnivariateChangePointDetectionResult {
+
/*
* Frequency extracted from the series, zero means no recurrent pattern has been
* found.
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateDetectionOptions.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateDetectionOptions.java
index a84d8b12ae70..e2e12b4fe14c 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateDetectionOptions.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateDetectionOptions.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Fluent;
@@ -9,9 +8,10 @@
import com.fasterxml.jackson.annotation.JsonProperty;
import java.util.List;
-/** The request of entire or last anomaly detection. */
+/** Request of the entire or last anomaly detection. */
@Fluent
public final class UnivariateDetectionOptions {
+
/*
* Time series data points. Points should be sorted by timestamp in ascending
* order to match the anomaly detection result. If the data is not sorted
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateLastDetectionResult.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateLastDetectionResult.java
index 7020f403d369..9b1737a45a58 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateLastDetectionResult.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/UnivariateLastDetectionResult.java
@@ -1,16 +1,16 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
import com.fasterxml.jackson.annotation.JsonCreator;
import com.fasterxml.jackson.annotation.JsonProperty;
-/** The response of last anomaly detection. */
+/** Response of the last anomaly detection. */
@Immutable
public final class UnivariateLastDetectionResult {
+
/*
* Frequency extracted from the series, zero means no recurrent pattern has been
* found.
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/VariableState.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/VariableState.java
index bcdd13530bfe..fe90eaee7fe2 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/VariableState.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/VariableState.java
@@ -1,16 +1,16 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
-import com.azure.core.annotation.Fluent;
+import com.azure.core.annotation.Immutable;
import com.fasterxml.jackson.annotation.JsonProperty;
import java.time.OffsetDateTime;
-/** Variable Status. */
-@Fluent
+/** Variable status. */
+@Immutable
public final class VariableState {
+
/*
* Variable name in variable states.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/VariableValues.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/VariableValues.java
index 8372ef5d93d8..3446f984d979 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/VariableValues.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/VariableValues.java
@@ -1,7 +1,6 @@
// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// Code generated by Microsoft (R) AutoRest Code Generator.
-
package com.azure.ai.anomalydetector.models;
import com.azure.core.annotation.Immutable;
@@ -12,6 +11,7 @@
/** Variable values. */
@Immutable
public final class VariableValues {
+
/*
* Variable name of last detection request.
*/
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/package-info.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/package-info.java
index 89b355aedf89..03840f39504b 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/package-info.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/models/package-info.java
@@ -4,16 +4,16 @@
/**
* Package containing the data models for AnomalyDetector. The Anomaly Detector API detects anomalies automatically in
- * time series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In
- * stateless mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained
- * by the time series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is
- * for detecting trend changes in time series. In stateful mode, user can store time series, the stored time series will
- * be used for detection anomalies. Under this mode, user can still use the above three functionalities by only giving a
- * time range without preparing time series in client side. Besides the above three functionalities, stateful model also
- * provide group based detection and labeling service. By leveraging labeling service user can provide labels for each
- * detection result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is
- * a kind of group based detection, this detection will find inconsistency ones in a set of time series. By using
- * anomaly detector service, business customers can discover incidents and establish a logic flow for root cause
- * analysis.
+ * time series data. It supports both a stateless detection mode and a stateful detection mode. In stateless mode, there
+ * are three functionalities. Entire Detect is for detecting the whole series, with the model trained by the time
+ * series. Last Detect is for detecting the last point, with the model trained by points before. ChangePoint Detect is
+ * for detecting trend changes in the time series. In stateful mode, the user can store time series. The stored time
+ * series will be used for detection anomalies. In this mode, the user can still use the preceding three functionalities
+ * by only giving a time range without preparing time series on the client side. Besides the preceding three
+ * functionalities, the stateful model provides group-based detection and labeling services. By using the labeling
+ * service, the user can provide labels for each detection result. These labels will be used for retuning or
+ * regenerating detection models. Inconsistency detection is a kind of group-based detection that finds inconsistencies
+ * in a set of time series. By using the anomaly detector service, business customers can discover incidents and
+ * establish a logic flow for root cause analysis.
*/
package com.azure.ai.anomalydetector.models;
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/package-info.java b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/package-info.java
index 0f8777c3c0d7..de8f5fee9994 100644
--- a/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/package-info.java
+++ b/sdk/anomalydetector/azure-ai-anomalydetector/src/main/java/com/azure/ai/anomalydetector/package-info.java
@@ -4,15 +4,16 @@
/**
* Package containing the classes for AnomalyDetector. The Anomaly Detector API detects anomalies automatically in time
- * series data. It supports two kinds of mode, one is for stateless using, another is for stateful using. In stateless
- * mode, there are three functionalities. Entire Detect is for detecting the whole series with model trained by the time
- * series, Last Detect is detecting last point with model trained by points before. ChangePoint Detect is for detecting
- * trend changes in time series. In stateful mode, user can store time series, the stored time series will be used for
- * detection anomalies. Under this mode, user can still use the above three functionalities by only giving a time range
- * without preparing time series in client side. Besides the above three functionalities, stateful model also provide
- * group based detection and labeling service. By leveraging labeling service user can provide labels for each detection
- * result, these labels will be used for retuning or regenerating detection models. Inconsistency detection is a kind of
- * group based detection, this detection will find inconsistency ones in a set of time series. By using anomaly detector
- * service, business customers can discover incidents and establish a logic flow for root cause analysis.
+ * series data. It supports both a stateless detection mode and a stateful detection mode. In stateless mode, there are
+ * three functionalities. Entire Detect is for detecting the whole series, with the model trained by the time series.
+ * Last Detect is for detecting the last point, with the model trained by points before. ChangePoint Detect is for
+ * detecting trend changes in the time series. In stateful mode, the user can store time series. The stored time series
+ * will be used for detection anomalies. In this mode, the user can still use the preceding three functionalities by
+ * only giving a time range without preparing time series on the client side. Besides the preceding three
+ * functionalities, the stateful model provides group-based detection and labeling services. By using the labeling
+ * service, the user can provide labels for each detection result. These labels will be used for retuning or
+ * regenerating detection models. Inconsistency detection is a kind of group-based detection that finds inconsistencies
+ * in a set of time series. By using the anomaly detector service, business customers can discover incidents and
+ * establish a logic flow for root cause analysis.
*/
package com.azure.ai.anomalydetector;