swagger: '2.0'
info:
  version: 2020-08-01-preview
  title: Microsoft Azure AccessControlClient AccessConnector Multivariate API
schemes:
- https
tags:
- name: Multivariate
paths:
  /multivariate/detect-batch/{resultId}:
    get:
      operationId: microsoftAzureMultivariateGetmultivariatebatchdetectionresult
      summary: Microsoft Azure Get Multivariate Anomaly Detection Result
      description: For asynchronous inference, get a multivariate anomaly detection result based on the<br>resultId value that the BatchDetectAnomaly API returns.
      parameters:
      - name: resultId
        in: path
        description: ID of a batch detection result.
        required: true
        type: string
        format: uuid
      responses:
        '200':
          description: The request has succeeded.
          schema:
            $ref: '#/definitions/Multivariate.MultivariateDetectionResult'
        default:
          description: An unexpected error response.
          schema:
            $ref: '#/definitions/Multivariate.ResponseError'
          headers:
            x-ms-error-code:
              type: string
              description: Error code.
      x-ms-examples:
        Get multivariate batch detection result:
          $ref: ./examples/GetResult.json
      tags:
      - Multivariate
  /multivariate/models:
    get:
      operationId: microsoftAzureMultivariateListmultivariatemodels
      summary: Microsoft Azure List Multivariate Models
      description: List models of a resource.
      parameters:
      - $ref: '#/parameters/Azure.Core.SkipQueryParameter'
      - $ref: '#/parameters/Azure.Core.TopQueryParameter'
      responses:
        '200':
          description: The request has succeeded.
          schema:
            $ref: '#/definitions/Multivariate.ModelList'
        default:
          description: An unexpected error response.
          schema:
            $ref: '#/definitions/Multivariate.ResponseError'
          headers:
            x-ms-error-code:
              type: string
              description: Error code.
      x-ms-examples:
        List multivariate models:
          $ref: ./examples/ListModel.json
      x-ms-pageable:
        nextLinkName: nextLink
      tags:
      - Multivariate
    post:
      operationId: microsoftAzureMultivariateTrainmultivariatemodel
      summary: Microsoft Azure Train A Multivariate Anomaly Detection Model
      description: Create and train a multivariate anomaly detection model. The request must<br>include a source parameter to indicate an Azure Blob<br>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<br>Storage folder that contains multiple CSV files, where each CSV file has<br>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<br>time stamp column.<br>The model object will be created and returned in the response, but the<br>training process happens asynchronously. To check the training status, call<br>GetMultivariateModel with the modelId value and check the status field in the<br>modelInfo object.
      parameters:
      - name: modelInfo
        in: body
        description: Model information.
        required: true
        schema:
          $ref: '#/definitions/Multivariate.ModelInfo'
      responses:
        '201':
          description: The request has succeeded and a new resource has been created as a result.
          schema:
            $ref: '#/definitions/Multivariate.AnomalyDetectionModel'
          headers:
            location:
              type: string
              description: Location and ID of the model.
        default:
          description: An unexpected error response.
          schema:
            $ref: '#/definitions/Multivariate.ResponseError'
          headers:
            x-ms-error-code:
              type: string
              description: Error code.
      x-ms-examples:
        Create and train multivariate model:
          $ref: ./examples/TrainModel.json
      tags:
      - Multivariate
  /multivariate/models/{modelId}:
    get:
      operationId: microsoftAzureMultivariateGetmultivariatemodel
      summary: Microsoft Azure Get Multivariate Model
      description: Get detailed information about the multivariate model, including the training status<br>and variables used in the model.
      parameters:
      - name: modelId
        in: path
        description: Model identifier.
        required: true
        type: string
      responses:
        '200':
          description: The request has succeeded.
          schema:
            $ref: '#/definitions/Multivariate.AnomalyDetectionModel'
        default:
          description: An unexpected error response.
          schema:
            $ref: '#/definitions/Multivariate.ResponseError'
          headers:
            x-ms-error-code:
              type: string
              description: Error code.
      x-ms-examples:
        Get a multivariate model:
          $ref: ./examples/GetModel.json
      tags:
      - Multivariate
    delete:
      operationId: microsoftAzureMultivariateDeletemultivariatemodel
      summary: Microsoft Azure Delete Multivariate Model
      description: Delete an existing multivariate model according to the modelId value.
      parameters:
      - name: modelId
        in: path
        description: Model identifier.
        required: true
        type: string
      responses:
        '204':
          description: 'There is no content to send for this request, but the headers may be useful. '
        default:
          description: An unexpected error response.
          schema:
            $ref: '#/definitions/Multivariate.ResponseError'
          headers:
            x-ms-error-code:
              type: string
              description: Error code.
      x-ms-examples:
        Delete multivariate model:
          $ref: ./examples/DeleteModel.json
      tags:
      - Multivariate
  /multivariate/models/{modelId}:detect-batch:
    post:
      operationId: microsoftAzureMultivariateDetectmultivariatebatchanomaly
      summary: Microsoft Azure Detect Multivariate Anomaly
      description: Submit a multivariate anomaly detection task with the modelId value of a trained model<br>and inference data. The input schema should be the same with the training<br>request. The request will finish asynchronously and return a resultId value to<br>query the detection result. The request should be a source link to indicate an<br>externally accessible Azure Storage URI that either points to an Azure Blob<br>Storage folder or points to a CSV file in Azure Blob Storage.
      parameters:
      - name: modelId
        in: path
        description: Model identifier.
        required: true
        type: string
      - name: options
        in: body
        description: Request of multivariate anomaly detection.
        required: true
        schema:
          $ref: '#/definitions/Multivariate.MultivariateBatchDetectionOptions'
      responses:
        '202':
          description: The request has been accepted for processing, but processing has not yet completed.
          schema:
            $ref: '#/definitions/Multivariate.MultivariateDetectionResult'
          headers:
            Operation-Id:
              type: string
              description: ID of the detection result.
            Operation-Location:
              type: string
              description: Location of the detection result.
        default:
          description: An unexpected error response.
          schema:
            $ref: '#/definitions/Multivariate.ResponseError'
          headers:
            x-ms-error-code:
              type: string
              description: Error code.
      x-ms-examples:
        Detect multivariate batch anomaly:
          $ref: ./examples/DetectAnomaly.json
      tags:
      - Multivariate
  /multivariate/models/{modelId}:detect-last:
    post:
      operationId: microsoftAzureMultivariateDetectmultivariatelastanomaly
      summary: Microsoft Azure Detect Anomalies In The Last Point Of The Request Body
      description: Submit a multivariate anomaly detection task with the modelId value of a trained model<br>and inference data. The inference data should be put into the request body in<br>JSON format. The request will finish synchronously and return the detection<br>immediately in the response body.
      parameters:
      - name: modelId
        in: path
        description: Model identifier.
        required: true
        type: string
      - name: options
        in: body
        description: Request of the last detection.
        required: true
        schema:
          $ref: '#/definitions/Multivariate.MultivariateLastDetectionOptions'
      responses:
        '200':
          description: The request has succeeded.
          schema:
            $ref: '#/definitions/Multivariate.MultivariateLastDetectionResult'
        default:
          description: An unexpected error response.
          schema:
            $ref: '#/definitions/Multivariate.ResponseError'
          headers:
            x-ms-error-code:
              type: string
              description: Error code.
      x-ms-examples:
        Detect multivariate last anomaly:
          $ref: ./examples/LastDetectAnomaly.json
      tags:
      - Multivariate
definitions:
  Azure.Core.uuid:
    type: string
    format: uuid
    description: Universally Unique Identifier
  Multivariate.ErrorResponse:
    type: object
    description: Error information that the API returned.
    properties:
      code:
        type: string
        description: Error code.
      message:
        type: string
        description: Message that explains the error that the service reported.
    required:
    - code
    - message
  Multivariate.CorrelationChanges:
    type: object
    description: Correlation changes among the anomalous variables.
    properties:
      changedVariables:
        type: array
        description: Correlated variables that have correlation changes under an anomaly.
        items:
          type: string
  Multivariate.DataSchema:
    type: string
    description: Data schema of the input data source. The default is OneTable.
    enum:
    - OneTable
    - MultiTable
    x-ms-enum:
      name: DataSchema
      modelAsString: true
      values:
      - name: OneTable
        value: OneTable
        description: OneTable means that your input data is in one CSV file, which contains one time stamp column and several variable columns. The default DataSchema value is OneTable.
      - name: MultiTable
        value: MultiTable
        description: MultiTable means that your input data is separated in multiple CSV files. Each file contains one time stamp column and one variable column, and the CSV file name should indicate the name of the variable. The default DataSchema value is OneTable.
  Multivariate.MultivariateLastDetectionResult:
    type: object
    description: Results of the last detection.
    properties:
      variableStates:
        type: array
        description: Variable status.
        items:
          $ref: '#/definitions/Multivariate.VariableState'
        x-ms-identifiers: []
      results:
        type: array
        description: Anomaly status and information.
        items:
          $ref: '#/definitions/Multivariate.AnomalyState'
        x-ms-identifiers: []
  Multivariate.FillNAMethod:
    type: string
    description: Field that indicates how missing values will be filled.
    enum:
    - Previous
    - Subsequent
    - Linear
    - Zero
    - Fixed
    x-ms-enum:
      name: FillNAMethod
      modelAsString: true
  Multivariate.ResponseError:
    type: object
    description: Error response.
    properties:
      code:
        type: string
        description: Error code.
      message:
        type: string
        description: Message that explains the error that the service reported.
    required:
    - code
    - message
  Multivariate.AlignMode:
    type: string
    enum:
    - Inner
    - Outer
    x-ms-enum:
      name: AlignMode
      modelAsString: true
  Multivariate.VariableValues:
    type: object
    description: Variable values.
    properties:
      variable:
        type: string
        description: Variable name of the last detection request.
      timestamps:
        type: array
        description: Time stamps of the last detection request.
        items:
          type: string
      values:
        type: array
        description: Values of variables.
        items:
          type: number
          format: float
    required:
    - variable
    - timestamps
    - values
  Multivariate.AnomalyInterpretation:
    type: object
    description: Interpretation of the anomalous time stamp.
    properties:
      variable:
        type: string
        description: Variable.
      contributionScore:
        type: number
        format: float
        description: 'This score shows the percentage that contributes to the anomalous time stamp. It''s a

          number between 0 and 1.'
      correlationChanges:
        $ref: '#/definitions/Multivariate.CorrelationChanges'
        description: Correlation changes among the anomalous variables.
  Multivariate.AnomalyState:
    type: object
    description: Anomaly status and information.
    properties:
      timestamp:
        type: string
        format: date-time
        description: Time stamp for this anomaly.
      value:
        $ref: '#/definitions/Multivariate.AnomalyValue'
        description: Detailed value of this anomalous time stamp.
      errors:
        type: array
        description: Error message for the current time stamp.
        items:
          $ref: '#/definitions/Multivariate.ErrorResponse'
        x-ms-identifiers: []
    required:
    - timestamp
  Multivariate.AnomalyValue:
    type: object
    description: Detailed information of the anomalous time stamp.
    properties:
      isAnomaly:
        type: boolean
        description: True if an anomaly is detected at the current time stamp.
      severity:
        type: number
        format: float
        description: 'Indicates the significance of the anomaly. The higher the severity, the more

          significant the anomaly is.'
        minimum: 0
        maximum: 1
      score:
        type: number
        format: float
        description: Raw anomaly score of severity, to help indicate the degree of abnormality.
        minimum: 0
        maximum: 2
      interpretation:
        type: array
        description: Interpretation of this anomalous time stamp.
        items:
          $ref: '#/definitions/Multivariate.AnomalyInterpretation'
        x-ms-identifiers: []
    required:
    - isAnomaly
    - severity
    - score
  Multivariate.AnomalyDetectionModel:
    type: object
    description: Response of getting a model.
    properties:
      modelId:
        $ref: '#/definitions/Azure.Core.uuid'
        description: Model identifier.
      createdTime:
        type: string
        format: date-time
        description: Date and time (UTC) when the model was created.
      lastUpdatedTime:
        type: string
        format: date-time
        description: Date and time (UTC) when the model was last updated.
      modelInfo:
        $ref: '#/definitions/Multivariate.ModelInfo'
        description: 'Training result of a model, including its status, errors, and diagnostics

          information.'
    required:
    - modelId
    - createdTime
    - lastUpdatedTime
  Multivariate.MultivariateDetectionResult:
    type: object
    description: Detection results for the resultId value.
    properties:
      resultId:
        $ref: '#/definitions/Azure.Core.uuid'
        description: Result identifier that's used to fetch the results of an inference call.
      summary:
        $ref: '#/definitions/Multivariate.MultivariateBatchDetectionResultSummary'
        description: Multivariate anomaly detection status.
      results:
        type: array
        description: Detection result for each time stamp.
        items:
          $ref: '#/definitions/Multivariate.AnomalyState'
        x-ms-identifiers: []
    required:
    - resultId
    - summary
    - results
  Multivariate.MultivariateBatchDetectionStatus:
    type: string
    enum:
    - CREATED
    - RUNNING
    - READY
    - FAILED
    x-ms-enum:
      name: MultivariateBatchDetectionStatus
      modelAsString: true
      values:
      - name: Created
        value: CREATED
      - name: Running
        value: RUNNING
      - name: Ready
        value: READY
      - name: Failed
        value: FAILED
  Multivariate.MultivariateBatchDetectionResultSummary:
    type: object
    description: Multivariate anomaly detection status.
    properties:
      status:
        $ref: '#/definitions/Multivariate.MultivariateBatchDetectionStatus'
        description: Status of detection results.
      errors:
        type: array
        description: Error message when detection fails.
        items:
          $ref: '#/definitions/Multivariate.ErrorResponse'
        x-ms-identifiers: []
      variableStates:
        type: array
        description: Variable status.
        items:
          $ref: '#/definitions/Multivariate.VariableState'
        x-ms-identifiers: []
      setupInfo:
        $ref: '#/definitions/Multivariate.MultivariateBatchDetectionOptions'
        description: 'Detection request for batch inference. This is an asynchronous inference that

          will need another API to get detection results.'
    required:
    - status
    - setupInfo
  Multivariate.AlignPolicy:
    type: object
    description: Manner of aligning multiple variables.
    properties:
      alignMode:
        $ref: '#/definitions/Multivariate.AlignMode'
        description: 'Field that indicates how to align different variables to the same

          time range.'
      fillNAMethod:
        $ref: '#/definitions/Multivariate.FillNAMethod'
        description: Field that indicates how missing values will be filled.
      paddingValue:
        type: number
        format: float
        description: Field that's required when fillNAMethod is Fixed.
  Multivariate.MultivariateLastDetectionOptions:
    type: object
    description: Request of the last detection.
    properties:
      variables:
        type: array
        description: 'Contains the inference data, including the name, time stamps (ISO 8601), and

          values of variables.'
        items:
          $ref: '#/definitions/Multivariate.VariableValues'
        x-ms-identifiers: []
      topContributorCount:
        type: integer
        format: int32
        description: 'Number of top contributed

          variables for one anomalous time stamp in the response. The default is

          10.'
        default: 10
    required:
    - variables
  Multivariate.VariableState:
    type: object
    description: Variable status.
    properties:
      variable:
        type: string
        description: Variable name in variable states.
      filledNARatio:
        type: number
        format: float
        description: Proportion of missing values that need to be filled by fillNAMethod.
        minimum: 0
        maximum: 1
      effectiveCount:
        type: integer
        format: int32
        description: Number of effective data points before fillNAMethod is applied.
      firstTimestamp:
        type: string
        format: date-time
        description: First valid time stamp with a value of input data.
      lastTimestamp:
        type: string
        format: date-time
        description: Last valid time stamp with a value of input data.
  Multivariate.ModelList:
    type: object
    description: Response of listing models.
    properties:
      models:
        type: array
        description: List of models.
        items:
          $ref: '#/definitions/Multivariate.AnomalyDetectionModel'
        x-ms-identifiers: []
      currentCount:
        type: integer
        format: int32
        description: Number of trained multivariate models.
      maxCount:
        type: integer
        format: int32
        description: Maximum number of models that can be trained for this Anomaly Detector resource.
      nextLink:
        type: string
        description: Link to fetch more models.
    required:
    - models
    - currentCount
    - maxCount
  Multivariate.DiagnosticsInfo:
    type: object
    description: Diagnostics information to help inspect the states of a model or variable.
    properties:
      modelState:
        $ref: '#/definitions/Multivariate.ModelState'
        description: Model status.
      variableStates:
        type: array
        description: Variable status.
        items:
          $ref: '#/definitions/Multivariate.VariableState'
        x-ms-identifiers: []
  Multivariate.MultivariateBatchDetectionOptions:
    type: object
    description: 'Detection request for batch inference. This is an asynchronous inference that

      will need another API to get detection results.'
    properties:
      dataSource:
        type: string
        format: uri
        description: 'Source link to the input data to indicate an accessible Azure Storage URI.

          It either points to an Azure Blob Storage folder or points to a CSV file in

          Azure Blob Storage, based on your data schema selection. The data schema should

          be exactly the same as those used in the training phase. The input data must

          contain at least slidingWindow entries preceding the start time of the data

          to be detected.'
      topContributorCount:
        type: integer
        format: int32
        description: Number of top contributed variables for one anomalous time stamp in the response.
        default: 10
      startTime:
        type: string
        format: date-time
        description: 'Start date/time of data for detection, which should

          be in ISO 8601 format.'
      endTime:
        type: string
        format: date-time
        description: 'End date/time of data for detection, which should

          be in ISO 8601 format.'
    required:
    - dataSource
    - startTime
    - endTime
  Multivariate.ModelStatus:
    type: string
    enum:
    - CREATED
    - RUNNING
    - READY
    - FAILED
    x-ms-enum:
      name: ModelStatus
      modelAsString: true
      values:
      - name: Created
        value: CREATED
        description: The model has been created. Training has been scheduled but not yet started.
      - name: Running
        value: RUNNING
        description: The model is being trained.
      - name: Ready
        value: READY
        description: The model has been trained and is ready to be used for anomaly detection.
      - name: Failed
        value: FAILED
        description: The model training failed.
  Multivariate.ModelState:
    type: object
    description: Model status.
    properties:
      epochIds:
        type: array
        description: 'Number of passes of the entire training dataset that the

          algorithm has completed.'
        items:
          type: integer
          format: int32
      trainLosses:
        type: array
        description: 'List of metrics used to assess how the model fits the training data for each

          epoch.'
        items:
          type: number
          format: float
      validationLosses:
        type: array
        description: 'List of metrics used to assess how the model fits the validation set for each

          epoch.'
        items:
          type: number
          format: float
      latenciesInSeconds:
        type: array
        description: Latency for each epoch.
        items:
          type: number
          format: float
  Multivariate.ModelInfo:
    type: object
    description: 'Training result of a model, including its status, errors, and diagnostics

      information.'
    properties:
      dataSource:
        type: string
        format: uri
        description: 'Source link to the input data to indicate an accessible Azure Storage URI.

          It either points to an Azure Blob Storage folder or points to a CSV file in

          Azure Blob Storage, based on your data schema selection.'
      dataSchema:
        $ref: '#/definitions/Multivariate.DataSchema'
        description: 'Data schema of the input data source. The default

          is OneTable.'
      startTime:
        type: string
        format: date-time
        description: 'Start date/time of training data, which should be

          in ISO 8601 format.'
      endTime:
        type: string
        format: date-time
        description: 'End date/time of training data, which should be

          in ISO 8601 format.'
      displayName:
        type: string
        description: 'Display name of the model. Maximum length is 24

          characters.'
        maxLength: 24
      slidingWindow:
        type: integer
        format: int32
        description: 'Number of previous time stamps that will be used to

          detect whether the time stamp is an anomaly or not.'
      alignPolicy:
        $ref: '#/definitions/Multivariate.AlignPolicy'
        description: Manner of aligning multiple variables.
      status:
        $ref: '#/definitions/Multivariate.ModelStatus'
        description: Model status.
        readOnly: true
      errors:
        type: array
        description: Error messages after failure to create a model.
        items:
          $ref: '#/definitions/Multivariate.ErrorResponse'
        readOnly: true
        x-ms-identifiers: []
      diagnosticsInfo:
        $ref: '#/definitions/Multivariate.DiagnosticsInfo'
        description: Diagnostics information to help inspect the states of a model or variable.
        readOnly: true
    required:
    - dataSource
    - startTime
    - endTime
parameters:
  Azure.Core.TopQueryParameter:
    name: top
    in: query
    description: The number of result items to return.
    required: false
    type: integer
    format: int32
    x-ms-parameter-location: method
  Azure.Core.SkipQueryParameter:
    name: skip
    in: query
    description: The number of result items to skip.
    required: false
    type: integer
    format: int32
    default: 0
    x-ms-parameter-location: method
x-ms-parameterized-host:
  hostTemplate: '{endpoint}'
  useSchemePrefix: false
  parameters:
  - $ref: '#/parameters/Endpoint'