bump mvad 07be669ac8e83c8766f10e99c59dbd2375614776 (#36166)

* bump mvad 07be669ac8e83c8766f10e99c59dbd2375614776 * fix test case and update api / snippets
Azure · May 10, 2023 · 715669c · 715669c
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diff --git a/sdk/anomalydetector/Azure.AI.AnomalyDetector/README.md b/sdk/anomalydetector/Azure.AI.AnomalyDetector/README.md
@@ -126,12 +126,13 @@ Console.WriteLine("Detecting anomalies in the entire time series.");
 
 try
 {
-    UnivariateEntireDetectionResult result = client.DetectUnivariateEntireSeries(request);
+    Response response = client.DetectUnivariateEntireSeries(request.ToRequestContent());
+    JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
 
     bool hasAnomaly = false;
     for (int i = 0; i < request.Series.Count; ++i)
     {
-        if (result.IsAnomaly[i])
+        if (result.GetProperty("isAnomaly")[i].GetBoolean())
         {
             Console.WriteLine($"An anomaly was detected at index: {i}.");
             hasAnomaly = true;

diff --git a/sdk/anomalydetector/Azure.AI.AnomalyDetector/api/Azure.AI.AnomalyDetector.netstandard2.0.cs b/sdk/anomalydetector/Azure.AI.AnomalyDetector/api/Azure.AI.AnomalyDetector.netstandard2.0.cs
@@ -53,9 +53,7 @@ public AnomalyDetectorClient(System.Uri endpoint, Azure.AzureKeyCredential crede
         public virtual Azure.Response DetectUnivariateChangePoint(Azure.Core.RequestContent content, Azure.RequestContext context = null) { throw null; }
         public virtual System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.UnivariateChangePointDetectionResult>> DetectUnivariateChangePointAsync(Azure.AI.AnomalyDetector.UnivariateChangePointDetectionOptions options, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
         public virtual System.Threading.Tasks.Task<Azure.Response> DetectUnivariateChangePointAsync(Azure.Core.RequestContent content, Azure.RequestContext context = null) { throw null; }
-        public virtual Azure.Response<Azure.AI.AnomalyDetector.UnivariateEntireDetectionResult> DetectUnivariateEntireSeries(Azure.AI.AnomalyDetector.UnivariateDetectionOptions options, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
         public virtual Azure.Response DetectUnivariateEntireSeries(Azure.Core.RequestContent content, Azure.RequestContext context = null) { throw null; }
-        public virtual System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.UnivariateEntireDetectionResult>> DetectUnivariateEntireSeriesAsync(Azure.AI.AnomalyDetector.UnivariateDetectionOptions options, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
         public virtual System.Threading.Tasks.Task<Azure.Response> DetectUnivariateEntireSeriesAsync(Azure.Core.RequestContent content, Azure.RequestContext context = null) { throw null; }
         public virtual Azure.Response<Azure.AI.AnomalyDetector.UnivariateLastDetectionResult> DetectUnivariateLastPoint(Azure.AI.AnomalyDetector.UnivariateDetectionOptions options, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
         public virtual Azure.Response DetectUnivariateLastPoint(Azure.Core.RequestContent content, Azure.RequestContext context = null) { throw null; }
@@ -230,11 +228,11 @@ public ModelState() { }
     }
     public partial class MultivariateBatchDetectionOptions
     {
-        public MultivariateBatchDetectionOptions(string dataSource, int topContributorCount, System.DateTimeOffset startTime, System.DateTimeOffset endTime) { }
+        public MultivariateBatchDetectionOptions(string dataSource, System.DateTimeOffset startTime, System.DateTimeOffset endTime) { }
         public string DataSource { get { throw null; } set { } }
         public System.DateTimeOffset EndTime { get { throw null; } set { } }
         public System.DateTimeOffset StartTime { get { throw null; } set { } }
-        public int TopContributorCount { get { throw null; } set { } }
+        public int? TopContributorCount { get { throw null; } set { } }
     }
     public partial class MultivariateBatchDetectionResultSummary
     {
@@ -343,18 +341,6 @@ public UnivariateDetectionOptions(System.Collections.Generic.IEnumerable<Azure.A
         public int? Sensitivity { get { throw null; } set { } }
         public System.Collections.Generic.IList<Azure.AI.AnomalyDetector.TimeSeriesPoint> Series { get { throw null; } }
     }
-    public partial class UnivariateEntireDetectionResult
-    {
-        internal UnivariateEntireDetectionResult() { }
-        public System.Collections.Generic.IReadOnlyList<float> ExpectedValues { get { throw null; } }
-        public System.Collections.Generic.IReadOnlyList<bool> IsAnomaly { get { throw null; } }
-        public System.Collections.Generic.IReadOnlyList<bool> IsNegativeAnomaly { get { throw null; } }
-        public System.Collections.Generic.IReadOnlyList<bool> IsPositiveAnomaly { get { throw null; } }
-        public System.Collections.Generic.IReadOnlyList<float> LowerMargins { get { throw null; } }
-        public int Period { get { throw null; } }
-        public System.Collections.Generic.IReadOnlyList<float> Severity { get { throw null; } }
-        public System.Collections.Generic.IReadOnlyList<float> UpperMargins { get { throw null; } }
-    }
     public partial class UnivariateLastDetectionResult
     {
         internal UnivariateLastDetectionResult() { }

diff --git a/...ydetector/Azure.AI.AnomalyDetector/samples/Sample1_DetectEntireSeriesAnomaly.md b/...ydetector/Azure.AI.AnomalyDetector/samples/Sample1_DetectEntireSeriesAnomaly.md
@@ -55,12 +55,13 @@ Console.WriteLine("Detecting anomalies in the entire time series.");
 
 try
 {
-    UnivariateEntireDetectionResult result = client.DetectUnivariateEntireSeries(request);
+    Response response = client.DetectUnivariateEntireSeries(request.ToRequestContent());
+    JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
 
     bool hasAnomaly = false;
     for (int i = 0; i < request.Series.Count; ++i)
     {
-        if (result.IsAnomaly[i])
+        if (result.GetProperty("isAnomaly")[i].GetBoolean())
         {
             Console.WriteLine($"An anomaly was detected at index: {i}.");
             hasAnomaly = true;

diff --git a/sdk/anomalydetector/Azure.AI.AnomalyDetector/src/Generated/AnomalyDetectorClient.cs b/sdk/anomalydetector/Azure.AI.AnomalyDetector/src/Generated/AnomalyDetectorClient.cs
diff --git a/sdk/anomalydetector/Azure.AI.AnomalyDetector/src/Generated/Docs/AnomalyDetectorClient.xml b/sdk/anomalydetector/Azure.AI.AnomalyDetector/src/Generated/Docs/AnomalyDetectorClient.xml
@@ -1,62 +1,6 @@
 <?xml version="1.0" encoding="utf-8"?>
 <doc>
   <members>
-    <member name="DetectUnivariateEntireSeriesAsync(UnivariateDetectionOptions,CancellationToken)">
-<example>
-This sample shows how to call DetectUnivariateEntireSeriesAsync with required parameters.
-<code><![CDATA[
-var credential = new AzureKeyCredential("<key>");
-var endpoint = new Uri("<https://my-service.azure.com>");
-var client = new AnomalyDetectorClient(endpoint, credential);
-
-var options = new UnivariateDetectionOptions(new TimeSeriesPoint[] 
-{
-    new TimeSeriesPoint(3.14f)
-{
-        Timestamp = DateTimeOffset.UtcNow,
-    }
-})
-{
-    Granularity = TimeGranularity.Yearly,
-    CustomInterval = 1234,
-    Period = 1234,
-    MaxAnomalyRatio = 3.14f,
-    Sensitivity = 1234,
-    ImputeMode = ImputeMode.Auto,
-    ImputeFixedValue = 3.14f,
-};
-var result = await client.DetectUnivariateEntireSeriesAsync(options);
-]]></code>
-</example>
-    </member>
-    <member name="DetectUnivariateEntireSeries(UnivariateDetectionOptions,CancellationToken)">
-<example>
-This sample shows how to call DetectUnivariateEntireSeries with required parameters.
-<code><![CDATA[
-var credential = new AzureKeyCredential("<key>");
-var endpoint = new Uri("<https://my-service.azure.com>");
-var client = new AnomalyDetectorClient(endpoint, credential);
-
-var options = new UnivariateDetectionOptions(new TimeSeriesPoint[] 
-{
-    new TimeSeriesPoint(3.14f)
-{
-        Timestamp = DateTimeOffset.UtcNow,
-    }
-})
-{
-    Granularity = TimeGranularity.Yearly,
-    CustomInterval = 1234,
-    Period = 1234,
-    MaxAnomalyRatio = 3.14f,
-    Sensitivity = 1234,
-    ImputeMode = ImputeMode.Auto,
-    ImputeFixedValue = 3.14f,
-};
-var result = client.DetectUnivariateEntireSeries(options);
-]]></code>
-</example>
-    </member>
     <member name="DetectUnivariateEntireSeriesAsync(RequestContent,RequestContext)">
 <example>
 This sample shows how to call DetectUnivariateEntireSeriesAsync with required request content, and how to parse the result.
@@ -941,7 +885,10 @@ var credential = new AzureKeyCredential("<key>");
 var endpoint = new Uri("<https://my-service.azure.com>");
 var client = new AnomalyDetectorClient(endpoint, credential);
 
-var options = new MultivariateBatchDetectionOptions("<dataSource>", 1234, DateTimeOffset.UtcNow, DateTimeOffset.UtcNow);
+var options = new MultivariateBatchDetectionOptions("<dataSource>", DateTimeOffset.UtcNow, DateTimeOffset.UtcNow)
+{
+    TopContributorCount = 1234,
+};
 var result = await client.DetectMultivariateBatchAnomalyAsync("<modelId>", options);
 ]]></code>
 </example>
@@ -954,14 +901,39 @@ var credential = new AzureKeyCredential("<key>");
 var endpoint = new Uri("<https://my-service.azure.com>");
 var client = new AnomalyDetectorClient(endpoint, credential);
 
-var options = new MultivariateBatchDetectionOptions("<dataSource>", 1234, DateTimeOffset.UtcNow, DateTimeOffset.UtcNow);
+var options = new MultivariateBatchDetectionOptions("<dataSource>", DateTimeOffset.UtcNow, DateTimeOffset.UtcNow)
+{
+    TopContributorCount = 1234,
+};
 var result = client.DetectMultivariateBatchAnomaly("<modelId>", options);
 ]]></code>
 </example>
     </member>
     <member name="DetectMultivariateBatchAnomalyAsync(string,RequestContent,RequestContext)">
 <example>
-This sample shows how to call DetectMultivariateBatchAnomalyAsync with required parameters and request content and parse the result.
+This sample shows how to call DetectMultivariateBatchAnomalyAsync with required parameters and request content, and how to parse the result.
+<code><![CDATA[
+var credential = new AzureKeyCredential("<key>");
+var endpoint = new Uri("<https://my-service.azure.com>");
+var client = new AnomalyDetectorClient(endpoint, credential);
+
+var data = new {
+    dataSource = "<dataSource>",
+    startTime = "2022-05-10T14:57:31.2311892-04:00",
+    endTime = "2022-05-10T14:57:31.2311892-04:00",
+};
+
+Response response = await client.DetectMultivariateBatchAnomalyAsync("<modelId>", RequestContent.Create(data));
+
+JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
+Console.WriteLine(result.GetProperty("resultId").ToString());
+Console.WriteLine(result.GetProperty("summary").GetProperty("status").ToString());
+Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("dataSource").ToString());
+Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("startTime").ToString());
+Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("endTime").ToString());
+Console.WriteLine(result.GetProperty("results")[0].GetProperty("timestamp").ToString());
+]]></code>
+This sample shows how to call DetectMultivariateBatchAnomalyAsync with all parameters and request content, and how to parse the result.
 <code><![CDATA[
 var credential = new AzureKeyCredential("<key>");
 var endpoint = new Uri("<https://my-service.azure.com>");
@@ -1004,7 +976,29 @@ Console.WriteLine(result.GetProperty("results")[0].GetProperty("errors")[0].GetP
     </member>
     <member name="DetectMultivariateBatchAnomaly(string,RequestContent,RequestContext)">
 <example>
-This sample shows how to call DetectMultivariateBatchAnomaly with required parameters and request content and parse the result.
+This sample shows how to call DetectMultivariateBatchAnomaly with required parameters and request content, and how to parse the result.
+<code><![CDATA[
+var credential = new AzureKeyCredential("<key>");
+var endpoint = new Uri("<https://my-service.azure.com>");
+var client = new AnomalyDetectorClient(endpoint, credential);
+
+var data = new {
+    dataSource = "<dataSource>",
+    startTime = "2022-05-10T14:57:31.2311892-04:00",
+    endTime = "2022-05-10T14:57:31.2311892-04:00",
+};
+
+Response response = client.DetectMultivariateBatchAnomaly("<modelId>", RequestContent.Create(data));
+
+JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
+Console.WriteLine(result.GetProperty("resultId").ToString());
+Console.WriteLine(result.GetProperty("summary").GetProperty("status").ToString());
+Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("dataSource").ToString());
+Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("startTime").ToString());
+Console.WriteLine(result.GetProperty("summary").GetProperty("setupInfo").GetProperty("endTime").ToString());
+Console.WriteLine(result.GetProperty("results")[0].GetProperty("timestamp").ToString());
+]]></code>
+This sample shows how to call DetectMultivariateBatchAnomaly with all parameters and request content, and how to parse the result.
 <code><![CDATA[
 var credential = new AzureKeyCredential("<key>");
 var endpoint = new Uri("<https://my-service.azure.com>");