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add .net samples (Azure#14579)
add .net samples
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‎sdk/anomalydetector/Azure.AI.AnomalyDetector/samples/README.md‎

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---
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page_type: sample
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languages:
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- csharp
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products:
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- azure
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- azure-cognitive-services
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- azure-anomaly-detector
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name: Azure Anomaly Detector samples for .NET
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description: Samples for the Azure.AI.AnomalyDetector client library
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---
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# Azure Anomaly Detector client SDK Samples
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These code samples show common scenario operations with the Anomaly Detector client library.
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|**Sample Name**|**Description**|
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|----------------|-------------|
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|[Sample1_DetectEntireSeriesAnomaly][sample_detect_entire_series_anomaly] |Detecting anomalies in the entire time series.|
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|[Sample2_DetectLastPointAnomaly][sample_detect_last_point_anomaly] |Detecting the anomaly status of the latest data point.|
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|[Sample3_DetectChangePoint][sample_detect_change_point] |Detecting change points in the entire time series.|
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[sample_detect_entire_series_anomaly]: ./Sample1_DetectEntireSeriesAnomaly.md
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[sample_detect_last_point_anomaly]: ./Sample2_DetectLastPointAnomaly.md
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[sample_detect_change_point]: ./Sample3_DetectChangePoint.md

‎sdk/anomalydetector/Azure.AI.AnomalyDetector/samples/Sample1_DetectEntireSeriesAnomaly.md‎

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# Detect Entire Series Anomaly
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This sample shows how to detect all the anomalies in the entire time series.
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To get started, make sure you have satisfied all the prerequisites and got all the resources required by [README][README].
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## Create an AnomalyDetectorClient
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To create a new `AnomalyDetectorClient` you need the endpoint and credentials from your resource. In the sample below you'll use an Anomaly Detector API key credential by creating an `AzureKeyCredential` object.
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You can set `endpoint` and `apiKey` based on an environment variable, a configuration setting, or any way that works for your application.
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```C# Snippet:CreateAnomalyDetectorClient
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//read endpoint and apiKey
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string endpoint = TestEnvironment.Endpoint;
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string apiKey = TestEnvironment.ApiKey;
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var endpointUri = new Uri(endpoint);
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var credential = new AzureKeyCredential(apiKey);
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//create client
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AnomalyDetectorClient client = new AnomalyDetectorClient(endpointUri, credential);
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//read data
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string datapath = Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), "samples", "data", "request-data.csv");
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```
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## Load time series and create DetectRequest
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You could download our [sample data][SampleData], read in the time series data and add it to a `DetectRequest` object.
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Call `File.ReadAllLines` with the file path and create a list of `TimeSeriesPoint` objects, and strip any new line characters. Extract the values and separate the timestamp from its numerical value, and add them to a new `TimeSeriesPoint` object.
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Make a `DetectRequest` object with the series of points, and `TimeGranularity.Daily` for the granularity (or periodicity) of the data points.
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```C# Snippet:ReadSeriesData
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List<TimeSeriesPoint> list = File.ReadAllLines(datapath, Encoding.UTF8)
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.Where(e => e.Trim().Length != 0)
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.Select(e => e.Split(','))
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.Where(e => e.Length == 2)
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.Select(e => new TimeSeriesPoint(DateTime.Parse(e[0]), float.Parse(e[1]))).ToList();
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//create request
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DetectRequest request = new DetectRequest(list, TimeGranularity.Daily);
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```
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## Detect anomalies of the entire series
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Call the client's `DetectEntireSeriesAsync` method with the `DetectRequest` object and await the response as an `EntireDetectResponse` object. Iterate through the response's `IsAnomaly` values and print any that are true. These values correspond to the index of anomalous data points, if any were found.
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```C# Snippet:DetectEntireSeriesAnomaly
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//detect
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Console.WriteLine("Detecting anomalies in the entire time series.");
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EntireDetectResponse result = await client.DetectEntireSeriesAsync(request).ConfigureAwait(false);
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if (result.IsAnomaly.Contains(true))
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{
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Console.WriteLine("An anomaly was detected at index:");
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for (int i = 0; i < request.Series.Count; ++i)
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{
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if (result.IsAnomaly[i])
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{
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Console.Write(i);
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Console.Write(" ");
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}
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}
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Console.WriteLine();
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}
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else
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{
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Console.WriteLine(" No anomalies detected in the series.");
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}
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```
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To see the full example source files, see:
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* [Detect Entire Series Anomaly](https://github.com/Azure/azure-sdk-for-net/blob/master/sdk/anomalydetector/Azure.AI.AnomalyDetector/tests/samples/Sample1_DetectEntireSeriesAnomaly.cs)
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[README]: https://github.com/Azure/azure-sdk-for-net/blob/master/sdk/anomalydetector/Azure.AI.AnomalyDetector/README.md
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[SampleData]: https://github.com/Azure/azure-sdk-for-net/tree/master/sdk/anomalydetector/Azure.AI.AnomalyDetector/tests/samples/data/request-data.csv

‎sdk/anomalydetector/Azure.AI.AnomalyDetector/samples/Sample2_DetectLastPointAnomaly.md‎

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# Detect Last Point Anomaly
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This sample shows how to detect the anomaly status of the latest data point.
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To get started, make sure you have satisfied all the prerequisites and got all the resources required by [README][README].
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## Create an AnomalyDetectorClient
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To create a new `AnomalyDetectorClient` you need the endpoint and credentials from your resource. In the sample below you'll use an Anomaly Detector API key credential by creating an `AzureKeyCredential` object.
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You can set `endpoint` and `apiKey` based on an environment variable, a configuration setting, or any way that works for your application.
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```C# Snippet:CreateAnomalyDetectorClient
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//read endpoint and apiKey
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string endpoint = TestEnvironment.Endpoint;
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string apiKey = TestEnvironment.ApiKey;
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var endpointUri = new Uri(endpoint);
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var credential = new AzureKeyCredential(apiKey);
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//create client
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AnomalyDetectorClient client = new AnomalyDetectorClient(endpointUri, credential);
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//read data
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string datapath = Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), "samples", "data", "request-data.csv");
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```
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## Load time series and create DetectRequest
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You could download our [sample data][SampleData], read in the time series data and add it to a `DetectRequest` object.
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Call `File.ReadAllLines` with the file path and create a list of `TimeSeriesPoint` objects, and strip any new line characters. Extract the values and separate the timestamp from its numerical value, and add them to a new `TimeSeriesPoint` object.
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Make a `DetectRequest` object with the series of points, and `TimeGranularity.Daily` for the granularity (or periodicity) of the data points.
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```C# Snippet:ReadSeriesData
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List<TimeSeriesPoint> list = File.ReadAllLines(datapath, Encoding.UTF8)
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.Where(e => e.Trim().Length != 0)
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.Select(e => e.Split(','))
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.Where(e => e.Length == 2)
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.Select(e => new TimeSeriesPoint(DateTime.Parse(e[0]), float.Parse(e[1]))).ToList();
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//create request
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DetectRequest request = new DetectRequest(list, TimeGranularity.Daily);
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```
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## Detect anomaly status of the latest data point
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Call the client's `DetectLastPointAsync` method with the `DetectRequest` object and await the response as a `LastDetectResponse` object. Check the response's `IsAnomaly` attribute to determine if the latest data point sent was an anomaly or not.
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```C# Snippet:DetectLastPointAnomaly
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//detect
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Console.WriteLine("Detecting the anomaly status of the latest point in the series.");
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LastDetectResponse result = await client.DetectLastPointAsync(request).ConfigureAwait(false);
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if (result.IsAnomaly)
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{
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Console.WriteLine("The latest point was detected as an anomaly.");
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}
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else
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{
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Console.WriteLine("The latest point was not detected as an anomaly.");
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}
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```
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To see the full example source files, see:
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* [Detect Last Point Anomaly](https://github.com/Azure/azure-sdk-for-net/blob/master/sdk/anomalydetector/Azure.AI.AnomalyDetector/tests/samples/Sample2_DetectLastPointAnomaly.cs)
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[README]: https://github.com/Azure/azure-sdk-for-net/blob/master/sdk/anomalydetector/Azure.AI.AnomalyDetector/README.md
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[SampleData]: https://github.com/Azure/azure-sdk-for-net/tree/master/sdk/anomalydetector/Azure.AI.AnomalyDetector/tests/samples/data/request-data.csv

‎sdk/anomalydetector/Azure.AI.AnomalyDetector/samples/Sample3_DetectChangePoint.md‎

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# Detect Change Point
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This sample shows how to detect the change point in time series.
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To get started, make sure you have satisfied all the prerequisites and got all the resources required by [README][README].
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## Create an AnomalyDetectorClient
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To create a new `AnomalyDetectorClient` you need the endpoint and credentials from your resource. In the sample below you'll use an Anomaly Detector API key credential by creating an `AzureKeyCredential` object.
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You can set `endpoint` and `apiKey` based on an environment variable, a configuration setting, or any way that works for your application.
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```C# Snippet:CreateAnomalyDetectorClient
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//read endpoint and apiKey
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string endpoint = TestEnvironment.Endpoint;
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string apiKey = TestEnvironment.ApiKey;
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var endpointUri = new Uri(endpoint);
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var credential = new AzureKeyCredential(apiKey);
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//create client
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AnomalyDetectorClient client = new AnomalyDetectorClient(endpointUri, credential);
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//read data
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string datapath = Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), "samples", "data", "request-data.csv");
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```
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## Load time series and create ChangePointDetectRequest
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You could download our [sample data][SampleData], read in the time series data and add it to a `ChangePointDetectRequest` object.
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Call `File.ReadAllLines` with the file path and create a list of `TimeSeriesPoint` objects, and strip any new line characters. Extract the values and separate the timestamp from its numerical value, and add them to a new `TimeSeriesPoint` object.
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Make a `ChangePointDetectRequest` object with the series of points, and `TimeGranularity.Daily` for the granularity (or periodicity) of the data points.
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```C# Snippet:ReadSeriesDataForChangePoint
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//read data
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string datapath = Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), "samples", "data", "request-data.csv");
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List<TimeSeriesPoint> list = File.ReadAllLines(datapath, Encoding.UTF8)
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.Where(e => e.Trim().Length != 0)
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.Select(e => e.Split(','))
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.Where(e => e.Length == 2)
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.Select(e => new TimeSeriesPoint(DateTime.Parse(e[0]), float.Parse(e[1]))).ToList();
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//create request
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ChangePointDetectRequest request = new ChangePointDetectRequest(list, TimeGranularity.Daily);
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```
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## Detect change point
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Call the client's `DetectChangePointAsync` method with the `ChangePointDetectRequest` object and await the response as a `ChangePointDetectResponse` object. Iterate through the response's `IsChangePoint` values and print any that are true. These values correspond to the index of change points, if any were found.
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```C# Snippet:DetectChangePoint
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//detect
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Console.WriteLine("Detecting the change point in the series.");
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ChangePointDetectResponse result = await client.DetectChangePointAsync(request).ConfigureAwait(false);
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if (result.IsChangePoint.Contains(true))
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{
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Console.WriteLine("A change point was detected at index:");
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for (int i = 0; i < request.Series.Count; ++i)
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{
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if (result.IsChangePoint[i])
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{
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Console.Write(i);
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Console.Write(" ");
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}
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}
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Console.WriteLine();
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}
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else
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{
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Console.WriteLine("No change point detected in the series.");
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}
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```
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To see the full example source files, see:
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* [Detect Change Point](https://github.com/Azure/azure-sdk-for-net/blob/master/sdk/anomalydetector/Azure.AI.AnomalyDetector/tests/samples/Sample3_DetectChangePoint.cs)
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[README]: https://github.com/Azure/azure-sdk-for-net/blob/master/sdk/anomalydetector/Azure.AI.AnomalyDetector/README.md
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[SampleData]: https://github.com/Azure/azure-sdk-for-net/tree/master/sdk/anomalydetector/Azure.AI.AnomalyDetector/tests/samples/data/request-data.csv

‎sdk/anomalydetector/Azure.AI.AnomalyDetector/tests/Azure.AI.AnomalyDetector.Tests.csproj‎

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<PackageReference Include="Azure.Identity" />
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</ItemGroup>
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<ItemGroup>
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<None Include="samples\data\*" CopyToOutputDirectory="PreserveNewest" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="$(AzureCoreTestFramework)" />
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<ProjectReference Include="..\src\Azure.AI.AnomalyDetector.csproj" />
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</ItemGroup>
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<ItemGroup>
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<Folder Include="samples\data\" />
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</ItemGroup>
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</Project>

‎sdk/anomalydetector/Azure.AI.AnomalyDetector/tests/samples/Sample1_DetectEntireSeriesAnomaly.cs‎

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// Copyright (c) Microsoft Corporation. All rights reserved.
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// Licensed under the MIT License.
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using System;
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using System.Collections.Generic;
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using System.IO;
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using System.Linq;
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using System.Reflection;
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using System.Text;
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using System.Threading.Tasks;
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using Azure.AI.AnomalyDetector.Models;
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using Azure.Core.TestFramework;
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using NUnit.Framework;
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namespace Azure.AI.AnomalyDetector.Tests.Samples
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{
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public partial class AnomalyDetectorSamples : SamplesBase<AnomalyDetectorTestEnvironment>
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{
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[Test]
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public async Task DetectEntireSeriesAnomaly()
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{
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#region Snippet:CreateAnomalyDetectorClient
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//read endpoint and apiKey
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string endpoint = TestEnvironment.Endpoint;
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string apiKey = TestEnvironment.ApiKey;
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var endpointUri = new Uri(endpoint);
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var credential = new AzureKeyCredential(apiKey);
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//create client
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AnomalyDetectorClient client = new AnomalyDetectorClient(endpointUri, credential);
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//read data
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string datapath = Path.Combine(Path.GetDirectoryName(Assembly.GetExecutingAssembly().Location), "samples", "data", "request-data.csv");
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#endregion
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#region Snippet:ReadSeriesData
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List<TimeSeriesPoint> list = File.ReadAllLines(datapath, Encoding.UTF8)
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.Where(e => e.Trim().Length != 0)
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.Select(e => e.Split(','))
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.Where(e => e.Length == 2)
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.Select(e => new TimeSeriesPoint(DateTime.Parse(e[0]), float.Parse(e[1]))).ToList();
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//create request
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DetectRequest request = new DetectRequest(list, TimeGranularity.Daily);
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#endregion
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#region Snippet:DetectEntireSeriesAnomaly
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//detect
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Console.WriteLine("Detecting anomalies in the entire time series.");
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EntireDetectResponse result = await client.DetectEntireSeriesAsync(request).ConfigureAwait(false);
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if (result.IsAnomaly.Contains(true))
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{
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Console.WriteLine("An anomaly was detected at index:");
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for (int i = 0; i < request.Series.Count; ++i)
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{
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if (result.IsAnomaly[i])
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{
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Console.Write(i);
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Console.Write(" ");
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}
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}
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Console.WriteLine();
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}
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else
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{
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Console.WriteLine(" No anomalies detected in the series.");
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}
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#endregion
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}
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}
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}

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