[Cog Serv Anomaly Detector] add sample codes (#14591)

* add samples and sample data * add REAME.md for samples * add javafdoc; rename variates; * add more comments
Azure · Sep 8, 2020 · 3f42cdb · 3f42cdb
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diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/samples/README.md b/sdk/anomalydetector/azure-ai-anomalydetector/src/samples/README.md
@@ -0,0 +1,59 @@
+---
+page_type: sample
+languages:
+  - java
+products:
+  - azure
+  - azure-cognitive-services
+  - azure-anomaly-detector
+urlFragment: anomalydetector-java-samples
+---
+
+# Azure Anomaly Detector client library samples for Java
+
+Azure Anomaly Detector samples are a set of self-contained Java programs that demonstrate interacting with Azure self-contained service using the client library. Each sample focuses on a specific scenario and can be executed independently.
+
+## Key concepts
+
+Key concepts are explained in detail [here][SDK_README_KEY_CONCEPTS].
+
+## Getting started
+
+Getting started explained in detail [here][SDK_README_GETTING_STARTED].
+
+## Examples
+
+The following sections provide code samples covering common scenario operations with the Azure Anomaly Detector client library.
+
+All of these samples need the endpoint to your Anomaly Detector resource, and your Anomaly Detector API key.
+
+|**File Name**|**Description**|
+|----------------|-------------|
+|[DetectAnomaliesEntireSeries.java][detect_anomaly_entire]|Detect anomalies as a batch|
+|[DetectAnomaliesLastPoint.java][detect_anomaly_last]|Detect if last point is anomaly|
+|[DetectChangePoints.java][detect_change_point]|Detect change points in series|
+
+## Troubleshooting
+
+Troubleshooting steps can be found [here][SDK_README_TROUBLESHOOTING].
+
+## Next steps
+
+See [Next steps][SDK_README_NEXT_STEPS].
+
+## Contributing
+
+If you would like to become an active contributor to this project please refer to our [Contribution
+Guidelines][SDK_README_CONTRIBUTING] for more information.
+
+<!-- LINKS -->
+[SDK_README_CONTRIBUTING]: ../../README.md#contributing
+[SDK_README_GETTING_STARTED]: ../../README.md#getting-started
+[SDK_README_TROUBLESHOOTING]: ../../README.md#troubleshooting
+[SDK_README_KEY_CONCEPTS]: ../../README.md#key-concepts
+[SDK_README_DEPENDENCY]: ../../README.md#include-the-package
+[SDK_README_NEXT_STEPS]: ../../README.md#next-steps
+
+[detect_anomaly_entire]: ./java/com/azure/ai/anomalydetector/DetectAnomaliesEntireSeries.java
+[detect_anomaly_last]: ./java/com/azure/ai/anomalydetector/DetectAnomaliesLastPoint.java
+[detect_change_point]: ./java/com/azure/ai/anomalydetector/DetectChangePoints.java
diff --git a/...lydetector/src/samples/java/com/azure/ai/anomalydetector/DetectAnomaliesEntireSeries.java b/...lydetector/src/samples/java/com/azure/ai/anomalydetector/DetectAnomaliesEntireSeries.java
@@ -0,0 +1,97 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+package com.azure.ai.anomalydetector;
+
+import com.azure.ai.anomalydetector.models.DetectRequest;
+import com.azure.ai.anomalydetector.models.EntireDetectResponse;
+import com.azure.ai.anomalydetector.models.TimeGranularity;
+import com.azure.ai.anomalydetector.models.TimeSeriesPoint;
+import com.azure.core.credential.AzureKeyCredential;
+import com.azure.core.http.ContentType;
+import com.azure.core.http.HttpClient;
+import com.azure.core.http.HttpHeaders;
+import com.azure.core.http.HttpPipeline;
+import com.azure.core.http.HttpPipelineBuilder;
+import com.azure.core.http.policy.AddHeadersPolicy;
+import com.azure.core.http.policy.AzureKeyCredentialPolicy;
+import com.azure.core.http.policy.HttpPipelinePolicy;
+
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.nio.file.Paths;
+import java.time.OffsetDateTime;
+import java.util.List;
+import java.util.stream.Collectors;
+
+/**
+ * Sample for detecting anomalies in a piece of time series.
+ */
+public class DetectAnomaliesEntireSeries {
+
+    /**
+     * Main method to invoke this demo.
+     *
+     * @param args Unused arguments to the program.
+     * @throws IOException Exception thrown when there is an error in reading all the lines from the csv file.
+     */
+    public static void main(final String[] args) throws IOException {
+        String endpoint = "<anomaly-detector-resource-endpoint>";
+        String key = "<anomaly-detector-resource-key>";
+        HttpHeaders headers = new HttpHeaders()
+            .put("Accept", ContentType.APPLICATION_JSON);
+
+        HttpPipelinePolicy authPolicy = new AzureKeyCredentialPolicy("Ocp-Apim-Subscription-Key",
+            new AzureKeyCredential(key));
+        AddHeadersPolicy addHeadersPolicy = new AddHeadersPolicy(headers);
+
+        HttpPipeline httpPipeline = new HttpPipelineBuilder().httpClient(HttpClient.createDefault())
+            .policies(authPolicy, addHeadersPolicy).build();
+        // Instantiate a client that will be used to call the service.
+        AnomalyDetectorClient anomalyDetectorClient = new AnomalyDetectorClientBuilder()
+            .pipeline(httpPipeline)
+            .endpoint(endpoint)
+            .buildClient();
+
+        // Read the time series from csv file and organize the time series into list of TimeSeriesPoint.
+        // The sample csv file has no header, and it contains 2 columns, namely timestamp and value.
+        // The following is a snippet of the sample csv file:
+        //      2018-03-01T00:00:00Z,32858923
+        //      2018-03-02T00:00:00Z,29615278
+        //      2018-03-03T00:00:00Z,22839355
+        //      2018-03-04T00:00:00Z,25948736
+        Path path = Paths.get("./src/samples/java/sample_data/request-data.csv");
+        List<String> requestData = Files.readAllLines(path);
+        List<TimeSeriesPoint> series = requestData.stream()
+            .map(line -> line.trim())
+            .filter(line -> line.length() > 0)
+            .map(line -> line.split(",", 2))
+            .filter(splits -> splits.length == 2)
+            .map(splits -> {
+                TimeSeriesPoint timeSeriesPoint = new TimeSeriesPoint();
+                timeSeriesPoint.setTimestamp(OffsetDateTime.parse(splits[0]));
+                timeSeriesPoint.setValue(Float.parseFloat(splits[1]));
+                return timeSeriesPoint;
+            })
+            .collect(Collectors.toList());
+
+        System.out.println("Detecting anomalies as a batch...");
+        DetectRequest request = new DetectRequest();
+        request.setSeries(series);
+        // Set the granularity to be DAILY since the minimal interval in time of the sample data is one day.
+        request.setGranularity(TimeGranularity.DAILY);
+        EntireDetectResponse response = anomalyDetectorClient.detectEntireSeries(request);
+        if (response.getIsAnomaly().contains(true)) {
+            System.out.println("Anomalies found in the following data positions:");
+            for (int i = 0; i < request.getSeries().size(); ++i) {
+                if (response.getIsAnomaly().get(i)) {
+                    System.out.print(i + " ");
+                }
+            }
+            System.out.println();
+        } else {
+            System.out.println("No anomalies were found in the series.");
+        }
+    }
+}
diff --git a/...omalydetector/src/samples/java/com/azure/ai/anomalydetector/DetectAnomaliesLastPoint.java b/...omalydetector/src/samples/java/com/azure/ai/anomalydetector/DetectAnomaliesLastPoint.java
@@ -0,0 +1,91 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+package com.azure.ai.anomalydetector;
+
+import com.azure.ai.anomalydetector.models.DetectRequest;
+import com.azure.ai.anomalydetector.models.LastDetectResponse;
+import com.azure.ai.anomalydetector.models.TimeGranularity;
+import com.azure.ai.anomalydetector.models.TimeSeriesPoint;
+import com.azure.core.credential.AzureKeyCredential;
+import com.azure.core.http.ContentType;
+import com.azure.core.http.HttpClient;
+import com.azure.core.http.HttpHeaders;
+import com.azure.core.http.HttpPipeline;
+import com.azure.core.http.HttpPipelineBuilder;
+import com.azure.core.http.policy.AddHeadersPolicy;
+import com.azure.core.http.policy.AzureKeyCredentialPolicy;
+import com.azure.core.http.policy.HttpPipelinePolicy;
+
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.nio.file.Paths;
+import java.time.OffsetDateTime;
+import java.util.List;
+import java.util.stream.Collectors;
+
+/**
+ * Sample for detecting whether the last point of time series is anomaly or not.
+ */
+public class DetectAnomaliesLastPoint {
+
+    /**
+     * Main method to invoke this demo.
+     *
+     * @param args Unused arguments to the program.
+     * @throws IOException Exception thrown when there is an error in reading all the lines from the csv file.
+     */
+    public static void main(final String[] args) throws IOException {
+        String endpoint = "<anomaly-detector-resource-endpoint>";
+        String key = "<anomaly-detector-resource-key>";
+        HttpHeaders headers = new HttpHeaders()
+            .put("Accept", ContentType.APPLICATION_JSON);
+
+        HttpPipelinePolicy authPolicy = new AzureKeyCredentialPolicy("Ocp-Apim-Subscription-Key",
+            new AzureKeyCredential(key));
+        AddHeadersPolicy addHeadersPolicy = new AddHeadersPolicy(headers);
+
+        HttpPipeline httpPipeline = new HttpPipelineBuilder().httpClient(HttpClient.createDefault())
+            .policies(authPolicy, addHeadersPolicy).build();
+        // Instantiate a client that will be used to call the service.
+        AnomalyDetectorClient anomalyDetectorClient = new AnomalyDetectorClientBuilder()
+            .pipeline(httpPipeline)
+            .endpoint(endpoint)
+            .buildClient();
+
+        // Read the time series from csv file and organize the time series into list of TimeSeriesPoint.
+        // The sample csv file has no header, and it contains 2 columns, namely timestamp and value.
+        // The following is a snippet of the sample csv file:
+        //      2018-03-01T00:00:00Z,32858923
+        //      2018-03-02T00:00:00Z,29615278
+        //      2018-03-03T00:00:00Z,22839355
+        //      2018-03-04T00:00:00Z,25948736
+        Path path = Paths.get("./src/samples/java/sample_data/request-data.csv");
+        List<String> requestData = Files.readAllLines(path);
+        List<TimeSeriesPoint> series = requestData.stream()
+            .map(line -> line.trim())
+            .filter(line -> line.length() > 0)
+            .map(line -> line.split(",", 2))
+            .filter(splits -> splits.length == 2)
+            .map(splits -> {
+                TimeSeriesPoint timeSeriesPoint = new TimeSeriesPoint();
+                timeSeriesPoint.setTimestamp(OffsetDateTime.parse(splits[0]));
+                timeSeriesPoint.setValue(Float.parseFloat(splits[1]));
+                return timeSeriesPoint;
+            })
+            .collect(Collectors.toList());
+
+        System.out.println("Determining if latest data point is an anomaly...");
+        DetectRequest request = new DetectRequest();
+        request.setSeries(series);
+        // Set the granularity to be DAILY since the minimal interval in time of the sample data is one day.
+        request.setGranularity(TimeGranularity.DAILY);
+        LastDetectResponse response = anomalyDetectorClient.detectLastPoint(request);
+        if (response.isAnomaly()) {
+            System.out.println("The latest point was detected as an anomaly.");
+        } else {
+            System.out.println("The latest point was not detected as an anomaly.");
+        }
+    }
+}
diff --git a/...-ai-anomalydetector/src/samples/java/com/azure/ai/anomalydetector/DetectChangePoints.java b/...-ai-anomalydetector/src/samples/java/com/azure/ai/anomalydetector/DetectChangePoints.java
@@ -0,0 +1,97 @@
+// Copyright (c) Microsoft Corporation. All rights reserved.
+// Licensed under the MIT License.
+
+package com.azure.ai.anomalydetector;
+
+import com.azure.ai.anomalydetector.models.ChangePointDetectRequest;
+import com.azure.ai.anomalydetector.models.ChangePointDetectResponse;
+import com.azure.ai.anomalydetector.models.TimeGranularity;
+import com.azure.ai.anomalydetector.models.TimeSeriesPoint;
+import com.azure.core.credential.AzureKeyCredential;
+import com.azure.core.http.ContentType;
+import com.azure.core.http.HttpClient;
+import com.azure.core.http.HttpHeaders;
+import com.azure.core.http.HttpPipeline;
+import com.azure.core.http.HttpPipelineBuilder;
+import com.azure.core.http.policy.AddHeadersPolicy;
+import com.azure.core.http.policy.AzureKeyCredentialPolicy;
+import com.azure.core.http.policy.HttpPipelinePolicy;
+
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.nio.file.Paths;
+import java.time.OffsetDateTime;
+import java.util.List;
+import java.util.stream.Collectors;
+
+/**
+ * Sample for detecting change points in a piece of time series.
+ */
+public class DetectChangePoints {
+
+    /**
+     * Main method to invoke this demo.
+     *
+     * @param args Unused arguments to the program.
+     * @throws IOException Exception thrown when there is an error in reading all the lines from the csv file.
+     */
+    public static void main(final String[] args) throws IOException {
+        String endpoint = "<anomaly-detector-resource-endpoint>";
+        String key = "<anomaly-detector-resource-key>";
+        HttpHeaders headers = new HttpHeaders()
+            .put("Accept", ContentType.APPLICATION_JSON);
+
+        HttpPipelinePolicy authPolicy = new AzureKeyCredentialPolicy("Ocp-Apim-Subscription-Key",
+            new AzureKeyCredential(key));
+        AddHeadersPolicy addHeadersPolicy = new AddHeadersPolicy(headers);
+
+        HttpPipeline httpPipeline = new HttpPipelineBuilder().httpClient(HttpClient.createDefault())
+            .policies(authPolicy, addHeadersPolicy).build();
+        // Instantiate a client that will be used to call the service.
+        AnomalyDetectorClient anomalyDetectorClient = new AnomalyDetectorClientBuilder()
+            .pipeline(httpPipeline)
+            .endpoint(endpoint)
+            .buildClient();
+
+        // Read the time series from csv file and organize the time series into list of TimeSeriesPoint.
+        // The sample csv file has no header, and it contains 2 columns, namely timestamp and value.
+        // The following is a snippet of the sample csv file:
+        //      2018-03-01T00:00:00Z,32858923
+        //      2018-03-02T00:00:00Z,29615278
+        //      2018-03-03T00:00:00Z,22839355
+        //      2018-03-04T00:00:00Z,25948736
+        Path path = Paths.get("./src/samples/java/sample_data/request-data.csv");
+        List<String> requestData = Files.readAllLines(path);
+        List<TimeSeriesPoint> series = requestData.stream()
+            .map(line -> line.trim())
+            .filter(line -> line.length() > 0)
+            .map(line -> line.split(",", 2))
+            .filter(splits -> splits.length == 2)
+            .map(splits -> {
+                TimeSeriesPoint timeSeriesPoint = new TimeSeriesPoint();
+                timeSeriesPoint.setTimestamp(OffsetDateTime.parse(splits[0]));
+                timeSeriesPoint.setValue(Float.parseFloat(splits[1]));
+                return timeSeriesPoint;
+            })
+            .collect(Collectors.toList());
+
+        System.out.println("Detecting change points...");
+        ChangePointDetectRequest request = new ChangePointDetectRequest();
+        request.setSeries(series);
+        // Set the granularity to be DAILY since the minimal interval in time of the sample data is one day.
+        request.setGranularity(TimeGranularity.DAILY);
+        ChangePointDetectResponse response = anomalyDetectorClient.detectChangePoint(request);
+        if (response.getIsChangePoint().contains(true)) {
+            System.out.println("Change points found in the following data positions:");
+            for (int i = 0; i < request.getSeries().size(); ++i) {
+                if (response.getIsChangePoint().get(i)) {
+                    System.out.print(i + " ");
+                }
+            }
+            System.out.println();
+        } else {
+            System.out.println("No change points were found in the series.");
+        }
+    }
+}
diff --git a/sdk/anomalydetector/azure-ai-anomalydetector/src/samples/java/sample_data/request-data.csv b/sdk/anomalydetector/azure-ai-anomalydetector/src/samples/java/sample_data/request-data.csv
@@ -0,0 +1,47 @@
+2018-03-01T00:00:00Z,32858923
+2018-03-02T00:00:00Z,29615278
+2018-03-03T00:00:00Z,22839355
+2018-03-04T00:00:00Z,25948736
+2018-03-05T00:00:00Z,34139159
+2018-03-06T00:00:00Z,33843985
+2018-03-07T00:00:00Z,33637661
+2018-03-08T00:00:00Z,32627350
+2018-03-09T00:00:00Z,29881076
+2018-03-10T00:00:00Z,22681575
+2018-03-11T00:00:00Z,24629393
+2018-03-12T00:00:00Z,34010679
+2018-03-13T00:00:00Z,33893888
+2018-03-14T00:00:00Z,33760076
+2018-03-15T00:00:00Z,33093515
+2018-03-16T00:00:00Z,29945555
+2018-03-17T00:00:00Z,22676212
+2018-03-18T00:00:00Z,25262514
+2018-03-19T00:00:00Z,33631649
+2018-03-20T00:00:00Z,34468310
+2018-03-21T00:00:00Z,34212281
+2018-03-22T00:00:00Z,38144434
+2018-03-23T00:00:00Z,34662949
+2018-03-24T00:00:00Z,24623684
+2018-03-25T00:00:00Z,26530491
+2018-03-26T00:00:00Z,35445003
+2018-03-27T00:00:00Z,34250789
+2018-03-28T00:00:00Z,33423012
+2018-03-29T00:00:00Z,30744783
+2018-03-30T00:00:00Z,25825128
+2018-03-31T00:00:00Z,21244209
+2018-04-01T00:00:00Z,22576956
+2018-04-02T00:00:00Z,31957221
+2018-04-03T00:00:00Z,33841228
+2018-04-04T00:00:00Z,33554483
+2018-04-05T00:00:00Z,32383350
+2018-04-06T00:00:00Z,29494850
+2018-04-07T00:00:00Z,22815534
+2018-04-08T00:00:00Z,25557267
+2018-04-09T00:00:00Z,34858252
+2018-04-10T00:00:00Z,34750597
+2018-04-11T00:00:00Z,34717956
+2018-04-12T00:00:00Z,34132534
+2018-04-13T00:00:00Z,30762236
+2018-04-14T00:00:00Z,22504059
+2018-04-15T00:00:00Z,26149060
+2018-04-16T00:00:00Z,35250105