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|[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nComing soon (#10865)\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription][azure_sub].\n- An existing [Cognitive Services][cognitive_resource] or Anomaly Detector resource. If you need to create the resource, you can use the [Azure Portal][azure_portal] or [Azure CLI][azure_cli].\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource either in the [Azure Portal][azure_portal] or by using the [Azure CLI][azure_cli] snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the [Azure Portal][azure_portal] to browse to your Anomaly Detector resource and retrieve an API key, or use the [Azure CLI][azure_cli] snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library][azure_identity]. 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Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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|[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nComing soon (#10865)\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription][azure_sub].\n- An existing [Cognitive Services][cognitive_resource] or Anomaly Detector resource. If you need to create the resource, you can use the [Azure Portal][azure_portal] or [Azure CLI][azure_cli].\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource either in the [Azure Portal][azure_portal] or by using the [Azure CLI][azure_cli] snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the [Azure Portal][azure_portal] to browse to your Anomaly Detector resource and retrieve an API key, or use the [Azure CLI][azure_cli] snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library][azure_identity]. To use the [DefaultAzureCredential][defaultazurecredential] provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to [register a new AAD application][register_aad_app] and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\nComing soon (#10865)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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|[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nComing soon (#10865)\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription][azure_sub].\n- An existing [Cognitive Services][cognitive_resource] or Anomaly Detector resource. If you need to create the resource, you can use the [Azure Portal][azure_portal] or [Azure CLI][azure_cli].\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource either in the [Azure Portal][azure_portal] or by using the [Azure CLI][azure_cli] snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the [Azure Portal][azure_portal] to browse to your Anomaly Detector resource and retrieve an API key, or use the [Azure CLI][azure_cli] snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library][azure_identity]. To use the [DefaultAzureCredential][defaultazurecredential] provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to [register a new AAD application][register_aad_app] and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\nComing soon (#10865)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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|[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nComing soon (#10865)\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription][azure_sub].\n- An existing [Cognitive Services][cognitive_resource] or Anomaly Detector resource. If you need to create the resource, you can use the [Azure Portal][azure_portal] or [Azure CLI][azure_cli].\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource either in the [Azure Portal][azure_portal] or by using the [Azure CLI][azure_cli] snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the [Azure Portal][azure_portal] to browse to your Anomaly Detector resource and retrieve an API key, or use the [Azure CLI][azure_cli] snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library][azure_identity]. To use the [DefaultAzureCredential][defaultazurecredential] provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to [register a new AAD application][register_aad_app] and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\nComing soon (#10865)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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SIGNATURE-----\r\n"},"main":"dist/index.js","_from":"file:/home/vsts/work/1/packages/azure-ai-anomaly-detector-3.0.0-alpha.20210118.1.tgz","types":"types/ai-anomaly-detector.d.ts","module":"dist-esm/src/index.js","readme":"# Azure Anomaly Detector client library for JavaScript\n\n[Azure AnomalyDetector](https://azure.microsoft.com/services/cognitive-services/anomaly-detector/) API enables you to monitor and detect abnormalities in your time series data with machine learning.\n\n[Source code](https://github.com/Azure/azure-sdk-for-js/blob/master/sdk/anomalydetector/ai-anomaly-detector/) |\n[Package (NPM)](https://www.npmjs.com/package/@azure/ai-anomaly-detector) |\n[API reference documentation](https://aka.ms/azsdk/net/docs/ref/anomalydetector) |\n[Product documentation](https://docs.microsoft.com/azure/cognitive-services/anomaly-detector/) |\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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`AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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SIGNATURE-----\r\n"},"main":"dist/index.js","_from":"file:/mnt/vss/_work/1/packages/azure-ai-anomaly-detector-3.0.0-alpha.20210222.1.tgz","types":"types/ai-anomaly-detector.d.ts","module":"dist-esm/src/index.js","readme":"# Azure Anomaly Detector client library for JavaScript\n\n[Azure AnomalyDetector](https://azure.microsoft.com/services/cognitive-services/anomaly-detector/) API enables you to monitor and detect abnormalities in your time series data with machine learning.\n\n[Source code](https://github.com/Azure/azure-sdk-for-js/blob/master/sdk/anomalydetector/ai-anomaly-detector/) |\n[Package (NPM)](https://www.npmjs.com/package/@azure/ai-anomaly-detector) |\n[API reference documentation](https://docs.microsoft.com/javascript/api/@azure/ai-anomaly-detector) |\n[Product documentation](https://docs.microsoft.com/azure/cognitive-services/anomaly-detector/) |\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Enable logs\n\nYou can set the following environment variable to see debug logs when using this library.\n\n- Getting debug logs from the Azure Anomaly Detector client library\n\n```bash\nexport DEBUG=azure*\n```\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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SIGNATURE-----\r\n"},"main":"dist/index.js","_from":"file:/mnt/vss/_work/1/packages/azure-ai-anomaly-detector-3.0.0-alpha.20210316.1.tgz","types":"types/ai-anomaly-detector.d.ts","module":"dist-esm/src/index.js","readme":"# Azure Anomaly Detector client library for JavaScript\n\n[Azure AnomalyDetector](https://azure.microsoft.com/services/cognitive-services/anomaly-detector/) API enables you to monitor and detect abnormalities in your time series data with machine learning.\n\n[Source code](https://github.com/Azure/azure-sdk-for-js/blob/master/sdk/anomalydetector/ai-anomaly-detector/) |\n[Package (NPM)](https://www.npmjs.com/package/@azure/ai-anomaly-detector) |\n[API reference documentation](https://docs.microsoft.com/javascript/api/@azure/ai-anomaly-detector) |\n[Product documentation](https://docs.microsoft.com/azure/cognitive-services/anomaly-detector/) |\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* test-dist temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"dev-tool samples prep && cd dist-samples && tsc -p .","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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SIGNATURE-----\r\n"},"main":"dist/index.js","_from":"file:/mnt/vss/_work/1/packages/azure-ai-anomaly-detector-3.0.0-alpha.20210402.1.tgz","types":"types/ai-anomaly-detector.d.ts","module":"dist-esm/src/index.js","readme":"# Azure Anomaly Detector client library for JavaScript\n\n[Azure AnomalyDetector](https://azure.microsoft.com/services/cognitive-services/anomaly-detector/) API enables you to monitor and detect abnormalities in your time series data with machine learning.\n\n[Source code](https://github.com/Azure/azure-sdk-for-js/blob/master/sdk/anomalydetector/ai-anomaly-detector/) |\n[Package (NPM)](https://www.npmjs.com/package/@azure/ai-anomaly-detector) |\n[API reference documentation](https://docs.microsoft.com/javascript/api/@azure/ai-anomaly-detector) |\n[Product documentation](https://docs.microsoft.com/azure/cognitive-services/anomaly-detector/) |\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/master/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"echo Obsolete.","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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SIGNATURE-----\r\n"},"main":"dist/index.js","_from":"file:/mnt/vss/_work/1/packages/azure-ai-anomaly-detector-3.0.0-alpha.20210609.1.tgz","types":"types/ai-anomaly-detector.d.ts","module":"dist-esm/src/index.js","readme":"# Azure Anomaly Detector client library for JavaScript\n\n[Azure AnomalyDetector](https://azure.microsoft.com/services/cognitive-services/anomaly-detector/) API enables you to monitor and detect abnormalities in your time series data with machine learning.\n\n[Source code](https://github.com/Azure/azure-sdk-for-js/blob/master/sdk/anomalydetector/ai-anomaly-detector/) |\n[Package (NPM)](https://www.npmjs.com/package/@azure/ai-anomaly-detector) |\n[API reference documentation](https://docs.microsoft.com/javascript/api/@azure/ai-anomaly-detector) |\n[Product documentation](https://docs.microsoft.com/azure/cognitive-services/anomaly-detector/) |\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/master/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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|\n[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/main/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=8.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"echo Obsolete.","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- Node.js version 8.x.x or higher\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/main/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=12.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"echo Obsolete.","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/main/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=12.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"echo Obsolete.","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/generatedClientContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/main/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=12.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","prebuild":"npm run clean","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"echo Obsolete.","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/anomalyDetectorContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/main/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=12.0.0"},"scripts":{"docs":"typedoc --excludePrivate --excludeNotExported --excludeExternals --stripInternal --mode file --out ./dist/docs ./src","lint":"eslint package.json api-extractor.json src test --ext .ts","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"npm run clean && tsc -p . && rollup -c 2>&1 && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json src test --ext .ts --fix --fix-type [problem,suggestion]","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && cross-env ONLY_NODE=true rollup -c 2>&1","build:test":"tsc -p . && rollup -c rollup.test.config.js 2>&1","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && cross-env ONLY_BROWSER=true rollup -c 2>&1","build:samples":"echo Obsolete.","unit-test:node":"mocha --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace dist-test/index.node.js","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace dist-esm/test/**/*.spec.js","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"","//metadata":{"constantPaths":[{"path":"src/generated/anomalyDetectorContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"","deprecated":"This library is no longer maintained. 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Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nimport { setLogLevel } from \"@azure/logger\";\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nconst { setLogLevel } = require(\"@azure/logger\");\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/main/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=12.0.0"},"scripts":{"lint":"eslint package.json api-extractor.json README.md src test --ext .ts,.javascript,.js","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"npm run clean && tsc -p . && dev-tool run bundle && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json README.md src test --ext .ts,.javascript,.js --fix --fix-type [problem,suggestion]","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && dev-tool run bundle","build:test":"tsc -p . && dev-tool run bundle","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && dev-tool run bundle","build:samples":"echo Obsolete.","unit-test:node":"mocha -r esm --require ts-node/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace \"test/{,!(browser)/**/}*.spec.ts\"","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace \"dist-esm/test/{,!(browser)/**/}*.spec.js\"","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"/mnt/vss/_work/1/packages/azure-ai-anomaly-detector/azure-ai-anomaly-detector-3.0.0-alpha.20220525.1.tgz","//metadata":{"constantPaths":[{"path":"src/generated/anomalyDetectorContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"sha512-i4fXZAm35Lg/+f9MI2xZ2DAfKdZ85nZgFDzmwoBd3vVxn7CfKrbnolW+f3I0WQ0OGoZjqNYYZN42eFNVtzL5uw==","deprecated":"This library is no longer maintained. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://nodejs.org/about/releases/)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nconst { setLogLevel } = require(\"@azure/logger\");\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nconst { setLogLevel } = require(\"@azure/logger\");\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nconst { setLogLevel } = require(\"@azure/logger\");\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nconst { setLogLevel } = require(\"@azure/logger\");\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/main/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=14.0.0"},"scripts":{"lint":"eslint package.json api-extractor.json README.md src test --ext .ts,.javascript,.js","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"npm run clean && tsc -p . && dev-tool run bundle && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json README.md src test --ext .ts,.javascript,.js --fix --fix-type [problem,suggestion]","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && dev-tool run bundle","build:test":"tsc -p . && dev-tool run bundle","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && dev-tool run bundle","build:samples":"echo Obsolete.","unit-test:node":"mocha -r esm --require ts-node/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace \"test/{,!(browser)/**/}*.spec.ts\"","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace \"dist-esm/test/{,!(browser)/**/}*.spec.js\"","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"/mnt/vss/_work/1/packages/azure-ai-anomaly-detector/azure-ai-anomaly-detector-3.0.0-alpha.20221017.1.tgz","//metadata":{"constantPaths":[{"path":"src/generated/anomalyDetectorContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"sha512-wws9kyXv01Z2fvVCCpwjQU9w4Ii96rRKrukUNhinWonG5eE32EyUEt1nFNMxsUI/Emis1vHO2grW+BVLiC02dw==","deprecated":"This library is no longer maintained. 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[Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Key concepts\n\nThe `AnomalyDetectorClient` provides methods for anomaly detection:\n\n- `detectEntireSeries` - Detects anomalies on an entire data set\n- `detectLastPoint` - Detects anomalies in the latest data point\n- `detectChangePoint` - Evaluates change point score of every series point\n\n## Getting started\n\n### Currently supported environments\n\n- [LTS versions of Node.js](https://github.com/nodejs/release#release-schedule)\n- Latest versions of Safari, Chrome, Edge, and Firefox.\n\nSee our [support policy](https://github.com/Azure/azure-sdk-for-js/blob/main/SUPPORT.md) for more details.\n\n### Prerequisites\n\n- An [Azure subscription](https://azure.microsoft.com/free/).\n- An existing Anomaly Detector resource.\n\nIf you use the Azure CLI, replace `` and `` with your own unique names:\n\n```PowerShell\naz cognitiveservices account create --kind AnomalyDetector --resource-group --name \n```\n\n### Install the `@azure/ai-anomaly-detector` package\n\nInstall the Azure Anomaly Detector client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure/ai-anomaly-detector\n```\n\n### Create and authenticate a `AnomalyDetectorClient`\n\nTo create a client object to access the Anomaly Detector API, you will need the `endpoint` of your Anomaly Detector resource and a `credential`. The Anomaly Detector client can use either Azure Active Directory credentials or an API key credential to authenticate.\n\nYou can find the endpoint for your Anomaly Detector resource in the Azure Portal by clicking `Keys and Endpoint` under Resource Management in the menu or by using the Azure CLI snippet below:\n\n```bash\naz cognitiveservices account show --name --resource-group --query \"endpoint\"\n```\n\n#### Using an API Key\n\nUse the Azure Portal to browse to your Anomaly Detector resource and retrieve an API key by clicking `Keys and Endpoint` under Resource Management, or use the Azure CLI snippet below:\n\n**Note:** Sometimes the API key is referred to as a \"subscription key\" or \"subscription API key.\"\n\n```PowerShell\naz cognitiveservices account keys list --resource-group --name \n```\n\nOnce you have an API key and endpoint, you can use the `AzureKeyCredential` class to authenticate the client as follows:\n\n```js\nconst { AnomalyDetectorClient, AzureKeyCredential } = require(\"@azure/ai-anomaly-detector\");\n\nconst client = new AnomalyDetectorClient(\"\", new AzureKeyCredential(\"\"));\n```\n\n#### Using an Azure Active Directory Credential\n\nClient API key authentication is used in most of the examples, but you can also authenticate with Azure Active Directory using the [Azure Identity library]. To use the DefaultAzureCredential provider shown below,\nor other credential providers provided with the Azure SDK, please install the `@azure/identity` package:\n\n```bash\nnpm install @azure/identity\n```\n\nYou will also need to register a new AAD application and grant access to Anomaly Detector by assigning the `\"Cognitive Services User\"` role to your service principal (note: other roles such as `\"Owner\"` will not grant the necessary permissions, only `\"Cognitive Services User\"` will suffice to run the examples and the sample code).\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: `AZURE_CLIENT_ID`, `AZURE_TENANT_ID`, `AZURE_CLIENT_SECRET`.\n\n```js\nconst { AnomalyDetectorClient } = require(\"@azure/ai-anomaly-detector\");\nconst { DefaultAzureCredential } = require(\"@azure/identity\");\n\nconst client = new AnomalyDetectorClient(\"\", new DefaultAzureCredential());\n```\n\n## Examples\n\n### Detect Change Points\n\nThis sample demonstrates how to detect change points on entire series.\n\n```javascript\nconst { AnomalyDetectorClient, TimeGranularity } = require(\"@azure/ai-anomaly-detector\");\nconst { AzureKeyCredential } = require(\"@azure/core-auth\");\n\n// You will need to set this environment variables in .env file or edit the following values\nconst apiKey = process.env[\"API_KEY\"] || \"\";\nconst endpoint = process.env[\"ENDPOINT\"] || \"\";\n\nasync function main() {\n // create client\n const client = new AnomalyDetectorClient(endpoint, new AzureKeyCredential(apiKey));\n\n // construct request\n const request = {\n series: [\n { timestamp: new Date(\"2018-03-01T00:00:00Z\"), value: 32858923 },\n { timestamp: new Date(\"2018-03-02T00:00:00Z\"), value: 29615278 },\n { timestamp: new Date(\"2018-03-03T00:00:00Z\"), value: 22839355 },\n { timestamp: new Date(\"2018-03-04T00:00:00Z\"), value: 25948736 },\n { timestamp: new Date(\"2018-03-05T00:00:00Z\"), value: 34139159 },\n { timestamp: new Date(\"2018-03-06T00:00:00Z\"), value: 33843985 },\n { timestamp: new Date(\"2018-03-07T00:00:00Z\"), value: 33637661 },\n { timestamp: new Date(\"2018-03-08T00:00:00Z\"), value: 32627350 },\n { timestamp: new Date(\"2018-03-09T00:00:00Z\"), value: 29881076 },\n { timestamp: new Date(\"2018-03-10T00:00:00Z\"), value: 22681575 },\n { timestamp: new Date(\"2018-03-11T00:00:00Z\"), value: 24629393 },\n { timestamp: new Date(\"2018-03-12T00:00:00Z\"), value: 34010679 },\n { timestamp: new Date(\"2018-03-13T00:00:00Z\"), value: 33893888 },\n { timestamp: new Date(\"2018-03-14T00:00:00Z\"), value: 33760076 },\n { timestamp: new Date(\"2018-03-15T00:00:00Z\"), value: 33093515 }\n ],\n granularity: TimeGranularity.daily\n };\n\n // get change point detect results\n const result = await client.detectChangePoint(request);\n const isChangePointDetected = result.isChangePoint.some((changePoint) => changePoint);\n\n if (isChangePointDetected) {\n console.log(\"Change points were detected from the series at index:\");\n result.isChangePoint.forEach((changePoint, index) => {\n if (changePoint === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n // output:\n // Change points were detected from the series at index:\n // 9\n}\n\nmain().catch((err) => {\n console.error(\"The sample encountered an error:\", err);\n});\n```\n\nMore Samples can be found [here](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\n\n## Troubleshooting\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nconst { setLogLevel } = require(\"@azure/logger\");\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nPlease take a look at the\n[samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector/samples)\ndirectory for detailed examples on how to use this library.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a\nContributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us\nthe rights to use your contribution. For details, visit https://cla.microsoft.com.\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide\na CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions\nprovided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).\nFor more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or\ncontact [opencode@microsoft.com](mailto:opencode@microsoft.com) with any additional questions or comments.\n\nIf you'd like to contribute to this library, please read the [contributing guide](https://github.com/Azure/azure-sdk-for-js/blob/main/CONTRIBUTING.md) to learn more about how to build and test the code.\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=14.0.0"},"scripts":{"lint":"eslint package.json api-extractor.json README.md src test --ext .ts,.javascript,.js","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"npm run clean && tsc -p . && dev-tool run bundle && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json README.md src test --ext .ts,.javascript,.js --fix --fix-type [problem,suggestion]","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && dev-tool run bundle","build:test":"tsc -p . && dev-tool run bundle","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && dev-tool run bundle","build:samples":"echo Obsolete.","unit-test:node":"mocha -r esm --require ts-node/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace \"test/{,!(browser)/**/}*.spec.ts\"","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace \"dist-esm/test/{,!(browser)/**/}*.spec.js\"","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"/mnt/vss/_work/1/packages/azure-ai-anomaly-detector/azure-ai-anomaly-detector-3.0.0-alpha.20221107.2.tgz","//metadata":{"constantPaths":[{"path":"src/generated/anomalyDetectorContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"sha512-KsJn+GL6j1wYB6WV0iHmwCpal4i7iymOt7mBkUfuQPkOpGpFxOZmxWbW0pPjEL/t3L+vs/Ks5lZoEUjD0yeRWg==","deprecated":"This library is no longer maintained. 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`@azure-rest/ai-anomaly-detector` package\n\nInstall the Azure AnomalyDetectorRest REST client REST client library for JavaScript with `npm`:\n\n```bash\nnpm install @azure-rest/ai-anomaly-detector\n```\n\n|SDK version|Supported API version of service |\n|-------------|---------------|\n|1.0.0-beta.1| 1.1|\n\n### Create and authenticate a `AnomalyDetectorRestClient`\n\nTo use an [Azure Active Directory (AAD) token credential](https://github.com/Azure/azure-sdk-for-js/blob/main/sdk/identity/identity/samples/AzureIdentityExamples.md#authenticating-with-a-pre-fetched-access-token),\nprovide an instance of the desired credential type obtained from the\n[@azure/identity](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/identity/identity#credentials) library.\n\nTo authenticate with AAD, you must first `npm` install [`@azure/identity`](https://www.npmjs.com/package/@azure/identity) \n\nAfter setup, you can choose which type of [credential](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/identity/identity#credentials) from `@azure/identity` to use.\nAs an example, [DefaultAzureCredential](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/identity/identity#defaultazurecredential)\ncan be used to authenticate the client.\n\nSet the values of the client ID, tenant ID, and client secret of the AAD application as environment variables:\nAZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET\n\n## Key concepts\n\nWith the Anomaly Detector, you can either detect anomalies in one variable using **Univariate Anomaly Detection**, or detect anomalies in multiple variables with **Multivariate Anomaly Detection**.\n\n|Feature |Description |\n|---------|---------|\n|Univariate Anomaly Detection | Detect anomalies in one variable, like revenue, cost, etc. The model was selected automatically based on your data pattern. |\n|Multivariate Anomaly Detection| Detect anomalies in multiple variables with correlations, which are usually gathered from equipment or other complex system. The underlying model used is Graph attention network.|\n\n### Univariate Anomaly Detection\n\nThe Univariate Anomaly Detection API enables you to monitor and detect abnormalities in your time series data without having to know machine learning. The algorithms adapt by automatically identifying and applying the best-fitting models to your data, regardless of industry, scenario, or data volume. Using your time series data, the API determines boundaries for anomaly detection, expected values, and which data points are anomalies.\n\nUsing the Anomaly Detector doesn't require any prior experience in machine learning, and the REST API enables you to easily integrate the service into your applications and processes.\n\nWith the Univariate Anomaly Detection, you can automatically detect anomalies throughout your time series data, or as they occur in real-time.\n\n|Feature |Description |\n|---------|---------|\n| Streaming detection| Detect anomalies in your streaming data by using previously seen data points to determine if your latest one is an anomaly. This operation generates a model using the data points you send, and determines if the target point is an anomaly. By calling the API with each new data point you generate, you can monitor your data as it's created. |\n| Batch detection | Use your time series to detect any anomalies that might exist throughout your data. This operation generates a model using your entire time series data, with each point analyzed with the same model. |\n| Change points detection | Use your time series to detect any trend change points that exist in your data. This operation generates a model using your entire time series data, with each point analyzed with the same model. |\n\n### Multivariate Anomaly Detection\n\nThe **Multivariate Anomaly Detection** APIs further enable developers by easily integrating advanced AI for detecting anomalies from groups of metrics, without the need for machine learning knowledge or labeled data. Dependencies and inter-correlations between up to 300 different signals are now automatically counted as key factors. This new capability helps you to proactively protect your complex systems such as software applications, servers, factory machines, spacecraft, or even your business, from failures.\n\nWith the Multivariate Anomaly Detection, you can automatically detect anomalies throughout your time series data, or as they occur in real-time. There are three processes to use Multivariate Anomaly Detection.\n\n- **Training**: Use Train Model API to create and train a model, then use Get Model Status API to get the status and model metadata.\n- **Inference**:\n - Use Async Inference API to trigger an asynchronous inference process and use Get Inference results API to get detection results on a batch of data.\n - You could also use Sync Inference API to trigger a detection on one timestamp every time.\n- **Other operations**: List Model API and Delete Model API are supported in Multivariate Anomaly Detection model for model management.\n\n### Thread safety\n\nWe guarantee that all client instance methods are thread-safe and independent of each other ([guideline](https://azure.github.io/azure-sdk/dotnet_introduction.html#dotnet-service-methods-thread-safety)). This ensures that the recommendation of reusing client instances is always safe, even across threads.\n\n## Examples\n\nThe following section provides several code snippets covering some of the most common Anomaly Detector service tasks, including:\n\n- [Univariate Anomaly Detection - Batch detection](#batch-detection)\n- [Univariate Anomaly Detection - Streaming detection](#streaming-detection)\n- [Univariate Anomaly Detection - Detect change points](#detect-change-points)\n- [Multivariate Anomaly Detection](#multivariate-anomaly-detection-sample)\n\n### Batch detection\n\n```typescript\nconst apiKey = process.env[\"ANOMALY_DETECTOR_API_KEY\"] || \"\";\nconst endpoint = process.env[\"ANOMALY_DETECTOR_ENDPOINT\"] || \"\";\nconst timeSeriesDataPath = \"./samples-dev/example-data/request-data.csv\";\n\nfunction read_series_from_file(path: string): Array {\n let result = Array();\n let input = fs.readFileSync(path).toString();\n let parsed = parse(input, { skip_empty_lines: true });\n parsed.forEach(function (e: Array) {\n result.push({ timestamp: new Date(e[0]), value: Number(e[1]) });\n });\n return result;\n}\n\nexport async function main() {\n // create client\n const credential = new AzureKeyCredential(apiKey);\n const client = AnomalyDetector(endpoint, credential);\n\n // construct request\n const options: DetectUnivariateEntireSeriesParameters = {\n body: {\n granularity: \"daily\",\n imputeMode: \"auto\",\n maxAnomalyRatio: 0.25,\n sensitivity: 95,\n series: read_series_from_file(timeSeriesDataPath),\n },\n headers: { \"Content-Type\": \"application/json\" },\n };\n\n // get last detect result\n const result = await client.path(\"/timeseries/entire/detect\").post(options);\n if (isUnexpected(result)) {\n throw result;\n }\n\n if (result.body.isAnomaly) {\n result.body.isAnomaly.forEach(function (anomaly, index) {\n if (anomaly === true) {\n console.log(index);\n }\n });\n } else {\n console.log(\"There is no anomaly detected from the series.\");\n }\n```\n\n### Streaming Detection\n\n```typescript\nconst apiKey = process.env[\"ANOMALY_DETECTOR_API_KEY\"] || \"\";\nconst endpoint = process.env[\"ANOMALY_DETECTOR_ENDPOINT\"] || \"\";\nconst timeSeriesDataPath = \"./samples-dev/example-data/request-data.csv\";\n\nfunction read_series_from_file(path: string): Array {\n let result = Array();\n let input = fs.readFileSync(path).toString();\n let parsed = parse(input, { skip_empty_lines: true });\n parsed.forEach(function (e: Array) {\n result.push({ timestamp: new Date(e[0]), value: Number(e[1]) });\n });\n return result;\n}\n\nexport async function main() {\n // create client\n const credential = new AzureKeyCredential(apiKey);\n const client = AnomalyDetector(endpoint, credential);\n\n // construct request\n const options: DetectUnivariateLastPointParameters = {\n body: {\n granularity: \"daily\",\n imputeFixedValue: 800,\n imputeMode: \"fixed\",\n maxAnomalyRatio: 0.25,\n sensitivity: 95,\n series: read_series_from_file(timeSeriesDataPath),\n },\n headers: { \"Content-Type\": \"application/json\" },\n };\n\n // get last detect result\n const result = await client.path(\"/timeseries/last/detect\").post(options);\n if (isUnexpected(result)) {\n throw result;\n }\n\n if (result.body.isAnomaly) {\n console.log(\"The latest point is detected as anomaly.\");\n } else {\n console.log(\"The latest point is not detected as anomaly.\");\n }\n```\n\n### Detect change points\n\n```typescript\nconst apiKey = process.env[\"ANOMALY_DETECTOR_API_KEY\"] || \"\";\nconst endpoint = process.env[\"ANOMALY_DETECTOR_ENDPOINT\"] || \"\";\nconst timeSeriesDataPath = \"./samples-dev/example-data/request-data.csv\";\n\nfunction read_series_from_file(path: string): Array {\n let result = Array();\n let input = fs.readFileSync(path).toString();\n let parsed = parse(input, { skip_empty_lines: true });\n parsed.forEach(function (e: Array) {\n result.push({ timestamp: new Date(e[0]), value: Number(e[1]) });\n });\n return result;\n}\n\nexport async function main() {\n const credential = new AzureKeyCredential(apiKey);\n const client = AnomalyDetector(endpoint, credential);\n const options: DetectUnivariateChangePointParameters = {\n body: {\n granularity: \"daily\",\n series: read_series_from_file(timeSeriesDataPath),\n },\n headers: { \"Content-Type\": \"application/json\" },\n };\n const result = await client.path(\"/timeseries/changepoint/detect\").post(options);\n if (isUnexpected(result)) {\n throw result;\n }\n\n if (result.body.isChangePoint === undefined) throw new Error(\"Empty isChangePoint\");\n if (\n result.body.isChangePoint.some(function (changePoint) {\n return changePoint === true;\n })\n ) {\n console.log(\"Change points were detected from the series at index:\");\n result.body.isChangePoint.forEach(function (changePoint, index) {\n if (changePoint === true) console.log(index);\n });\n } else {\n console.log(\"There is no change point detected from the series.\");\n }\n```\n\n### Multivariate Anomaly Detection Sample\n\nTo see how to use Anomaly Detector library to conduct Multivariate Anomaly Detection, see this [sample](https://github.com/Azure/azure-sdk-for-js/blob/main/sdk/anomalydetector/ai-anomaly-detector-rest/samples/v1-beta/typescript/src/sample_multivariate_detection.ts).\n\n## Troubleshooting\n\n### General\n\n### Logging\n\nEnabling logging may help uncover useful information about failures. In order to see a log of HTTP requests and responses, set the `AZURE_LOG_LEVEL` environment variable to `info`. Alternatively, logging can be enabled at runtime by calling `setLogLevel` in the `@azure/logger`:\n\n```javascript\nconst { setLogLevel } = require(\"@azure/logger\");\n\nsetLogLevel(\"info\");\n```\n\nFor more detailed instructions on how to enable logs, you can look at the [@azure/logger package docs](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/core/logger).\n\n## Next steps\n\nThese code samples show common scenario operations with the Azure Anomaly Detector library. More samples can be found under the [samples](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/anomalydetector/Azure.AI.AnomalyDetector/tests/samples/) directory.\n\n- Univariate Anomaly Detection - Batch Detection: [sample_detect_entire_series_anomaly.ts](https://github.com/Azure/azure-sdk-for-js/blob/main/sdk/anomalydetector/ai-anomaly-detector-rest/samples/v1-beta/typescript/src/sample_detect_entire_series_anomaly.ts)\n\n- Univariate Anomaly Detection - Streaming Detection: [ample_detect_last_point_anomaly.ts](https://github.com/Azure/azure-sdk-for-js/blob/main/sdk/anomalydetector/ai-anomaly-detector-rest/samples/v1-beta/typescript/src/sample_detect_last_point_anomaly.ts)\n\n- Univariate Anomaly Detection - Change Point Detection: [sample_detect_change_point.ts](https://github.com/Azure/azure-sdk-for-js/blob/main/sdk/anomalydetector/ai-anomaly-detector-rest/samples/v1-beta/typescript/src/sample_detect_change_point.ts)\n\n- Multivariate Anomaly Detection: [sample_multivariate_detection.ts](https://github.com/Azure/azure-sdk-for-js/blob/main/sdk/anomalydetector/ai-anomaly-detector-rest/samples/v1-beta/typescript/src/sample_multivariate_detection.ts)\n\n### Additional documentation\n\nFor more extensive documentation on Azure Anomaly Detector, see the [Anomaly Detector documentation](https://learn.microsoft.com/azure/cognitive-services/anomaly-detector/overview) on docs.microsoft.com.\n\n## Contributing\n\nThis project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit [cla.microsoft.com][cla].\n\nWhen you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.\n\nThis project has adopted the [Microsoft Open Source Code of Conduct][code_of_conduct]. For more information see the [Code of Conduct FAQ][coc_faq] or contact [opencode@microsoft.com][coc_contact] with any additional questions or comments.\n\n\n[cla]: https://cla.microsoft.com\n[code_of_conduct]: https://opensource.microsoft.com/codeofconduct/\n[coc_faq]: https://opensource.microsoft.com/codeofconduct/faq/\n[coc_contact]: mailto:opencode@microsoft.com\n- [Source code](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector-rest)\n- [Package (NPM)](https://www.npmjs.com/package/@azure-rest/ai-anomaly-detector)\n- [API reference documentation](https://docs.microsoft.com/javascript/api/@azure-rest/ai-anomaly-detector?view=azure-node-preview)\n- [Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/anomalydetector/ai-anomaly-detector-rest/samples)\n","browser":{"./dist-esm/test/utils/environment.ts":"./dist-esm/test/utils/environment.browser.ts"},"engines":{"node":">=14.0.0"},"scripts":{"lint":"eslint package.json api-extractor.json README.md src test --ext .ts,.javascript,.js","pack":"npm pack 2>&1","test":"npm run build:test && npm run unit-test && npm run integration-test","audit":"node ../../../common/scripts/rush-audit.js && rimraf node_modules package-lock.json && npm i --package-lock-only 2>&1 && npm audit","build":"npm run clean && tsc -p . && dev-tool run bundle && api-extractor run --local","clean":"rimraf dist dist-* temp types *.tgz *.log","format":"prettier --write --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","lint:fix":"eslint package.json api-extractor.json README.md src test --ext .ts,.javascript,.js --fix --fix-type [problem,suggestion]","test:node":"npm run build:test && npm run unit-test:node && npm run integration-test:node","unit-test":"npm run unit-test:node && npm run unit-test:browser","build:node":"tsc -p . && dev-tool run bundle","build:test":"tsc -p . && dev-tool run bundle","extract-api":"tsc -p . && api-extractor run --local","check-format":"prettier --list-different --config ../../../.prettierrc.json --ignore-path ../../../.prettierignore \"src/**/*.ts\" \"test/**/*.ts\" \"*.{js,json}\"","test:browser":"npm run build:test && npm run unit-test:browser && npm run integration-test:browser","build:browser":"tsc -p . && dev-tool run bundle","build:samples":"echo Obsolete.","unit-test:node":"mocha -r esm --require ts-node/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 1200000 --full-trace \"test/{,!(browser)/**/}*.spec.ts\"","execute:samples":"npm run build:samples && dev-tool samples run dist-samples/javascript dist-samples/typescript/dist/dist-samples/typescript/src/","integration-test":"npm run integration-test:node && npm run integration-test:browser","unit-test:browser":"karma start --single-run","integration-test:node":"nyc mocha -r esm --require source-map-support/register --reporter ../../../common/tools/mocha-multi-reporter.js --timeout 5000000 --full-trace \"dist-esm/test/{,!(browser)/**/}*.spec.js\"","integration-test:browser":"karma start --single-run"},"_npmUser":{"name":"azure-sdk","email":"azure-sdk-npmjs@microsoft.com"},"prettier":"@azure/eslint-plugin-azure-sdk/prettier.json","sdk-type":"client","_resolved":"/mnt/vss/_work/1/packages/azure-ai-anomaly-detector/azure-ai-anomaly-detector-3.0.0-alpha.20221207.2.tgz","//metadata":{"constantPaths":[{"path":"src/generated/anomalyDetectorContext.ts","prefix":"packageVersion"},{"path":"src/constants.ts","prefix":"SDK_VERSION"}]},"_integrity":"sha512-PcVBHug/P17Obc7l6S5kovJDE6ReuMfb3rLdqxfUMMFGvDcN42tZH7cifUTFz/d2IfO9SDkGj/rMjz7y9pTH9Q==","deprecated":"This library is no longer maintained. 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