Anomaly Detector v1.1-preview
The Anomaly Detection service detects anomalies automatically in time series data. It supports several functionalities, one is for detecting anomalies in single time-series, including entire, last and change point detection. The other is detecting anomalies in multiple time-series. With univariate anomaly detection ability, business customers can discover incidents and establish a logic flow for root cause analysis. The multivariate anomaly detection APIs in Anomaly Detector analyze dependencies and inter-correlations between different signals. It enables customers to gather a group of related time-series and detect failures with a wholistic view. To ensure online service quality is one of the main reasons we developed this service. Our team is dedicated to continuing to improve the anomaly detection service to provide precise results.
This Multivariate Anomaly Detection is currently available in:
- East US - eastus.api.cognitive.microsoft.com
- East US 2 - eastus2.api.cognitive.microsoft.com
- South Central US - southcentralus.api.cognitive.microsoft.com
- UK South - uksouth.api.cognitive.microsoft.com
- West Europe - westeurope.api.cognitive.microsoft.com
- West US 2 - westus2.api.cognitive.microsoft.com
Multivariate Anomaly Detection - Get Multivariate Anomaly Detection Result
Get multivariate anomaly detection result based on resultId returned by the DetectAnomalyAsync api
Select the testing console in the region where you created your resource:
Open API testing consoleRequest URL
Request parameters
string
Format - uuid. Result identifier.
Request headers
string
Subscription key which provides access to this API. Found in your Cognitive Services accounts.
Request body
Response 200
Get Multivariate Anomaly Detection Result by Result Id.
{
"resultId": "ecc7301a-f82a-11eb-85be-9a8be3529ef3",
"summary": {
"status": "READY",
"errors": [],
"variableStates": [{
"variable": "pumpPressureB",
"filledNARatio": 0.0,
"effectiveCount": 800,
"startTime": "2020-10-01T13:30:00Z",
"endTime": "2020-10-07T02:40:00Z",
"errors": []
}, {
"variable": "opticalLFiltered",
"filledNARatio": 0.0,
"effectiveCount": 800,
"startTime": "2020-10-01T13:30:00Z",
"endTime": "2020-10-07T02:40:00Z",
"errors": []
}, {
"variable": "rotationalB",
"filledNARatio": 0.0,
"effectiveCount": 800,
"startTime": "2020-10-01T13:30:00Z",
"endTime": "2020-10-07T02:40:00Z",
"errors": []
}, {
"variable": "pumpPressureA",
"filledNARatio": 0.0,
"effectiveCount": 800,
"startTime": "2020-10-01T13:30:00Z",
"endTime": "2020-10-07T02:40:00Z",
"errors": []
}, {
"variable": "rotationalA",
"filledNARatio": 0.0,
"effectiveCount": 800,
"startTime": "2020-10-01T13:30:00Z",
"endTime": "2020-10-07T02:40:00Z",
"errors": []
}, {
"variable": "rotationalC",
"filledNARatio": 0.0,
"effectiveCount": 800,
"startTime": "2020-10-01T13:30:00Z",
"endTime": "2020-10-07T02:40:00Z",
"errors": []
}, {
"variable": "pumpPressureTarget",
"filledNARatio": 0.0,
"effectiveCount": 800,
"startTime": "2020-10-01T13:30:00Z",
"endTime": "2020-10-07T02:40:00Z",
"errors": []
}, {
"variable": "opticalRFiltered",
"filledNARatio": 0.0,
"effectiveCount": 800,
"startTime": "2020-10-01T13:30:00Z",
"endTime": "2020-10-07T02:40:00Z",
"errors": []
}],
"setupInfo": {
"source": "{your_sas_url}",
"startTime": "2020-10-01T13:30:00Z",
"endTime": "2020-10-07T03:00:00Z"
}
},
"results": [{
"timestamp": "2020-10-01T13:30:00Z",
"value": {
"contributors": [{
"contributionScore": 1.6104390621185303,
"variable": "pumpPressureB"
}, {
"contributionScore": 1.5020194053649902,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 1.4727952480316162,
"variable": "pumpPressureA"
}, {
"contributionScore": 1.2808641195297241,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.2620043754577637,
"variable": "opticalRFiltered"
}, {
"contributionScore": 0.14519721269607544,
"variable": "rotationalB"
}, {
"contributionScore": 0.036691248416900635,
"variable": "rotationalC"
}, {
"contributionScore": 0.02692180871963501,
"variable": "rotationalA"
}],
"isAnomaly": true,
"severity": 0.5337404608726501,
"score": 0.9171165823936462
},
"errors": []
}, {
"timestamp": "2020-10-01T13:40:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.6928471326828003
},
"errors": []
}, {
"timestamp": "2020-10-01T13:50:00Z",
"value": {
"contributors": [{
"contributionScore": 1.7182817459106445,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.7182817459106445,
"variable": "opticalLFiltered"
}, {
"contributionScore": 0.9544153809547424,
"variable": "rotationalC"
}, {
"contributionScore": 0.9541400074958801,
"variable": "rotationalA"
}, {
"contributionScore": 0.9222342371940613,
"variable": "rotationalB"
}, {
"contributionScore": 0.8359994888305664,
"variable": "pumpPressureB"
}, {
"contributionScore": 0.8037763833999634,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 0.7538774013519287,
"variable": "pumpPressureA"
}],
"isAnomaly": true,
"severity": 0.630062997341156,
"score": 1.0826258659362793
},
"errors": []
}, {
"timestamp": "2020-10-01T14:00:00Z",
"value": {
"contributors": [{
"contributionScore": 1.7182817459106445,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.7182817459106445,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.4336364269256592,
"variable": "pumpPressureA"
}, {
"contributionScore": 1.376896858215332,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 1.3088722229003906,
"variable": "pumpPressureB"
}, {
"contributionScore": 0.9250281453132629,
"variable": "rotationalA"
}, {
"contributionScore": 0.8944095969200134,
"variable": "rotationalC"
}, {
"contributionScore": 0.882785975933075,
"variable": "rotationalB"
}],
"isAnomaly": true,
"severity": 0.7462536692619324,
"score": 1.2822741270065308
},
"errors": []
}, {
"timestamp": "2020-10-01T14:10:00Z",
"value": {
"contributors": [{
"contributionScore": 1.6991353034973145,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.694100022315979,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.4585132598876953,
"variable": "pumpPressureA"
}, {
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"variable": "pumpPressureTarget"
}, {
"contributionScore": 1.3274012804031372,
"variable": "pumpPressureB"
}, {
"contributionScore": 0.9164133071899414,
"variable": "rotationalB"
}, {
"contributionScore": 0.866317093372345,
"variable": "rotationalC"
}, {
"contributionScore": 0.8660727143287659,
"variable": "rotationalA"
}],
"isAnomaly": true,
"severity": 0.7439216375350952,
"score": 1.2782670259475708
},
"errors": []
}, {
"timestamp": "2020-10-01T14:20:00Z",
"value": {
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"contributionScore": 1.6245548725128174,
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"contributionScore": 0.9680769443511963,
"variable": "rotationalA"
}, {
"contributionScore": 0.9265761375427246,
"variable": "rotationalB"
}, {
"contributionScore": 0.9060559272766113,
"variable": "rotationalC"
}],
"isAnomaly": true,
"severity": 0.8161752223968506,
"score": 1.402419090270996
},
"errors": []
}, {
"timestamp": "2020-10-01T14:30:00Z",
"value": {
"contributors": [{
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}, {
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"variable": "pumpPressureTarget"
}, {
"contributionScore": 1.7182817459106445,
"variable": "pumpPressureA"
}, {
"contributionScore": 1.5525915622711182,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.5448042154312134,
"variable": "opticalRFiltered"
}, {
"contributionScore": 0.8039817214012146,
"variable": "rotationalB"
}, {
"contributionScore": 0.7015066742897034,
"variable": "rotationalA"
}, {
"contributionScore": 0.6109602451324463,
"variable": "rotationalC"
}],
"isAnomaly": true,
"severity": 0.7542918920516968,
"score": 1.296086072921753
},
"errors": []
}, {
"timestamp": "2020-10-01T14:40:00Z",
"value": {
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}],
"isAnomaly": true,
"severity": 0.6902437210083008,
"score": 1.1860332489013672
},
"errors": []
}, {
"timestamp": "2020-10-01T14:50:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.7803113460540771
},
"errors": []
}, {
"timestamp": "2020-10-01T15:00:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.7682037949562073
},
"errors": []
}, {
"timestamp": "2020-10-01T15:10:00Z",
"value": {
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"timestamp": "2020-10-01T15:20:00Z",
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"contributionScore": 1.4592379331588745,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.4505878686904907,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.2094842195510864,
"variable": "pumpPressureA"
}, {
"contributionScore": 1.1603872776031494,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 1.1160619258880615,
"variable": "pumpPressureB"
}, {
"contributionScore": 0.6183352470397949,
"variable": "rotationalA"
}, {
"contributionScore": 0.5217719674110413,
"variable": "rotationalC"
}, {
"contributionScore": 0.4763341546058655,
"variable": "rotationalB"
}],
"isAnomaly": true,
"severity": 0.5828642845153809,
"score": 1.0015251636505127
},
"errors": []
}, {
"timestamp": "2020-10-06T23:00:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.6047506928443909
},
"errors": []
}, {
"timestamp": "2020-10-06T23:10:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.618984043598175
},
"errors": []
}, {
"timestamp": "2020-10-06T23:20:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.7891684770584106
},
"errors": []
}, {
"timestamp": "2020-10-06T23:30:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.7626413106918335
},
"errors": []
}, {
"timestamp": "2020-10-06T23:40:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.6756367087364197
},
"errors": []
}, {
"timestamp": "2020-10-06T23:50:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.739004909992218
},
"errors": []
}, {
"timestamp": "2020-10-07T00:00:00Z",
"value": {
"contributors": [{
"contributionScore": 1.5414330959320068,
"variable": "pumpPressureB"
}, {
"contributionScore": 1.442026972770691,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 1.4114974737167358,
"variable": "pumpPressureA"
}, {
"contributionScore": 1.1544840335845947,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.1453908681869507,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.067752480506897,
"variable": "rotationalB"
}, {
"contributionScore": 0.8641642332077026,
"variable": "rotationalA"
}, {
"contributionScore": 0.18897020816802979,
"variable": "rotationalC"
}],
"isAnomaly": true,
"severity": 0.6413179039955139,
"score": 1.1019649505615234
},
"errors": []
}, {
"timestamp": "2020-10-07T00:10:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.6551157236099243
},
"errors": []
}, {
"timestamp": "2020-10-07T00:20:00Z",
"value": {
"contributors": [{
"contributionScore": 1.5387310981750488,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.5308823585510254,
"variable": "opticalLFiltered"
}, {
"contributionScore": 0.963092565536499,
"variable": "rotationalA"
}, {
"contributionScore": 0.9484185576438904,
"variable": "rotationalB"
}, {
"contributionScore": 0.9298431873321533,
"variable": "rotationalC"
}, {
"contributionScore": 0.8505274653434753,
"variable": "pumpPressureB"
}, {
"contributionScore": 0.82359778881073,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 0.7558652758598328,
"variable": "pumpPressureA"
}],
"isAnomaly": true,
"severity": 0.6067804098129272,
"score": 1.0426198244094849
},
"errors": []
}, {
"timestamp": "2020-10-07T00:30:00Z",
"value": {
"contributors": [{
"contributionScore": 1.4388535022735596,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.413731336593628,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.3498133420944214,
"variable": "rotationalB"
}, {
"contributionScore": 1.1354453563690186,
"variable": "rotationalA"
}, {
"contributionScore": 1.1079165935516357,
"variable": "rotationalC"
}, {
"contributionScore": 0.9180120825767517,
"variable": "pumpPressureB"
}, {
"contributionScore": 0.8829984068870544,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 0.8183854818344116,
"variable": "pumpPressureA"
}],
"isAnomaly": true,
"severity": 0.65946364402771,
"score": 1.1331443786621094
},
"errors": []
}, {
"timestamp": "2020-10-07T00:40:00Z",
"value": {
"contributors": [{
"contributionScore": 1.4322271347045898,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.406791090965271,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.0877306461334229,
"variable": "rotationalA"
}, {
"contributionScore": 1.000722050666809,
"variable": "rotationalB"
}, {
"contributionScore": 0.9907549619674683,
"variable": "rotationalC"
}, {
"contributionScore": 0.8871068358421326,
"variable": "pumpPressureB"
}, {
"contributionScore": 0.82485431432724,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 0.7302252650260925,
"variable": "pumpPressureA"
}],
"isAnomaly": true,
"severity": 0.6081956624984741,
"score": 1.0450515747070312
},
"errors": []
}, {
"timestamp": "2020-10-07T00:50:00Z",
"value": {
"contributors": [{
"contributionScore": 1.6697537899017334,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.65485417842865,
"variable": "opticalLFiltered"
}, {
"contributionScore": 0.9734489321708679,
"variable": "rotationalA"
}, {
"contributionScore": 0.9447827339172363,
"variable": "rotationalC"
}, {
"contributionScore": 0.9301097393035889,
"variable": "pumpPressureA"
}, {
"contributionScore": 0.9178533554077148,
"variable": "rotationalB"
}, {
"contributionScore": 0.8823643326759338,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 0.8651296496391296,
"variable": "pumpPressureB"
}],
"isAnomaly": true,
"severity": 0.6429603695869446,
"score": 1.1047871112823486
},
"errors": []
}, {
"timestamp": "2020-10-07T01:00:00Z",
"value": {
"contributors": [{
"contributionScore": 1.5553147792816162,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.5544214248657227,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.0358619689941406,
"variable": "pumpPressureA"
}, {
"contributionScore": 1.003510594367981,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 0.9562128186225891,
"variable": "pumpPressureB"
}, {
"contributionScore": 0.5543459057807922,
"variable": "rotationalB"
}, {
"contributionScore": 0.4442446231842041,
"variable": "rotationalA"
}, {
"contributionScore": 0.3606458306312561,
"variable": "rotationalC"
}],
"isAnomaly": true,
"severity": 0.5430248379707336,
"score": 0.9330697655677795
},
"errors": []
}, {
"timestamp": "2020-10-07T01:10:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.6658228635787964
},
"errors": []
}, {
"timestamp": "2020-10-07T01:20:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.8076028227806091
},
"errors": []
}, {
"timestamp": "2020-10-07T01:30:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.6779837608337402
},
"errors": []
}, {
"timestamp": "2020-10-07T01:40:00Z",
"value": {
"contributors": [{
"contributionScore": 1.2836734056472778,
"variable": "pumpPressureA"
}, {
"contributionScore": 1.270790696144104,
"variable": "opticalRFiltered"
}, {
"contributionScore": 1.2506517171859741,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.2237169742584229,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 1.1823384761810303,
"variable": "pumpPressureB"
}, {
"contributionScore": 0.35488617420196533,
"variable": "rotationalA"
}, {
"contributionScore": 0.31017839908599854,
"variable": "rotationalB"
}, {
"contributionScore": 0.25516462326049805,
"variable": "rotationalC"
}],
"isAnomaly": true,
"severity": 0.5187886357307434,
"score": 0.8914250731468201
},
"errors": []
}, {
"timestamp": "2020-10-07T01:50:00Z",
"value": {
"contributors": [{
"contributionScore": 1.6669286489486694,
"variable": "pumpPressureA"
}, {
"contributionScore": 1.56824791431427,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 1.5283300876617432,
"variable": "pumpPressureB"
}, {
"contributionScore": 1.1303236484527588,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.1150496006011963,
"variable": "opticalRFiltered"
}, {
"contributionScore": 0.30496424436569214,
"variable": "rotationalA"
}, {
"contributionScore": 0.2483479380607605,
"variable": "rotationalC"
}, {
"contributionScore": 0.23704832792282104,
"variable": "rotationalB"
}],
"isAnomaly": true,
"severity": 0.5673720240592957,
"score": 0.9749050736427307
},
"errors": []
}, {
"timestamp": "2020-10-07T02:00:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.7609139680862427
},
"errors": []
}, {
"timestamp": "2020-10-07T02:10:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.7707102298736572
},
"errors": []
}, {
"timestamp": "2020-10-07T02:20:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.7775367498397827
},
"errors": []
}, {
"timestamp": "2020-10-07T02:30:00Z",
"value": {
"isAnomaly": false,
"severity": 0.0,
"score": 0.5664929747581482
},
"errors": []
}, {
"timestamp": "2020-10-07T02:40:00Z",
"value": {
"contributors": [{
"contributionScore": 1.3469595909118652,
"variable": "pumpPressureB"
}, {
"contributionScore": 1.262937068939209,
"variable": "pumpPressureTarget"
}, {
"contributionScore": 1.248587727546692,
"variable": "pumpPressureA"
}, {
"contributionScore": 1.055064082145691,
"variable": "opticalLFiltered"
}, {
"contributionScore": 1.0251697301864624,
"variable": "opticalRFiltered"
}, {
"contributionScore": 0.908318281173706,
"variable": "rotationalC"
}, {
"contributionScore": 0.19656026363372803,
"variable": "rotationalA"
}, {
"contributionScore": 0.14594846963882446,
"variable": "rotationalB"
}],
"isAnomaly": true,
"severity": 0.523018479347229,
"score": 0.8986931443214417
},
"errors": []
}]
}{
"required": [
"resultId",
"results",
"summary"
],
"properties": {
"resultId": {
"type": "string",
"format": "uuid",
"example": "45aad126-aafd-11ea-b8fb-d89ef3400c5f"
},
"summary": {
"description": "Multivariate anomaly detection status",
"required": [
"setupInfo",
"status"
],
"properties": {
"status": {
"type": "string",
"description": "Multivariate anomaly detection status",
"example": "READY",
"enum": [
"CREATED",
"RUNNING",
"READY",
"FAILED"
],
"x-ms-enum": {
"name": "DetectionStatus",
"modelAsString": false
}
},
"errors": {
"type": "array",
"description": "Error message when creating or training model fails.",
"items": {
"required": [
"code",
"message"
],
"properties": {
"code": {
"type": "string",
"x-nullable": false,
"description": "The error Code"
},
"message": {
"type": "string",
"x-nullable": false,
"description": "A message explaining the error reported by the service."
}
},
"type": "object"
}
},
"variableStates": {
"type": "array",
"example": [
{
"variable": "ad_input",
"filledNARatio": 0.0,
"effectiveCount": 26,
"startTime": "2019-04-01T00:00:00Z",
"endTime": "2019-04-01T00:25:00Z",
"errors": []
},
{
"variable": "ad_on_timer_output",
"filledNARatio": 0.0,
"effectiveCount": 26,
"startTime": "2019-04-01T00:00:00Z",
"endTime": "2019-04-01T00:25:00Z",
"errors": []
},
{
"variable": "ad_output",
"filledNARatio": 0.0,
"effectiveCount": 26,
"startTime": "2019-04-01T00:00:00Z",
"endTime": "2019-04-01T00:25:00Z",
"errors": []
},
{
"variable": "ad_series_init",
"filledNARatio": 0.0,
"effectiveCount": 26,
"startTime": "2019-04-01T00:00:00Z",
"endTime": "2019-04-01T00:25:00Z",
"errors": []
},
{
"variable": "cpu",
"filledNARatio": 0.0,
"effectiveCount": 26,
"startTime": "2019-04-01T00:00:00Z",
"endTime": "2019-04-01T00:25:00Z",
"errors": []
},
{
"variable": "data_in_speed",
"filledNARatio": 0.0,
"effectiveCount": 26,
"startTime": "2019-04-01T00:00:00Z",
"endTime": "2019-04-01T00:25:00Z",
"errors": []
},
{
"variable": "data_out_speed",
"filledNARatio": 0.0,
"effectiveCount": 26,
"startTime": "2019-04-01T00:00:00Z",
"endTime": "2019-04-01T00:25:00Z",
"errors": []
},
{
"variable": "F-Link_last_check_point_duration",
"filledNARatio": 0.0,
"effectiveCount": 26,
"startTime": "2019-04-01T00:00:00Z",
"endTime": "2019-04-01T00:25:00Z",
"errors": []
},
{
"variable": "ingestion",
"filledNARatio": 0.0,
"effectiveCount": 26,
"startTime": "2019-04-01T00:00:00Z",
"endTime": "2019-04-01T00:25:00Z",
"errors": []
}
],
"items": {
"properties": {
"variable": {
"type": "string",
"description": "Variable name."
},
"filledNARatio": {
"type": "number",
"description": "Merged NA ratio of a variable.",
"minimum": 0,
"maximum": 1
},
"effectiveCount": {
"type": "integer",
"description": "Effective time-series points count."
},
"startTime": {
"type": "string",
"format": "date-time",
"description": "Start time of a variable"
},
"endTime": {
"type": "string",
"format": "date-time",
"description": "End time of a variable"
},
"errors": {
"type": "array",
"description": "Error message when parse variable",
"items": {
"required": [
"code",
"message"
],
"properties": {
"code": {
"type": "string",
"x-nullable": false,
"description": "The error Code"
},
"message": {
"type": "string",
"x-nullable": false,
"description": "A message explaining the error reported by the service."
}
},
"type": "object"
}
}
},
"type": "object"
}
},
"setupInfo": {
"description": "Request to submit a detection.",
"required": [
"source",
"endTime",
"startTime"
],
"properties": {
"source": {
"type": "string",
"description": "The blob link to the input data. It should be a zipped folder containing csv files. Each csv file should has two columns with header 'timestamp' and 'value' (case sensitive). The file name will be used as the variable name. The variables used for detection should be exactly the same as for training. Please refer to the sample data to prepare your own data accordingly.",
"example": "{your_sas_url}"
},
"startTime": {
"type": "string",
"format": "date-time",
"description": "A required field, start time of data to be used for detection, should be date-time.",
"example": "2019-04-01T00:15:00Z"
},
"endTime": {
"type": "string",
"format": "date-time",
"description": "A required field, end time of data to be used for detection, should be date-time.",
"example": "2019-04-01T00:40:00Z"
}
},
"type": "object",
"example": {
"source": "{your_sas_url}",
"startTime": "2019-04-01T00:15:00Z",
"endTime": "2019-04-01T00:40:00Z"
}
}
},
"type": "object"
},
"results": {
"type": "array",
"description": "anomaly status of each timestamp",
"items": {
"required": [
"timestamp"
],
"properties": {
"timestamp": {
"type": "string",
"format": "date-time",
"description": "timestamp",
"example": "2020-01-01T00:00:00Z"
},
"value": {
"required": [
"isAnomaly",
"severity"
],
"properties": {
"contributors": {
"type": "array",
"description": "If current timestamp is an anomaly, contributors will show potential root cause for thus anomaly. Contributors can help us understand why current timestamp has been detected as an anomaly.",
"items": {
"properties": {
"contributionScore": {
"type": "number",
"description": "The higher the contribution score is, the more likely the variable to be the root cause of a anomaly.",
"example": 0.6,
"minimum": 0,
"maximum": 2
},
"variable": {
"type": "string",
"description": "Variable name of a contributor",
"example": "ingestion"
}
},
"type": "object"
}
},
"isAnomaly": {
"type": "boolean",
"description": "To indicate whether current timestamp is anomaly or not",
"example": true
},
"severity": {
"type": "number",
"description": "anomaly score of the current timestamp, the more significant an anomaly is, the higher the score will be",
"example": 0.8,
"minimum": 0,
"maximum": 1
},
"score": {
"type": "number",
"description": "anomaly score of the current timestamp, the more significant an anomaly is, the higher the score will be, score measures global significance",
"example": 0.1,
"minimum": 0,
"maximum": 2
}
},
"type": "object"
},
"errors": {
"type": "array",
"description": "Error message when inference this timestamp",
"items": {
"required": [
"code",
"message"
],
"properties": {
"code": {
"type": "string",
"x-nullable": false,
"description": "The error Code"
},
"message": {
"type": "string",
"x-nullable": false,
"description": "A message explaining the error reported by the service."
}
},
"type": "object"
}
}
},
"type": "object"
}
}
},
"type": "object",
"description": "Anomaly Response of one detection corresponds to a resultId."
}Response 500
Internal Server Error.
Response 403
The certificate you provided is not accepted by server.
Response 400
Possible Errors:
- ResultNotExist
The result does not exist.
{
"code" : "ResultNotExist",
"message" : "The result does not exist."
}{
"required": [
"code",
"message"
],
"properties": {
"code": {
"type": "string",
"x-nullable": false,
"description": "The error Code"
},
"message": {
"type": "string",
"x-nullable": false,
"description": "A message explaining the error reported by the service."
}
},
"type": "object"
}Response 405
Method Not Allowed.
Code samples
@ECHO OFF
curl -v -X GET "https://virginia.api.cognitive.microsoft.us/anomalydetector/v1.1-preview/multivariate/results/{resultId}"
-H "Ocp-Apim-Subscription-Key: {subscription key}"
--data-ascii "{body}"
using System;
using System.Net.Http.Headers;
using System.Text;
using System.Net.Http;
using System.Web;
namespace CSHttpClientSample
{
static class Program
{
static void Main()
{
MakeRequest();
Console.WriteLine("Hit ENTER to exit...");
Console.ReadLine();
}
static async void MakeRequest()
{
var client = new HttpClient();
var queryString = HttpUtility.ParseQueryString(string.Empty);
// Request headers
client.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", "{subscription key}");
var uri = "https://virginia.api.cognitive.microsoft.us/anomalydetector/v1.1-preview/multivariate/results/{resultId}?" + queryString;
var response = await client.GetAsync(uri);
}
}
} // // This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
import java.net.URI;
import org.apache.http.HttpEntity;
import org.apache.http.HttpResponse;
import org.apache.http.client.HttpClient;
import org.apache.http.client.methods.HttpGet;
import org.apache.http.client.utils.URIBuilder;
import org.apache.http.impl.client.HttpClients;
import org.apache.http.util.EntityUtils;
public class JavaSample
{
public static void main(String[] args)
{
HttpClient httpclient = HttpClients.createDefault();
try
{
URIBuilder builder = new URIBuilder("https://virginia.api.cognitive.microsoft.us/anomalydetector/v1.1-preview/multivariate/results/{resultId}");
URI uri = builder.build();
HttpGet request = new HttpGet(uri);
request.setHeader("Ocp-Apim-Subscription-Key", "{subscription key}");
// Request body
StringEntity reqEntity = new StringEntity("{body}");
request.setEntity(reqEntity);
HttpResponse response = httpclient.execute(request);
HttpEntity entity = response.getEntity();
if (entity != null)
{
System.out.println(EntityUtils.toString(entity));
}
}
catch (Exception e)
{
System.out.println(e.getMessage());
}
}
}
<!DOCTYPE html>
<html>
<head>
<title>JSSample</title>
<script src="http://ajax.googleapis.com/ajax/libs/jquery/1.9.0/jquery.min.js"></script>
</head>
<body>
<script type="text/javascript">
$(function() {
var params = {
// Request parameters
};
$.ajax({
url: "https://virginia.api.cognitive.microsoft.us/anomalydetector/v1.1-preview/multivariate/results/{resultId}?" + $.param(params),
beforeSend: function(xhrObj){
// Request headers
xhrObj.setRequestHeader("Ocp-Apim-Subscription-Key","{subscription key}");
},
type: "GET",
// Request body
data: "{body}",
})
.done(function(data) {
alert("success");
})
.fail(function() {
alert("error");
});
});
</script>
</body>
</html>
#import <Foundation/Foundation.h>
int main(int argc, const char * argv[])
{
NSAutoreleasePool * pool = [[NSAutoreleasePool alloc] init];
NSString* path = @"https://virginia.api.cognitive.microsoft.us/anomalydetector/v1.1-preview/multivariate/results/{resultId}";
NSArray* array = @[
// Request parameters
@"entities=true",
];
NSString* string = [array componentsJoinedByString:@"&"];
path = [path stringByAppendingFormat:@"?%@", string];
NSLog(@"%@", path);
NSMutableURLRequest* _request = [NSMutableURLRequest requestWithURL:[NSURL URLWithString:path]];
[_request setHTTPMethod:@"GET"];
// Request headers
[_request setValue:@"{subscription key}" forHTTPHeaderField:@"Ocp-Apim-Subscription-Key"];
// Request body
[_request setHTTPBody:[@"{body}" dataUsingEncoding:NSUTF8StringEncoding]];
NSURLResponse *response = nil;
NSError *error = nil;
NSData* _connectionData = [NSURLConnection sendSynchronousRequest:_request returningResponse:&response error:&error];
if (nil != error)
{
NSLog(@"Error: %@", error);
}
else
{
NSError* error = nil;
NSMutableDictionary* json = nil;
NSString* dataString = [[NSString alloc] initWithData:_connectionData encoding:NSUTF8StringEncoding];
NSLog(@"%@", dataString);
if (nil != _connectionData)
{
json = [NSJSONSerialization JSONObjectWithData:_connectionData options:NSJSONReadingMutableContainers error:&error];
}
if (error || !json)
{
NSLog(@"Could not parse loaded json with error:%@", error);
}
NSLog(@"%@", json);
_connectionData = nil;
}
[pool drain];
return 0;
}
<?php
// This sample uses the Apache HTTP client from HTTP Components (http://hc.apache.org/httpcomponents-client-ga/)
require_once 'HTTP/Request2.php';
$request = new Http_Request2('https://virginia.api.cognitive.microsoft.us/anomalydetector/v1.1-preview/multivariate/results/{resultId}');
$url = $request->getUrl();
$headers = array(
// Request headers
'Ocp-Apim-Subscription-Key' => '{subscription key}',
);
$request->setHeader($headers);
$parameters = array(
// Request parameters
);
$url->setQueryVariables($parameters);
$request->setMethod(HTTP_Request2::METHOD_GET);
// Request body
$request->setBody("{body}");
try
{
$response = $request->send();
echo $response->getBody();
}
catch (HttpException $ex)
{
echo $ex;
}
?>########### Python 2.7 #############
import httplib, urllib, base64
headers = {
# Request headers
'Ocp-Apim-Subscription-Key': '{subscription key}',
}
params = urllib.urlencode({
})
try:
conn = httplib.HTTPSConnection('virginia.api.cognitive.microsoft.us')
conn.request("GET", "/anomalydetector/v1.1-preview/multivariate/results/{resultId}?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
print(data)
conn.close()
except Exception as e:
print("[Errno {0}] {1}".format(e.errno, e.strerror))
####################################
########### Python 3.2 #############
import http.client, urllib.request, urllib.parse, urllib.error, base64
headers = {
# Request headers
'Ocp-Apim-Subscription-Key': '{subscription key}',
}
params = urllib.parse.urlencode({
})
try:
conn = http.client.HTTPSConnection('virginia.api.cognitive.microsoft.us')
conn.request("GET", "/anomalydetector/v1.1-preview/multivariate/results/{resultId}?%s" % params, "{body}", headers)
response = conn.getresponse()
data = response.read()
print(data)
conn.close()
except Exception as e:
print("[Errno {0}] {1}".format(e.errno, e.strerror))
####################################require 'net/http'
uri = URI('https://virginia.api.cognitive.microsoft.us/anomalydetector/v1.1-preview/multivariate/results/{resultId}')
uri.query = URI.encode_www_form({
})
request = Net::HTTP::Get.new(uri.request_uri)
# Request headers
request['Ocp-Apim-Subscription-Key'] = '{subscription key}'
# Request body
request.body = "{body}"
response = Net::HTTP.start(uri.host, uri.port, :use_ssl => uri.scheme == 'https') do |http|
http.request(request)
end
puts response.body