> ## Documentation Index
> Fetch the complete documentation index at: https://docs.canaryedge.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Detect Changepoints

> Azure-compatible endpoint to detect distribution changes in a time series

Detect points where the underlying data distribution changes. Canary implements this by computing the energy gradient: the rate of change of the prediction error over a sliding window. This endpoint is fully compatible with the Azure Anomaly Detector changepoint API.

Both `/anomalydetector/v1.0/timeseries/changepoint/detect` and `/anomalydetector/v1.1/timeseries/changepoint/detect` are supported.

<ParamField body="series" type="array" required>
  Array of data points, each with `timestamp` (ISO 8601) and `value` (number). Minimum 12 points, maximum 8640 points. Timestamps must be sorted ascending with no duplicates.
</ParamField>

<ParamField body="granularity" type="string" default="none">
  Time interval between points. One of: `yearly`, `monthly`, `weekly`, `daily`, `hourly`, `minutely`, `secondly`, `microsecond`, `none`.
</ParamField>

<ParamField body="customInterval" type="integer" default={1}>
  Multiplier for granularity.
</ParamField>

<ParamField body="period" type="integer" default={0}>
  Seasonality period. Set to `0` for auto-detection.
</ParamField>

<ParamField body="maxAnomalyRatio" type="number" default={0.25}>
  Maximum fraction of points flagged. Must be between 0 and 0.5 (exclusive).
</ParamField>

<ParamField body="sensitivity" type="integer" default={95}>
  Detection sensitivity (0-99).
</ParamField>

<ResponseField name="period" type="integer">
  Detected seasonality period.
</ResponseField>

<ResponseField name="isChangePoint" type="boolean[]">
  Whether each point is a changepoint.
</ResponseField>

<ResponseField name="confidenceScores" type="number[]">
  Confidence score from 0.0 to 1.0 for each point.
</ResponseField>

### How Changepoint Detection Works

1. The energy gradient is computed: `gradient[i] = mean(energies[i:i+k]) - mean(energies[i-k:i])` where `k = max(period, 5)`.
2. A point is a changepoint if its gradient exceeds the 95th percentile of all gradients.
3. The gradient must be a local maximum (greater than or equal to both neighbors).
4. Minimum spacing between changepoints equals the detected period.

<RequestExample>
  ```bash cURL theme={null}
  curl -X POST https://api.canaryedge.com/anomalydetector/v1.1/timeseries/changepoint/detect \
    -H "Content-Type: application/json" \
    -H "Ocp-Apim-Subscription-Key: YOUR_API_KEY" \
    -d '{
      "series": [
        {"timestamp": "2018-03-01T00:00:00Z", "value": 32858923},
        {"timestamp": "2018-03-02T00:00:00Z", "value": 29615278},
        {"timestamp": "2018-03-03T00:00:00Z", "value": 28988966},
        {"timestamp": "2018-03-04T00:00:00Z", "value": 28943783},
        {"timestamp": "2018-03-05T00:00:00Z", "value": 33521547},
        {"timestamp": "2018-03-06T00:00:00Z", "value": 34127843},
        {"timestamp": "2018-03-07T00:00:00Z", "value": 32497298},
        {"timestamp": "2018-03-08T00:00:00Z", "value": 29615278},
        {"timestamp": "2018-03-09T00:00:00Z", "value": 28988966},
        {"timestamp": "2018-03-10T00:00:00Z", "value": 28943783},
        {"timestamp": "2018-03-11T00:00:00Z", "value": 33521547},
        {"timestamp": "2018-03-12T00:00:00Z", "value": 72000000}
      ],
      "granularity": "daily",
      "sensitivity": 95
    }'
  ```
</RequestExample>

<ResponseExample>
  ```json 200 theme={null}
  {
    "period": 7,
    "isChangePoint": [false, false, false, false, false, false, false, false, false, false, false, true],
    "confidenceScores": [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.87]
  }
  ```
</ResponseExample>