Data reduction by using the swinging door algorithm.
Beginning at the last archived value (1) and the next snapshots (2, 3, ...) a swinging door is constructed, that is only allowed to close and not to open. Green area in the figure below.
When an incoming value (6) lies outside the allowed area, so the last snapshot (5) get stored, and beginning at this snapshot (5) a new swinging door to the incoming (6) value gets opened.
Therefore maintaining the trend in the data.
| Name | Description |
|---|---|
| CompDev | (absolut) compression deviation |
| ExMax | length of x/time before for sure a value gets recoreded |
| ExMin | length of x/time within no value gets recorded (after the last archived value) |
| Data | # datapoints | average | sigma | skewness | kurtosis |
|---|---|---|---|---|---|
| raw | 1000 | 19.2854 | 1.2968 | -2.1689 | 7.0397 |
| compressed | 418 | 19.2833 | 1.2984 | -2.1682 | 7.0428 |
As can be seen statistics didn't change significantally, but the count of recorded datapoints was reduced -- by filtering noise -- by 58%.