... | ... | @@ -169,7 +169,7 @@ To use the power profiling service, define a `<powerProfilingConf>` block with t |
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| `obsIds`* | One or more observer IDs for which this service should be used. Note that all IDs used here have to have a target configuration as well. | ID(s) of the observer(s) to use |
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| `offset`* | Defines the start of the power measurement relative to the test start (offset in seconds). | |
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| `duration` | Duration in seconds of the power measurement. | |
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| `samplingRate` | Sampling rate [Hz] for the power measurement.<br />**Note:** For sampling rates below 1000Hz, the measurements will be averaged over *1000 / samplingRate* samples (i.e. internally, the min. sampling frequency is always 1kHz and the downsampled results are average values). However, accuracy loss can still occur for very low currents. | possible values: 1, 10, 100, 1000, 2000, 4000, 8000, 16000, 32000, 64000. default: 1000 |
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| `samplingRate` | Sampling rate [Hz] for the power measurement.<br /> | possible values: 1, 10, 100, 1000, 2000, 4000, 8000, 16000, 32000, 64000. default: 1000 |
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| `fileFormat` | File format. The csv format is more convenient (text), but results in large files. If you want to parse the data manually, you can use the rld format (binary). Parsing tools are available [here](https://pypi.org/project/rocketlogger/). | possible values: csv, rld. default: csv |
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| `aggregate` | Targeted sampling rate after aggregation, must be smaller than the sampling rate. If set, the results will be downsampled (averaged) to the specified rate in Hertz. <br />**Note:** This option can only be used with file format 'csv'. | possible values: 0, 1, 10, 100, 1000, 2000, 4000, 8000, 16000, 32000. default: 0 (no aggregation) |
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