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# LABDA Accelerometers
A package designed to process data from movement sensors – accelerometers.
- Auto-calibration
- Non-wear detection
- Metrics: Counts, ENMO
- Python
See [documentation](#) for more details.
## Installation
Install using `pip install labda-accelerometers`.
## A Simple Example
```python
import pandas as pd
from labda_accelerometers import Metrics, AutoCalibrate, WearDetection
df = AutoCalibrate().calibrate(df)
print(df)
#> acc_x acc_y acc_z
#> datetime
#> 2021-09-09 00:00:07.009999990+02:00 -0.099318 -0.128671 0.995101
#> 2021-09-09 00:00:07.019999981+02:00 0.076385 -0.267248 0.995101
#> 2021-09-09 00:00:07.029999971+02:00 0.092358 -0.267248 0.927356
epoch = 1 # In seconds
acc_wear = WearDetection(epoch=epoch).from_acceleration(df)
metrics = Metrics(epoch=epoch)
enmo = metrics.enmo(df)
counts = metrics.counts(df)
results = pd.concat([acc_wear, enmo, counts], axis=1)
print(results)
#> wear enmo counts_x counts_y counts_z counts_vm
#> datetime
#> 2021-09-09 00:00:07+02:00 False 0.022882 0 5 51 51.244511
#> 2021-09-09 00:00:08+02:00 False 0.024908 0 0 6 6.000000
#> 2021-09-09 00:00:09+02:00 False 0.014403 0 0 0 0.000000
```
Detailed information on labda-accelerometers processing and features is available [here](#).
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