semvec/pypi-packages huggingface dataset:
labda-accelerometers 0.1.2
A package designed to process data from movement sensors – accelerometers.
Requires Python: >=3.11
Keywords: accelerometers, movement-behavior, physical-activity, sensors

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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](#).
geocat.viz 2025.7.0
GeoCAT-viz is the visualization component of the GeoCAT project and provides implementations of convenience functions for publication-ready plotting of geosciences data
Requires Python: >=3.10


# GeoCAT-viz

GeoCAT-viz contains tools to help plot geoscience data, including convenience and plotting functions that are
used to facilitate plotting geosciences data with Matplotlib, Cartopy, and other visualization packages.
GeoCAT-viz functionality is used by
[GeoCAT-examples](https://github.com/NCAR/geocat-examples).

|          **CI**          |           [![GitHub Workflow Status][github-ci-badge]][github-ci-link]           |
|:------------------------:|:--------------------------------------------------------------------------------:|
|         **Docs**         |                  [![Documentation Status][rtd-badge]][rtd-link]                  |
|       **Package**        |       [![Conda][conda-badge]][conda-link] [![PyPI][pypi-badge]][pypi-link]       |
|       **License**        |                 [![License][license-badge]][license-badge-link]                  |
|         **DOI**          |                          [![DOI][doi-badge]][doi-link]                           |

# Documentation

[GeoCAT Homepage](https://geocat.ucar.edu/)

[GeoCAT-viz Contributor's Guide](https://geocat-viz.readthedocs.io/en/latest/contrib.html)

[GeoCAT-viz Documentation on Read the Docs](https://geocat-viz.readthedocs.io)

# Installation instructions

Please see our documentation for [installation instructions](https://geocat-viz.readthedocs.io/en/latest/installation.html).

# Citing GeoCAT-viz

If you use this software, please cite it as described at the [GeoCAT-viz - Citation](
https://geocat-viz.readthedocs.io/en/latest/citation.html) page.

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