semvec/pypi-packages huggingface dataset:
mirofile 0.1
Python module for using MIROSLAV files as file-like objects with seamless preprocessing. MIROSLAV is a FOSS tool for monitoring activity of laboratory rodents.
Requires Python: >=3.12

# `mirofile` - Your buddy for dealing with raw MIROSLAV data

#### What is it?

**MIROSLAV (Multicage InfraRed Open Source Locomotor Activity eValuator)** is a platform for non-invasive monitoring of circadian locomotor activity in laboratory rodents. All of its hardware and software components are described in the paper: #url

This `mirofile` library, acting as a file-like object, loads raw MIROSLAV files containing experimental data and parses them into a sequence of lists, each containing appropriately-typed timestamps and sensor readings, which can then be turned into a `pandas` data frame by the user.

A script which exemplifies the use of this library can also be found in the MIROSLAV paper's data repository: #url.

#### How to install?

`mirofile` is [available on PyPi](https://pypi.org/project/mirofile/) can be installed with `pip`:

```bash
pip install mirofile
```

##### Dependencies

 * [`tqdm`](https://pypi.org/project/tqdm/) - can be also be installed with `pip`

#### License

The code is distributed under GPLv3.
pymoog 1.0.0
The python wrapper to run LTE spectra synthesis code MOOG.
Requires Python: >=3.5

# pymoog

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7582434.svg)](https://doi.org/10.5281/zenodo.7582434) [![Documentation Status](https://readthedocs.org/projects/pymoog/badge/?version=latest)](https://pymoog.readthedocs.io/en/latest/?badge=latest)

## News

pymoog is now 1.0.0! The main drivers are all availalbe (binary, doflux, synpop and abpop newly added), with many bugs fixed. 
Note that there are some breaking changes compared to the previous versions, and the description will be availabe in the [documentation](https://pymoog.readthedocs.io/en/latest/) soon.

Thanks the very useful synpop and abpop example provided by Charli Sakari. 

------------------------------------- 

`pymoog` is a python3 wrapper for running the LTE spectrum synthesis part of the code [MOOG](https://www.as.utexas.edu/~chris/moog.html) written by Chris Sneden.
It wraps up the (a bit) teidous steps for generating a synthetic spectra into four python commands, while retaining the functions provided by MOOG.
Besides, it also provides some other functions for analysing the MOOG result, mainly contribution function and fitting stellar parameters.

Here you can:
- generate a synthetic spectra
- alter the stellar parameters for the spectra, such as $T_\mathrm{eff}$, metallicity, abundance ratios or resolution.
- determine some stellar parameters, such as microturbulance velocity or abundance ratios.

without considering:
- where to grab stellar atmosphere models and line lists
- how to interpolate the models.

Documentation (including the installation) is available in [here](https://pymoog.readthedocs.io/en/latest/).

## Acknowledgement

This package has made use of the VALD database, operated at Uppsala University, the Institute of Astronomy RAS in Moscow, and the University of Vienna.