semvec/pypi-packages huggingface dataset:
LSFExtractor 0.0.1
A Python module to estimate the Line Spread Function
License: MIT License

# LSFExtractor

## Description

This module enables users to extract the Line Spread Function (LSF) from any type of spectral cube. The provided code automatically handles multiple axes in the datacube. 

Currently, the code estimates the LSF only for ALMA data cubes, but we are actively developing support for additional types of cubes.


## Getting Started

### Installing

Releases are registered on PyPI, and development is occurring at the project's [GitHub page](https://github.com/nsotostuardo/LSFExtractor).



### Executing program


First we need to import the module to the python script or notebook.

```
import LSFExtractor as lsf
```

The module executes by creating an instance of the class with just the path to a cube file, and then using the `get_LSF` method.

```
cube = lsf.Cube('path_to_file')
cube.get_LSF()
```

The method returns a list of length three corresponding to LSF, LSF lower error, and LSF upper error, respectively. It can also be accessed using the `.LSF` attribute of the class

```
 LSF, LSF_lower, LSF_upper = cube.LSF
````

The class includes the method `.save_LSF(path, format = '.3f', write = True)` which creates an Astropy QTable with the code's output and saves it as an ASCII table in the file named `path_LSF.dat`


```
cube.save_LSF('new_path')
```

More documentation can be found inside the .py files.

## Authors


* [jigonzal](https://github.com/jigonzal)
* [nsotostuardo](https://github.com/nsotostuardo)

## Version History

* 0.1
    * Initial Release

## License

This project is licensed under a MIT style license - see the LICENSE.md file for details

## Acknowledgments

Inspiration, code snippets, etc.

* [LSF](https://github.com/jigonzal/LSF)
* [The Astropy Project](https://github.com/astropy)
* [awesome-readme](https://github.com/matiassingers/awesome-readme)