semvec/pypi-packages huggingface dataset:
MPoL 0.2.0
Regularized Maximum Likelihood Imaging for Radio Astronomy
Requires Python: >=3.8

# MPoL

[![Tests](https://github.com/MPoL-dev/MPoL/actions/workflows/tests.yml/badge.svg?branch=main)](https://github.com/MPoL-dev/MPoL/actions/workflows/tests.yml)
[![gh-pages docs](https://github.com/MPoL-dev/MPoL/actions/workflows/gh_docs.yml/badge.svg)](https://mpol-dev.github.io/MPoL/)
[![DOI](https://zenodo.org/badge/224543208.svg)](https://zenodo.org/badge/latestdoi/224543208)

A Million Points of Light are needed to synthesize image cubes from interferometers.

MPoL is a flexible Python package designed for Regularized Maximum Likelihood imaging. We focus on supporting spectral line and continuum observations from interferometers like the Atacama Large Millimeter/Submillimeter Array (ALMA) and the Karl G. Jansky Very Large Array (VLA). There is potential to extend the package to work on other Fourier reconstruction problems like sparse aperture masking and kernel phase interferometry.

Documentation and installation instructions: [https://mpol-dev.github.io/MPoL/](https://mpol-dev.github.io/MPoL/)

## Citation

If you use this package or derivatives of it, please cite

    @software{mpol,
    author       = {Ian Czekala and
                    Jeff Jennings and   
                    Brianna Zawadzki and
                    Ryan Loomis and
                    Kadri Nizam and 
                    Megan Delamer and 
                    Kaylee de Soto and
                    Robert Frazier and
                    Hannah Grzybowski and
                    Mary Ogborn and                    
                    Tyler Quinn},
    title        = {MPoL-dev/MPoL: v0.2.0 Release},
    month        = nov,
    year         = 2023,
    publisher    = {Zenodo},
    version      = {v0.2.0},
    doi          = {10.5281/zenodo.3594081},
    url          = {https://doi.org/10.5281/zenodo.3594081}
    }

---
Copyright Ian Czekala and contributors 2019-23
rescan 1.0.4
A Modern Port scanner in python
Requires Python: >=3.8
Keywords: Port Scanner,Modern

                                                         
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---------------------------
# Rescan
A modern port scanner for recon written in python

# Installation
- `pip install rescan`
- `rescan info` for more information

#  Debug Setup
- `git clone https://github.com/snowkluster/rescan.git`
- `python3 -m pip install -r requirements.txt`

# Help
- `rescan --help`
stactools-landsat 0.5.0
stactools package for Landsat data
Keywords: stactools,pystac,catalog,STAC,Landsat

# stactools-landsat

[![PyPI](https://img.shields.io/pypi/v/stactools-landsat)](https://pypi.org/project/stactools-landsat/)

- Name: landsat
- Package: `stactools.landsat`
- PyPI: <https://pypi.org/project/stactools-landsat/>
- Owners:
  - @lossyrob
  - @pjhartzell
  - @gadomski
- Dataset homepages:
  - <https://www.usgs.gov/landsat-missions>
  - <https://landsat.gsfc.nasa.gov/>
- STAC extensions used:
  - [classification](https://github.com/stac-extensions/classification)
  - [eo](https://github.com/stac-extensions/eo)
  - [landsat](https://stac-extensions.github.io/landsat/v2.0.0/schema.json)
  - [proj](https://github.com/stac-extensions/projection/)
  - [raster](https://github.com/stac-extensions/raster)
  - [scientific](https://github.com/stac-extensions/scientific)
  - [view](https://github.com/stac-extensions/view)

This repository will assist you in the generation of STAC files for Landsat datasets. The table below provides an overview on Landsat Mission's sensors and band wavelengths.

<!-- markdownlint-disable MD033 -->
<img width="1147" alt="Landsat Missions - Sensors and Band Wavelengths" src="https://user-images.githubusercontent.com/1312546/190440352-0b6e2c81-f1b4-48ff-bcf1-5b5addba1bd9.png">
<!-- markdownlint-enable MD033 -->

Source: <https://pubs.usgs.gov/fs/2015/3081/fs20153081.pdf>

## Examples

### STAC Collections and Items

- [Collection](examples/landsat-c2-l2/collection.json)
- [Item](examples/landsat-c2-l1/LM01_L1GS_001010_19720908_02_T2/LM01_L1GS_001010_19720908_02_T2.json)

### Command-line usage

To create a STAC `Item`:

```bash
stac landsat create-item --mtl tests/data-files/oli-tirs/LC08_L2SP_047027_20201204_20210313_02_T1_MTL.xml --output examples --usgs_geometry
```

To create a STAC `Collection` from a text file containing a list of Landsat scene XML metadata files:

```bash
stac landsat create-collection --file_list examples/c2-l2-file-list.txt --output examples/landsat-c2-l2 --id landsat-c2-l2 --usgs_geometry
```

The above `create-collection` command is exactly how the contents of the `examples/landsat-c2-l2` directory are generated.