semvec/pypi-packages huggingface dataset:
MOD16-JPL 1.1.0
JPL implementation of the MOD16 evapotranspiration algorithm for high resolution instantaneous remote sensing imagery
Requires Python: >=3.10

# JPL implementation of the MOD16 evapotranspiration remote sensing model

[![CI](https://github.com/JPL-Evapotranspiration-Algorithms/MOD16-JPL/actions/workflows/ci.yml/badge.svg)](https://github.com/JPL-Evapotranspiration-Algorithms/MOD16-JPL/actions/workflows/ci.yml)

The MODIS Global Evapotranspiration Project (MOD16) is a software package developed by a team of researchers from NASA Jet Propulsion Laboratory and the University of Montana. This software is a Python implementation of the MOD16 evapotranspiration algorithm, designed to process high-resolution instantaneous remote sensing imagery.

Unique features of the software include the ability to process remote sensing data with the MOD16 model and partition latent heat flux into canopy transpiration, interception, and soil evaporation. The MOD16 algorithm has been re-implemented to run on instantaneous high spatial resolution remote sensing imagery instead of 8-day MODIS imagery, making the model more accessible for remote sensing researchers.

The software is written entirely in Python and is intended to be distributed using the pip package manager.

The software was developed as part of a research grant by the NASA Research Opportunities in Space and Earth Sciences (ROSES) program. It was designed for use by the Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission as a precursor for the Surface Biology and Geology (SBG) mission. However, it may also be useful for general remote sensing and GIS projects in Python. This package can be utilized for remote sensing research in Jupyter notebooks and deployed for operations in data processing pipelines. 

The software is being released according to the SPD-41 open-science requirements of NASA-funded ROSES projects.

Gregory H. Halverson (they/them)<br>
[gregory.h.halverson@jpl.nasa.gov](mailto:gregory.h.halverson@jpl.nasa.gov)<br>
NASA Jet Propulsion Laboratory 329G

Kanishka Mallick (he/him)<br>
[kaniska.mallick@gmail.com](mailto:kaniska.mallick@gmail.com)<br>
Luxembourg Institute of Science and Technology

Claire Villanueva-Weeks (she/her)<br>
[claire.s.villanueva-weeks@jpl.nasa.gov](mailto:claire.s.villanueva-weeks@jpl.nasa.gov)<br>
NASA Jet Propulsion Laboratory 329G

## Installation

```
pip install MOD16-JPL
```

## Usage

```
import MOD16_JPL
```

## References

- Mu, Q., Zhao, M., & Running, S. W. (2011). Improvements to a MODIS global terrestrial evapotranspiration algorithm. *Remote Sensing of Environment*, 115(8), 1781-1800. doi:10.1016/j.rse.2011.02.019
- Mu, Q., Heinsch, F. A., Zhao, M., & Running, S. W. (2007). Development of a global evapotranspiration algorithm based on MODIS and global meteorology data. *Remote Sensing of Environment*, 111(4), 519-536. doi:10.1016/j.rse.2007.04.015
ncrar-audio 0.3.9
Audio tools supporting psiexperiment
Requires Python: >=3.7

NCRAR audio
-----------

To find out what audio devices are installed:

    python -m sounddevice

Copyright notice 

© 2021-2023, ncrar-audio development team

Portions of this project were funded by:

* The National Center for Rehabilitative Auditory Research at the Portland VA Medical Center on contract 36C26021P0557 awarded to Buran Consulting, LLC.
* Various NIH grants to Brad Buran, Stephen David, Naomi Bramhall and other investigators at the Oregon Hearing Research Center.
METIforST 0.5
METI: Deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics

# METI
METI (Morphology-Enhanced Spatial Transcriptome Analysis Integrator) is an novel analytic framework that systematically analyzes cancer cells and cells of the TME by incorporating spatial gene expression, tissue histology, and prior knowledge of cancer and TME cells. METI starts with the identification of key cellular components and their states within the TME, including various immune cells and their transcriptional states, tumor stromal components such as cancer-associated fibroblasts (CAFs), and the epithelial compartment. Meanwhile, METI offers complementary information on cell morphology for various cell type from the H&E images. The combined results from gene expression and histology features provide a comprehensive understanding of the spatial cellular composition and organization within the tissue. For more information, please check out: https://github.com/Flashiness/METI
bpdp-cli 0.1.0
CLI of BPDP
Requires Python: >=3.10

# bpdp_cli: The command line interface of bpdp algrithm
This package is separated from the bpdp package because it needs additional libraries to read the wav/mp3/... files. 

## Installation 
One can install the scripts using pip
```Bash
pip install bpdp_cli
```

## Usage:
1. Extract from single .wav file using default arguments
```Bash
bpdp -i test.wav
```
This will create a test.bpdp.txt contains the epochs.

2. Extract all .wav files from directory
```Bash
bpdp -I test_dir/
```
This will extract all .wav files in the directory recursively. 
For example, if a file test_dir/a/01/a01.wav is in the test_dir/, test_dir/a/01/a01.bpdp.txt will be created.

3. Dry run mode
```
bpdp -I test_dir/ --dry_run
```
This will prevent the actual calculation, file reads and writes.
esto 1.0.0
El Zen de Python en español
Requires Python: >=3.6

# Esto

El Zen de Python en español.

## Instalación

```bash
pip install esto

Uso

import esto

Esto imprimirá el Zen de Python en español.

Descripción

Este módulo es una adaptación en español del famoso "Zen de Python", que originalmente fue escrito por Tim Peters. Utiliza un cifrado ROT13 para ocultar el texto y luego lo decodifica al importar el módulo.

Autor

    Autor: Alonso Palomino F. (alias @alpfa)

    Fecha de creación: Jue 13 Mar 2025 01:26:01

Licencia

Este proyecto está bajo la licencia MIT. Para más detalles, consulta el archivo LICENSE.

Contribuciones

¡Las contribuciones son bienvenidas! Si tienes alguna idea para mejorar este proyecto, no dudes en hacer un fork y enviar un pull request.

Issues

Si encuentras algún problema o tienes alguna sugerencia, por favor abre un issue.

¡Gracias por usar esto! Espero que disfrutes del Zen de Python en español.