Metadata-Version: 2.1
Name: imdlib
Version: 0.1.15
Summary: A tool for handling and downloading IMD gridded data
Home-page: https://github.com/iamsaswata/
Author: Saswata Nandi
Author-email: iamsaswata@yahoo.com
License: MIT
Keywords: imd,India,rainfall,data,hydrology,IMD,grid,grided,gridded
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Hydrology
Requires-Python: >=3.0
Description-Content-Type: text/markdown
License-File: LICENSE

# imdlib
[![Build Status](https://github.com/iamsaswata/imdlib/actions/workflows/pypi.yml/badge.svg)](https://github.com/iamsaswata/imdlib/actions/workflows/pypi.yml)
![GitHub](https://img.shields.io/github/license/iamsaswata/imdlib)
![PyPI](https://img.shields.io/pypi/v/imdlib)
![Conda](https://img.shields.io/conda/v/iamsaswata/imdlib)
[![Downloads](https://pepy.tech/badge/imdlib)](https://pepy.tech/project/imdlib)


This is a python package to download and handle binary grided data from Indian Meterological department (IMD).

## Installation

> pip install imdlib
 
 or

> conda install -c iamsaswata imdlib

or 

> pip install git+https://github.com/iamsaswata/imdlib.git


## Documentation

[Tutorial](https://saswatanandi.github.io/softwares/imdlib)
[Tutorial](https://pratiman-91.github.io/blog.html)

## Video Tutorial  
  
[![IMDLIB - Albedo Foundation](https://img.youtube.com/vi/uSIPPY5WRaM/0.jpg)](https://www.youtube.com/watch?v=uSIPPY5WRaM)

## License

imdlib is available under the [MIT](https://opensource.org/licenses/MIT) license.

## Citation

If you are using imdlib and would like to cite it in academic publication, we would certainly appreciate it. We recommend to use the zenodo DOI for this purpose:

Nandi, S., Patel, P., and Swain, S. (2022). IMDLIB: A python library for IMD gridded data. Zenodo. https://doi.org/10.5281/zenodo.7205414

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.7205414.svg)](https://doi.org/10.5281/zenodo.7205414)

## Publications using IMDLIB  

Swain, S., Mishra, S. K., Pandey, A., & Dayal, D. (2022). Assessment of drought trends and variabilities over the agriculture-dominated Marathwada Region, India. *Environmental Monitoring and Assessment, 194(12)*, 1-18. 
[[DOI]](https://doi.org/10.1007/s10661-022-10532-8)  
  
Swain, S., Mishra, S. K., Pandey, A., Dayal, D., & Srivastava, P. K. (2022). Appraisal of historical trends in maximum and minimum temperature using multiple non-parametric techniques over the agriculture-dominated Narmada Basin, India. *Environmental Monitoring and Assessment*, 194(12), 1-23. [[DOI]](https://doi.org/10.1007/s10661-022-10534-6) 

Venkatesh, S., Kirubakaran, T., Ayaz, R. M., Umar, S. M., & Parimalarenganayaki, S. (2023). Non-parametric Approaches to Identify Rainfall Pattern in Semi-Arid Regions: Ranipet, Vellore, and Tirupathur Districts, Tamil Nadu, India. *In River Dynamics and Flood Hazards* (pp. 507-525). Springer, Singapore.  [[DOI]](https://doi.org/10.1007/978-981-19-7100-6_28) 
