Skip to main content

Python Hail Retrieval Toolkit (pyhail) ⛈️📡🧊

This toolkit provides a collection of hail retrieval techniques for weather radar data.

Library Dependencies

  • numpy
  • scipy
  • numba

Supporter radar file readers

Notebook plotting Dependencies

  • matplotlib

Hail Retrivals

*Note that the Q confidence vector from Park et al. 2009 has not been implemented and all pixels are assigned a value of q=1.

MESH is implemented for both pyart radar (PPI) and grid (Cartesian) data!

Install using pypi

pip install pyhail

Install from source

To install pyhail, you can either download and unpack the zip file of the source code or use git to checkout the repository:

git clone git@github.com:joshua-wx/pyhail.git

To install in your home directory, use:

python setup.py install --user

Use

This project is maintained by Joshua Soderholm. Any problems? Please use the Github issue tracker.

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyhail-3.1.0.tar.gz (418.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

pyhail-3.1.0-py3-none-any.whl (24.6 kB view details)

Uploaded Python 3

File details

Details for the file pyhail-3.1.0.tar.gz.

File metadata

  • Download URL: pyhail-3.1.0.tar.gz
  • Upload date:
  • Size: 418.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.3

File hashes

Hashes for pyhail-3.1.0.tar.gz
Algorithm Hash digest
SHA256 f82fecabfe15e120c0bc420c996c2f5c376a299056286e52fb6f3187737db9c8
MD5 ecb629b2781df964f7ec12dee82edd35
BLAKE2b-256 b477053368daf5d42c0ca9a781d9edeacbc47fb78f1dd62f68d1202467bc5704

See more details on using hashes here.

File details

Details for the file pyhail-3.1.0-py3-none-any.whl.

File metadata

  • Download URL: pyhail-3.1.0-py3-none-any.whl
  • Upload date:
  • Size: 24.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.12.3

File hashes

Hashes for pyhail-3.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 76e740d421d21b4c5b7877bcaad453f790cb7e48728a94e7a992bc7e7fe8ac9a
MD5 9715ccb5478f336d34ea7aaa7bf71c76
BLAKE2b-256 4484e7de3b83e44ec9f484e86b52e7179dae1e12da91930f6974a8d16675733b

See more details on using hashes here.

Release history Release notifications | RSS feed

3.4.2

2 files

3.4.1

2 files

3.3.2

2 files

3.3.1

2 files

3.3.0

2 files

3.2.2

2 files

3.2.1

2 files

3.2.0

2 files

3.1.1

2 files

This release

3.1.0 This release

2 files

3.0.2

2 files

3.0.1

2 files

3.0.0

1 file

2.4.1

2 files

2.4

2 files

2.3.3

2 files

2.3.2

2 files

2.3.1

2 files

2.3

2 files

2.2

2 files

2.0.1

2 files

2.0.0

4 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page