Skip to main content

This package provides tools to homogenize, process, and analyze global disdrometer data.

Project description

DISDRODB - A package to standardize, process and analyze global disdrometer data.

DOI PyPI version Conda Version Build Status Coverage Status Documentation Status Code style: black License

DISDRODB is part of an initial effort to index, collect and homogenize drop size distribution (DSD) data sets across the globe, as well as to establish a global standard for disdrometers observations data sharing. DISDRODB standards are being established following FAIR data best practices and Climate & Forecast (CF) conventions, and will facilitate the preprocessing, analysis and visualization of disdrometer data.

The DISDRODB archive is composed of 3 product levels:

  • L0 provides the raw sensors measurements converted into a standardized netCDF4 format.
  • L1 provides L0 homogenized and quality-checked data.
  • L2 provides scientific products derived from the L1 data.

The code required to the generate the DISDRODB archive is enclosed in the production directory of the repository.

The code facilitating the analysis and visualization of the DISDRODB archive is available in the api directory.

The software documentation is available at https://disdrodb.readthedocs.io/en/latest/.

Currently:

  • only the DISDRODB L0 product generation has been implemented;
  • the pipeline for DISDRODB L1 and L2 product generation is in development;
  • the DISDRODB API is in development;
  • more than 300 sensors have been already processed to DISDRODB L0;
  • tens of institutions have manifested their interest in adopting the DISDRODB tools and standards.

Consequently IT IS TIME TO GET INVOLVED. If you have ideas, algorithms, data or expertise to share, do not hesitate to GET IN TOUCH !!!

Installation

DISDRODB can be installed from PyPI with pip:

pip install disdrodb

In future, it will become available from conda-forge for conda installations:

conda install -c conda-forge disdrodb

Contributors

License

The content of this repository is released under the terms of the MIT license.

Project details


Download files

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

Source Distribution

disdrodb-0.0.13.tar.gz (84.6 kB view details)

Uploaded Source

Built Distribution

disdrodb-0.0.13-py3-none-any.whl (194.6 kB view details)

Uploaded Python 3

File details

Details for the file disdrodb-0.0.13.tar.gz.

File metadata

  • Download URL: disdrodb-0.0.13.tar.gz
  • Upload date:
  • Size: 84.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for disdrodb-0.0.13.tar.gz
Algorithm Hash digest
SHA256 cbace112c80bade1b1e83dbd0478497f0a0f5a779df9803d435c96a5c2113436
MD5 50983cf000eccdd788d2670dc13dc586
BLAKE2b-256 66b971d85d15eb155cfe858dbed32260433747ba6fc145bfd764a4960164090f

See more details on using hashes here.

File details

Details for the file disdrodb-0.0.13-py3-none-any.whl.

File metadata

  • Download URL: disdrodb-0.0.13-py3-none-any.whl
  • Upload date:
  • Size: 194.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.11.1

File hashes

Hashes for disdrodb-0.0.13-py3-none-any.whl
Algorithm Hash digest
SHA256 1c4f3b82046c93c800360f4074bdb206d50d637b616af9f465fa0bc6e2a3fe98
MD5 ca2c6db8aa634775b4dc9ee28e063d86
BLAKE2b-256 e9145a81119b4e7d3b9f503c584aca4010415415c9da092bdecc959663c68b42

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page