Skip to main content

A collections of functions for meteorological verification.

Project description

# MetEva

MetEva aims to provide fast and efficient evaluation and validation methods and processes for weather forecasting products. From numerical models, objective forecasting methods, refined grid forecasts to forecast product application, MetEva can play a role in promoting cross-process and cross-departmental verification information sharing, providing technical support for improving forecast quality.

Generally, Meteva is a pure python program library that provides commonly used algorithms for reading and writing , mapping, and evalution of various kind of waather forecast data. Meanwhile, MetEva provides a wealth of examples for the use of validation algorithms. It contains 20 + items of data reading and writing functions, 10 + items of convenient plotting functions, 100 + items of basic valadation algorithms, 20 + items of application tools for evaluation and validation, and supports 30 + classification methods for fine-scale evaluation.

## Version

MetEva-1.9.1.4

## Dependencies

numpy>=1.12.1, pandas>=1.0.4, netCDF4>=1.4.2, scipy>=0.19.0, xarray>=0.10.0, scikit-learn>=0.21.2

matplotlib>=3.0.0, httplib2>=0.12.0, protobuf < 3.20.0, pyshp>=2.1.0, tables>=3.4.4, urllib3>=1.21.1

## Install

Please install metdig under anaconda enviroment.

The installation can be completed by executing the command “pip install meteva”.

This library only supports running on Python versions above 3.7.

## More Information

For detailed usage instructions, please refer to the content of this website: https://www.showdoc.cn/meteva

#nmc_verification 提供气象产品检验相关程序 说明文档详见: https://www.showdoc.cc/meteva

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

meteva-1.9.5.1.tar.gz (508.8 kB view details)

Uploaded Source

Built Distribution

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

meteva-1.9.5.1-py3-none-any.whl (3.8 MB view details)

Uploaded Python 3

File details

Details for the file meteva-1.9.5.1.tar.gz.

File metadata

  • Download URL: meteva-1.9.5.1.tar.gz
  • Upload date:
  • Size: 508.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.8.18

File hashes

Hashes for meteva-1.9.5.1.tar.gz
Algorithm Hash digest
SHA256 3f9cd61e45090c965a2b0cef34912dba3be7c04dd2a5b683f6208f9858d6f34e
MD5 2e5e00faf354d46627fc29bf7dbc6d4b
BLAKE2b-256 b3bbdf4e88677174dfd6d000b076c32da36e05c8003d6d41aeeedf6cf48de094

See more details on using hashes here.

File details

Details for the file meteva-1.9.5.1-py3-none-any.whl.

File metadata

  • Download URL: meteva-1.9.5.1-py3-none-any.whl
  • Upload date:
  • Size: 3.8 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.8.18

File hashes

Hashes for meteva-1.9.5.1-py3-none-any.whl
Algorithm Hash digest
SHA256 401aa4ad529db473026adf0abe372262bd00e1e6c20dbade99ee3c1db7e11e27
MD5 3f734d110fbe7df08590166c2f58846b
BLAKE2b-256 d55cb9abb6ea2408d777747930234a76ef2ebc3f8d6b8d2c284e837d9aed5ecb

See more details on using hashes here.

Supported by

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