Skip to main content

A CF-compliant earth science data analysis library

Project description

CF Python

The Python cf package is an Earth science data analysis library that is built on a complete implementation of the CF data model.

Documentation

http://ncas-cms.github.io/cf-python

Dask

From version 3.14.0, the cf package uses Dask for all of its data manipulations.

Recipes

https://ncas-cms.github.io/cf-python/recipes

Tutorial

https://ncas-cms.github.io/cf-python/tutorial

Installation

http://ncas-cms.github.io/cf-python/installation

Command line utilities

During installation the cfa command line utility is also installed, which

  • generates text descriptions of field constructs contained in files, and

  • creates new datasets aggregated from existing files.

Visualization

Powerful, flexible, and very simple to produce visualizations of field constructs are available with the cf-plot package, that needs to be installed seprately to the cf package.

See the cfplot gallery for the full range of plotting possibilities with example code.

Functionality

The cf package implements the CF data model for its internal data structures and so is able to process any CF-compliant dataset. It is not strict about CF-compliance, however, so that partially conformant datasets may be ingested from existing datasets and written to new datasets. This is so that datasets which are partially conformant may nonetheless be modified in memory.

The cf package can:

  • read field constructs from netCDF, CDL, Zarr, PP and UM datasets,

  • be fully flexible with respect to dataset storage chunking,

  • create new field constructs in memory,

  • write and append field constructs to netCDF datasets on disk,

  • read, write, and create coordinates defined by geometry cells,

  • read netCDF and CDL datasets containing hierarchical groups,

  • inspect field constructs,

  • test whether two field constructs are the same,

  • modify field construct metadata and data,

  • create subspaces of field constructs,

  • write field constructs to netCDF datasets on disk,

  • incorporate, and create, metadata stored in external files,

  • read, write, and create data that have been compressed by convention (i.e. ragged or gathered arrays, or coordinate arrays compressed by subsampling), whilst presenting a view of the data in its uncompressed form,

  • combine field constructs arithmetically,

  • manipulate field construct data by arithmetical and trigonometrical operations,

  • perform statistical collapses on field constructs,

  • perform histogram, percentile and binning operations on field constructs,

  • regrid structured grid, mesh and DSG field constructs with (multi-)linear, nearest neighbour, first- and second-order conservative and higher order patch recovery methods, including 3-d regridding,

  • apply convolution filters to field constructs,

  • create running means from field constructs,

  • apply differential operators to field constructs,

  • create derived quantities (such as relative vorticity),

  • read and write that data that are quantized to eliminate false precision.

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

cf_python-3.18.0.tar.gz (1.5 MB view details)

Uploaded Source

File details

Details for the file cf_python-3.18.0.tar.gz.

File metadata

  • Download URL: cf_python-3.18.0.tar.gz
  • Upload date:
  • Size: 1.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.3

File hashes

Hashes for cf_python-3.18.0.tar.gz
Algorithm Hash digest
SHA256 49e4e36c06be36242c4c5a88252ea68c3ed43a1c2e1a5a60802131105210b792
MD5 bf357187336039aa3f09de65e814e405
BLAKE2b-256 fca60dfab36a33ccdf102980deaaab0fc8154f2a8a27b9730f3862638721393d

See more details on using hashes here.

Supported by

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