cf python package

Introduction

Version 3.17.0 for version 1.12 of the CF conventions.

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

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 that are partially conformant may nonetheless be modified in memory.

A basic example of reading a field construct from a file and inspecting it.
>>>
>>> import cf
>>> f = cf.read('file.nc')
>>> f
[<CF Field: air_temperature(time(12), latitude(64), longitude(128)) K>]
>>> print(f[0])
Field: air_temperature (ncvar%tas)
----------------------------------
Data            : air_temperature(time(12), latitude(64), longitude(128)) K
Cell methods    : time(12): mean (interval: 1.0 month)
Dimension coords: time(12) = [1991-11-16 00:00:00, ..., 1991-10-16 12:00:00] noleap
                : latitude(64) = [-87.8638, ..., 87.8638] degrees_north
                : longitude(128) = [0.0, ..., 357.1875] degrees_east
                : height(1) = [2.0] m

The cf package uses Dask for all of its array manipulation and can:

  • read field constructs and domain constructs from netCDF, CDL, PP and UM datasets with a choice of netCDF backends,

  • read files from OPeNDAP servers and S3 object stores,

  • create new field constructs in memory,

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

  • read, write, and manipulate UGRID mesh topologies,

  • 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).

Visualisation

Powerful, flexible, and user-friendly visualisations of field constructs are available with the cf-plot package that is installed separately to cf (see the cf-plot documentation for details).

See the cf-plot gallery for the wide range of plotting possibilities with example code.

_images/cfplot_example.png

Example output of cf-plot displaying a cf field construct.

Performance

As of version 3.14.0 (released 2023-01-31), cf uses Dask for all of its data manipulations, which provides lazy, parallelised, and out-of-core computations of array operations.

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.

CF data model

The CF (Climate and Forecast) metadata conventions (http://cfconventions.org) provide a description of the physical meaning of data and of their spatial and temporal properties and are designed to promote the creation, processing, and sharing of climate and forecasting data using netCDF files and libraries (https://www.unidata.ucar.edu/software/netcdf).

The CF data model identifies the fundamental elements (“constructs”) of the CF conventions and shows how they relate to each other, independently of the netCDF encoding.

The CF data model defines a field construct for storing data with all of its metadata. It is defined in CF-1.12 as follows:

field construct

corresponds to a CF-netCDF data variable with all of its metadata. It consists of

  • descriptive properties that apply to field construct as a whole (e.g. the standard name),

  • a data array,

  • a domain construct that describes the locations of each cell of the data array (i.e. the “domain”),

  • metadata constructs that describe the physical nature of the data array, defined by

    field ancillary constructs

    corresponding to CF-netCDF ancillary variables

    cell method constructs

    corresponding to a CF-netCDF cell_methods attribute of data variable

domain construct

that describes the locations of each cell of the domain. It may exist independently of a field construct and consists of

  • descriptive properties that apply to domain construct as a whole,

  • metadata constructs that describe the locations of each cell of the domain, defined by

domain axis constructs

corresponding to CF-netCDF dimensions or scalar coordinate variables

dimension coordinate constructs

corresponding to CF-netCDF coordinate variables or numeric scalar coordinate variables

auxiliary coordinate constructs

corresponding to CF-netCDF auxiliary coordinate variables and non-numeric scalar coordinate variables

coordinate reference constructs

corresponding to CF-netCDF grid mapping variables or the formula_terms attribute of a coordinate variable

domain ancillary constructs

corresponding to CF-netCDF variables named by the formula_terms attribute of a coordinate variable

cell measure constructs

corresponding to CF-netCDF cell measure variables

domain topology constructs

corresponding to CF-netCDF UGRID mesh topology variables

cell connectivity constructs

corresponding to CF-netCDF UGRID connectivity variables


_images/cfdm_field.svg

The constructs of the CF data model described using UML. The field construct corresponds to a CF-netCDF data variable. The domain construct provides the linkage between the field construct and the constructs which describe measurement locations and cell properties. It is useful to define an abstract generic coordinate construct that can be used to refer to coordinates when the their type (dimension or auxiliary coordinate construct) is not an issue.

References

Eaton, B., Gregory, J., Drach, B., Taylor, K., Hankin, S., Caron, J.,

Signell, R., et al. NetCDF Climate and Forecast (CF) Metadata Conventions. CF Conventions Committee. https://cfconventions.org/cf-conventions/cf-conventions.html

Hassell, D., and Bartholomew, S. L. (2020). cfdm: A Python reference

implementation of the CF data model. Journal of Open Source Software, 5(54), 2717, https://doi.org/10.21105/joss.02717

Hassell, D., Gregory, J., Blower, J., Lawrence, B. N., and

Taylor, K. E. (2017). A data model of the Climate and Forecast metadata conventions (CF-1.6) with a software implementation (cf-python v2.1), Geosci. Model Dev., 10, 4619-4646, https://doi.org/10.5194/gmd-10-4619-2017

Rew, R., and Davis, G. (1990). NetCDF: An Interface for Scientific

Data Access. IEEE Computer Graphics and Applications, 10(4), 76–82. https://doi.org/10.1109/38.56302

Rew, R., Hartnett, E., and Caron, J. (2006). NetCDF-4: Software

Implementing an Enhanced Data Model for the Geosciences. In 22nd International Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology. AMS. Retrieved from https://www.unidata.ucar.edu/software/netcdf/papers/2006-ams.pdf

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