cfdm package

Introduction

Version 1.8.7.0 for version 1.8 of the CF conventions.

The Python cfdm package is a reference implementation of the CF data model.

The CF data model is a complete representation of the CF (Climate and Forecast) metadata conventions (http://cfconventions.org) for storing geoscientific datasets. It can describe any conceivable CF-compliant dataset. Therefore cfdm, a software implementation of the CF data model, will also be able to process any CF-compliant dataset.

The cfdm package is, however, not strict about CF-compliance, so that non-conformant datasets may be created or ingested from existing datasets and written to new datasets. This is so that existing datasets which are non-CF-compliant may be processed by cfdm, ideally being modified in memory to be (more) CF-compliant.

Functionality

The cdfm library can create field constructs ab initio, or read them from netCDF files, inspect, subspace and modify in memory, and write them to CF-netCDF dataset files. As long as it can interpret the data, cfdm does not enforce CF-compliance, allowing non-compliant datasets to be read, processed, corrected and rewritten.

It does not contain higher-level analysis functions (such as regidding) because the expectation is that other libraries will build on cfdm, inheriting its comprehensive knowledge of the CF conventions, to add more sophisticated methods.

A simple example of reading a field construct from a file and inspecting it.
>>> import cfdm
>>> f = cfdm.read('file.nc')
>>> f
[<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) = [0450-11-16 00:00:00, ..., 0451-10-16 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 cfdm package can

  • read field constructs from netCDF and CDL datasets,

  • create new field constructs in memory,

  • write field constructs to netCDF datasets on disk,

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

  • read and write netCDF4 string data-type variables,

  • read, write, and create 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,

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

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

Note that the cfdm package enables the representation and creation of CF field constructs, but it is largely up to the user to use them in a CF-compliant way.

A command line tool is provided that allows inspection of datasets outside of a Python environment:

Inspect a dataset from the command line.
$ cfdump file.nc
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) = [0450-11-16 00:00:00, ..., 0451-10-16 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