spacegrids 1.9

Spacegrids is an open source library providing a Numpy array with grids, labelled axes and associated grid-related mathematical methods such as regridding and integration. Spacegrids provides an object data model of Netcdf data that ensures consistency between a Numpy data array and its grid under common operations (and so avoiding common pitfalls related to axis interpretation), and much more. It is a write less do more library for everyday use.

These interactive plots from Netcdf data are based on Spacegrids.

The Field, Gr (grid) and Coord objects make everyday use easy:

>>> import spacegrids as sg
>>> D = sg.info(nonick = True)
>>> P = sgPproject(D['my_project'] , nonick = True)
>>> P.load(['temperature','u'])
>>> # obtain the axes objects under their names T,X,Y,Z:
>>> for c in P['some_experiment'].axes:
>>>   exec c.name + ' = c'  # now we can refer to X,Y
>>> TEMP = P['some_experiment']['temperature']
>>> U = P['some_experiment']['u'] # zonal velocity
>>> TEMP_sliced = TEMP[Y,:50] # slice. Note Y axis object
>>> m_TEMP = TEMP_sliced/(X*Y) # take hor. mean
>>> TEMP_regridded = TEMP.regrid(U.gr)  # U grid differs

Features

• A numpy array with grid allowing automatic alignment and dimension broadcasting
• Easy to use and intuitive regridding functionality
• A data object model corresponding closely to Netcdf
• Easier IO via abstraction of IO with multiple Netcdf files
• Makes working with output of many experiments easy via aggregation methods
• The Field class eliminates errors arising from picking the wrong array index
• Quicker plotting due to automatic labels, axes etc.
• Distance-related methods such as spatial differentiation and integration on sphere
• Extensive unit tests and documentation

There is lots of documentation, both in the source code and elsewhere. Other documentation can be found at:

• a practical tutorial
• a more advanced tutorial
• an overview of all classes, methods and functions
• interactive Netcdf data plots based on Spacegrids

Installation

Install spacegrids simply by running (on command line):

pip install spacegrids

Dependencies: numpy, scipy, matplotlib (NetCDF4 optional). On Ubuntu/ Debian, install dependencies via package manager if pip install fails:

apt-get install python-{tk,numpy,matplotlib,scipy}

On Mac, pip can be installed via “sudo easy_install pip”.

Contribute

• Issue Tracker: github.com/willo12/spacegrids/issues
• Source Code: github.com/willo12/spacegrids

Support

If you are having issues, please let us know.

License

The project is licensed under the BSD license.