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numpy array with grids and associated operations

Project description

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 = = 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'  # 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 grid differs


  • 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:


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”.


  • Issue Tracker:
  • Source Code:


If you are having issues, please let us know.


The project is licensed under the BSD license.

Project details

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