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 = 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:
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.
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