Working with ODYSSEA data

ODYSSEA SST data can be considered from two feature perspectives :
  • GridTimeSeries
  • Grid

Using ODYSSEA data as GridTimeSeries

We can ignore the fact that each grid at each time step is stored in an individual file, by using a storage class aggregating all files altogether. Only the file pattern is to be provided to this class.

>>> import data.gridtimeteries
>>> import mapper.urlseries
>>>
>>> l4_pattern = '/home2/taveeg/data/operation/project/myocean/sst-tac/odyssea/v2/med/analysed_sst_002/%Y/%j/%Y%2m%2d-IFR-L4_GHRSST-SSTfnd-ODYSSEA-MED_002-v2.0-fv1.0.nc'
>>> odysseaFiles = mapper.urlseries.URLSeries( urlpattern=l4_pattern )
>>> odysseaTimeSeries = data.gridtimeseries.GridTimeSeries()
>>> odysseaTimeSeries.load( odysseaFiles )

Using ODYSSEA data as grid

If no temporal aspect is considered, and one wants to work on one or a few independant time steps, ODYSSEA data grids can be accessed directly.

>>> import datamodel.grid
>>> import mapper.ncfile
>>> ncf = mapper.ncfile.NCFile( URL = "/home2/taveeg/data/operation/project/myocean/sst-tac/odyssea/v2/med/analysed_sst_002/2011/260/20110917-IFR-L4_GHRSST-SSTfnd-ODYSSEA-MED_002-v2.0-fv1.0.nc" )
>>> g = datamodel.grid.Grid()
>>> g.load( ncf )

Displaying data

>>> g.display_map( 'analysed_sst', output='toto.png' )