import matplotlib.pylab as plt import numpy as np import sys import xarray as xr from copy import deepcopy import ecco_v4_py as ecco # ### 'c' point: ``SSH`` # In[2]: data_dir = '/Volumes/ECCO_BASE/ECCO_v4r3/nctiles_monthly/SSH/' var = 'SSH' var_type = 'c' ssh_all_tiles = ecco.load_all_tiles_from_netcdf(data_dir, var, var_type) ecco.minimal_metadata(ssh_all_tiles) # ### 'u' point: ``ADVxSNOW`` # # ``ADVxSNOW`` is the horizontal advective flux of snow in each tile's $x$ direction. # In[3]: data_dir = '/Volumes/ECCO_BASE/ECCO_v4r3/nctiles_monthly/ADVxSNOW/' var = 'ADVxSNOW' var_type = 'u' advxsnow_all_tiles = ecco.load_all_tiles_from_netcdf(data_dir, var, var_type) ecco.minimal_metadata(advxsnow_all_tiles) # ### 'v' point: ``ADVySNOW`` #
# # Let's load tile 3 of the 'u' point horizontal velocity in the local $x$ direction variable, ``UVEL``. # In[12]: data_dir = '/Volumes/ECCO_BASE/ECCO_v4r3/nctiles_monthly/UVEL/' var = 'UVEL' var_type = 'u' tile_index = 3 uvel_tile_3 = ecco.load_tile_from_netcdf(data_dir, var, var_type, tile_index) # Let's look at `uvel_tile_3`. This time let's also remove some of the descriptive NetCDF file *Attributes* using a little routine called `minimal_metadata`. We've already seen these attributes a number of times. # In[13]: ecco.minimal_metadata(uvel_tile_3) # In[14]: uvel_tile_3 # `uvel_tile_3` has one *Data variable*, ``UVEL``. Let's take a look at the ``UVEL`` `DataArary`: # In[15]: uvel_tile_3.UVEL # #### Dimensional coordinates # As expected, ``UVEL`` uses the **i_g, j** coordinates for its horizontal dimensions. Unlike ``SSH``, ``UVEL`` has three-dimensions in space so we find a **k** coordinate. The ordering of the three-dimensional ECCO v4 output is **time, tile, k, j, i**. # # #### Non-dimensional coordinates
import ecco_v4_py as ecco import warnings warnings.filterwarnings('ignore') get_ipython().magic(u'pylab inline') pylab.rcParams['figure.figsize'] = (10, 6) # In[2]: data_dir='/Volumes/ECCO_BASE/ECCO_v4r3/nctiles_monthly/SSH/' var = 'SSH' var_type = 'c' ssh_all_tiles = ecco.load_all_tiles_from_netcdf(data_dir, var, var_type) ecco.minimal_metadata(ssh_all_tiles) # In[3]: ssh_all_tiles # Now we'll use the two methods to access the ``SSH`` `DataArray`, # In[4]: ssh_A = ssh_all_tiles.SSH ssh_B = ssh_all_tiles['SSH']