Merge pull request #26 from ECCO-GROUP/lat-lon2

copying existing tutorial building interpolation from scratch

Author: ifenty

Tutorials_as_Jupyter_Notebooks/ECCO_v4_Interpolating_Fields_to_LatLon_Grid.ipynb

@@ -229,7 +229,7 @@
     "\n",
     "Under the hood of ``plot_proj_to_lat_longrid`` is a call to the very useful routine ``resample_to_latlon`` which is the now described in more detail\n",
     "\n",
-    "## ``resample_to_latlon``\n",
+    "## resample_to_latlon\n",
     "\n",
     "``resample_to_latlon`` takes a field with a cooresponding set of lat lon coordinates (the *source* grid) and interpolates to a new lat-lon *target* grid.  The arrangement of coordinates in the *source* grid is arbitrary. One also provides the $bounds$ of the new lat lon grid.  The example shown above uses -90..90N and -180..180E by default.  In addition, one specifies which interpolation scheme to use (*mapping method*) and the *radius of influence*, the radius around the *target* grid cells within which to search for values from the *source* grid.   "
    ]
@@ -1510,7 +1510,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Saving = easy with xarray\n"
+    "### Saving is easy with xarray\n"
    ]
   },
   {

Tutorials_as_Jupyter_Notebooks/ECCO_v4_Interpolating_to_latlon.ipynb

@@ -0,0 +1 @@
+../Tutorials_as_Jupyter_Notebooks/ECCO_v4_Interpolating_to_latlon.ipynb

doc/ECCO_v4_Interpolating_to_latlon.ipynb

@@ -47,7 +47,7 @@ The `ecco_v4_py`_ package used in this tutorial was inspired by the `xmitgcm`_ p
    ECCO_v4_Loading_LLC_compact_binary_files.ipynb
    ECCO_v4_Combining_Multiple_Datasets.ipynb
    ECCO_v4_Saving_Datasets_and_DataArrays_to_NetCDF.ipynb
-   ECCO_v4_Interpolating_Fields_to_LatLon_Grid.ipynb
+   ECCO_v4_Interpolating_to_latlon.ipynb
 
 .. toctree::
    :maxdepth: 2