updated rotate script

unit_tests/rotate_pts.py

 """
 Source: https://gist.github.com/LyleScott/d17e9d314fbe6fc29767d8c5c029c362
 
-Adapted Function to rotate NEMO grid for unit testing.
+Adapted Function to rotate NEMO grid for unit testing. rot variable defines how much rotation
+occurs, the results are then plotted in a figure showing original (blue points) and rotated (red) grids.
+The source coordinate grid is also plotted (green).
 
 """
-
 from math import cos,sin,radians
 import numpy as np
 import xarray as xr
@@ -12,19 +13,23 @@ import matplotlib.pyplot as plt
 import cartopy
 import cartopy.crs as ccrs
 
+# TODO: add in auto max and min lat and lon
+# TODO: remove hard coded file names and directories.
+
 def rotate_around_point(lat_in,lon_in, radians , origin=(0, 0)):
     """Rotate a point around a given point.
     """
+    # create empty lat and lon arrays that match input
     new_lon = np.zeros(np.shape(lon_in))
     new_lat = np.zeros(np.shape(lat_in))
-
+    # extract origin lat and lon as offset
     offset_lat, offset_lon = origin
     cos_rad = cos(radians)
     sin_rad = sin(radians)
-
+    # cycle through lat and lon arrays and calcule new lat and lon values based on rotation
+    # and origin values
     for indx in range(np.shape(lat_in)[0]):
         for indy in range(np.shape(lon_in)[1]):
-
             adjusted_lat = (lat_in[indx,indy] - offset_lat)
             adjusted_lon = (lon_in[indx,indy] - offset_lon)
             new_lat[indx,indy] = offset_lat + cos_rad * adjusted_lat + -sin_rad * adjusted_lon
@@ -34,6 +39,7 @@ def rotate_around_point(lat_in,lon_in, radians , origin=(0, 0)):
 
 def plot_grids(lat_in,lon_in,new_lat,new_lon,src_lat,src_lon):
 
+    # define lat and lon extents (define in future using input values?)
     maxlat = 72
     minlat = 32
     maxlon = 18
@@ -55,38 +61,41 @@ def plot_grids(lat_in,lon_in,new_lat,new_lon,src_lat,src_lon):
     ax1.add_feature(cartopy.feature.COASTLINE, zorder=10)  # add coastline polyline
     gl1 = ax1.gridlines(crs=ccrs.PlateCarree(), linewidth=2, color='black', alpha=0.5, linestyle='--', draw_labels=True)
 
+    # tile 1D lat and lon to 2D arrays for plotting (src lat and lon only)
     src_lon = np.tile(src_lon, (np.shape(src_lat)[0], 1))
     src_lat = np.tile(src_lat, (np.shape(src_lon)[1], 1))
     src_lat = np.rot90(src_lat)
 
+    # plot lat and lon for all grids
     ax.plot(lon_in, lat_in, color='blue', marker='.')
     ax.plot(src_lon,src_lat, color='green', marker='.')
     ax1.plot(new_lon,new_lat, color='red', marker='.')
     ax1.plot(src_lon,src_lat, color='green',marker='.')
+    # tweak margins of subplots as tight layout doesn't work
     plt.subplots_adjust(left=0.01, right=1, top=0.9, bottom=0.05,wspace=0.01)
 
     plt.show()
 
 
 def _main():
+    #open source (parent) and destination (child) grids
     ds = xr.open_dataset('unit_tests/test_data/dst_hgr_zps.nc')
     src = xr.open_dataset('unit_tests/test_data/src_coordinates.nc')
+    # set rotation and origin point
     rot = 45
     theta = radians(rot)
     origin = (54, -6)
+    # generate new lat and lon
     new_lat,new_lon = rotate_around_point(ds.nav_lat.values[:],ds.nav_lon.values[:],theta,origin)
+    # plot orginal, rotatated and source lat and lon
     plot_grids(ds.nav_lat.values[:],ds.nav_lon.values[:],new_lat,new_lon,src.latitude.values[:],src.longitude.values[:])
+    # save new lat lon to dataset
     ds.nav_lat.values[:], ds.nav_lon.values[:] = new_lat,new_lon
+    # save dataset to netcdf
     ds.to_netcdf('unit_tests/test_data/rot_'+str(rot)+'_dst_hgr_zps.nc')
+    # close data files
     ds.close()
     src.close()
 
-
-
-
-
-
-
-
 if __name__ == '__main__':
     _main()
\ No newline at end of file