diff --git a/unit_tests/coord_gen.py b/unit_tests/gen_tools.py
similarity index 80%
rename from unit_tests/coord_gen.py
rename to unit_tests/gen_tools.py
index c05e3bf082d6bce6e4e57a7dcd4c8b3fc45fa8b9..ea41ff989d8db6832e801e417eb2babe2f981700 100644
--- a/unit_tests/coord_gen.py
+++ b/unit_tests/gen_tools.py
@@ -9,6 +9,13 @@ example grid set up
import numpy as np
from netCDF4 import Dataset
+from math import cos,sin,radians
+import numpy as np
+#import xarray as xr
+import matplotlib.pyplot as plt
+from math import radians
+#import cartopy
+#import cartopy.crs as ccrs
def set_hgrid(dx, dy, jpi, jpj, zoffx=0, zoffy=0,sf=1):
if sf > 1:
@@ -24,10 +31,6 @@ def set_hgrid(dx, dy, jpi, jpj, zoffx=0, zoffy=0,sf=1):
lonf = np.zeros((jpi, jpj))
latf = np.zeros((jpi, jpj))
-
-
-
-
for i in range(0, jpi):
lont[i, :] = zoffx * dx * 1.e-3 + dx * 1.e-3 * np.float(i)
lonu[i, :] = zoffx * dx * 1.e-3 + dx * 1.e-3 * (np.float(i) + 0.5)
@@ -382,3 +385,68 @@ def write_domcfg(fileout, ln_zco, ln_zps, ln_sco, ln_isfcav, jperio, bat,
# Close off pointer
dataset.close()
+
+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
+ new_lon[indx,indy] = offset_lon + sin_rad * adjusted_lat + cos_rad * adjusted_lon
+
+ return new_lat, new_lon
+
+def plot_grids(lat_in,lon_in,new_lat,new_lon,off_lat,off_lon,src_lat,src_lon):
+
+ # define lat and lon extents (define in future using input values?)
+ #maxlat = 72
+ #minlat = 32
+ #maxlon = 18
+ #minlon = -28
+
+ plt.figure(figsize=[18, 18]) # a new figure window
+
+ ax = plt.subplot(221)#, projection=ccrs.PlateCarree()) # specify (nrows, ncols, axnum)
+ #ax.set_extent([minlon,maxlon,minlat,maxlat],crs=ccrs.PlateCarree()) #set extent
+ #ax.set_title('Original Grid', fontsize=20,y=1.05) #set title
+ #ax.add_feature(cartopy.feature.LAND, zorder=0) # add land polygon
+ #ax.add_feature(cartopy.feature.COASTLINE, zorder=10) # add coastline polyline
+ #gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=2, color='black', alpha=0.5, linestyle='--', draw_labels=True)
+
+ ax1 = plt.subplot(222)#, projection=ccrs.PlateCarree()) # specify (nrows, ncols, axnum)
+ #ax1.set_extent([minlon,maxlon,minlat,maxlat],crs=ccrs.PlateCarree()) #set extent
+ #ax1.set_title('Rotated Grid', fontsize=20,y=1.05) #set title
+ #ax1.add_feature(cartopy.feature.LAND, zorder=0) # add land polygon
+ #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)
+
+ ax2 = plt.subplot(223)
+ ax3 = plt.subplot(224)
+
+ # plot lat and lon for all grids
+ ax.plot(lon_in, lat_in, color='blue', marker='.', linestyle="")
+ ax.plot(src_lon,src_lat, color='green', marker='o', linestyle="")
+ ax1.plot(new_lon,new_lat, color='red', marker='.', linestyle="")
+ ax1.plot(src_lon,src_lat, color='green',marker='o',linestyle="")
+ ax2.plot(off_lon,off_lat, color='yellow',marker='.',linestyle="")
+ ax2.plot(src_lon, src_lat, color='green', marker='o', linestyle="")
+ # 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()
\ No newline at end of file
diff --git a/unit_tests/rotate_pts.py b/unit_tests/rotate_pts.py
deleted file mode 100644
index c2a529336b4b5774da13d543d9d9cb21c6efdd25..0000000000000000000000000000000000000000
--- a/unit_tests/rotate_pts.py
+++ /dev/null
@@ -1,170 +0,0 @@
-"""
-Source: https://gist.github.com/LyleScott/d17e9d314fbe6fc29767d8c5c029c362
-
-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
-import matplotlib.pyplot as plt
-import cartopy
-import cartopy.crs as ccrs
-
-import unit_tests.coord_gen as cg
-
-# 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
- new_lon[indx,indy] = offset_lon + sin_rad * adjusted_lat + cos_rad * adjusted_lon
-
- return new_lat, new_lon
-
-def plot_grids(lat_in,lon_in,new_lat,new_lon,off_lat,off_lon,src_lat,src_lon):
-
- # define lat and lon extents (define in future using input values?)
- #maxlat = 72
- #minlat = 32
- #maxlon = 18
- #minlon = -28
-
- plt.figure(figsize=[18, 18]) # a new figure window
-
- ax = plt.subplot(221)#, projection=ccrs.PlateCarree()) # specify (nrows, ncols, axnum)
- #ax.set_extent([minlon,maxlon,minlat,maxlat],crs=ccrs.PlateCarree()) #set extent
- #ax.set_title('Original Grid', fontsize=20,y=1.05) #set title
- #ax.add_feature(cartopy.feature.LAND, zorder=0) # add land polygon
- #ax.add_feature(cartopy.feature.COASTLINE, zorder=10) # add coastline polyline
- #gl = ax.gridlines(crs=ccrs.PlateCarree(), linewidth=2, color='black', alpha=0.5, linestyle='--', draw_labels=True)
-
- ax1 = plt.subplot(222)#, projection=ccrs.PlateCarree()) # specify (nrows, ncols, axnum)
- #ax1.set_extent([minlon,maxlon,minlat,maxlat],crs=ccrs.PlateCarree()) #set extent
- #ax1.set_title('Rotated Grid', fontsize=20,y=1.05) #set title
- #ax1.add_feature(cartopy.feature.LAND, zorder=0) # add land polygon
- #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)
-
- ax2 = plt.subplot(223)
- ax3 = plt.subplot(224)
-
- # plot lat and lon for all grids
- ax.plot(lon_in, lat_in, color='blue', marker='.', linestyle="")
- ax.plot(src_lon,src_lat, color='green', marker='o', linestyle="")
- ax1.plot(new_lon,new_lat, color='red', marker='.', linestyle="")
- ax1.plot(src_lon,src_lat, color='green',marker='o',linestyle="")
- ax2.plot(off_lon,off_lat, color='yellow',marker='.',linestyle="")
- ax2.plot(src_lon, src_lat, color='green', marker='o', linestyle="")
- # 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():
- #Source Coords
- dx = 1000 # units in km
- dy = 1000 # units in Km
- jpi = 15
- jpj = 15
- jpk = 10
- max_dep = 100
- min_dep = 10
- z_end_dim = 1
- h_fname = 'unit_tests/test_data/test_src__hgr_zps.nc'
- z_fname = 'unit_tests/test_data/test_src_zgr_zps.nc'
- grid_h1 = cg.set_hgrid(dx,dy,jpi,jpj)
- grid_z1 = cg.set_zgrid(grid_h1,jpk,max_dep,min_dep,z_end_dim)
- write_coord_H = cg.write_coord_H(h_fname,grid_h1)
- write_coord_Z = cg.write_coord_Z(z_fname,grid_h1,grid_z1)
- if write_coord_H + write_coord_Z == 0:
- print("Success!")
-
- #Dst Coords
- dx = 100 # units in km
- dy = 100 # units in Km
- jpi = 100
- jpj = 100
- zoffx = 20
- zoffy = 20
- jpk = 10
- max_dep = 100
- min_dep = 10
- z_end_dim = 1
- sf = 10
- h_fname = 'unit_tests/test_data/test_dst_hgr_zps.nc'
- z_fname = 'unit_tests/test_data/test_dst_zgr_zps.nc'
- grid_h2 = cg.set_hgrid(dx,dy,jpi,jpj,zoffx,zoffy,sf)
- grid_z2 = cg.set_zgrid(grid_h2,jpk,max_dep,min_dep,z_end_dim)
- write_coord_H = cg.write_coord_H(h_fname,grid_h2)
- write_coord_Z = cg.write_coord_Z(z_fname,grid_h2,grid_z2)
- if write_coord_H + write_coord_Z == 0:
- print("Success!")
-
- # set rotation and origin point
- rot = 45
- theta = radians(rot)
- origin = (7,7)
-
-
- rot_lat,rot_lon = rotate_around_point(grid_h2['latt'],grid_h2['lont'],theta,origin)
-
- #offset coords
- dx = 100 # units in km
- dy = 100 # units in Km
- jpi = 100
- jpj = 100
- zoffx = 25
- zoffy = 25
- jpk = 10
- max_dep = 100
- min_dep = 10
- z_end_dim = 1
- sf = 10
- h_fname = 'unit_tests/test_data/test_dst_offset_hgr_zps.nc'
- z_fname = 'unit_tests/test_data/test_dst_offset_zgr_zps.nc'
- grid_h3 = cg.set_hgrid(dx,dy,jpi,jpj,zoffx,zoffy,sf)
- grid_z3 = cg.set_zgrid(grid_h2,jpk,max_dep,min_dep,z_end_dim)
- write_coord_H = cg.write_coord_H(h_fname,grid_h3)
- write_coord_Z = cg.write_coord_Z(z_fname,grid_h3,grid_z3)
- if write_coord_H + write_coord_Z == 0:
- print("Success!")
-
-
- # plot orginal, rotatated and source lat and lon
- plot_grids(grid_h2['latt'],grid_h2['lont'],rot_lat,rot_lon,grid_h3['latt'], \
- grid_h3['lont'],grid_h1['latt'],grid_h1['lont'])
- # 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
diff --git a/unit_tests/test_gen.py b/unit_tests/test_gen.py
new file mode 100644
index 0000000000000000000000000000000000000000..9582100cf7acdcb5fd7e6e03e7908afbe6e336fb
--- /dev/null
+++ b/unit_tests/test_gen.py
@@ -0,0 +1,106 @@
+"""
+Source: https://gist.github.com/LyleScott/d17e9d314fbe6fc29767d8c5c029c362
+
+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).
+
+"""
+import unit_tests.gen_tools as gt
+
+# TODO: remove hard coded file names and directories.
+# TODO: organise the variables better, (maybe in a single dict?)
+
+def _main():
+ #Source Coords
+ dx = 1000 # units in km
+ dy = 1000 # units in Km
+ jpi = 15
+ jpj = 15
+ jpk = 10
+ max_dep = 100
+ min_dep = 10
+ z_end_dim = 1
+ h_fname = 'unit_tests/test_data/test_src_hgr_zps.nc'
+ z_fname = 'unit_tests/test_data/test_src_zgr_zps.nc'
+ grid_h1 = gt.set_hgrid(dx,dy,jpi,jpj)
+ grid_z1 = gt.set_zgrid(grid_h1,jpk,max_dep,min_dep,z_end_dim)
+ write_coord_H = gt.write_coord_H(h_fname,grid_h1)
+ write_coord_Z = gt.write_coord_Z(z_fname,grid_h1,grid_z1)
+ if write_coord_H + write_coord_Z == 0:
+ print("Success!")
+
+ #Dst Coords
+ dx = 100 # units in km
+ dy = 100 # units in Km
+ jpi = 100
+ jpj = 100
+ zoffx = 20
+ zoffy = 20
+ jpk = 10
+ max_dep = 100
+ min_dep = 10
+ z_end_dim = 1
+ sf = 10
+ h_fname = 'unit_tests/test_data/test_dst_hgr_zps.nc'
+ z_fname = 'unit_tests/test_data/test_dst_zgr_zps.nc'
+ grid_h2 = gt.set_hgrid(dx,dy,jpi,jpj,zoffx,zoffy,sf)
+ grid_z2 = gt.set_zgrid(grid_h2,jpk,max_dep,min_dep,z_end_dim)
+ write_coord_H = gt.write_coord_H(h_fname,grid_h2)
+ write_coord_Z = gt.write_coord_Z(z_fname,grid_h2,grid_z2)
+ if write_coord_H + write_coord_Z == 0:
+ print("Success!")
+
+ # set rotation and origin point
+ rot = 45
+ theta = gt.radians(rot)
+ origin = (7,7)
+
+ # rotate grid
+ rot_h_fname = 'unit_tests/test_data/test_rot_dst_hgr_zps.nc'
+ rot_z_fname = 'unit_tests/test_data/test_rot_dst_zgr_zps.nc'
+ grid_rot = grid_h2.copy()
+ grid_rot['latt'], grid_rot['lont'] = gt.rotate_around_point(grid_h2['latt'],grid_h2['lont'],theta,origin)
+ grid_rot['latu'], grid_rot['lonu'] = gt.rotate_around_point(grid_h2['latu'], grid_h2['lonu'], theta, origin)
+ grid_rot['latv'], grid_rot['lonv'] = gt.rotate_around_point(grid_h2['latv'], grid_h2['lonv'], theta, origin)
+ grid_rot['latf'], grid_rot['lonf'] = gt.rotate_around_point(grid_h2['latf'], grid_h2['lonf'], theta, origin)
+ write_coord_H = gt.write_coord_H(rot_h_fname,grid_rot)
+ write_coord_Z = gt.write_coord_Z(rot_z_fname,grid_rot,grid_z2)
+ if write_coord_H + write_coord_Z == 0:
+ print("Success!")
+
+ # offset grid
+ dx = 100 # units in km
+ dy = 100 # units in Km
+ jpi = 100
+ jpj = 100
+ zoffx = 25
+ zoffy = 25
+ jpk = 10
+ max_dep = 100
+ min_dep = 10
+ z_end_dim = 1
+ sf = 10
+ h_fname = 'unit_tests/test_data/test_dst_offset_hgr_zps.nc'
+ z_fname = 'unit_tests/test_data/test_dst_offset_zgr_zps.nc'
+ grid_h3 = gt.set_hgrid(dx,dy,jpi,jpj,zoffx,zoffy,sf)
+ grid_z3 = gt.set_zgrid(grid_h2,jpk,max_dep,min_dep,z_end_dim)
+ write_coord_H = gt.write_coord_H(h_fname,grid_h3)
+ write_coord_Z = gt.write_coord_Z(z_fname,grid_h3,grid_z3)
+ if write_coord_H + write_coord_Z == 0:
+ print("Success!")
+
+
+ # plot orginal, rotatated and source lat and lon
+ gt.plot_grids(grid_h2['latt'],grid_h2['lont'],grid_rot['latt'],grid_rot['lont'],grid_h3['latt'], \
+ grid_h3['lont'],grid_h1['latt'],grid_h1['lont'])
+ # 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