Merge branch 'tpxo_velocities' into 'master'

tpxo: flag to get tidal velocity instead of transport

See merge request !98

dgpy/scripts/slimPre.py

@@ -532,14 +532,11 @@ def read_temporal_serie(file_name, time=None, output_netcdf=None):
             write_file(output_netcdf[0], region=None, time=time, data=[(output_netcdf[1], valVec)])
         return (time, valVec)
 
-    
-
-
-def tpxo_tide(region, time, data_file_name=None): 
+def tpxo_tide(region, time, data_file_name=None, export_as_transport=True):
     """Give TPXO tides data
     
     This function will download the files tpxo and generate the data at the requested time steps.
-    It will return the tpxo tides as variables (ssh, ssu, ssv)
+    It will return the tpxo tides as variables (ssh, u, v) with u and v as transport (default) or velocity
     
     keyword arguments:
     
@@ -549,6 +546,8 @@ def tpxo_tide(region, time, data_file_name=None):
         Time object of the instant at which put the data
     * data_file_name
         name of the netcdf data file where tides are exported (optional)
+    * export_transport
+        flag to specify whether exports are water transport [m^2/s] (True) or velocity [m/s] (False) (default: True)
     """
     lonlat = Coordinate_system(region, data_proj='+proj=latlong +ellps=WGS84')
     h = u = v = np.empty((1,1))
@@ -557,8 +556,11 @@ def tpxo_tide(region, time, data_file_name=None):
     h_file_name = slim_private.dgftp.get( ("/slim_data/tides/%s" % h_file_name) )
     u_file_name = slim_private.dgftp.get( ("/slim_data/tides/%s" % u_file_name) )
     tide_ssh = dgpy.slimFunctionTpxo(h_file_name,'ha','hp','lon_z','lat_z')
-    tide_u = dgpy.slimFunctionTpxo(u_file_name,'Ua','up','lon_u','lat_u')
-    tide_v = dgpy.slimFunctionTpxo(u_file_name,'Va','vp','lon_v','lat_v')
+    varUtpxo = 'Ua' if export_as_transport else 'ua'
+    varVtpxo = 'Va' if export_as_transport else 'va'
+    factor = 1 if export_as_transport else 0.01   # from cm/s to m/s for velocities
+    tide_u = dgpy.slimFunctionTpxo(u_file_name,varUtpxo,'up','lon_u','lat_u')
+    tide_v = dgpy.slimFunctionTpxo(u_file_name,varVtpxo,'vp','lon_v','lat_v')
     if not region._empty:
         lonlat_coordinates = lonlat.coordinates * 180 / np.pi
         n = np.size(time._time)
@@ -569,8 +571,8 @@ def tpxo_tide(region, time, data_file_name=None):
         v = np.empty((n,m))
         for i in range(n):
             h[i,:] = tide_ssh.getAtPoints(lonlat_coordinates, time._time[i])[:,0]
-            u[i,:] = tide_u.getAtPoints(lonlat_coordinates, time._time[i])[:,0]
-            v[i,:] = tide_v.getAtPoints(lonlat_coordinates, time._time[i])[:,0]
+            u[i,:] = factor*np.array(tide_u.getAtPoints(lonlat_coordinates, time._time[i]))[:,0]
+            v[i,:] = factor*np.array(tide_v.getAtPoints(lonlat_coordinates, time._time[i]))[:,0]
 
         (u, v) = lonlat.rotate(u,v)