Extracted capsizing illustration from example_leeway to new example_l…

…eeway_capsizing

examples/example_leeway.py

@@ -22,30 +22,16 @@
 reader_norkyst = reader_netCDF_CF_generic.Reader(o.test_data_folder() +
     '16Nov2015_NorKyst_z_surface/norkyst800_subset_16Nov2015.nc')
 
-#%%
-# Adding readers successively, and specifying which variables they
-# shall provide. This way, order of adding readers does not matter
-o.add_reader(reader_norkyst,
-              variables=['x_sea_water_velocity', 'y_sea_water_velocity'])
-o.add_reader(reader_arome, variables=['x_wind', 'y_wind'])
+o.add_reader(reader_norkyst)
+o.add_reader(reader_arome)
 o.set_config('environment:fallback:x_sea_water_velocity', 0)
 o.set_config('environment:fallback:y_sea_water_velocity', 0)
 
-#%%
-# Activating capsizing for high winds, with probability per hour given by
-# p(windspeed) = 0.5 + 0.5*tanh((windspeed-wind_threshold)/sigma)
-o.set_config('capsizing', True)
-o.set_config('capsizing:wind_threshold', 30)
-o.set_config('capsizing:wind_threshold_sigma', 5)
-o.set_config('capsizing:leeway_fraction', 0.4)  # Reducing leeway coefficients to 40% of original after capsize
-
-o.plot_capsize_probability()
-
 #%%
 # Seed leeway elements at defined position and time
 object_type = 26  # 26 = Life-raft, no ballast
 o.seed_elements(lon=4.5, lat=59.6, radius=100, number=1000,
-                 time=reader_arome.start_time, object_type=object_type)
+                time=reader_arome.start_time, object_type=object_type)
 
 #%%
 # Running model
@@ -55,14 +41,6 @@
 # Print and plot results
 print(o)
 
-#%%
-# Animation illustrating effect of capsizing
-from matplotlib.colors import ListedColormap
-o.animation(color='capsized', cmap=ListedColormap(['black','red']), fast=True)
-
-#%%
-# .. image:: /gallery/animations/example_leeway_0.gif
-
 #%%
 # Animation with current as background.
 # Note that drift is also depending on wind, which is not shown.
@@ -71,7 +49,7 @@
              cmap=cmocean.cm.speed, vmin=0, vmax=.8, bgalpha=.7, land_color='#666666', fast=True)
 
 #%%
-# .. image:: /gallery/animations/example_leeway_1.gif
+# .. image:: /gallery/animations/example_leeway_0.gif
 
 o.plot(fast=True)
 
@@ -80,5 +58,5 @@
 d, dsub, dstr, lon, lat = o.get_density_array(pixelsize_m=3000)
 strand_density = xr.DataArray(dstr[-1,:,:], coords={'lon_bin': lon[0:-1], 'lat_bin': lat[0:-1]})
 o.plot(fast=True, background=strand_density.where(strand_density>0),
-        vmin=0, vmax=20, clabel='Density of stranded elements',
-        show_elements=False, linewidth=0)
+       vmin=0, vmax=20, cmap=cmocean.cm.dense, clabel='Density of stranded elements',
+       show_elements=False, linewidth=0)

examples/example_leeway_capsizing.py

@@ -0,0 +1,73 @@
+#!/usr/bin/env python
+"""
+Leeway capsizing
+==================================
+"""
+
+from datetime import timedelta
+import cmocean
+import xarray as xr
+from opendrift.readers import reader_netCDF_CF_generic
+from opendrift.models.leeway import Leeway
+
+o = Leeway(loglevel=0)  # Set loglevel to 0 for debug information
+
+# Atmospheric model for wind
+#reader_arome = reader_netCDF_CF_generic.Reader('https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc')
+reader_arome = reader_netCDF_CF_generic.Reader(o.test_data_folder() +
+    '16Nov2015_NorKyst_z_surface/arome_subset_16Nov2015.nc')
+
+# Ocean model for current
+#reader_norkyst = reader_netCDF_CF_generic.Reader('https://thredds.met.no/thredds/dodsC/mepslatest/meps_lagged_6_h_latest_2_5km_latest.nc')
+reader_norkyst = reader_netCDF_CF_generic.Reader(o.test_data_folder() +
+    '16Nov2015_NorKyst_z_surface/norkyst800_subset_16Nov2015.nc')
+
+o.add_reader(reader_norkyst)
+o.add_reader(reader_arome)
+
+#%%
+# Activating capsizing for high winds, with probability per hour given by
+# p(windspeed) = 0.5 + 0.5*tanh((windspeed-wind_threshold)/sigma)
+o.set_config('capsizing', True)
+o.set_config('capsizing:wind_threshold', 30)
+o.set_config('capsizing:wind_threshold_sigma', 5)
+o.set_config('capsizing:leeway_fraction', 0.4)  # Reducing leeway coefficients to 40% of original after capsize
+
+o.plot_capsize_probability()
+
+#%%
+# Seed leeway elements at defined position and time
+object_type = 26  # 26 = Life-raft, no ballast
+o.seed_elements(lon=4.5, lat=59.6, radius=100, number=1000,
+                 time=reader_arome.start_time, object_type=object_type)
+
+#%%
+# Running model
+o.run(duration=timedelta(hours=48), time_step=900, time_step_output=3600)
+
+#%%
+# Print and plot results
+print(o)
+
+#%%
+# Animation illustrating effect of capsizing
+from matplotlib.colors import ListedColormap
+o.animation(color='capsized', cmap=ListedColormap(['black','red']), fast=True)
+
+#%%
+# .. image:: /gallery/animations/example_leeway_capsizing_0.gif
+
+#%%
+# Reverse run, also with probability of (un)-capsizing
+o = Leeway()
+o.add_reader(reader_norkyst)
+o.add_reader(reader_arome)
+o.set_config('capsizing', True)
+o.seed_elements(lon=4.4, lat=61.0, radius=100, number=1000,
+                capsized=1,  # now we seed all objects as already capsized
+                time=reader_arome.end_time, object_type=object_type)
+o.run(time_step=-900, duration=timedelta(hours=48), time_step_output=timedelta(hours=1))
+o.animation(color='capsized', cmap=ListedColormap(['black','red']), fast=True)
+
+#%%
+# .. image:: /gallery/animations/example_leeway_capsizing_1.gif