def grid_error():
"""
Perform grid error study for routing given real weather.
Return a plot of the difference between results as a function
of grid error.
"""
tahiti = Location(-149.426, -17.651)
hawaii = Location(-157.92, 21.83)
fm = gen_env_model()
craft = tong_uncertain(1.0, 1.0, fm)
wind_fname = pp + "analysis/poly_data/data_dir/wind_forecast.nc"
waves_fname = pp + "analysis/poly_data/data_dir/wave_data.nc"
diagram_path = pp + "analysis/poly_data"
sd = datetime(1976, 5, 1, 0, 0)
dist, bearing = haversine(tahiti.long, tahiti.lat, hawaii.long,
hawaii.lat)
nodes = np.array([10])
times = []
h_vals = []
for count, node in enumerate(nodes):
node_distance = dist/node
r = Route(tahiti, hawaii, node, node,
node_distance*1000.0, craft)
x, y, land = return_co_ords(r.start.long, r.finish.long,
r.start.lat, r.finish.lat,
r.n_ranks, r.n_width, r.d_node)
tws, twd = process_wind(wind_fname, x, y)
wd, wh, wp = process_waves(waves_fname, x, y)
def run_single(n, d=30000):
"""Run multiple simulations for example scenario."""
start = Location(-14.0, 47.0)
finish = Location(-6.0, 47.0)
craft = return_boat_perf()
no_nodes = n
r = Route(start, finish, no_nodes, no_nodes, d, craft)
wind_fname = "/Users/thomasdickson/Documents/sail_routing/routing/domain_application/data_dir/wind_forecast.nc"
diagram_path = "/Users/thomasdickson/Documents/python_routing/analysis/output/multiple"
time = datetime(2014, 7, 1, 0, 0)
x, y, land = return_co_ords(r.start.long, r.finish.long, r.start.lat,
r.finish.lat, r.n_ranks, r.n_width, r.d_node)
jt, et, pf_vals = min_time_calculate(r, wind_fname, time, craft)
plot_route(time, r, x, y, et, jt, pf_vals,
diagram_path + "/single_route_%.0f_%.0f.png" % (n, d))
return jt, et, pf_vals
def run_simulation():
start = Location(-14.0, 47.0)
finish = Location(-6.0, 47.0)
craft = return_boat_perf()
no_nodes = 10
r = Route(start, finish, no_nodes, no_nodes, 30000.0, craft)
wind_fname = "/Users/thomasdickson/Documents/sail_routing/routing/domain_application/data_dir/wind_forecast.nc"
diagram_path = "/Users/thomasdickson/Documents/python_routing/analysis/output/multiple"
t = datetime(2014, 7, 1, 0, 0)
x, y, land = return_co_ords(r.start.long, r.finish.long, r.start.lat,
r.finish.lat, r.n_ranks, r.n_width, r.d_node)
jt, et, pf_vals = min_time_calculate(r, wind_fname, time, craft)
vt = datetime.fromtimestamp(jt) - t
print("Journey time is: ", vt)
plot_route(time, r, x, y, et, jt, pf_vals,
diagram_path + "/single_route.png")
def run_uncertain_performance_simulation():
"""Run routing simulations for a given day with uncertain performance."""
start = Location(-149.426, -17.651)
finish = Location(-157.92, 21.83)
start_date = datetime(1976, 5, 1, 0, 0)
n_nodes = 150
n_width = n_nodes
print("Nodes in rank: ", n_nodes)
print("Nodes in width: ", n_width)
dist, bearing = haversine(start.long, start.lat, finish.long, finish.lat)
node_distance = 2000 * dist / n_width
print("Node height distance is ", dist / n_nodes * 1000, " m")
print("Node width distance is ", node_distance, " m")
area = node_distance * dist / n_nodes * 1000
total_area = n_nodes * n_width * area
h = (1 / (n_nodes * n_width) * total_area)**0.5
print("h = {0} ".format(h))
pyroute_path = "/Users/thomasdickson/Documents/python_routing/"
wind_fname = pyroute_path + "analysis/poly_data/data_dir/finney_wind_forecast.nc"
waves_fname = pyroute_path + "analysis/poly_data/data_dir/finney_wave_data.nc"
dia_path = pyroute_path + "analysis/poly_data/finney_sims"
unc = np.linspace(0.95, 1.05, 3)
results = np.zeros_like(unc)
route_x = []
route_y = []
fm = gen_env_model()
for n, i in enumerate(unc):
craft = tong_uncertain(i, 1.0, fm)
r = Route(start, finish, n_nodes, n_width, node_distance, craft)
x, y, land = return_co_ords(r.start.long, r.finish.long, r.start.lat,
r.finish.lat, r.n_ranks, r.n_width,
r.d_node)
tws, twd = process_wind(wind_fname, x, y)
wd, wh, wp = process_waves(waves_fname, x, y)
jt, et, x_r, y_r = min_time_calculate(r, start_date, craft, x, y, land,
tws, twd, wd, wh, wp)
vt = datetime.fromtimestamp(jt) - start_date
results[n] = vt.total_seconds() / (60.0 * 60.0)
print(results[n] / 24)
route_x.append(x_r)
route_y.append(y_r)
plot_uncertainty(unc, results)
plt.savefig(dia_path + "/unc_vt_test_" + str(h) + ".png")
plot_uncertain_routes(start, r, x, y, unc, route_x, route_y, results)
plt.savefig(dia_path + "/unc_vt_routes_test_" + str(h) + ".png")
def run_simulation_over_days():
"""Run routing simulations between tahiti and marquesas."""
tahiti = Location(-149.426, -17.651)
hawaii = Location(-157.92, 21.83)
fm = gen_env_model()
craft = tong_uncertain(1.0, 1.0, fm)
n_nodes = 40
n_width = n_nodes
print("Nodes in rank: ", n_nodes)
print("Nodes in width: ", n_width)
dist, bearing = haversine(tahiti.long, tahiti.lat, hawaii.long,
hawaii.lat)
node_distance = 4000*dist/n_width
print("Node height distance is ", dist/n_nodes*1000, " m")
print("Node width distance is ", node_distance, " m")
area = node_distance*dist/n_nodes*1000
total_area = n_nodes * n_width * area
h = (1/(n_nodes * n_width) * total_area)**0.5
print("h = {0} ".format(h))
r = Route(tahiti, hawaii, n_nodes, n_width,
node_distance, craft)
wind_fname = pp + "analysis/poly_data/data_dir/finney_wind_forecast.nc"
waves_fname = pp + "analysis/poly_data/data_dir/finney_wave_data.nc"
dia_path = pp + "analysis/poly_data/finney_sims/"
sd = datetime(1976, 5, 1, 0, 0)
ed = datetime(1976, 5, 2, 0, 0)
dt = [d for d in datetime_range(sd, ed, {'days': 1, 'hours': 0})]
for t in dt:
x, y, land = return_co_ords(r.start.long, r.finish.long,
r.start.lat, r.finish.lat,
r.n_ranks, r.n_width, r.d_node)
tws, twd = process_wind(wind_fname, x, y)
wd, wh, wp = process_waves(waves_fname, x, y)
jt, et, x_r, y_r = min_time_calculate(r, t, craft,
x, y, land,
tws, twd, wd, wh, wp)
vt = datetime.fromtimestamp(jt) - t
print("Journey time is: ", vt)
fill = 10
string = str(t)+"_"+str(craft.apf)+"_"+str(craft.unc)+"_"+str(n_nodes)
plot_mt_route(t, r, x, y, x_r, y_r,
et, jt, fill,
dia_path+string+"_")
def reliability_uncertainty_routing():
"""Routing for a range of uncertainty and reliability levels."""
rel_levels = np.array([0.81, 0.91, 1.0])
unc_levels = np.array([0.95, 1.0, 1.05])
test_matrix = np.array(np.meshgrid(rel_levels,
unc_levels)).T.reshape(-1, 2)
fts = []
start = Location(-2.3700, 50.256)
finish = Location(-61.777, 17.038)
fm = gen_env_model()
craft = asv_uncertain(1.0, 1.0, fm)
weather_path = pp + "analysis/asv_transat/2016_jan_march.nc"
diagram_path = pp + "analysis/asv_transat/results/"
sd = datetime(2016, 1, 2, 6, 0)
dist, bearing = haversine(start.long, start.lat,
finish.long, finish.lat)
nodes = 60
node_distance = 4000*dist/nodes
r = Route(start, finish, nodes, nodes,
node_distance*1000.0, craft)
x, y, land = return_co_ords(r.start.long, r.finish.long,
r.start.lat, r.finish.lat,
r.n_ranks, r.n_width, r.d_node)
tws, twd, wd, wh, wp = process_era5_weather(weather_path, x, y)
for i in range(test_matrix.shape[0]):
craft = asv_uncertain(test_matrix[i, 1], test_matrix[i, 0], fm)
jt, et, x_r, y_r = min_time_calculate(r, sd, craft,
x, y, land,
tws, twd, wd, wh, wp)
vt = datetime.fromtimestamp(jt) - sd
fts.append(vt.total_seconds())
results = np.array(fts)
print(results)
save_array = np.hstack((test_matrix, results[..., None]))
print(save_array)
with open(diagram_path+"unc_reliability_routing_"+strftime("""%Y-%m-%d
%H:%M:%S""",
gmtime())+".txt",
'wb') as f:
np.savetxt(f, save_array, delimiter='\t', fmt='%1.3f')
def asv_grid_error():
"""
Check convergence of solution.
Using Maribot Vane performance estimates for the transatlantic voyage.
"""
start = Location(-2.3700, 50.256)
finish = Location(-61.777, 17.038)
fm = gen_env_model()
craft = asv_uncertain(1.0, 1.0, fm)
weather_path = pp + "analysis/asv_transat/2016_jan_march.nc"
diagram_path = pp + "analysis/asv_transat/results/"
sd = datetime(2016, 1, 1, 6, 0)
dist, bearing = haversine(start.long, start.lat,
finish.long, finish.lat)
nodes = np.array([640])
times = []
h_vals = []
for count, node in enumerate(nodes):
node_distance = 4000*dist/node
r = Route(start, finish, node, node,
node_distance*1000.0, craft)
x, y, land = return_co_ords(r.start.long, r.finish.long,
r.start.lat, r.finish.lat,
r.n_ranks, r.n_width, r.d_node)
tws, twd, wd, wh, wp = process_era5_weather(weather_path, x, y)
jt, et, x_r, y_r = min_time_calculate(r, sd, craft,
x, y, land,
tws, twd, wd, wh, wp)
vt = datetime.fromtimestamp(jt) - sd
print("Journey time is: ", vt)
h_vals.append(calc_h(node, node_distance**2))
vt = datetime.fromtimestamp(jt) - sd
print(h_vals[-1], " ", vt)
times.append(vt.total_seconds())
h_vals, times = np.array(h_vals), np.array(times)
with open(diagram_path+"asv_convergence_"+strftime("%Y-%m-%d %H:%M:%S",
gmtime())+".txt", 'wb') as f:
np.savetxt(f, np.c_[nodes, h_vals, times], delimiter='\t')
def run_simulation_over_days():
"""Run transat routing simulations."""
# Specify the bounds of the whole region
lon1 = -59.9
lat1 = -1.77
lon2 = -6.4
lat2 = 61.5
start = Location(-12.0, 45.0)
finish = Location(-60.0, 17.5)
fm = gen_env_model()
craft = asv_uncertain(1.0, 0.89, fm)
n_nodes = 40
n_width = n_nodes
print("Nodes in rank: ", n_nodes)
print("Nodes in width: ", n_width)
dist, bearing = haversine(start.long, start.lat,
finish.long, finish.lat)
node_distance = 4000*dist/n_width
print("Node height distance is ", dist/n_nodes*1000, " m")
print("Node width distance is ", node_distance, " m")
area = node_distance*dist/n_nodes*1000
total_area = n_nodes * n_width * area
h = (1/(n_nodes * n_width) * total_area)**0.5
print("h = {0} ".format(h))
r = Route(start, finish, n_nodes, n_width,
node_distance, craft)
weather_path = pp + "analysis/asv_transat/2016_jan_march.nc"
dia_path = pp + "analysis/asv_transat/results/"
sd = datetime(2008, 1, 2, 6, 0)
ed = datetime(2008, 1, 3, 6, 0)
dt = [d for d in datetime_range(sd, ed, {'days': 1, 'hours': 0})]
x, y, land = return_co_ords(r.start.long, r.finish.long,
r.start.lat, r.finish.lat,
r.n_ranks, r.n_width, r.d_node)
tws, twd, wd, wh, wp = process_era5_weather(weather_path, x, y)
tws = change_area_values(tws, 15.0, lon1, lat1, lon2, lat2)
twd = change_area_values(twd, 0.0, lon1, lat1, lon2, lat2)
wd = change_area_values(wd, 0.0, lon1, lat1, lon2, lat2)
wh = change_area_values(wh, 0.0, lon1, lat1, lon2, lat2)
a2 = 5.0
lon1_area2 = -40.0-a2
lon2_area2 = -40.0+a2
lat1_area2 = 33.0-a2
lat2_area2 = 33.0+a2
wh = change_area_values(wh, 4.0, lon1_area2, lat1_area2, lon2_area2,
lat2_area2)
a1 = 3.0
lon1_area1 = -40.0-a1
lon2_area1 = -40.0+a1
lat1_area1 = 33.0-a1
lat2_area1 = 33.0+a1
wd = change_area_values(wd, 240.0, lon1_area1, lat1_area1,
lon2_area1, lat2_area1)
for t in dt:
jt, et, x_r, y_r = min_time_calculate(r, t, craft,
x, y, land,
tws, twd, wd, wh, wp)
vt = datetime.fromtimestamp(jt) - t
print("Journey time is: ", vt)
fill = 10
string = str(t)+"_"+str(craft.apf)+"_"+str(craft.unc)+"_"+str(n_nodes)
plot_failure_route(t, r, x, y, x_r, y_r,
et, jt, fill,
dia_path+string+"_")
def failure_controlled_weather():
"""Load weather file for simulations."""
rel_levels = np.array([0.81, 0.95, 1.0])
unc_levels = np.array([1.0])
test_matrix = np.array(np.meshgrid(rel_levels,
unc_levels)).T.reshape(-1, 2)
fts = []
start = Location(-2.3700, 50.256)
finish = Location(-61.777, 17.038)
fm = gen_env_model()
craft = asv_uncertain(1.0, 1.0, fm)
weather_path = pp + "analysis/asv_transat/2016_jan_march.nc"
diagram_path = pp + "analysis/failure_model/"
sd = datetime(2008, 1, 2, 6, 0)
dist, bearing = haversine(start.long, start.lat, finish.long, finish.lat)
nodes = 20
node_distance = 4000 * dist / nodes
r = Route(start, finish, nodes, nodes, node_distance * 1000.0, craft)
x, y, land = return_co_ords(r.start.long, r.finish.long, r.start.lat,
r.finish.lat, r.n_ranks, r.n_width, r.d_node)
tws, twd, wd, wh, wp = process_era5_weather(weather_path, x, y)
# Alter the weather for the entire domain
lon1 = -59.9
lat1 = -1.77
lon2 = -6.4
lat2 = 61.5
tws = change_area_values(tws, 15.0, lon1, lat1, lon2, lat2)
twd = change_area_values(twd, 270.0, lon1, lat1, lon2, lat2)
# Alter the wave conditions
wd = change_area_values(wd, 90.0, lon1, lat1, lon2, lat2)
wh = change_area_values(wh, 0.0, lon1, lat1, lon2, lat2)
# # Alter the weather for the smaller area
a1 = 3.0
lon1_area1 = -40.0 - a1
lon2_area1 = -40.0 + a1
lat1_area1 = 33.0 - a1
lat2_area1 = 33.0 + a1
wd = change_area_values(wd, 180.0, lon1_area1, lat1_area1, lon2_area1,
lat2_area1)
a2 = 5.0
lon1_area2 = -40.0 - a2
lon2_area2 = -40.0 + a2
lat1_area2 = 33.0 - a2
lat2_area2 = 33.0 + a2
wh = change_area_values(wh, 4.0, lon1_area2, lat1_area2, lon2_area2,
lat2_area2)
for i in range(test_matrix.shape[0]):
craft = asv_uncertain(test_matrix[i, 1], test_matrix[i, 0], fm)
jt, et, x_r, y_r = min_time_calculate(r, sd, craft, x, y, land, tws,
twd, wd, wh, wp)
vt = datetime.fromtimestamp(jt) - sd
fts.append(vt.total_seconds())
results = np.array(fts)
print(results)
save_array = np.hstack((test_matrix, results[..., None]))
print(save_array)
with open(
diagram_path + "control_" +
strftime("""%Y-%m-%d %H:%M:%S""", gmtime()) + ".txt", 'wb') as f:
np.savetxt(f, save_array, delimiter='\t', fmt='%1.3f')