sde = SedDepEroder(mg, input_file)
# don't allow overwriting of these, just in case
try:
x_profiles
except NameError:
x_profiles = []
z_profiles = []
S_profiles = []
A_profiles = []
# plot init conds
if make_output_plots:
mg = fr.route_flow(grid=mg)
pylab.figure('long_profile_anim')
ylim([0, y_max])
prf.analyze_channel_network_and_plot(mg)
savefig('0profile_anim_init.png')
close('long_profile_anim')
(profile_IDs, dists_upstr) = prf.analyze_channel_network_and_plot(mg)
start_node = [profile_IDs[0]]
time_on = time()
#perform the loops:
for i in range(nt):
#print 'loop ', i
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
mg = fr.run_one_step()
#mg.calc_grad_across_cell_faces(mg.at_node['topographic__elevation'])
#neighbor_slopes = mg.calc_grad_along_node_links(mg.at_node['topographic__elevation'])
#mean_slope = np.mean(np.fabs(neighbor_slopes),axis=1)
sde = SedDepEroder(mg, input_file)
# don't allow overwriting of these, just in case
try:
x_profiles
except NameError:
x_profiles = []
z_profiles = []
S_profiles = []
A_profiles = []
# plot init conds
if make_output_plots:
mg = fr.route_flow(grid=mg)
pylab.figure('long_profile_anim')
ylim([0, y_max])
prf.analyze_channel_network_and_plot(mg)
savefig('0profile_anim_init.png')
close('long_profile_anim')
(profile_IDs, dists_upstr) = prf.analyze_channel_network_and_plot(mg)
start_node = [profile_IDs[0]]
time_on = time()
#perform the loops:
for i in range(nt):
#print 'loop ', i
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift_per_step
mg = fr.run_one_step()
#mg.calc_grad_across_cell_faces(mg.at_node['topographic__elevation'])
#neighbor_slopes = mg.calc_grad_along_node_links(mg.at_node['topographic__elevation'])
#mean_slope = np.mean(np.fabs(neighbor_slopes),axis=1)
print("Short step!")
dt = time_to_run - elapsed_time
mg = fr.route_flow(method='D8')
#print 'Area: ', numpy.max(mg.at_node['drainage_area'])
#mg = fsp.erode(mg)
mg, _, _ = sp.erode(mg,
dt,
node_drainage_areas='drainage_area',
slopes_at_nodes='topographic__steepest_slope',
K_if_used='K_values')
#add uplift
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift * dt
elapsed_time += dt
if counter % 20 == 0:
pylab.figure('profiles')
profiles = prf.analyze_channel_network_and_plot(mg)
counter += 1
time_off = time.time()
print('Elapsed time: ', time_off - time_on)
time_off = time.time()
print('Elapsed time: ', time_off - time_on)
#Finalize and plot
elev = mg['node']['topographic__elevation']
elev_r = mg.node_vector_to_raster(elev)
# Clear previous plots
pylab.figure(1)
pylab.close()
def run_one_step(self):
""" """
# find the faulted node with the largest drainage area.
largest_da = np.max(self._model.grid.at_node['drainage_area'][
self._model.boundary_handler['NormalFault'].faulted_nodes == True])
largest_da_ind = np.where(
self._model.grid.at_node['drainage_area'] == largest_da)[0][0]
start_node = self._model.grid.at_node['flow__receiver_node'][
largest_da_ind]
(profile_IDs, dists_upstr) = analyze_channel_network_and_plot(
self._model.grid,
number_of_channels=1,
starting_nodes=[start_node],
create_plot=False)
elevs = model.z[profile_IDs]
self.relative_times.append(self._model.model_time /
model.params['run_duration'])
offset = np.min(elevs[0])
max_distance = np.max(dists_upstr[0][0])
self.channel_segments.append(
np.array((dists_upstr[0][0], elevs[0] - offset)).T)
self.xnormalized_segments.append(
np.array((dists_upstr[0][0] / max_distance, elevs[0] - offset)).T)
self.relative_times.append(self._model.model_time /
model.params['run_duration'])
colors = cm.viridis_r(self.relative_times)
xmin = [xy.min(axis=0)[0] for xy in self.channel_segments]
ymin = [xy.min(axis=0)[1] for xy in self.channel_segments]
xmax = [xy.max(axis=0)[0] for xy in self.channel_segments]
ymax = [xy.max(axis=0)[1] for xy in self.channel_segments]
fs = (8, 6)
fig, ax = plt.subplots(figsize=fs, dpi=300)
ax.set_xlim(0, max(xmax))
ax.set_ylim(0, max(ymax))
line_segments = LineCollection(self.channel_segments,
colors=colors,
linewidth=0.5)
ax.add_collection(line_segments)
yr = str(self._model.model_time / (1e6)).zfill(4)
plt.savefig('profile_' + yr + '.png')
plt.close()
fig, ax = plt.subplots(figsize=fs, dpi=300)
ax.set_xlim(0, 1)
ax.set_ylim(0, max(ymax))
line_segments = LineCollection(self.xnormalized_segments,
colors=colors,
linewidth=0.5)
ax.add_collection(line_segments)
yr = str(self._model.model_time / (1e6)).zfill(4)
plt.savefig('normalized_profile_' + yr + '.png')
plt.close()
plt.figure()
plot_channels_in_map_view(self._model.grid, profile_IDs)
plt.savefig('topography_' + yr + '.png')
plt.close()
plt.figure()
imshow_grid(model.grid,
model.grid.at_node['soil__depth'],
cmap='viridis',
limits=(0, 15))
plt.savefig('soil_' + yr + '.png')
plt.close()
plt.figure()
imshow_grid(self._model.grid,
self._model.grid.at_node['sediment__flux'],
cmap='viridis')
plt.savefig('sediment_flux_' + yr + '.png')
plt.close()
U_eff = U_fast + U_back
U_eff_slow = U_slow + U_back
area = np.sort(self._model.grid.at_node['drainage_area'][
self._model.boundary_handler['NormalFault'].faulted_nodes == True])
area = area[area > 0]
little_q = (
area *
self._model.params['runoff_rate'])**self._model.params['m_sp']
#area_to_the_m = area ** self._model.params['m_sp']
detachment_prediction = (
(U_eff / (self._model.params['K_rock_sp']))
**(1.0 / self._model.params['n_sp']) *
(1.0 / little_q)**(1.0 / self._model.params['n_sp']))
transport_prediction = (
((U_eff * self._model.params['v_sc']) /
(self._model.params['K_sed_sp'] *
self._model.params['runoff_rate'])) +
((U_eff) / (self._model.params['K_sed_sp'])))**(
1.0 / self._model.params['n_sp']) * (
(1.0 / little_q)**(1.0 / self._model.params['n_sp']))
space_prediction = (
((U_eff * self._model.params['v_sc']) * (1.0 - Ff) /
(self._model.params['K_sed_sp'] *
self._model.params['runoff_rate'])) +
((U_eff) / (self._model.params['K_rock_sp'])))**(
1.0 / self._model.params['n_sp']) * (
(1.0 / little_q)**(1.0 / self._model.params['n_sp']))
detachment_prediction_slow = (
(U_eff_slow / (self._model.params['K_rock_sp']))
**(1.0 / self._model.params['n_sp']) *
(1.0 / little_q)**(1.0 / self._model.params['n_sp']))
transport_prediction_slow = (
((U_eff_slow * self._model.params['v_sc']) /
(self._model.params['K_sed_sp'] *
self._model.params['runoff_rate'])) +
((U_eff_slow) / (self._model.params['K_sed_sp'])))**(
1.0 / self._model.params['n_sp']) * (
(1.0 / little_q)**(1.0 / self._model.params['n_sp']))
space_prediction_slow = (
((U_eff_slow * self._model.params['v_sc']) * (1.0 - Ff) /
(self._model.params['K_sed_sp'] *
self._model.params['runoff_rate'])) +
((U_eff_slow) / (self._model.params['K_rock_sp'])))**(
1.0 / self._model.params['n_sp']) * (
(1.0 / little_q)**(1.0 / self._model.params['n_sp']))
# TODO need to fix space predictions here to include new soil thickness.
fs = (8, 6)
fig, ax = plt.subplots(figsize=fs, dpi=300)
plt.plot(area,
detachment_prediction,
'c',
lw=5,
label='Detachment Prediction')
plt.plot(area, transport_prediction, 'b', label='Transport Prediction')
plt.plot(area, space_prediction, 'm', label='Space Prediction')
plt.plot(area, detachment_prediction_slow, 'c', lw=5, alpha=0.3)
plt.plot(area, transport_prediction_slow, 'b', alpha=0.3)
plt.plot(area, space_prediction_slow, 'm', alpha=0.3)
plt.plot(self._model.grid.at_node['drainage_area'][
self._model.boundary_handler['NormalFault'].faulted_nodes == True],
self._model.grid.at_node['topographic__steepest_slope']
[self._model.boundary_handler['NormalFault'].faulted_nodes ==
True],
'k.',
label='Fault Block Nodes')
plt.plot(self._model.grid.at_node['drainage_area']
[self._model.boundary_handler['NormalFault'].faulted_nodes ==
False],
self._model.grid.at_node['topographic__steepest_slope']
[self._model.boundary_handler['NormalFault'].faulted_nodes ==
False],
'r.',
label='Unfaulted Nodes')
plt.plot(self._model.grid.at_node['drainage_area'][profile_IDs],
self._model.grid.at_node['topographic__steepest_slope']
[profile_IDs],
'g.',
label='Main Channel Nodes')
plt.legend()
ax.set_xscale('log')
ax.set_yscale('log')
plt.xlabel('log 10 Area')
plt.ylabel('log 10 Slope')
plt.savefig('slope_area_' + yr + '.png')
plt.close()
model = Model(params=params, OutputWriters=ChannelPlotter)
model.run(output_fields=output_fields)
#%%
# find the faulted node with the largest drainage area.
largest_da = np.max(model.grid.at_node['drainage_area'][
model.boundary_handler['NormalFault'].faulted_nodes == True])
largest_da_ind = np.where(
model.grid.at_node['drainage_area'] == largest_da)[0][0]
#plt.figure()
#imshow_grid(model.grid, model.grid.at_node['drainage_area'] == largest_da, cmap='viridis')
#plt.show()
(profile_IDs, dists_upstr) = analyze_channel_network_and_plot(
model.grid, number_of_channels=1, starting_nodes=[largest_da_ind])
elevs = model.z[profile_IDs]
data_frame = pd.DataFrame.from_dict(
data={
'distance': dists_upstr[0][0],
'elevation': elevs[0],
'area': model.grid.at_node['drainage_area'][profile_IDs][0],
'slope': model.grid.at_node['topographic__steepest_slope'][profile_IDs]
[0]
})
data_frame.to_csv('truth_profile.csv')
with open(sys.argv[-1], 'w') as f:
relief = model.z[model.grid.core_nodes].max() - model.z[
model.grid.core_nodes].min()
counter = 0.
while elapsed_time < time_to_run:
print(elapsed_time)
if elapsed_time+dt>time_to_run:
print("Short step!")
dt = time_to_run - elapsed_time
mg = fr.route_flow(method='D8')
#print 'Area: ', numpy.max(mg.at_node['drainage_area'])
#mg = fsp.erode(mg)
mg,_,_ = sp.erode(mg, dt, node_drainage_areas='drainage_area', slopes_at_nodes='topographic__steepest_slope', K_if_used='K_values')
#add uplift
mg.at_node['topographic__elevation'][mg.core_nodes] += uplift*dt
elapsed_time += dt
if counter%20 == 0:
pylab.figure('profiles')
profiles = prf.analyze_channel_network_and_plot(mg)
counter += 1
time_off = time.time()
print('Elapsed time: ', time_off-time_on)
time_off = time.time()
print('Elapsed time: ', time_off-time_on)
#Finalize and plot
elev = mg['node']['topographic__elevation']
elev_r = mg.node_vector_to_raster(elev)
# Clear previous plots
pylab.figure(1)
pylab.close()
