def test_route_to_multiple_error_raised():
mg = RasterModelGrid((10, 10))
z = mg.add_zeros('node', 'topographic__elevation')
z += mg.x_of_node + mg.y_of_node
fa = FlowAccumulator(mg, flow_director='MFD')
fa.run_one_step()
with pytest.raises(NotImplementedError):
analyze_channel_network_and_plot(mg)
with pytest.raises(NotImplementedError):
channel_nodes(mg,
mg.at_node['topographic__steepest_slope'],
mg.at_node['drainage_area'],
mg.at_node['flow__receiver_node'],
number_of_channels=1,
threshold=1.0)
def test_route_to_multiple_error_raised():
mg = RasterModelGrid((10, 10))
z = mg.add_zeros('node', 'topographic__elevation')
z += mg.x_of_node + mg.y_of_node
fa = FlowAccumulator(mg, flow_director='MFD')
fa.run_one_step()
with pytest.raises(NotImplementedError):
analyze_channel_network_and_plot(mg)
with pytest.raises(NotImplementedError):
channel_nodes(mg,
mg.at_node['topographic__steepest_slope'],
mg.at_node['drainage_area'],
mg.at_node['flow__receiver_node'],
number_of_channels=1,
threshold=1.0)
def plot_and_calc_concavities_final_run(directory='.'):
"""
Plots S-A for final topo saved in folder "directory".
Returns (k_s, concavity) for lin regression on log log trend.
Concavity is defined as positive.
"""
mg2 = deepcopy(mg)
z2 = mg2.add_zeros('node', 'topographic__elevation', noclobber=False)
fr2 = FlowRouter(mg2)
# search for topo saves, to establish the num files, codes etc:
prefixed_z = [
filename for filename in os.listdir(directory)
if filename.startswith('topographic__elevation')
]
# grab the unique ID, so we can differentiate plots (if desired)
unique_ID = prefixed_z[0][-14:-4]
# work on first save to establish num digits
_format = 0
while True:
char = prefixed_z[-1][-16 - _format]
try:
num = int(char)
except ValueError: # was a str
break
else:
_format += 1
# load the final topo:
z2[:] = np.loadtxt(directory + '/' + prefixed_z[-1])
# create a new flow map:
fr2.run_one_step()
profile_IDs = channel_nodes(mg2,
mg2.at_node['topographic__steepest_slope'],
mg2.at_node['drainage_area'],
mg2.at_node['flow__receiver_node'])
ch_dists = get_distances_upstream(
mg2, len(mg2.at_node['topographic__steepest_slope']), profile_IDs,
mg2.at_node['flow__link_to_receiver_node'])
slopes = mg2.at_node['topographic__steepest_slope'][profile_IDs[0]]
areas = mg2.at_node['drainage_area'][profile_IDs[0]]
logslopes = np.log(slopes)
logareas = np.log(areas)
goodvals = np.logical_and(np.isfinite(logslopes), np.isfinite(logareas))
concavity, log_k_s, _, _, _ = linregress(logareas[goodvals],
logslopes[goodvals])
k_s = np.exp(log_k_s)
loglog(areas, slopes, 'x')
loglog(areas, k_s * areas**concavity, '-')
xlabel('Drainage area (m**2)')
ylabel('Slope (m/m)')
return k_s, -concavity
def draw_profile(grid, figure_name='profile'):
"""Plot the current channel long profile.
"""
figure(figure_name)
profile_IDs = channel_nodes(grid,
grid.at_node['topographic__steepest_slope'],
grid.at_node['drainage_area'],
grid.at_node['flow__receiver_node'])
ch_dists = get_distances_upstream(
grid, len(grid.at_node['topographic__steepest_slope']), profile_IDs,
grid.at_node['flow__link_to_receiver_node'])
plot(ch_dists[0], grid.at_node['topographic__elevation'][profile_IDs[0]])
xlabel('Distance downstream (m)')
ylabel('Elevation (m)')
sp = SPEroder(mg, input_file)
diffuse = PerronNLDiffuse(mg, input_file)
lin_diffuse = DiffusionComponent(grid=mg, input_stream=input_file)
#perform the loops:
for i in xrange(nt):
#note the input arguments here are not totally standardized between modules
#mg = diffuse.diffuse(mg, i*dt)
mg = lin_diffuse.diffuse(mg, dt)
mg = fr.route_flow(grid=mg)
mg = sp.erode(mg)
##plot long profiles along channels
pylab.figure(6)
profile_IDs = prf.channel_nodes(mg, mg.at_node['steepest_slope'],
mg.at_node['drainage_area'],
mg.at_node['upstream_ID_order'],
mg.at_node['flow_receiver'])
dists_upstr = prf.get_distances_upstream(
mg, len(mg.at_node['steepest_slope']), profile_IDs,
mg.at_node['links_to_flow_receiver'])
prf.plot_profiles(dists_upstr, profile_IDs,
mg.at_node['topographic_elevation'])
print 'Completed loop ', i
print 'Completed the simulation. Plotting...'
#Finalize and plot
# Clear previous plots
pylab.figure(1)
pylab.close()
#max_slope = np.max(np.fabs(neighbor_slopes),axis=1)
#mg,_,capacity_out = tl.erode(mg,dt,slopes_at_nodes='topographic__steepest_slope')
#mg,_,capacity_out = tl.erode(mg,dt,slopes_at_nodes=max_slope)
mg_copy = deepcopy(mg)
mg, _ = sde.erode(mg, dt)
#print sde.iterations_in_dt
#print 'capacity ', np.amax(capacity_out[mg.core_nodes])
#print 'rel sed ', np.nanmax(sed_in[mg.core_nodes]/capacity_out[mg.core_nodes])
if i % out_interval == 0:
print('loop ', i)
print(
'max_slope',
np.amax(mg.at_node['topographic__steepest_slope'][mg.core_nodes]))
pylab.figure("long_profiles")
profile_IDs = prf.channel_nodes(
mg, mg.at_node['topographic__steepest_slope'],
mg.at_node['drainage_area'], mg.at_node['flow__receiver_node'])
dists_upstr = prf.get_distances_upstream(
mg, len(mg.at_node['topographic__steepest_slope']), profile_IDs,
mg.at_node['flow__link_to_receiver_node'])
prf.plot_profiles(dists_upstr, profile_IDs,
mg.at_node['topographic__elevation'])
if i % out_interval == 0:
x_profiles.append(dists_upstr)
z_profiles.append(mg.at_node['topographic__elevation'][profile_IDs])
S_profiles.append(
mg.at_node['topographic__steepest_slope'][profile_IDs])
A_profiles.append(mg.at_node['drainage_area'][profile_IDs])
if make_output_plots:
pylab.figure('long_profile_anim')
#prf.plot_profiles(dists_upstr, profile_IDs, mg.at_node['topographic_elevation'])
#neighbor_slopes = mg.calculate_gradient_along_node_links(mg.at_node['topographic_elevation'])
#mean_slope = np.mean(np.fabs(neighbor_slopes),axis=1)
#max_slope = np.max(np.fabs(neighbor_slopes),axis=1)
#mg,_,capacity_out = tl.erode(mg,dt,slopes_at_nodes='steepest_slope')
#mg,_,capacity_out = tl.erode(mg,dt,slopes_at_nodes=max_slope)
mg_copy = deepcopy(mg)
mg,_ = sde.erode(mg,dt)
#print sde.iterations_in_dt
#print 'capacity ', np.amax(capacity_out[mg.core_nodes])
#print 'rel sed ', np.nanmax(sed_in[mg.core_nodes]/capacity_out[mg.core_nodes])
if i%100 == 0:
print 'loop ', i
print 'max_slope', np.amax(mg.at_node['steepest_slope'][mg.core_nodes])
pylab.figure("long_profiles")
profile_IDs = prf.channel_nodes(mg, mg.at_node['steepest_slope'],
mg.at_node['drainage_area'], mg.at_node['upstream_ID_order'],
mg.at_node['flow_receiver'])
dists_upstr = prf.get_distances_upstream(mg, len(mg.at_node['steepest_slope']),
profile_IDs, mg.at_node['links_to_flow_receiver'])
prf.plot_profiles(dists_upstr, profile_IDs, mg.at_node['topographic_elevation'])
#mg.update_boundary_nodes()
#vid.add_frame(mg, 'topographic_elevation')
print 'Completed the simulation. Plotting...'
time_off = time()
#Finalize and plot
elev = mg['node']['topographic_elevation']
#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)
#max_slope = np.max(np.fabs(neighbor_slopes),axis=1)
#mg,_,capacity_out = tl.erode(mg,dt,slopes_at_nodes='topographic__steepest_slope')
#mg,_,capacity_out = tl.erode(mg,dt,slopes_at_nodes=max_slope)
mg_copy = deepcopy(mg)
mg,_ = sde.erode(mg,dt)
#print sde.iterations_in_dt
#print 'capacity ', np.amax(capacity_out[mg.core_nodes])
#print 'rel sed ', np.nanmax(sed_in[mg.core_nodes]/capacity_out[mg.core_nodes])
if i%out_interval == 0:
print('loop ', i)
print('max_slope', np.amax(mg.at_node['topographic__steepest_slope'][mg.core_nodes]))
pylab.figure("long_profiles")
profile_IDs = prf.channel_nodes(mg, mg.at_node['topographic__steepest_slope'],
mg.at_node['drainage_area'], mg.at_node['flow__receiver_node'])
dists_upstr = prf.get_distances_upstream(mg, len(mg.at_node['topographic__steepest_slope']),
profile_IDs, mg.at_node['flow__link_to_receiver_node'])
prf.plot_profiles(dists_upstr, profile_IDs, mg.at_node['topographic__elevation'])
if i%out_interval == 0:
x_profiles.append(dists_upstr)
z_profiles.append(mg.at_node['topographic__elevation'][profile_IDs])
S_profiles.append(mg.at_node['topographic__steepest_slope'][profile_IDs])
A_profiles.append(mg.at_node['drainage_area'][profile_IDs])
if make_output_plots:
pylab.figure('long_profile_anim')
#prf.plot_profiles(dists_upstr, profile_IDs, mg.at_node['topographic_elevation'])
plot(dists_upstr,mg.at_node['topographic_elevation'][profile_IDs])
ylim([0,y_max])
if i==0:
savefig('profile_anim_000'+str(i)+'.png')
mg.at_node["topographic__elevation"][mg.core_nodes] += uplift_per_step
mg = fr.route_flow(grid=mg)
if DL_or_TL == "TL":
mg, _ = tle.erode(mg, dt)
else:
mg, _, _ = spe.erode(mg, dt=dt)
if i % init_interval == 0:
print("loop {0}".format(i))
print(
"max_slope",
np.amax(mg.at_node["topographic__steepest_slope"][mg.core_nodes]),
)
pylab.figure("long_profiles_init")
profile_IDs = prf.channel_nodes(
mg,
mg.at_node["topographic__steepest_slope"],
mg.at_node["drainage_area"],
mg.at_node["flow__receiver_node"],
)
dists_upstr = prf.get_distances_upstream(
mg,
len(mg.at_node["topographic__steepest_slope"]),
profile_IDs,
mg.at_node["flow__link_to_receiver_node"],
)
prf.plot_profiles(dists_upstr, profile_IDs,
mg.at_node["topographic__elevation"])
print("completed run to steady state...")
if show_figs_in_run:
show() # will cause a hang
diffuse = PerronNLDiffuse(mg, input_file)
lin_diffuse = LinearDiffuser(grid=mg, input_stream=input_file)
# perform the loops:
for i in xrange(nt):
# note the input arguments here are not totally standardized between modules
# mg = diffuse.diffuse(mg, i*dt)
mg = lin_diffuse.diffuse(dt)
mg = fr.route_flow()
mg = sp.erode(mg)
mg.at_node["topographic__elevation"][mg.core_nodes] += uplift_per_step
##plot long profiles along channels
pylab.figure(6)
profile_IDs = prf.channel_nodes(
mg, mg.at_node["topographic__steepest_slope"], mg.at_node["drainage_area"], mg.at_node["flow_receiver"]
)
dists_upstr = prf.get_distances_upstream(
mg, len(mg.at_node["topographic__steepest_slope"]), profile_IDs, mg.at_node["links_to_flow_receiver"]
)
prf.plot_profiles(dists_upstr, profile_IDs, mg.at_node["topographic__elevation"])
print("Completed loop ", i)
print("Completed the simulation. Plotting...")
# Finalize and plot
# Clear previous plots
pylab.figure(1)
pylab.close()
def draw_profile_evolution(start,
stop,
step,
format,
directory='.',
force_same_nodes=False,
plot_field_downstream=None,
different_runs_different_plots=True):
"""Plot a set of long profiles, loaded from saved data.
"format" is the number of numbers in the file string.
e.g., "00150" is 5. "012345" is 6.
"plot_field_downstream" is the string of a field at which values should
also be plotted, on a second figure.
"""
mg2 = deepcopy(mg)
z2 = mg2.add_zeros('node', 'topographic__elevation', noclobber=False)
fr2 = FlowRouter(mg2)
first = True
for i in xrange(start, stop, step):
num_zeros = format - len(str(i))
numberstr = '0' * num_zeros + str(i) + '_'
# search for this string as a topo:
prefixed = [
filename for filename in os.listdir(directory)
if filename.startswith('topographic__elevation_' + numberstr)
]
# grab the unique ID, so we can differentiate plots (if desired)
unique_ID = prefixed[0][-14:-4]
print('Plotting the profile with unique ID: ' + unique_ID)
try:
z2[:] = np.loadtxt(directory + '/' + prefixed[0])
except IndexError:
raise IndexError(
"it's likely you've mis-set directory, or end is out of range")
if plot_field_downstream is not None:
prefixedvals = [
filename for filename in os.listdir(directory)
if filename.startswith(plot_field_downstream + '_' + numberstr)
]
field_vals = np.loadtxt(directory + '/' + prefixedvals[0])
fr2.run_one_step()
if force_same_nodes:
if first:
if different_runs_different_plots:
draw_profile(mg2, figure_name=('profile_' + unique_ID))
else:
draw_profile(mg2)
first = False
if plot_field_downstream is not None:
if different_runs_different_plots:
figure('field_values_downstream_' + unique_ID)
else:
figure('field_values_downstream')
plot(ch_dists[0], field_vals[profile_IDs[0]])
else:
if different_runs_different_plots:
figure('profile_' + unique_ID)
else:
figure('profile')
plot(ch_dists[0],
mg2.at_node['topographic__elevation'][profile_IDs[0]])
if plot_field_downstream is not None:
if different_runs_different_plots:
figure('field_values_downstream_' + unique_ID)
else:
figure('field_values_downstream')
plot(ch_dists[0], field_vals[profile_IDs[0]])
else:
if different_runs_different_plots:
draw_profile(mg2, figure_name=('profile_' + unique_ID))
else:
draw_profile(mg2)
if plot_field_downstream is not None:
profile_IDs = channel_nodes(
mg2, mg2.at_node['topographic__steepest_slope'],
mg2.at_node['drainage_area'],
mg2.at_node['flow__receiver_node'])
ch_dists = get_distances_upstream(
mg2, len(mg2.at_node['topographic__steepest_slope']),
profile_IDs, mg2.at_node['flow__link_to_receiver_node'])
if different_runs_different_plots:
figure('field_values_downstream_' + unique_ID)
else:
figure('field_values_downstream')
plot(ch_dists[0], field_vals[profile_IDs[0]])
if plot_field_downstream is not None:
if different_runs_different_plots:
figure('field_values_downstream_' + unique_ID)
else:
figure('field_values_downstream')
xlabel('Distance downstream (m)')
ylabel('Field value')
## optional print statement
print('i', i)
## to see what fields are created:
#rmg1.at_node.keys()
## Plotting the topography
plt.figure(1)
imshow_grid(rmg1, 'topographic__elevation')
## More plotting...
## find the location of the largest channels
profile_IDs = prf.channel_nodes(rmg1,
rmg1.at_node['topographic__steepest_slope'],
rmg1.at_node['drainage_area'],
rmg1.at_node['flow__receiver_node'],
number_of_channels=2)
## find the distances upstream at each node along the profile
profile_upstream_dists = prf.get_distances_upstream(
rmg1, len(rmg1.at_node['topographic__steepest_slope']), profile_IDs,
rmg1.at_node['flow__link_to_receiver_node'])
## plot elevation vs. distance
plt.figure(2)
plt.plot(profile_upstream_dists[0], z1[profile_IDs[0]], 'b-', label='chan 1')
plt.plot(profile_upstream_dists[1], z1[profile_IDs[1]], 'r-', label='chan 2')
plt.title('elevation profiles')
plt.ylabel('elevation [m]')
plt.xlabel('distance upstream [m]')