def test_mask_is_stable():
mg = RasterModelGrid((10, 10))
mg.add_zeros("node", "topographic__elevation")
np.random.seed(3542)
noise = np.random.rand(mg.size("node"))
mg.at_node["topographic__elevation"] += noise
fr = FlowAccumulator(mg, flow_director="D8")
fsc = FastscapeEroder(mg, K_sp=0.01, m_sp=0.5, n_sp=1)
for x in range(2):
fr.run_one_step()
fsc.run_one_step(dt=10.0)
mg.at_node["topographic__elevation"][mg.core_nodes] += 0.01
mask = np.zeros(len(mg.at_node["topographic__elevation"]), dtype=np.uint8)
mask[np.where(mg.at_node["drainage_area"] > 0)] = 1
mask0 = mask.copy()
dd = DrainageDensity(mg, channel__mask=mask)
mask1 = mask.copy()
dd.calc_drainage_density()
mask2 = mask.copy()
assert_array_equal(mask0, mask1)
assert_array_equal(mask0[mg.core_nodes], mask2[mg.core_nodes])
def CalandConv_DrainageDensity(rmg, DD_thrshld, filename):
rmg.at_node['topographic__elevation'][rmg.core_nodes]
channels = np.array(rmg.at_node['drainage_area'] > DD_thrshld,
dtype=np.uint8)
dd = DrainageDensity(rmg, channel__mask=channels)
mean_drainage_density = dd.calc_drainage_density()
print 'the mean drainage density of %s is: %f' % (filename,
mean_drainage_density)
return mean_drainage_density
def test_updating_with_array_provided():
mg = RasterModelGrid((10, 10))
mg.add_zeros("node", "topographic__elevation")
noise = np.random.rand(mg.size("node"))
mg.at_node["topographic__elevation"] += noise
fr = FlowAccumulator(mg, flow_director="D8")
fr.run_one_step()
mask = np.zeros(len(mg.at_node["topographic__elevation"]), dtype=np.uint8)
mask[np.where(mg.at_node["drainage_area"] > 5)] = 1
dd = DrainageDensity(mg, channel__mask=mask)
with pytest.raises(NotImplementedError):
dd._update_channel_mask()
def test_providing_array_and_kwargs():
mg = RasterModelGrid((10, 10))
mg.add_zeros("node", "topographic__elevation")
noise = np.random.rand(mg.size("node"))
mg.at_node["topographic__elevation"] += noise
fr = FlowAccumulator(mg, flow_director="D8")
fr.run_one_step()
mask = np.zeros(len(mg.at_node["topographic__elevation"]), dtype=np.uint8)
mask[np.where(mg.at_node["drainage_area"] > 5)] = 1
with pytest.warns(UserWarning):
DrainageDensity(mg, channel__mask=mask, area_coefficient=1)
with pytest.warns(UserWarning):
DrainageDensity(mg, channel__mask=mask, slope_coefficient=1)
with pytest.warns(UserWarning):
DrainageDensity(mg, channel__mask=mask, area_exponent=1)
with pytest.warns(UserWarning):
DrainageDensity(mg, channel__mask=mask, slope_exponent=1)
with pytest.warns(UserWarning):
DrainageDensity(mg, channel__mask=mask, channelization_threshold=1)
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()
channel__mask = mg.zeros(at="node")
with pytest.raises(NotImplementedError):
DrainageDensity(mg, channel__mask=channel__mask)
def test_bool_mask():
mg = RasterModelGrid((10, 10))
mg.add_zeros("node", "topographic__elevation")
noise = np.random.rand(mg.size("node"))
mg.at_node["topographic__elevation"] += noise
fr = FlowAccumulator(mg, flow_director="D8")
fr.run_one_step()
mask = np.zeros(len(mg.at_node["topographic__elevation"]), dtype=bool)
mask[np.where(mg.at_node["drainage_area"] > 5)] = 1
with pytest.raises(ValueError):
DrainageDensity(mg, channel__mask=mask)
def test_missing_fields():
mg = RasterModelGrid((10, 10))
mg.add_zeros("node", "topographic__elevation")
with pytest.raises(FieldError):
DrainageDensity(
mg,
area_coefficient=1,
slope_coefficient=1,
area_exponent=1,
slope_exponent=1,
channelization_threshold=1,
)
def test_mask_field_exists():
mg = RasterModelGrid((10, 10))
mg.add_zeros("node", "topographic__elevation")
mg.add_zeros("node", "channel__mask")
noise = np.random.rand(mg.size("node"))
mg.at_node["topographic__elevation"] += noise
fr = FlowAccumulator(mg, flow_director="D8")
fr.run_one_step()
mask = np.zeros(len(mg.at_node["topographic__elevation"]), dtype=np.uint8)
mask[np.where(mg.at_node["drainage_area"] > 5)] = 1
with pytest.warns(UserWarning):
DrainageDensity(mg, channel__mask=mask)
def test_missing_area_coefficient():
mg = RasterModelGrid((10, 10))
mg.add_zeros("node", "topographic__elevation")
noise = np.random.rand(mg.size("node"))
mg.at_node["topographic__elevation"] += noise
fr = FlowAccumulator(mg, flow_director="D8")
fr.run_one_step()
with pytest.raises(ValueError):
DrainageDensity(
mg,
slope_coefficient=1,
area_exponent=1,
slope_exponent=1,
channelization_threshold=1,
)
hd = HeightAboveDrainageCalculator(mg, channel_mask=network_curvature)
try:
hd.run_one_step()
hand_curvature[:] = mg.at_node["height_above_drainage__elevation"].copy()
df_output['mean_hand_curvature'] = np.mean(hand_curvature[mg.core_nodes])
hd.channel_mask = network_sat
hd.run_one_step()
hand_sat[:] = mg.at_node["height_above_drainage__elevation"].copy()
df_output['mean_hand_sat_interstorm'] = np.mean(hand_sat[mg.core_nodes])
except:
print('failed to calculate HAND')
######## Calculate drainage density
dd = DrainageDensity(mg, channel__mask=np.uint8(network_curvature))
try:
channel_mask = mg.at_node['channel__mask']
df_output['dd_curvature'] = dd.calculate_drainage_density()
df_output['mean hillslope len curvature'] = 1 / (2 *
df_output['dd_curvature'])
channel_mask[:] = np.uint8(network_sat)
df_output['dd_sat_interstorm'] = dd.calculate_drainage_density()
df_output['mean hillslope len sat interstorm'] = 1 / (
2 * df_output['dd_sat_interstorm'])
except:
print('failed to calculate drainage density')
####### calculate elevation change
network[:] = curvature > 0
######## Calculate HAND
hand = mg.add_zeros('node', 'hand')
hd = HeightAboveDrainageCalculator(mg, channel_mask=network)
hd.run_one_step()
hand[:] = mg.at_node["height_above_drainage__elevation"].copy()
df_output['mean hand'] = np.mean(hand[mg.core_nodes])
cell_area = max(mg.cell_area_at_node)
df_output['hand mean ridges'] = np.mean(
hand[mg.at_node["drainage_area"] == cell_area])
######## Calculate drainage density
if isinstance(mg, RasterModelGrid):
dd = DrainageDensity(mg, channel__mask=np.uint8(network))
channel_mask = mg.at_node['channel__mask']
df_output['drainage density'] = dd.calculate_drainage_density()
df_output['mean hillslope len'] = 1 / (2 * df_output['drainage density'])
df_output['mean hillslope len ridges'] = np.mean(
mg.at_node["surface_to_channel__minimum_distance"][
mg.at_node["drainage_area"] == cell_area])
####### calculate relief change
output_interval = int(files[1].split('_')[-1][:-3]) - int(
files[0].split('_')[-1][:-3])
dt_nd = output_interval * dtg / tg
relief_change = np.zeros(len(files))
for i in range(1, len(files)):
grid = from_netcdf(files[i])
elev = grid.at_node['topographic__elevation']
