def test_calculate_landslide_probability_lognormal_method():
"""Testing the main method 'calculate_landslide_probability()' with
'lognormal' method.
"""
grid_2 = RasterModelGrid((5, 4), spacing=(0.2, 0.2))
gridnum = grid_2.number_of_nodes
np.random.seed(seed=6)
grid_2.at_node['topographic__slope'] = np.random.rand(gridnum)
scatter_dat = np.random.randint(1, 10, gridnum)
grid_2.at_node['topographic__specific_contributing_area']= (
np.sort(np.random.randint(30, 900, gridnum)))
grid_2.at_node['soil__transmissivity']= (
np.sort(np.random.randint(5, 20, gridnum), -1))
grid_2.at_node['soil__mode_total_cohesion']= (
np.sort(np.random.randint(30, 900, gridnum)))
grid_2.at_node['soil__minimum_total_cohesion']= (
grid_2.at_node['soil__mode_total_cohesion'] - scatter_dat)
grid_2.at_node['soil__maximum_total_cohesion']= (
grid_2.at_node['soil__mode_total_cohesion'] + scatter_dat)
grid_2.at_node['soil__internal_friction_angle']= (
np.sort(np.random.randint(26, 37, gridnum)))
grid_2.at_node['soil__thickness']= (
np.sort(np.random.randint(1, 10, gridnum)))
grid_2.at_node['soil__density']= (2000. * np.ones(gridnum))
ls_prob_lognormal = LandslideProbability(grid_2, number_of_iterations=10,
groundwater__recharge_distribution='lognormal',
groundwater__recharge_mean=5.,
groundwater__recharge_standard_deviation=0.25,
seed=6)
ls_prob_lognormal.calculate_landslide_probability()
np.testing.assert_almost_equal(
grid_2.at_node['landslide__probability_of_failure'][5], 0.8)
np.testing.assert_almost_equal(
grid_2.at_node['landslide__probability_of_failure'][9], 0.4)
def setup_grid():
"""Setting up test raster grid.
"""
grid = RasterModelGrid((20, 20), spacing=10e0)
grid.at_node['topographic__slope'] = (np.zeros(grid.number_of_nodes,
dtype=float))
ls_prob = LandslideProbability(grid)
globals().update({'ls_prob': LandslideProbability(grid)})
def test_calculate_landslide_probability_lognormal_spatial_method():
"""Testing the main method 'calculate_landslide_probability()' with
'lognormal_spatial' method.
"""
grid_3 = RasterModelGrid((5, 4), xy_spacing=(0.2, 0.2))
gridnum = grid_3.number_of_nodes
np.random.seed(seed=7)
grid_3.at_node["topographic__slope"] = np.random.rand(gridnum)
scatter_dat = np.random.randint(1, 10, gridnum)
grid_3.at_node["topographic__specific_contributing_area"] = np.sort(
np.random.randint(30, 900, gridnum)
)
grid_3.at_node["soil__transmissivity"] = np.sort(
np.random.randint(5, 20, gridnum), -1
)
grid_3.at_node["soil__mode_total_cohesion"] = np.sort(
np.random.randint(30, 900, gridnum)
)
grid_3.at_node["soil__minimum_total_cohesion"] = (
grid_3.at_node["soil__mode_total_cohesion"] - scatter_dat
)
grid_3.at_node["soil__maximum_total_cohesion"] = (
grid_3.at_node["soil__mode_total_cohesion"] + scatter_dat
)
grid_3.at_node["soil__internal_friction_angle"] = np.sort(
np.random.randint(26, 37, gridnum)
)
grid_3.at_node["soil__thickness"] = np.sort(np.random.randint(1, 10, gridnum))
grid_3.at_node["soil__density"] = 2000. * np.ones(gridnum)
ls_prob_lognormal_spatial = LandslideProbability(
grid_3,
number_of_iterations=10,
groundwater__recharge_distribution="lognormal_spatial",
groundwater__recharge_mean=np.random.randint(2, 7, gridnum),
groundwater__recharge_standard_deviation=np.random.rand(gridnum),
seed=7,
)
ls_prob_lognormal_spatial.calculate_landslide_probability()
np.testing.assert_almost_equal(
grid_3.at_node["landslide__probability_of_failure"][5], 0.4
)
np.testing.assert_almost_equal(
grid_3.at_node["landslide__probability_of_failure"][9], 0.29999999
)
def test_calculate_landslide_probability_uniform_method():
"""Testing the main method 'calculate_landslide_probability()' with
'uniform' method.
"""
grid_1 = RasterModelGrid((5, 4), xy_spacing=(0.2, 0.2))
gridnum = grid_1.number_of_nodes
np.random.seed(seed=5)
grid_1.at_node["topographic__slope"] = np.random.rand(gridnum)
scatter_dat = np.random.randint(1, 10, gridnum)
grid_1.at_node["topographic__specific_contributing_area"] = np.sort(
np.random.randint(30, 900, gridnum)
)
grid_1.at_node["soil__transmissivity"] = np.sort(
np.random.randint(5, 20, gridnum), -1
)
grid_1.at_node["soil__mode_total_cohesion"] = np.sort(
np.random.randint(30, 900, gridnum)
)
grid_1.at_node["soil__minimum_total_cohesion"] = (
grid_1.at_node["soil__mode_total_cohesion"] - scatter_dat
)
grid_1.at_node["soil__maximum_total_cohesion"] = (
grid_1.at_node["soil__mode_total_cohesion"] + scatter_dat
)
grid_1.at_node["soil__internal_friction_angle"] = np.sort(
np.random.randint(26, 37, gridnum)
)
grid_1.at_node["soil__thickness"] = np.sort(np.random.randint(1, 10, gridnum))
grid_1.at_node["soil__density"] = 2000. * np.ones(gridnum)
ls_prob_uniform = LandslideProbability(
grid_1,
number_of_iterations=10,
groundwater__recharge_distribution="uniform",
groundwater__recharge_min_value=20.,
groundwater__recharge_max_value=120.,
seed=5,
)
ls_prob_uniform.calculate_landslide_probability()
np.testing.assert_almost_equal(
grid_1.at_node["landslide__probability_of_failure"][5], 1.
)
np.testing.assert_almost_equal(
grid_1.at_node["landslide__probability_of_failure"][9], 0.
)
def test_calculate_landslide_probability_uniform_method():
"""Testing the main method 'calculate_landslide_probability()' with
'uniform' method.
"""
grid_1 = RasterModelGrid((5, 4), spacing=(0.2, 0.2))
gridnum = grid_1.number_of_nodes
np.random.seed(seed=5)
grid_1.at_node["topographic__slope"] = np.random.rand(gridnum)
scatter_dat = np.random.randint(1, 10, gridnum)
grid_1.at_node["topographic__specific_contributing_area"] = np.sort(
np.random.randint(30, 900, gridnum)
)
grid_1.at_node["soil__transmissivity"] = np.sort(
np.random.randint(5, 20, gridnum), -1
)
grid_1.at_node["soil__mode_total_cohesion"] = np.sort(
np.random.randint(30, 900, gridnum)
)
grid_1.at_node["soil__minimum_total_cohesion"] = (
grid_1.at_node["soil__mode_total_cohesion"] - scatter_dat
)
grid_1.at_node["soil__maximum_total_cohesion"] = (
grid_1.at_node["soil__mode_total_cohesion"] + scatter_dat
)
grid_1.at_node["soil__internal_friction_angle"] = np.sort(
np.random.randint(26, 37, gridnum)
)
grid_1.at_node["soil__thickness"] = np.sort(np.random.randint(1, 10, gridnum))
grid_1.at_node["soil__density"] = 2000. * np.ones(gridnum)
ls_prob_uniform = LandslideProbability(
grid_1,
number_of_iterations=10,
groundwater__recharge_distribution="uniform",
groundwater__recharge_min_value=20.,
groundwater__recharge_max_value=120.,
seed=5,
)
ls_prob_uniform.calculate_landslide_probability()
np.testing.assert_almost_equal(
grid_1.at_node["landslide__probability_of_failure"][5], 1.
)
np.testing.assert_almost_equal(
grid_1.at_node["landslide__probability_of_failure"][9], 0.
)
def test_calculate_landslide_probability_lognormal_spatial_method():
"""Testing the main method 'calculate_landslide_probability()' with
'lognormal_spatial' method.
"""
grid_3 = RasterModelGrid((5, 4), xy_spacing=(0.2, 0.2))
gridnum = grid_3.number_of_nodes
np.random.seed(seed=7)
grid_3.add_zeros("soil__saturated_hydraulic_conductivity", at="node")
grid_3.at_node["topographic__slope"] = np.random.rand(gridnum)
scatter_dat = np.random.randint(1, 10, gridnum).astype(float)
grid_3.at_node["topographic__specific_contributing_area"] = np.sort(
np.random.randint(30, 900, gridnum).astype(float))
grid_3.at_node["soil__transmissivity"] = np.sort(
np.random.randint(5, 20, gridnum).astype(float), -1)
grid_3.at_node["soil__mode_total_cohesion"] = np.sort(
np.random.randint(30, 900, gridnum).astype(float))
grid_3.at_node["soil__minimum_total_cohesion"] = (
grid_3.at_node["soil__mode_total_cohesion"] - scatter_dat)
grid_3.at_node["soil__maximum_total_cohesion"] = (
grid_3.at_node["soil__mode_total_cohesion"] + scatter_dat)
grid_3.at_node["soil__internal_friction_angle"] = np.sort(
np.random.randint(26, 37, gridnum).astype(float))
grid_3.at_node["soil__thickness"] = np.sort(
np.random.randint(1, 10, gridnum).astype(float))
grid_3.at_node["soil__density"] = 2000.0 * np.ones(gridnum)
ls_prob_lognormal_spatial = LandslideProbability(
grid_3,
number_of_iterations=10,
groundwater__recharge_distribution="lognormal_spatial",
groundwater__recharge_mean=np.random.randint(2, 7,
gridnum).astype(float),
groundwater__recharge_standard_deviation=np.random.rand(gridnum),
seed=7,
)
ls_prob_lognormal_spatial.calculate_landslide_probability()
np.testing.assert_almost_equal(
grid_3.at_node["landslide__probability_of_failure"][5], 0.4)
np.testing.assert_almost_equal(
grid_3.at_node["landslide__probability_of_failure"][9], 0.29999999)
def ls_prob():
grid = RasterModelGrid((20, 20), xy_spacing=10e0)
grid.add_zeros("topographic__slope", at="node", dtype=float)
grid.add_zeros("topographic__specific_contributing_area", at="node")
grid.add_zeros("soil__transmissivity", at="node")
grid.add_zeros("soil__saturated_hydraulic_conductivity", at="node")
grid.add_zeros("soil__mode_total_cohesion", at="node")
grid.add_zeros("soil__minimum_total_cohesion", at="node")
grid.add_zeros("soil__maximum_total_cohesion", at="node")
grid.add_zeros("soil__internal_friction_angle", at="node")
grid.add_zeros("soil__density", at="node")
grid.add_zeros("soil__thickness", at="node")
return LandslideProbability(grid)
def ls_prob():
grid = RasterModelGrid((20, 20), spacing=10e0)
grid.add_zeros('topographic__slope', at='node', dtype=float)
return LandslideProbability(grid)