def test_nmg_no_cell_area():
y_of_node = (0, 1, 2, 2)
x_of_node = (0, 0, -1, 1)
nodes_at_link = ((1, 0), (2, 1), (3, 1))
nmg = NetworkModelGrid((y_of_node, x_of_node), nodes_at_link)
nmg.add_field("topographic__elevation", nmg.x_of_node + nmg.y_of_node, at="node")
with pytest.raises(FieldError):
FlowAccumulator(nmg)
def test_nmg_no_cell_area():
y_of_node = (0, 1, 2, 2)
x_of_node = (0, 0, -1, 1)
nodes_at_link = ((1, 0), (2, 1), (3, 1))
nmg = NetworkModelGrid((y_of_node, x_of_node), nodes_at_link)
nmg.add_field("topographic__elevation", nmg.x_of_node + nmg.y_of_node, at="node")
with pytest.raises(FieldError):
FlowAccumulator(nmg)
def test_network_from_file():
file_strn = (
"yx_of_node:\n"
" - [0, 1, 2, 2]\n"
" - [0, 0, -1, 1]\n"
"links:\n"
" - [1, 0]\n"
" - [2, 1]\n"
" - [3, 1]\n"
"xy_of_reference:\n"
" - 12345\n"
" - 678910\n"
"axis_name:\n"
" - 'spam'\n"
" - 'eggs'\n"
"axis_units:\n"
" - 'smoot'\n"
" - 'parsec'"
)
file_like = StringIO(file_strn)
mg = NetworkModelGrid.from_file(file_like)
assert_array_equal(mg.x_of_node, np.array([0.0, 0.0, -1.0, 1.0]))
assert_array_equal(mg.y_of_node, np.array([0.0, 1.0, 2.0, 2.0]))
assert_array_equal(mg.nodes_at_link, np.array([[0, 1], [2, 1], [1, 3]]))
assert mg.axis_units == ("smoot", "parsec")
assert mg.axis_name == ("spam", "eggs")
assert mg.xy_of_reference == (12345, 678910)
def test_network_from_file():
file_strn = ("yx_of_node:\n"
" - [0, 1, 2, 2]\n"
" - [0, 0, -1, 1]\n"
"links:\n"
" - [1, 0]\n"
" - [2, 1]\n"
" - [3, 1]\n"
"xy_of_reference:\n"
" - 12345\n"
" - 678910\n"
"axis_name:\n"
" - 'spam'\n"
" - 'eggs'\n"
"axis_units:\n"
" - 'smoot'\n"
" - 'parsec'")
file_like = StringIO(file_strn)
mg = NetworkModelGrid.from_file(file_like)
assert_array_equal(mg.x_of_node, np.array([0., 0., -1., 1.]))
assert_array_equal(mg.y_of_node, np.array([0., 1., 2., 2.]))
assert_array_equal(mg.nodes_at_link, np.array([[0, 1], [2, 1], [1, 3]]))
assert mg.axis_units == ("smoot", "parsec")
assert mg.axis_name == ("spam", "eggs")
assert mg.xy_of_reference == (12345, 678910)
def test_network_from_file():
file_like = StringIO(
"""
yx_of_node:
- [0, 1, 2, 2]
- [0, 0, -1, 1]
links:
- [1, 0]
- [2, 1]
- [3, 1]
xy_of_reference:
- 12345
- 678910
xy_axis_name:
- 'spam'
- 'eggs'
xy_axis_units:
- 'smoot'
- 'parsec'
"""
)
mg = NetworkModelGrid.from_file(file_like)
assert_array_equal(mg.x_of_node, np.array([0.0, 0.0, -1.0, 1.0]))
assert_array_equal(mg.y_of_node, np.array([0.0, 1.0, 2.0, 2.0]))
assert_array_equal(mg.nodes_at_link, np.array([[0, 1], [2, 1], [1, 3]]))
assert mg.axis_units == ("smoot", "parsec")
assert mg.axis_name == ("spam", "eggs")
assert mg.xy_of_reference == (12345, 678910)
def test_network_from_dict():
params = {
"yx_of_node": [(0, 1, 2, 2), (0, 0, -1, 1)],
"links": ((1, 0), (2, 1), (3, 1)),
"axis_name": ("spam", "eggs"),
"axis_units": ("smoot", "parsec"),
"xy_of_reference": (12345, 678910),
}
mg = NetworkModelGrid.from_dict(params)
assert_array_equal(mg.x_of_node, np.array([0.0, 0.0, -1.0, 1.0]))
assert_array_equal(mg.y_of_node, np.array([0.0, 1.0, 2.0, 2.0]))
assert_array_equal(mg.nodes_at_link, np.array([[0, 1], [2, 1], [1, 3]]))
assert mg.axis_units == ("smoot", "parsec")
assert mg.axis_name == ("spam", "eggs")
assert mg.xy_of_reference == (12345, 678910)
def test_network_from_dict():
params = {
"yx_of_node": [(0, 1, 2, 2), (0, 0, -1, 1)],
"links": ((1, 0), (2, 1), (3, 1)),
"axis_name": ("spam", "eggs"),
"axis_units": ("smoot", "parsec"),
"xy_of_reference": (12345, 678910),
}
mg = NetworkModelGrid.from_dict(params)
assert_array_equal(mg.x_of_node, np.array([0., 0., -1., 1.]))
assert_array_equal(mg.y_of_node, np.array([0., 1., 2., 2.]))
assert_array_equal(mg.nodes_at_link, np.array([[0, 1], [2, 1], [1, 3]]))
assert mg.axis_units == ("smoot", "parsec")
assert mg.axis_name == ("spam", "eggs")
assert mg.xy_of_reference == (12345, 678910)
def simple_network():
y_of_node = (0, 1, 2, 2)
x_of_node = (0, 0, -1, 1)
nodes_at_link = ((1, 0), (2, 1), (3, 1))
mg = NetworkModelGrid((y_of_node, x_of_node), nodes_at_link)
return mg
def test_pulser_defaults_equal():
y_of_node = (0, 100, 200)
x_of_node = (0, 0, 100)
nodes_at_link = ((1, 0), (2, 1), (1, 2))
#create network model grid
grid = NetworkModelGrid((y_of_node, x_of_node), nodes_at_link)
grid.at_link["channel_width"] = np.full(grid.number_of_links, 1.0) # m
grid.at_link["channel_slope"] = np.full(grid.number_of_links, .01) # m / m
grid.at_link["reach_length"] = np.full(grid.number_of_links, 100.0) # m
# instantiate pulse
make_pulse = SedimentPulser(grid)
# obtain values for all defaults of initializer
default_rho_sediment = make_pulse._rho_sediment
default_std_dev = make_pulse._std_dev
default_time_to_pulse = make_pulse._time_to_pulse
#assign d50 of lognormal sediment distribution
d50 = 1.5
# "run model" for single time step (will pulse once)
for time in range(1):
# call pulser
parcels = make_pulse(d50, time)
# obtain values for all defaults of call
# can we access these somehow from 'make_pulse' so they aren't hard-coded?
default_n_parcels = 100
default_link_to_pulse = 0
default_abrasion_rate = 0.0
default_time_arrival = 0.0 #for this case we only have 1 time step
# check values-----------
np.testing.assert_equal(
parcels.dataset.element_id.values,
np.expand_dims(np.full(n_parcels, default_link_to_pulse),1)
)
np.testing.assert_equal(
parcels.dataset.starting_link.values,
np.expand_dims(np.full(n_parcels, default_link_to_pulse),1)
)
# test
np.testing.assert_equal(
parcels.dataset.abrasion_rate.values,
np.expand_dims(np.full(n_parcels, default_abrasion_rate),1)
)
# test starting location
np.testing.assert_equal(
parcels.dataset.time_arrival_in_link.values,
np.expand_dims(np.full(n_parcels, default_time_arrival),1)
)
# test D distribution
ks_test_stat, pval = scipy.stats.kstest(
np.ravel(parcels.dataset.D),
"lognorm",
scipy.stats.lognorm.fit(np.ravel(parcels.dataset.D))
)
if pval < 0.05:
raise ValueError('D distribution not lognormal')