def test_grid_var_spacing():
model = BmiGridmet()
model.initialize()
shape = np.empty(2, dtype=np.float)
tmp2 = np.array([0.041667, 0.041667])
npt.assert_almost_equal(model.get_grid_spacing(grid_id, shape),
tmp2,
decimal=4)
def test_value_size():
model = BmiGridmet()
model.initialize()
grid_id = model.get_var_grid("daily_maximum_temperature")
size = model.get_grid_size(grid_id)
vals1 = np.empty(size)
z = model.get_value("daily_maximum_temperature", vals1)
assert model.get_grid_size(0) == z.size
def test_grid_var_origin():
model = BmiGridmet()
model.initialize()
shape = np.empty(2, dtype=np.float)
tmp2 = np.array([25.066667, -124.77])
npt.assert_almost_equal(model.get_grid_origin(grid_id, shape),
tmp2,
decimal=2)
def test_grid_var_item_count():
model = BmiGridmet()
model.initialize()
count = model.get_input_item_count()
assert count == 0
count = model.get_output_item_count()
assert count == 3
def test_update():
model = BmiGridmet()
model.initialize()
for inc in range(6):
model.update()
npt.assert_almost_equal(
model.get_current_time(), (inc + 1) * model.get_time_step()
)
def test_initialize_defaults():
model = BmiGridmet()
model.initialize()
grid_id = model.get_var_grid("daily_maximum_temperature")
size = model.get_grid_size(grid_id)
vals = np.empty(size)
model.get_value("daily_maximum_temperature", vals)
min = np.nanmin(vals)
max = np.nanmax(vals)
npt.assert_almost_equal(min, 266.399, decimal=2)
npt.assert_almost_equal(max, 305.0, decimal=1)
def test_get_value_copy():
model = BmiGridmet()
model.initialize()
grid_id = model.get_var_grid("daily_maximum_temperature")
size = model.get_grid_size(grid_id)
vals1 = np.empty(size)
vals2 = np.empty(size)
z0 = model.get_value("daily_maximum_temperature", vals1)
z1 = model.get_value("daily_maximum_temperature", vals2)
assert z0 is not z1
npt.assert_array_almost_equal(z0, z1)
def test_grid_var_names():
model = BmiGridmet()
model.initialize()
names = model.get_input_var_names()
assert names == ("")
names = model.get_output_var_names()
assert names == (
"daily_maximum_temperature",
"daily_minimum_temperature",
"precipitation_amount",
)
def test_initialize_from_file():
import datetime
import os
import tempfile
import yaml
yamldict = {
"_start_date": datetime.date(year=2020, month=1, day=1),
"_end_date": datetime.date(year=2020, month=1, day=7),
}
with tempfile.NamedTemporaryFile("w", delete=False) as fp:
fp.write((yaml.dump(yamldict, sort_keys=False)))
name = fp.name
model = BmiGridmet()
model.initialize(name)
os.remove(name)
shape = np.empty(2, dtype=np.int)
tmp = model.get_grid_shape(0, shape)
tmp2 = np.array([585, 1386])
npt.assert_almost_equal(tmp, tmp2)
def test_grid_id():
model = BmiGridmet()
model.initialize()
assert model.get_var_grid("daily_maximum_temperature") == grid_id
def test_end_time():
model = BmiGridmet()
model.initialize()
npt.assert_almost_equal(model.get_end_time(), 7.0)
import tempfile
import yaml
import datetime
def print_times(x):
print(x.get_start_time())
print(x.get_time_step())
print(x.get_time_units())
print(x.get_current_time())
print(x.get_end_time())
x = BmiGridmet()
# x.initialize('gridmet_bmi.yaml')
x.initialize()
print(x.get_input_var_names())
print(x.get_output_var_names())
grid_id = x.get_var_grid('daily_maximum_temperature')
size = x.get_grid_size(grid_id)
shape = np.empty(2, dtype=np.int)
origin = np.empty(2, dtype=np.float)
delta = np.empty(2, dtype=np.float)
x.get_grid_origin(grid_id, origin)
x.get_grid_spacing(grid_id, spacing=delta)
tmp = x.get_grid_shape(grid_id, shape)
print(type(shape), shape[0], shape[1], shape)
tmp2 = np.array([585, 1386])
npt.assert_almost_equal(shape, np.array([585, 1386]))
vals = np.zeros(size)
x.get_value('daily_maximum_temperature', vals)
def test_grid_var_shape_fail():
model = BmiGridmet()
model.initialize()
shape = np.empty(2, dtype=np.int)
with pytest.raises(KeyError):
model.get_grid_shape(invalid_grid_id, shape)
def test_grid_var_type():
model = BmiGridmet()
model.initialize()
assert model.get_var_type("daily_maximum_temperature") == "float32"
def test_grid_var_shape():
model = BmiGridmet()
model.initialize()
shape = np.empty(2, dtype=np.int)
tmp2 = np.array([585, 1386])
npt.assert_equal(model.get_grid_shape(grid_id, shape), tmp2)
def test_grid_var_size_fail():
model = BmiGridmet()
model.initialize()
with pytest.raises(KeyError):
model.get_grid_size(invalid_grid_id)
def test_grid_var_size():
model = BmiGridmet()
model.initialize()
assert model.get_grid_size(grid_id) == 810810
def test_grid_type():
model = BmiGridmet()
model.initialize()
assert model.get_grid_type(grid_id) == "uniform_rectilinear"
def test_grid_var_units():
model = BmiGridmet()
model.initialize()
assert model.get_var_units("daily_maximum_temperature") == "K"
assert model.get_var_units("precipitation_amount") == "mm"
def test_finalize():
model = BmiGridmet()
model.initialize()
model.update()
model.finalize()
def test_grid_var_rank():
model = BmiGridmet()
model.initialize()
assert model.get_grid_rank(grid_id) == 2