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_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_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)
# 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)
print(np.nanmin(vals))
print(np.nanmax(vals))
print_times(x)
x.update()
print_times(x)
tmp = 0
x.finalize()
# 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
# print(name)