def test_overwrite(self):
ts = TESTDATA['raven-gr4j-cemaneige-nc-ts']
model = GR4JCN()
model(ts,
start_date=dt.datetime(2000, 1, 1),
end_date=dt.datetime(2002, 1, 1),
area=4250.6,
elevation=843.0,
latitude=54.4848,
longitude=-123.3659,
params=(0.529, -3.396, 407.29, 1.072, 16.9, 0.947)
)
qsim1 = model.q_sim.copy(deep=True)
m1 = qsim1.mean()
model(ts, params=(0.5289, -3.397, 407.3, 1.071, 16.89, .948), overwrite=True)
qsim2 = model.q_sim.copy(deep=True)
m2 = qsim2.mean()
assert m1 != m2
np.testing.assert_almost_equal(m1, m2, 1)
d = model.diagnostics
np.testing.assert_almost_equal(d['DIAG_NASH_SUTCLIFFE'], -0.0269642, 2)
def test_simple(self):
ts = TESTDATA['raven-gr4j-cemaneige-nc-ts']
model = GR4JCN(tempfile.mkdtemp())
model.rvi.start_date = dt.datetime(2000, 1, 1)
model.rvi.end_date = dt.datetime(2002, 1, 1)
model.rvi.run_name = 'test'
model.rvh.name = 'Salmon'
model.rvh.area = '4250.6'
model.rvh.elevation = '843.0'
model.rvh.latitude = 54.4848
model.rvh.longitude = -123.3659
model.rvp.params = model.params(0.529, -3.396, 407.29, 1.072, 16.9, 0.947)
model([ts, ])
d = model.diagnostics
# yields NSE=0.???? for full period 1954-2010
np.testing.assert_almost_equal(d['DIAG_NASH_SUTCLIFFE'], -0.0371048, 2)
hds = model.q_sim
assert hds.attrs['long_name'] == 'Simulated outflows'
# Check attributes
assert model.hydrograph.attrs['model_id'] == 'gr4jcn'
def test_simple(self):
ts = TESTDATA['ostrich-gr4j-cemaneige-nc-ts']
model = GR4JCN_OST()
params = (0.529, -3.396, 407.29, 1.072, 16.9, 0.053)
low = (0.01, -15.0, 10.0, 0.0, 1.0, 0.0)
high = (2.5, 10.0, 700.0, 7.0, 30.0, 1.0)
model(ts,
start_date=dt.datetime(1954, 1, 1),
duration=208,
area=4250.6,
elevation=843.0,
latitude=54.4848,
longitude=-123.3659,
params=params,
lowerBounds=low,
upperBounds=high,
algorithm='DDS',
random_seed=0,
max_iterations=10,
)
d = model.diagnostics
np.testing.assert_almost_equal(d['DIAG_NASH_SUTCLIFFE'], 0.486033, 4)
# Random number seed: 123
# Budget: 10
# Algorithm: DDS
# :StartDate 1954-01-01 00:00:00
# :Duration 208
opt_para = model.calibrated_params
opt_func = model.obj_func
np.testing.assert_almost_equal(opt_para, [2.423961, 3.758972, 204.3856, 5.866946, 16.60408, 0.3728098], 4,
err_msg='calibrated parameter set is not matching expected value')
np.testing.assert_almost_equal(opt_func, -0.486033, 4,
err_msg='calibrated NSE is not matching expected value')
# # Random number seed: 123
# # Budget: 50
# # Algorithm: DDS
# # :StartDate 1954-01-01 00:00:00
# # :Duration 20819
# np.testing.assert_almost_equal( opt_para, [0.3243268,3.034247,407.2890,2.722774,12.18124,0.9468769], 4,
# err_msg='calibrated parameter set is not matching expected value')
# np.testing.assert_almost_equal( opt_func, -0.5779910, 4,
# err_msg='calibrated NSE is not matching expected value')
gr4j = GR4JCN()
gr4j(ts,
start_date=dt.datetime(1954, 1, 1),
duration=208,
area=4250.6,
elevation=843.0,
latitude=54.4848,
longitude=-123.3659,
params=opt_para,
)
np.testing.assert_almost_equal(gr4j.diagnostics['DIAG_NASH_SUTCLIFFE'], d['DIAG_NASH_SUTCLIFFE'])
def test_assign(self):
model = GR4JCN()
model.assign('run_name', 'test')
assert model.rvi.run_name == 'test'
model.assign('params', np.array([0.529, -3.396, 407.29, 1.072, 16.9, 0.947]))
assert model.rvp.params.GR4J_X1 == 0.529
model.assign('params', [0.529, -3.396, 407.29, 1.072, 16.9, 0.947])
assert model.rvp.params.GR4J_X1 == 0.529
model.assign('params', (0.529, -3.396, 407.29, 1.072, 16.9, 0.947))
assert model.rvp.params.GR4J_X1 == 0.529
def test_run(self):
ts = TESTDATA['raven-gr4j-cemaneige-nc-ts']
model = GR4JCN()
model(ts,
start_date=dt.datetime(2000, 1, 1),
end_date=dt.datetime(2002, 1, 1),
area=4250.6,
elevation=843.0,
latitude=54.4848,
longitude=-123.3659,
params=(0.529, -3.396, 407.29, 1.072, 16.9, 0.947)
)
d = model.diagnostics
np.testing.assert_almost_equal(d['DIAG_NASH_SUTCLIFFE'], -0.0371048, 2)
def test_parallel_params(self):
ts = TESTDATA['raven-gr4j-cemaneige-nc-ts']
model = GR4JCN()
model(ts,
start_date=dt.datetime(2000, 1, 1),
end_date=dt.datetime(2002, 1, 1),
area=4250.6,
elevation=843.0,
latitude=54.4848,
longitude=-123.3659,
params=[(0.529, -3.396, 407.29, 1.072, 16.9, 0.947), (0.528, -3.4, 407.3, 1.07, 17, .95)]
)
assert len(model.diagnostics) == 2
assert model.hydrograph.dims['params'] == 2
def test_parallel_basins(self, input2d):
ts = input2d
model = GR4JCN()
model(ts,
start_date=dt.datetime(2000, 1, 1),
end_date=dt.datetime(2002, 1, 1),
area=4250.6,
elevation=843.0,
latitude=54.4848,
longitude=-123.3659,
params=[0.529, -3.396, 407.29, 1.072, 16.9, 0.947],
nc_index=[0, 0],
name=['basin1', 'basin2'],
)
assert len(model.diagnostics) == 2
assert len(model.hydrograph.nbasins) == 2
np.testing.assert_array_equal(model.hydrograph.basin_name[:], ['basin1', 'basin2'])
from pywps import LiteralInput
LOGGER = logging.getLogger("PYWPS")
"""
Notes
-----
The configuration files for RAVEN's GR4J-Cemaneige model and in models/raven-gr4j-cemaneige.
All parameters that could potentially be user-defined are tagged using {}. These tags need to be replaced by
actual values before the model is launched.
"""
params_defaults = GR4JCN.params(GR4J_X1=0.529,
GR4J_X2=-3.396,
GR4J_X3=407.29,
GR4J_X4=1.072,
CEMANEIGE_X1=16.9,
CEMANEIGE_X2=0.947)
params = LiteralInput('params', 'Comma separated list of model parameters',
abstract='Parameters: ' + ', '.join(params_defaults._fields),
data_type='string',
default=', '.join(str(p) for p in list(params_defaults)),
min_occurs=0,
max_occurs=config.max_parallel_processes)
class RavenGR4JCemaNeigeProcess(RavenProcess):
"""
RAVEN emulator for the GR4J-Cemaneige model.
def test_rvobjs(self):
model = GR4JCN(tempfile.mkdtemp())
a = model.rvobjs
assert a
def test_tags(self):
model = GR4JCN(tempfile.mkdtemp())
tags = model.tags
assert 'run_name' in tags
def test_version(self):
model = Raven()
assert model.version == '2.9'
model = GR4JCN()
assert model.version == '2.9'