def test_ExternalDriftKriging_3(self):
"""testing the basic behaviour of the ExternalDriftKriging class
with missing drift terms"""
ip = ipol.ExternalDriftKriging(self.src, self.trg, '1.0 Lin(2.0)',
src_drift=None,
trg_drift=None)
self.assertRaises(ValueError, ip, self.vals)
def test_nnearest_warning(self):
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter("always")
ipol.Idw(self.src, self.trg, nnearest=len(self.src) + 1)
ipol.OrdinaryKriging(self.src, self.trg, nnearest=len(self.src) + 1)
ipol.ExternalDriftKriging(self.src, self.trg, nnearest=len(self.src) + 1)
for item in w:
assert issubclass(item.category, UserWarning)
assert "nnearest" in str(item.message)
def test_ExternalDriftKriging_3(self):
"""testing the basic behaviour of the ExternalDriftKriging class
with missing drift terms"""
ip = ipol.ExternalDriftKriging(
self.src, self.trg, "1.0 Lin(2.0)", src_drift=None, trg_drift=None
)
with pytest.raises(ValueError):
ip(self.vals)
def test_MissingErrors(self):
with pytest.raises(ipol.MissingSourcesError):
ipol.Nearest(np.array([]), self.trg)
with pytest.raises(ipol.MissingTargetsError):
ipol.Nearest(self.src, np.array([]))
with pytest.raises(ipol.MissingSourcesError):
ipol.Idw(np.array([]), self.trg)
with pytest.raises(ipol.MissingTargetsError):
ipol.Idw(self.src, np.array([]))
with pytest.raises(ipol.MissingSourcesError):
ipol.Linear(np.array([]), self.trg)
with pytest.raises(ipol.MissingTargetsError):
ipol.Linear(self.src, np.array([]))
with pytest.raises(ipol.MissingSourcesError):
ipol.OrdinaryKriging(np.array([]), self.trg)
with pytest.raises(ipol.MissingTargetsError):
ipol.OrdinaryKriging(self.src, np.array([]))
with pytest.raises(ipol.MissingSourcesError):
ipol.ExternalDriftKriging(np.array([]), self.trg)
with pytest.raises(ipol.MissingTargetsError):
ipol.ExternalDriftKriging(self.src, np.array([]))
def test_ExternalDriftKriging_1(self):
"""testing the basic behaviour of the ExternalDriftKriging class
with drift terms constant over multiple fields"""
ip = ipol.ExternalDriftKriging(self.src, self.trg, '1.0 Lin(2.0)',
src_drift=self.src_d,
trg_drift=self.trg_d)
res = ip(self.vals)
self.assertTrue(np.all(res == np.array([[1., 2., 3.],
[3., 2., 1.],
[5., 2., -1.],
[7., 2., -3.]])))
def test_ExternalDriftKriging_1(self):
"""testing the basic behaviour of the ExternalDriftKriging class
with drift terms constant over multiple fields"""
ip = ipol.ExternalDriftKriging(self.src, self.trg, '1.0 Lin(2.0)',
src_drift=self.src_d,
trg_drift=self.trg_d)
# input more than one dataset
res = ip(self.vals)
self.assertTrue(np.all(res == np.array([[1., 2., 3.],
[3., 2., 1.],
[5., 2., -1.],
[7., 2., -3.]])))
# input only one flat array
res = ip(self.vals[:, 2])
self.assertTrue(np.allclose(res, np.array([3., 1., -1., -3.])))
def test_ExternalDriftKriging_2(self):
"""testing the basic behaviour of the ExternalDriftKriging class
with drift terms varying over multiple fields"""
src_d = np.array([[0.0, 0.0, 0.0], [1.0, 1.0, 1.0]])
trg_d = np.array([[0.0, 0.0, 0.0], [1.0, 1.0, 1.0], [2.0, 2.0, 2.0],
[3.0, 3.0, 3.0]])
ip = ipol.ExternalDriftKriging(self.src,
self.trg,
"1.0 Lin(2.0)",
src_drift=src_d,
trg_drift=trg_d)
res = ip(self.vals)
assert np.all(res == np.array([[1.0, 2.0, 3.0], [3.0, 2.0, 1.0],
[5.0, 2.0, -1.0], [7.0, 2.0, -3.0]]))
# input only one flat array
res = ip(self.vals[:, 2], src_drift=src_d[:, 2], trg_drift=trg_d[:, 2])
assert np.allclose(res, np.array([3.0, 1.0, -1.0, -3.0]))
