def test_interpolate(self):
src = np.arange(10)[:, None]
trg = np.linspace(0, 20, 40)[:, None]
vals = np.hstack((np.sin(src), 10. + np.sin(src)))
vals[3:5, 1] = np.nan
ipol_result = ipol.interpolate(src,
trg,
vals,
ipol.Idw,
remove_missing=True,
nnearest=2)
np.testing.assert_allclose(ipol_result[3:5, 1],
np.array([10.880571, 10.909297]))
ipol_result = ipol.interpolate(src,
trg,
vals[:, 1],
ipol.Idw,
remove_missing=True,
nnearest=2)
np.testing.assert_allclose(ipol_result[3:5],
np.array([10.880571, 10.909136]))
vals = np.dstack((np.sin(src), 10. + np.sin(src)))
vals[3:5, :, 1] = np.nan
def test_interpolate(self):
src = np.arange(10)[:, None]
trg = np.linspace(0, 20, 40)[:, None]
vals = np.hstack((np.sin(src), 10. + np.sin(src)))
vals[3:5, 1] = np.nan
ipol_result = ipol.interpolate(src, trg, vals, ipol.Idw,
remove_missing=True, nnearest=2)
np.testing.assert_allclose(ipol_result[3:5, 1],
np.array([10.880571, 10.909297]))
ipol_result = ipol.interpolate(src, trg, vals[:, 1], ipol.Idw,
remove_missing=True, nnearest=2)
np.testing.assert_allclose(ipol_result[3:5],
np.array([10.880571, 10.909136]))
vals = np.dstack((np.sin(src), 10. + np.sin(src)))
vals[3:5, :, 1] = np.nan
def test_interpolate(self):
src = np.arange(10)[:, None]
trg = np.linspace(0, 20, 40)[:, None]
vals = np.hstack((np.sin(src), 10. + np.sin(src)))
vals[3:5, 1] = np.nan
print(np.any(np.isnan(vals.ravel())))
ipol_result = ipol.interpolate(src, trg, vals, ipol.Idw, nnearest=2)
np.testing.assert_allclose(ipol_result[3:5, 1],
np.array([10.880571, 10.909137]))
ipol_result = ipol.interpolate(src,
trg,
vals[:, 1],
ipol.Idw,
nnearest=2)
np.testing.assert_allclose(ipol_result[3:5],
np.array([10.880571, 10.909137]))
vals = np.dstack((np.sin(src), 10. + np.sin(src)))
vals[3:5, :, 1] = np.nan
self.assertRaises(
NotImplementedError,
lambda: ipol.interpolate(src, trg, vals, ipol.Idw, nnearest=2))
