def test_unknown_elsewhere_different(self):
data = Orange.data.Table("iris")
with data.unlocked():
data.X[0, 1] = np.nan
data.X[1, 1] = np.nan
data.X[1, 2] = np.nan
im = Interpolate(getx(data))
im.interpfn = interp1d_with_unknowns_numpy
interpolated = im(data)
self.assertAlmostEqual(interpolated.X[0, 1], 3.25)
self.assertAlmostEqual(interpolated.X[1, 1], 3.333333333333334)
self.assertAlmostEqual(interpolated.X[1, 2], 1.766666666666667)
self.assertFalse(np.any(np.isnan(interpolated.X)))
im.interpfn = interp1d_with_unknowns_scipy
interpolated = im(data)
self.assertAlmostEqual(interpolated.X[0, 1], 3.25)
self.assertAlmostEqual(interpolated.X[1, 1], 3.333333333333334)
self.assertAlmostEqual(interpolated.X[1, 2], 1.766666666666667)
self.assertFalse(np.any(np.isnan(interpolated.X)))
save_X = interpolated.X
im.interpfn = interp1d_wo_unknowns_scipy
interpolated = im(data)
self.assertTrue(np.any(np.isnan(interpolated.X)))
# parts without unknown should be the same
np.testing.assert_almost_equal(data.X[2:], save_X[2:])
def test_time():
fns = ["collagen", dust(), spectra20nea(), "peach_juice.dpt"]
for fn in fns:
print(fn)
data = Table(fn)
print(data.X.shape)
data[0, 2] = np.nan
t = time.time()
interpolated = Interpolate(getx(data), handle_nans=False)(data)
print("no nan", time.time() - t)
t = time.time()
intp = Interpolate(getx(data), handle_nans=True)
intp.interpfn = interp1d_with_unknowns_numpy
interpolated = intp(data)
print("nan handling with numpy", time.time() - t)
intp.interpfn = interp1d_with_unknowns_scipy
interpolated = intp(data)
print("nan handling with scipy", time.time() - t)
assert(not np.any(np.isnan(interpolated.X)))
def test_unknown_elsewhere_different(self):
data = Orange.data.Table("iris")
data.X[0, 1] = np.nan
data.X[1, 1] = np.nan
data.X[1, 2] = np.nan
im = Interpolate(getx(data))
im.interpfn = interp1d_with_unknowns_numpy
interpolated = im(data)
self.assertAlmostEqual(interpolated.X[0, 1], 3.25)
self.assertAlmostEqual(interpolated.X[1, 1], 3.333333333333334)
self.assertAlmostEqual(interpolated.X[1, 2], 1.766666666666667)
self.assertFalse(np.any(np.isnan(interpolated.X)))
im.interpfn = interp1d_with_unknowns_scipy
interpolated = im(data)
self.assertAlmostEqual(interpolated.X[0, 1], 3.25)
self.assertAlmostEqual(interpolated.X[1, 1], 3.333333333333334)
self.assertAlmostEqual(interpolated.X[1, 2], 1.766666666666667)
self.assertFalse(np.any(np.isnan(interpolated.X)))
save_X = interpolated.X
im.interpfn = interp1d_wo_unknowns_scipy
interpolated = im(data)
self.assertTrue(np.any(np.isnan(interpolated.X)))
# parts without unknown should be the same
np.testing.assert_almost_equal(data.X[2:], save_X[2:])
