fdfit: update tests

It is no longer needed to explicitly provide finite inversion limits. We will only use the interpolation method in the range where our data lives, and outside we always use explicit optimization.

lumicks/pylake/fitting/tests/test_fd_models.py

@@ -59,7 +59,7 @@ def test_models():
     # Check the tWLC and inverted tWLC model
     params = [5, 5, 5, 3, 2, 1, 6, 4.11]
     assert twlc_distance("tWLC").verify_jacobian(independent, params)
-    assert twlc_force("itWLC").verify_jacobian(independent, params)
+    assert twlc_force("itWLC").verify_jacobian(independent, params, rtol=1e-4)
 
     # Check whether the twistable wlc model manipulates the data order
     np.testing.assert_allclose(

lumicks/pylake/fitting/tests/test_model_composition.py

@@ -134,21 +134,14 @@ def test_subtract_independent_offset_unit(model, param, unit):
     assert model.defaults[param].unit == unit
 
 
-def test_interpolation_inversion():
-    m = ewlc_odijk_distance("Nucleosome").invert(independent_max=120.0, interpolate=True)
+@pytest.mark.parametrize("method", ["exact", "interp_lsq", "interp_root"])
+def test_interpolation_inversion(method):
+    m = ewlc_odijk_distance("Nucleosome").invert(independent_max=120.0, method=method)
     parvec = [5.77336105517341, 7.014180463612673, 1500.0000064812095, 4.11]
     result = np.array([0.17843862, 0.18101283, 0.18364313, 0.18633117, 0.18907864])
     np.testing.assert_allclose(m._raw_call(np.arange(10, 250, 50) / 1000, parvec), result)
 
 
-@pytest.mark.parametrize("param", [{"independent_max": np.inf}, {"independent_min": -np.inf}])
-def test_interpolation_invalid_range(param):
-    with pytest.raises(
-        ValueError, match="Inversion limits have to be finite when using interpolation method"
-    ):
-        ewlc_odijk_distance("Nucleosome").invert(**param, interpolate=True)
-
-
 def test_uuids():
     m1, m2 = (Model(name, lambda x: x, dependent="x") for name in ("M1", "M2"))
     m3 = CompositeModel(m1, m2)