Fix tBuLi#339 by defining t_smaller as <= t0, and t_bigger as > t0

symfit/core/models.py

@@ -1167,17 +1167,17 @@ def eval_components(self, *args, **kwargs):
  # np.flip is needed because odeint wants the first point to be t_initial
  # and so t_smaller is a declining series.
  if t_initial in t_like:
- t_bigger = t_like[t_like >= t_initial]
+ t_bigger = t_like[t_like > t_initial]
  t_smaller = t_like[t_like <= t_initial][::-1]
  else:
  t_bigger = np.concatenate(
  (np.array([t_initial]), t_like[t_like > t_initial])
  )
  t_smaller = np.concatenate(
- (np.array([t_initial]), t_like[t_like < t_initial][::-1])
+ (np.array([t_initial]), t_like[t_like <= t_initial][::-1])
  )
  # Properly ordered time axis containing t_initial
- t_total = np.concatenate((t_smaller[::-1][:-1], t_bigger))
+ t_total = np.concatenate((t_smaller[::-1], t_bigger))
 
  # Call the numerical integrator. Note that we only pass the
  # model_params, which will be used by sympy_to_py to create something we
@@ -1203,7 +1203,7 @@ def eval_components(self, *args, **kwargs):
  *self.lsoda_args, **self.lsoda_kwargs
  )
 
- ans = np.concatenate((ans_smaller[1:][::-1], ans_bigger))
+ ans = np.concatenate((ans_smaller[::-1], ans_bigger))
  if t_initial in t_like:
  # The user also requested to know the value at t_initial, so keep it.
  return ans.T

tests/test_ode.py

@@ -258,3 +258,27 @@ def test_initial_parameters():
  assert ode_model.params == [a0, c0, k, l, m, p]
  assert ode_model.initial_params == [a0, c0]
  assert ode_model.model_params == [a0, k, l, m, p]
+
+
+def test_duplicate_initial_t():
+ """
+ Tests that having duplicate t0 values in tdata doesn't cause shape mismatch issues, such as in #339
+ """
+ tdata = np.array([0, 10, 10, 26, 44, 70, 120])
+ adata = 10e-4 * np.array([54, 54, 44, 34, 27, 20, 14])
+
+ a, b, t = variables('a, b, t')
+ k = Parameter('k', 0.1)
+
+ model_dict = {
+ D(a, t): - k * a ** 2,
+ D(b, t): k * a ** 2,
+ }
+
+ ode_model = ODEModel(model_dict, initial={t: 26, a: adata[0], b: 0.0})
+
+ fit = Fit(ode_model, t=tdata, a=adata, b=None)
+ try:
+ fit_result = fit.execute()
+ except ValueError:
+ pytest.fail()