Fix tBuLi#339 by setting t_bigger >= t0 and t_smaller < t0

In addition, prepend t0 to /both/ t_bigger and t_smaller as needed, and
if that was needed, trim the result appropriately

symfit/core/models.py

@@ -1166,19 +1166,26 @@ def eval_components(self, *args, **kwargs):
  # initial value, and to integrate those seperately. At the end we rejoin them.
  # 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_smaller = t_like[t_like <= t_initial][::-1]
- else:
+ t_bigger = t_like[t_like >= t_initial]
+ t_smaller = t_like[t_like < t_initial][::-1]
+
+ # Time access must start with t_initial. So add that point if needed. We also need to remember we added those
+ # points so we can remove them again later.
+ prepended_to_bigger = False
+ prepended_to_smaller = False
+ if t_bigger.size and t_bigger[0] != t_initial:
  t_bigger = np.concatenate(
- (np.array([t_initial]), t_like[t_like > t_initial])
+ (np.array([t_initial]), t_bigger)
  )
+ prepended_to_bigger = True
+ if t_smaller.size and t_smaller[0] != t_initial:
  t_smaller = np.concatenate(
- (np.array([t_initial]), t_like[t_like < t_initial][::-1])
+ (np.array([t_initial]), t_smaller)
  )
- # Properly ordered time axis containing t_initial
- t_total = np.concatenate((t_smaller[::-1][:-1], t_bigger))
+ prepended_to_smaller = True
 
+ # Properly ordered time axis containing t_initial
+ 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
  # can evaluate numerically.
@@ -1203,15 +1210,13 @@ def eval_components(self, *args, **kwargs):
  *self.lsoda_args, **self.lsoda_kwargs
  )
 
- ans = np.concatenate((ans_smaller[1:][::-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
- else:
- # The user didn't ask for the value at t_initial, so exclude it.
- # (t_total contains all the t-points used for the integration,
- # and so is t_like with t_initial inserted at the right position).
- return ans[t_total != t_initial].T
+ # If we had to prepend t_initial to the time axes, remove those data points from the results
+ if prepended_to_bigger:
+ ans_bigger = ans_bigger[1:]
+ if prepended_to_smaller:
+ ans_smaller = ans_smaller[1:]
+ ans = np.concatenate((ans_smaller[::-1], ans_bigger))
+ return ans.T
 
  def __call__(self, *args, **kwargs):
  """