Symfit

y_data = np.array([10, 20, 30, 40, 50])

- Switched `scipy.integrate.odeint` for the more modern `scipy.integrate.solve_ivp`. This greatly expands the possible ODE solvers one can use. By default, we still use `odeint`'s LSODA with the old settings so existing code is not affected.
- Significant clean-up of the code base by removing some features which were once introduced to support both py2.7 and py3.x.

- Fixed critical pickling bug caused by a change in sympy's pickling (342).
- Minor bug fixes.

- Changed licence from GNU to MIT.
- Added python 3.9 support, dropped python 3.5.
- Add jupyter latex printing.
- Remove leastsqbound.py, adapt MINPACK minimizer to use scipy.optimize.least_squares.
- Improved pickling.
- Improved various tests.
- Various bugfixes.

Bugfix release.

Most importantly this fixes the printing of `HadamardPower` objects, relaxes demands on the scipy version, and switches from unittest to pytest.

Symfit 0.5.2 offers a fantastic new feature: `ODEModel`s now also accept parameter objects as initial values, allowing them to be optimized as well! Additionally it undoes some of the performance penalties that were accidentally introduced in 0.5.0-0.5.1, making it as fast again as the 0.4.x series.

Full changelog:
- ODEModels can now use parameters for their initial values, so these can be optimized during the fitting!
- Hessian and jacobian models are now generated lazily to prevent slow model building.
- The output of models was a namedtuple, which has a limit to the amount of arguments in older python versions. This has therefore been replaced by a custom tuple subclass called ModelOutput.
- Numerous small big fixes
- Documentation improvements