Big mishmash of improvements, mostly to predictor generation and testing

* Allow 'tr' as a name for trapezoid rule

* Add option to higher_order_start to set starting dt

* Disable adaptivity checks because they are annoying

* Add option to _odeint to woble the step size about randomly

* Add handling of proper Jacobian functions to _odeint

* Add function get_ltes_from_data, with test

* Remove Real=True from sympy vars because it breaks things

* Make test_symbolic_compare_step_time_residual actually work
  was comparing only bdf3, which is impossibly complicated, now compare
  just bdf2, which works

* Add Jacobian symbolic functions to midpoint_method_killer_problem() in
  example residuals

* Add option to use exact y values in predictor generator

* Add option to use finite differenced dy values in predictor generator
  Not really complete, only works for constant step!

* Add option to use specific dy function for exp in predictor generator
  Again, needs work. Only added so that we can use it in a self test...

* Take general symbolic expr in predictor generator
  + use to get other functions as needed

* Add test of numerical predictor func to test_tr_ab2_scheme_generation()

* Comment out test_predictor_error_numerical, doesn't work well

* Evaluate bdf2_imr at different points when used inside generated predictors
  use more recent points, reduce history dependence.
autopep8 everything
Throw away all the non-working adaptive imr methods