Lifelines

Bug fixes for py3.5.

New features
- New univariate model, `SplineFitter`, that uses cubic splines to model the cumulative hazard.
- To aid users with selecting the best parametric model, there is a new `lifelines.utils.find_best_parametric_model` function that will iterate through the models and return the model with the lowest AIC (by default).
- custom parametric regression models can now do left and interval censoring.

New features
- New `predict_hazard` for parametric regression models.
- New lymph node cancer dataset, originally from *H.F. for the German Breast Cancer Study Group (GBSG) (1994)*

Bug fixes
- fixes error thrown when converge of regression models fails.
- `kwargs` is now used in `plot_covariate_groups`
- fixed bug where large exponential numbers in `print_summary` were not being suppressed correctly.

- Bug fix for PyPI

New features
- `StatisticalResult.print_summary` supports html output.

Bug fixes
- fix import in `printer.py`
- fix html printing with Univariate models.

New features
- new `lifelines.plotting.rmst_plot` for pretty figures of survival curves and RMSTs.
- new variance calculations for `lifelines.utils.resticted_mean_survival_time`
- performance improvements on regression models' preprocessing. Should make datasets with
high number of columns more performant.

Bug fixes
- fixed `print_summary` for AAF class.
- fixed repr for `sklearn_adapter` classes.
- fixed `conditional_after` in Cox model with strata was used.