Lifelines

New features
- Faster NPMLE for interval censored data
- New weightings available in the `logrank_test`: `wilcoxon`, `tarone-ware`, `peto`, `fleming-harrington`. Thanks sean-reed
- new interval censored dataset: `lifelines.datasets.load_mice`

Bug fixes
- Cleared up some mislabeling in `plot_loglogs`. Thanks sean-reed!
- tuples are now able to be used as input in univariate models.

New features
- Non parametric interval censoring is now available, _experimentally_. Not all edge cases are fully checked, and some features are missing. Try it under `KaplanMeierFitter.fit_interval_censoring`

New features
- `find_best_parametric_model` can handle left and interval censoring. Also allows for more fitting options.
- `AIC_` is a property on parametric models, and `AIC_partial_` is a property on Cox models.
- `penalizer` in all regression models can now be an array instead of a float. This enables new functionality and better
control over penalization. This is similar (but not identical) to `penalty.factors` in glmnet in R.
- some convergence tweaks which should help recent performance regressions.

New features
- At the cost of some performance, convergence is improved in many models.
- New `lifelines.plotting.plot_interval_censored_lifetimes` for plotting interval censored data - thanks sean-reed!

Bug fixes
- fixed bug where `cdf_plot` and `qq_plot` were not factoring in the weights correctly.

New features
- `plot_lifetimes` accepts pandas Series.

Bug fixes
- Fixed important bug in interval censoring models. Users using interval censoring are strongly advised to upgrade.
- Improved `at_risk_counts` for subplots.
- More data validation checks for `CoxTimeVaryingFitter`

Bug fixes
- Improved stability of interval censoring in parametric models.
- setting a dataframe in `ancillary_df` works for interval censoring
- `.score` works for interval censored models