Lifelines

- Changing liscense to valilla MIT.
- Speed up `NelsonAalenFitter.fit` considerably.

- Python3 fix for `CoxPHFitter.plot`.

- fixes regression in `KaplanMeierFitter.plot` when using Seaborn and lifelines.
- introduce a new `.plot` function to a fitted `CoxPHFitter` instance. This plots the hazard coefficients and their confidence intervals.
- in all plot methods, the `ix` kwarg has been deprecated in favour of a new `loc` kwarg. This is to align with Pandas deprecating `ix`

- fix in internal normalization for `CoxPHFitter` predict methods.

- corrected bug that was returning the wrong baseline survival and hazard values in `CoxPHFitter` when `normalize=True`.
- removed `normalize` kwarg in `CoxPHFitter`. This was causing lots of confusion for users, and added code complexity. It's really nice to be able to remove it.
- correcting column name in `CoxPHFitter.baseline_survival_`
- `CoxPHFitter.baseline_cumulative_hazard_` is always centered, to mimic R's `basehaz` API.
- new `predict_log_partial_hazards` to `CoxPHFitter`

- adding `plot_loglogs` to `KaplanMeierFitter`
- added a (correct) check to see if some columns in a dataset will cause convergence problems.
- removing `flat` argument in `plot` methods. It was causing confusion. To replicate it, one can set `ci_force_lines=True` and `show_censors=True`.
- adding `strata` keyword argument to `CoxPHFitter` on initialization (ex: `CoxPHFitter(strata=['v1', 'v2'])`. Why? Fitters initialized with `strata` can now be passed into `k_fold_cross_validation`, plus it makes unit testing `strata` fitters easier.
- If using `strata` in `CoxPHFitter`, access to strata specific baseline hazards and survival functions are available (previously it was a blended valie). Prediction also uses the specific baseline hazards/survivals.
- performance improvements in `CoxPHFitter` - should see at least a 10% speed improvement in `fit`.