Lifelines

The tests were re-factored to be shipped with the package. Let me know if this causes problems.


Bug fixes
- fixed error in plotting models with "lower" or "upper" was in the label name.
- fixed bug in plot_covariate_groups for AFT models when >1d arrays were used for values arg.

Bug fixes
- fixed `predict_` methods in AFT models when `timeline` was not specified.
- fixed error in `qq_plot`
- fixed error when submitting a model in `qth_survival_time`
- `CoxPHFitter` now displays correct columns values when changing alpha param.

New features
- Serializing lifelines is better supported. Packages like joblib and pickle are now supported. Thanks AbdealiJK!
- `conditional_after` now available in `CoxPHFitter.predict_median`
- Suppressed some unimportant warnings.

Bug fixes
- fixed initial_point being ignored in AFT models.

New features
- new `ApproximationWarning` to tell you if the package is making an potentially mislead approximation.

Bug fixes
- fixed a bug in parametric prediction for interval censored data.
- realigned values in `print_summary`.
- fixed bug in `survival_difference_at_fixed_point_in_time_test`

API Changes

- `utils.qth_survival_time` no longer takes a `cdf` argument - users should take the compliment (1-cdf).
- Some previous `StatisticalWarnings` have been replaced by `ApproximationWarning`

New features
- `conditional_after` works for `CoxPHFitter` prediction models 😅

Bug fixes

API Changes
- `CoxPHFitter.baseline_cumulative_hazard_`'s column is renamed `"baseline cumulative hazard"` - previously it was `"baseline hazard"`. (Only applies if the model has no strata.)
- `utils.dataframe_interpolate_at_times` renamed to `utils.interpolate_at_times_and_return_pandas`.

New features
- Improvements to the __repr__ of models that takes into accounts weights.
- Better support for predicting on Pandas Series

Bug fixes
- Fixed issue where `fit_interval_censoring` wouldn't accept lists.
- Fixed an issue with `AalenJohansenFitter` failing to plot confidence intervals.

API Changes
- `_get_initial_value` in parametric univariate models is renamed `_create_initial_point`