[contrasting project] add test for study loader. refactor their init function to have a better error message.

[quantile regression project]  fix bugs in daily_observations.py for the creation of the coordinates for the daily fit. some fix to prepare for some potential non stationary exponential model one day

[quantile regression project] add test exp simulations (stationary and non stationary) for models on annual maxima. Prepare the code to fit with non stationary exponential models

[quantile regression project] add annual maxima osbervation from daily exponential. add sammple_r_function as argument to rmargin_from_nb_obs. add abstract extreme params

[quantile regression project] add annual maxima osbervation from daily exponential. add sammple_r_function as argument to rmargin_from_nb_obs

[quantile regression project] refactor simulations. add transformed coordinate to the quantile functions

[quantile regression project] refactor imports for quantile estimators. two fix: nb_obs=1 in GevSimulation.py and df_merged correspond to df_coordinates from now on (such as it takes into account the transformation if there is one)

[refactor] refactor test_quantile_estimator.py. Quantile estimators works for any temporal coordinates.

[paper 1] add plot for the presentation. increase the size of the legend for uncertainty curves. add sample function for the GevParams class.

[paper 1] add plot with the difference in return level (and relative difference) for the big shapes. we conclude that there is big difference indeed

[paper 1] add upper and lower bound into the gev param object. Add script to run fit wihout maximum, and then compare the upper bound with the maximum values that was removed. The test is ok for all altitudes, the upper bound found was always higher than the maximum values

[Confidence Interval] use fix r.ci.fevd.mle_fixed for the Gumbel case in the Python code. fix the R code one more time for the gradient

[PAPER 1] add gumbel type for mle fit. add study_visualizer_for_shape_repartition both for gumbel VS stationary and stationary VS non-stationary