change alpha confidence uncertainty to 80% uncertainty interval when i run the main code.
create 3 qqplots overlaid, one for each altitude.
remove the exclusion of some bootstrap samples (in particular we remove the threshold equal to 2000)

[contrasting] implement bootstrap confidence interval both for pointwise stationary models and for elevation-temporal models. accelerate bootstraping with multiprocessing & storing of fitted functions only (storing the estimator was impossible).

[contrasting] for preliminary_analysis.py from now we use fevd fit method & fit on series with more than 90% of non zero maxima. improve coherence plot

[contrasting] improve pointwise_gev_study_visualizer.py with a linear regression against the altitude. modify the _maxima_gev depending on the fit method

[contrasting] add pointwise_gev_study_visualizer.py and add confidence interval for the gev parameters for is_mev fit method

[contrasting] add temporal covariate argument to the margin model class, so that we could use the global temperature as covariate.

[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] 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.