[projections] add visualizer_for_sensitivity.py based on visualizer_for_projection_ensemble.py. add temperature_to_year.py file.
Fix max abs recurrent issue (when it was equal to zero). add one test for one fold fit, that was that due to a scale parameter that was close to zero, and was causing instabilities in the nllh value. This is fixed by changing the check for implausible in one fold fit, and by saying that if the scale parameter is close to zero then the parameter is undefined.

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.