[contrasting]  fix test_gev_spatio_temporal_polynomial_extremes_mle.py for computing the confidence interval. improve coherence curve. remove sensitivity checks in one fold fit. add significant percentages for histograms of models selected. deactivate some tests for speed purpose

[contrasting] add xlabel, remove 300m from the lower altitude group. add condition that we consider only altitude for which the massif has less than 10% of non zero annual maxima. return period is changed to 100.

[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 quadratic & cross terms Gumbel altitudinal models & fix a recurrent bug that happenning when checking the AIC value

[contrasting] fix polynomial_margin_model.py creation. extend the form_dict for spatio temporal models.

[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

[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 params_start_fit_bayesian for gelman convergence. add some random init param for the beginning of the MCMC chain.

[PAPER 1] taking into account psnow when computing TDRL and also when computing return level uncertainties

[CONFIDENCE INTERVAL] in the non stationary case, only the normal method is defined. in the stationary, i managed to add test the "boot" method. But for the "proflik" method there was a crash in R related to the spline, that i did not resolve

[CONFIDENCE INTERVAL] add confidence interval test for the normal (i.e. delta) confidence interval method

[CONFIDENCE INTERVAL] check that ci code return the same interval and mean posterior for the return level as my code with coordinates from 0 to 49. and also with transformed coordinates

[EXTREME ESTIMATOR] add test confidence interval. Add confidence interval with the ci method in the Bayesian case. add test for the stationary case. put the division by 100 (to get snow load) in eurocode vizualizer