[projection snowfall] adapt the one_fold_fit.py code to handle fit with a single altitude. Modify altitude_class by altitude_group, adapt tests. Modify the DefaultAltitudeGroup. adapt main_projections_ensemble.py

[projection snowfall] add main_sensitivity_one_altitude_range.py. add detail plot for each massif for the return level

[projection swe] modify interval (and data constraint) for temperature sensitivity. add invidual plots in sensitivity. add changes plot in sensitivity.

[projection swe] add crpss and train train test. improve the plot. fix bug for selection of plausible models.

[projection snowfall] add massif_names for cache computation in abstract_study.py. implement bootstrap indicator. add bootstrap return level that are physically plausible

[projection snowfall] add preliminary analysis for the work on model with effect related to the GCM or RCM type.

[projection snowfall] improve one_fold_fit_merge.py. improve interval for the sensitivity plot. Add is_temperature_interval and is_shift_interval to define the intervals.

[refactor] fix issue. the temporal covariate is the the anomaly of temperature smoothed with a spline

[refactor] update main_season_repartition_of_maxima.py to compare swe results, for safran 2019 and adamont v2, to show the limit of their indicator.

[projections] fix and refactor temperature_to_year.py. Focus on the median merge function, rather than the mean merge function.

[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.

Try to reuse the previous code as much as possible.

[projections] add AnomalyTemperatureTemporalCovariate and test. and anomaly computation for cmip5 global temperatures

integrate DatasetForClimateModels into altitude_studies.py

[projections] in an adamont_studies.py study can have different year_min and year max. Refactor adamont_gcm_rcm_couples.py. Add rcp_extended 2.6 et 4.5. Fix erroneous data for some couple for the scenario 8.5. Add main_data.py.

[projections] add plot global temp. also centered the global temp on the winter year. and average on the past 30 years