Skip to content
GitLab
Select Git revision
  • master default
You can move around the graph by using the arrow keys.
Created with Raphaël 2.2.012Apr9842130Mar292625232218161510432126Feb25242322191817161512985432125Jan19158723Dec226Nov2523191816121110628Oct232219171412872129Sep2825211816151410983131Aug30Jul292827242220171615230Jun2926252423181716151211815May1330Apr292722201918171587631Mar302726252423201918167643228Feb27261813121110730Jan24222120138718Dec17161110532129Nov2827262523222113731Oct3028252422211816420Sep1918111095431Jul2925171615121Jun19181712111097654329May2827232221201615141310976328Mar2522212019181187[projection snowfall] fix error in one fold fit for the temperature covariate & for the significance.[projection snowfall] modify altitude_class to altitude_group in visualizer_for_projection_ensemble.py. fix index for ensemble dataset. add plot_relative_change_in_return_level.py[projection snowfall] add the 27 non stationary spline models of interest.[projection snowfall] add functions_utils.py. modify one_fold_fit.py so that it may support one altitude fit.[projection snowfall] add global temperature for 2020[projection snowfall] refactor nb_params.[projection snowfall] validate aic and bic for the spline models.[projection snowfall] refactor nb_params. so that is it associated to the margin_function rather than to the margin_model.[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 spline simulation. implement splines for k=1. pass test_gev_temporal_spline.py[projection snowfall] fix one issue for evgam coefficients. refactor param_name_to_dim -> param_name_to_dims in the result objects.[projection snowfall] add spline_margin_function.py and test with it. test_gev_temporal_spline.py is not yet validated for the nllh.[projection snowfall] add test_gev_temporal_polynomial_evgam.py and pass the tests.[projection snowfall] add other test for tet_gev_temporal_evgam[projection snowfall] add evgam call for abstract_temporal_linear_margin_model.py. account for log_scale in the margin_function. rename get_coord_df to get_r_dataframe_from_python_dataframe. create evgam_fixed.R for debugging[projection snowfall] install evgam successfully alongside R > 3.5[projection snowfall] remove test with respect to fevd bayesian, due to differences with the test. i do not use it, so it does not matter. But maybe with the change of R version, the code changed. still try to install evgam[projection snowfall] fix temperature for HadGem. rely on the merge visualizer.[projection snowfall] refactor first_year and last_year in OneFoldFit. and apply the code to check the difference in spatial patterns between safran 2020 reanalysis and ADAMont v2[projection snowfall] add comparison_window_for_the_max.py[projection snowfall] add main_sensitivity_one_altitude_range.py. add detail plot for each massif for the return level[projection snowfall] add modification to try to account for gcm parameters, without success[projection swe] modify parameters for the spline. modify temp invervals.[projection swe] add sensitivity for return levels.[projection swe] modify interval (and data constraint) for temperature sensitivity. add invidual plots in sensitivity. add changes plot in sensitivity.[projection swe] add test_ensemble_fit.py. start margin model with effect[projection swe] add new version for the temperature covariate.[projection swe] move projected swe to archive folder[projection swe] add crpss and train train test. improve the plot. fix bug for selection of plausible models.[projection swe] add model_as_truth.py. add default weight solver and a file for the method with bootstrap[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] improve weight computation for knutti_weight_solver.py[projection snowfall] add weight solver[projection snowfall] add preliminary analysis for the work on model with effect related to the GCM or RCM type.[projection snowfall] add together fit, and its usage into visualizer_for_sensitivity.py[projection snowfall] modify interval limits. plot both merge & mean aggregation.[projection snowfall] add main_projections_ensemble.py where we try together_ensemble_fit.py[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.[projection swe] implement knutti_weight_computer.py and refactor the rest of the code.[projection swe] add non-stationary weight computer. refactor code for the weights.