diff --git a/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py b/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py
index 871664206f47b842014b85389581f8813b8ed182..3117c25d4aa33c9a50794e2e8343428358feeb10 100644
--- a/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py
+++ b/extreme_data/meteo_france_data/adamont_data/cmip5/climate_explorer_cimp5.py
@@ -93,14 +93,16 @@ def dat_to_csv(csv_filepath, txt_filepath, gcm):
l = df_temp_until_july.sum(axis=1).values + df_temp_after_august.sum(axis=1).values
l /= 12
l = [np.nan] + list(l)
+ l = np.array(l)
assert len(l) == len(df.index)
+ l[l < 280] = np.nan
# First we compute the standard column
df = set_anomaly(df, mean_data=l, spline=False)
# Then we regress some cubic spline on the temperature columns
noisy_data = df[get_column_name(anomaly=False, spline=False)]
- ind = noisy_data > -50
+ ind = ~noisy_data.isna()
spline_data = noisy_data.copy()
spline_data.loc[ind] = apply_cubic_spline(noisy_data.loc[ind].index.values, noisy_data.loc[ind].values, gcm)
df = set_anomaly(df, mean_data=spline_data, spline=True)
diff --git a/extreme_data/meteo_france_data/adamont_data/cmip5/plot_temperatures.py b/extreme_data/meteo_france_data/adamont_data/cmip5/plot_temperatures.py
index 2c68e0c8df016cd16a21a805f17d90455a6092a4..f7e0782705a6f9c32657f3f982110ba1bdf6795b 100644
--- a/extreme_data/meteo_france_data/adamont_data/cmip5/plot_temperatures.py
+++ b/extreme_data/meteo_france_data/adamont_data/cmip5/plot_temperatures.py
@@ -32,7 +32,7 @@ def main_plot_temperature_with_spline_on_top(anomaly=True):
scenarios = rcp_scenarios
for scenario in scenarios:
label = gcm if scenario == scenarios[0] else None
- plot_temperature_for_rcp_gcm(ax, gcm, scenario, year_min=1951, year_max=2005, linestyle=linestyle,
+ plot_temperature_for_rcp_gcm(ax, gcm, scenario, year_min=1850, year_max=2005, linestyle=linestyle,
label=label, spline=spline, anomaly=anomaly)
plot_temperature_for_rcp_gcm(ax, gcm, scenario, year_min=2005, year_max=2100, spline=spline, anomaly=anomaly)
diff --git a/extreme_trend/ensemble_fit/independent_ensemble_fit/one_fold_fit_merge.py b/extreme_trend/ensemble_fit/independent_ensemble_fit/one_fold_fit_merge.py
index 2345fca525b115ad750cb6db68ca60456a73b3be..d749c0811cfbc795adb9ebe0064ec5533bb91014 100644
--- a/extreme_trend/ensemble_fit/independent_ensemble_fit/one_fold_fit_merge.py
+++ b/extreme_trend/ensemble_fit/independent_ensemble_fit/one_fold_fit_merge.py
@@ -32,3 +32,7 @@ class OneFoldFitMerge(OneFoldFit):
merged_relative_changes = list(self.merge_function(np.array(all_relative_changes), axis=0))
assert len(all_relative_changes[0]) == len(merged_relative_changes)
return merged_relative_changes
+
+ @property
+ def best_shape(self):
+ return self.merge_function([o.best_shape for o in self.one_fold_fit_list])
diff --git a/extreme_trend/ensemble_fit/visualizer_for_projection_ensemble.py b/extreme_trend/ensemble_fit/visualizer_for_projection_ensemble.py
index 70ba33714669917ca51c329e2fe8303a018e1efa..096e5e9ec9f7b65f780fdeeb2ec90b9ef6d4e5b5 100644
--- a/extreme_trend/ensemble_fit/visualizer_for_projection_ensemble.py
+++ b/extreme_trend/ensemble_fit/visualizer_for_projection_ensemble.py
@@ -112,7 +112,7 @@ class VisualizerForProjectionEnsemble(object):
merge_keys = [AbstractEnsembleFit.Median_merge, AbstractEnsembleFit.Mean_merge]
keys = self.gcm_rcm_couples + merge_keys
# Only plot Mean for speed
- keys = [AbstractEnsembleFit.Mean_merge]
+ # keys = [AbstractEnsembleFit.Mean_merge]
for key in keys:
visualizer_list = [independent_ensemble_fit.gcm_rcm_couple_to_visualizer[key]
if key in self.gcm_rcm_couples
diff --git a/projects/past_extreme_snowfall/section_data_and_results/preliminary_analysis.py b/projects/past_extreme_snowfall/section_data_and_results/preliminary_analysis.py
index ff04a43df66d4ffae21261a4cec76fe0d70034cc..0b9ee6d3f6c9c9e902ef34a46f23d0fc30e64e7e 100644
--- a/projects/past_extreme_snowfall/section_data_and_results/preliminary_analysis.py
+++ b/projects/past_extreme_snowfall/section_data_and_results/preliminary_analysis.py
@@ -206,9 +206,9 @@ def main_paper2():
def main_paper3():
altitudes = list(chain.from_iterable(altitudes_for_groups))
# altitudes = [1200, 1500, 1800]
- for scenario in rcp_scenarios[2:]:
+ for scenario in rcp_scenarios[:]:
gcm_rcm_couples = get_gcm_rcm_couples(scenario)
- gcm_rcm_couples =[('CNRM-CM5', 'CCLM4-8-17')]
+ # gcm_rcm_couples =[('CNRM-CM5', 'CCLM4-8-17')]
for gcm_rcm_couple in gcm_rcm_couples:
visualizer = PointwiseGevStudyVisualizer(AdamontSnowfall, altitudes=altitudes, scenario=scenario,
gcm_rcm_couple=gcm_rcm_couple)
diff --git a/projects/projected_extreme_snowfall/data/main_data.py b/projects/projected_extreme_snowfall/data/main_data.py
index f20e2858bf50acd438cbb9301084e84a5eca762f..898b8ebaeb8698d9c831dfb66985de5b9bb8f293 100644
--- a/projects/projected_extreme_snowfall/data/main_data.py
+++ b/projects/projected_extreme_snowfall/data/main_data.py
@@ -20,12 +20,11 @@ from extreme_data.meteo_france_data.scm_models_data.utils import Season
def main():
scm_study_class = SafranSnowfall1Day
adamont_study_class = AdamontSnowfall
- year_min = 2006
+ year_min = 1950
year_max = 2100
massif_names = ['Vanoise']
season = Season.annual
scenarios = rcm_scenarios_extended
- scenarios = rcp_scenarios
altitudes = [600, 2100, 3600]
for altitude, adamont_scenario in list(zip(altitudes, scenarios))[:]:
plt.figure(figsize=(10, 5))
@@ -38,7 +37,7 @@ def main():
season=season, scenario=adamont_scenario)
print(altitude, adamont_scenario)
adamont_studies.plot_maxima_time_series_adamont(massif_names=massif_names,
- scm_study=scm_study, legend_and_labels=True)
+ scm_study=scm_study, legend_and_labels=False)
if __name__ == '__main__':
diff --git a/projects/projected_extreme_snowfall/results/main_projections_ensemble.py b/projects/projected_extreme_snowfall/results/main_projections_ensemble.py
index 49ea77965240ff8de59e9e4dda1baa15f6e8cd61..864f6f95f88a9a06a432d5378ed7d5903879eaf1 100644
--- a/projects/projected_extreme_snowfall/results/main_projections_ensemble.py
+++ b/projects/projected_extreme_snowfall/results/main_projections_ensemble.py
@@ -39,7 +39,7 @@ from extreme_data.meteo_france_data.scm_models_data.utils import Season
def main():
start = time.time()
study_class = AdamontSnowfall
- ensemble_fit_classes = [IndependentEnsembleFit, TogetherEnsembleFit][1:]
+ ensemble_fit_classes = [IndependentEnsembleFit, TogetherEnsembleFit][:1]
temporal_covariate_for_fit = [TimeTemporalCovariate,
AnomalyTemperatureWithSplineTemporalCovariate][0]
set_seed_for_test()
@@ -58,12 +58,12 @@ def main():
gcm_rcm_couples = get_gcm_rcm_couples(scenario)
if fast is None:
massif_names = None
- gcm_rcm_couples = gcm_rcm_couples
+ gcm_rcm_couples = gcm_rcm_couples[:2]
AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
altitudes_list = altitudes_for_groups[3:]
elif fast:
massif_names = ['Vanoise', 'Haute-Maurienne']
- gcm_rcm_couples = gcm_rcm_couples[:]
+ gcm_rcm_couples = gcm_rcm_couples[:2]
AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
altitudes_list = altitudes_for_groups[:1]
else: