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Olivier Kaufmann authored0baa8e44
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import datetime
import time
from typing import List
import matplotlib
from extreme_trend.ensemble_fit.together_ensemble_fit.together_ensemble_fit import TogetherEnsembleFit
matplotlib.use('Agg')
import matplotlib as mpl
mpl.rcParams['text.usetex'] = True
mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
from extreme_trend.ensemble_fit.independent_ensemble_fit.independent_ensemble_fit import IndependentEnsembleFit
from extreme_trend.ensemble_fit.visualizer_for_projection_ensemble import VisualizerForProjectionEnsemble
from extreme_trend.ensemble_fit.visualizer_for_sensitivity import VisualizerForSensivity
from spatio_temporal_dataset.coordinates.temporal_coordinates.temperature_covariate import \
AnomalyTemperatureWithSplineTemporalCovariate
from extreme_fit.model.margin_model.polynomial_margin_model.utils import \
ALTITUDINAL_GEV_MODELS_BASED_ON_POINTWISE_ANALYSIS
from extreme_fit.model.utils import set_seed_for_test
from extreme_data.meteo_france_data.adamont_data.adamont.adamont_safran import AdamontSnowfall
from extreme_data.meteo_france_data.adamont_data.adamont_scenario import AdamontScenario, get_gcm_rcm_couples, \
rcp_scenarios
from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
TimeTemporalCovariate
from extreme_fit.model.result_from_model_fit.result_from_extremes.abstract_extract_eurocode_return_level import \
AbstractExtractEurocodeReturnLevel
from extreme_trend.one_fold_fit.altitude_group import altitudes_for_groups
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:]
temporal_covariate_for_fit = [TimeTemporalCovariate,
AnomalyTemperatureWithSplineTemporalCovariate][1]
set_seed_for_test()
AbstractExtractEurocodeReturnLevel.ALPHA_CONFIDENCE_INTERVAL_UNCERTAINTY = 0.2
fast = False
scenarios = rcp_scenarios[::-1] if fast is False else [AdamontScenario.rcp85]
for scenario in scenarios:
gcm_rcm_couples = get_gcm_rcm_couples(scenario)
if fast is None:
massif_names = None
gcm_rcm_couples = gcm_rcm_couples
AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
altitudes_list = altitudes_for_groups[3:]
elif fast:
massif_names = ['Vanoise', 'Haute-Maurienne']
gcm_rcm_couples = gcm_rcm_couples[:]
AbstractExtractEurocodeReturnLevel.NB_BOOTSTRAP = 10
altitudes_list = altitudes_for_groups[:1]
else:
massif_names = ['Vanoise']
altitudes_list = altitudes_for_groups[3:]
assert isinstance(gcm_rcm_couples, list)
assert isinstance(altitudes_list, List)
assert isinstance(altitudes_list[0], List)
print('Scenario is', scenario)
print('Covariate is {}'.format(temporal_covariate_for_fit))
model_classes = ALTITUDINAL_GEV_MODELS_BASED_ON_POINTWISE_ANALYSIS
assert scenario in rcp_scenarios
visualizer = VisualizerForProjectionEnsemble(
altitudes_list, gcm_rcm_couples, study_class, Season.annual, scenario,
model_classes=model_classes,
ensemble_fit_classes=ensemble_fit_classes,
massif_names=massif_names,
temporal_covariate_for_fit=temporal_covariate_for_fit,
remove_physically_implausible_models=True,
gcm_to_year_min_and_year_max=None,
)
visualizer.plot()
end = time.time()
duration = str(datetime.timedelta(seconds=end - start))
print('Total duration', duration)
if __name__ == '__main__':
main()