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Delaigue Olivier authored78450ae3
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# import time
# import os.path as op
# import matplotlib.pyplot as plt
# from collections import OrderedDict
#
# from experiment.meteo_france_data.scm_models_data.visualization.study_visualization.study_visualizer import \
# StudyVisualizer
# from extreme_fit.model.result_from_model_fit.result_from_extremes.eurocode_return_level_uncertainties import \
# ConfidenceIntervalMethodFromExtremes
# from papers.exceeding_snow_loads.result_trends_and_return_levels.plot_uncertainty_curves import \
# plot_uncertainty_massifs
# from experiment.eurocode_data.massif_name_to_departement import MASSIF_NAMES_ALPS
# from experiment.eurocode_data.utils import EUROCODE_ALTITUDES
# from experiment.meteo_france_data.scm_models_data.crocus.crocus import CrocusSwe3Days, CrocusSweTotal
# from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.altitude_hypercube_visualizer import \
# AltitudeHypercubeVisualizer
# from experiment.meteo_france_data.scm_models_data.visualization.hypercube_visualization.utils_hypercube import \
# load_altitude_visualizer
# from extreme_fit.model.margin_model.linear_margin_model.temporal_linear_margin_models import StationaryTemporalModel, \
# NonStationaryLocationAndScaleTemporalModel
#
# # Model class
# import matplotlib as mpl
#
# from root_utils import VERSION_TIME
#
# mpl.rcParams['text.usetex'] = True
# mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
#
#
# def massif_name_to_ordered_return_level_uncertainties(model_class, last_year_for_the_data, altitudes, massif_names,
# uncertainty_methods, temporal_covariate):
# # Load model name
# model_name = get_model_name(model_class)
# # Load altitude visualizer
# altitude_visualizer = load_altitude_visualizer(AltitudeHypercubeVisualizer, altitudes=altitudes,
# last_starting_year=None, nb_data_reduced_for_speed=False,
# only_first_one=False, save_to_file=False,
# exact_starting_year=1958,
# first_starting_year=None,
# study_classes=[CrocusSwe3Days, CrocusSweTotal][1:],
# trend_test_class=None) # type: AltitudeHypercubeVisualizer
# # Loop on the data
# assert isinstance(altitude_visualizer.tuple_to_study_visualizer, OrderedDict)
# massif_name_to_ordered_eurocode_level_uncertainty = {
# massif_name: {ci_method: [] for ci_method in uncertainty_methods} for massif_name in massif_names}
# for altitude, visualizer in altitude_visualizer.tuple_to_study_visualizer.items():
# print('{} processing altitude = {} '.format(model_name, altitude))
# for ci_method in uncertainty_methods:
# d = visualizer.massif_name_to_altitude_and_eurocode_level_uncertainty(model_class, last_year_for_the_data,
# massif_names, ci_method,
# temporal_covariate)
# # Append the altitude one by one
# for massif_name, return_level_uncertainty in d.items():
# massif_name_to_ordered_eurocode_level_uncertainty[massif_name][ci_method].append(
# return_level_uncertainty)
# return {model_name: massif_name_to_ordered_eurocode_level_uncertainty}
#
#
# def plot_ci_graphs(altitudes, massif_names, model_class_and_last_year, show, temporal_covariate, uncertainty_methods):
# model_name_to_massif_name_to_ordered_return_level = {}
# for model_class, last_year_for_the_data in model_class_and_last_year:
# start = time.time()
# model_name_to_massif_name_to_ordered_return_level.update(
# massif_name_to_ordered_return_level_uncertainties(model_class, last_year_for_the_data, altitudes,
# massif_names, uncertainty_methods, temporal_covariate))
# duration = time.time() - start
# print('Duration:', model_class, duration)
# # Transform the dictionary into the desired format
# massif_name_to_model_name_to_ordered_return_level_uncertainties = {}
# for massif_name in massif_names:
# d2 = {model_name: model_name_to_massif_name_to_ordered_return_level[model_name][massif_name] for model_name in
# model_name_to_massif_name_to_ordered_return_level.keys()}
# massif_name_to_model_name_to_ordered_return_level_uncertainties[massif_name] = d2
# # Plot graph
# plot_uncertainty_massifs(
# massif_name_to_model_name_to_ordered_return_level_uncertainties, nb_massif_names=len(massif_names),
# nb_model_names=len(model_class_and_last_year))
# if show:
# plt.show()
# else:
# massif_names_str = '_'.join(massif_names)
# model_names_str = '_'.join(
# [model_name for model_name in model_name_to_massif_name_to_ordered_return_level.keys()])
# filename = op.join(VERSION_TIME, model_names_str + '_' + massif_names_str)
# StudyVisualizer.savefig_in_results(filename)
#
#
# def main_drawing():
# fast_plot = [True, False][0]
# temporal_covariate = 2017
# # Select parameters
# massif_names = MASSIF_NAMES_ALPS[:]
# model_class_and_last_year = [
# (StationaryTemporalModel, 2017),
# (NonStationaryLocationAndScaleTemporalModel, 2017),
# # Add the temperature here
# ][:]
# altitudes = EUROCODE_ALTITUDES[:]
# uncertainty_methods = [ConfidenceIntervalMethodFromExtremes.my_bayes,
# ConfidenceIntervalMethodFromExtremes.ci_mle]
# show = False
#
# if fast_plot:
# show = True
# model_class_and_last_year = model_class_and_last_year[:]
# altitudes = altitudes[-2:]
# # altitudes = altitudes[:]
# massif_names = massif_names[:1]
# uncertainty_methods = uncertainty_methods[:]
#
# plot_ci_graphs(altitudes, massif_names, model_class_and_last_year, show, temporal_covariate, uncertainty_methods)
#
#
# # Create 5 main plots
# def main_5_drawings():
# model_class_and_last_year = [
# (StationaryTemporalModel, 2017),
# (NonStationaryLocationAndScaleTemporalModel, 2017),
# # Add the temperature here
# ][:1]
# altitudes = EUROCODE_ALTITUDES[:]
# uncertainty_methods = [ConfidenceIntervalMethodFromExtremes.my_bayes,
# ConfidenceIntervalMethodFromExtremes.ci_mle]
# show = False
# massif_names = MASSIF_NAMES_ALPS[:]
# temporal_covariate = 2017
# m = 4
# n = (23 // m) + 1
# for i in list(range(n))[:]:
# massif_names = MASSIF_NAMES_ALPS[m * i: m * (i+1)]
# print(massif_names)
# plot_ci_graphs(altitudes, massif_names, model_class_and_last_year, show, temporal_covariate, uncertainty_methods)
#
#
# def main_3_massif_of_interest():
# massif_names = ['Parpaillon', 'Chartreuse', 'Maurienne'][1:]
# model_class_and_last_year = [
# (StationaryTemporalModel, 2017),
# (NonStationaryLocationAndScaleTemporalModel, 2017),
# # Add the temperature here
# ][:]
# altitudes = EUROCODE_ALTITUDES[1:]
# uncertainty_methods = [ConfidenceIntervalMethodFromExtremes.my_bayes,
# ConfidenceIntervalMethodFromExtremes.ci_mle][:]
# temporal_covariate = 2017
# show = False
# plot_ci_graphs(altitudes, massif_names, model_class_and_last_year, show, temporal_covariate, uncertainty_methods)
#
#
# if __name__ == '__main__':
# # main_drawing()
# # main_5_drawings()
# main_3_massif_of_interest()