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Le Roux Erwan authored
[contrasting] add temporal covariate argument to the margin model class, so that we could use the global temperature as covariate.
a8c94b83
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import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
from extreme_fit.model.margin_model.polynomial_margin_model.utils import ALTITUDINAL_GEV_MODELS, \
ALTITUDINAL_GEV_MODELS_LOCATION_QUADRATIC_MINIMUM, ALTITUDINAL_GEV_MODELS_LOCATION_ONLY_SCALE_ALTITUDES, ALTITUDINAL_GEV_MODELS_LOCATION
from projects.altitude_spatial_model.altitudes_fit.one_fold_analysis.plot_total_aic import plot_total_aic, \
plot_individual_aic
from spatio_temporal_dataset.coordinates.temporal_coordinates.abstract_temporal_covariate_for_fit import \
MeanGlobalTemperatureCovariate
mpl.rcParams['text.usetex'] = True
mpl.rcParams['text.latex.preamble'] = [r'\usepackage{amsmath}']
from extreme_data.meteo_france_data.scm_models_data.visualization.utils import create_adjusted_axes
from projects.altitude_spatial_model.altitudes_fit.one_fold_analysis.one_fold_fit import OneFoldFit
from projects.exceeding_snow_loads.utils import dpi_paper1_figure
from extreme_data.meteo_france_data.scm_models_data.safran.safran import SafranSnowfall1Day, SafranSnowfall3Days, \
SafranSnowfall5Days, SafranSnowfall7Days, SafranPrecipitation1Day, SafranPrecipitation3Days, \
SafranPrecipitation5Days, SafranPrecipitation7Days
from extreme_data.meteo_france_data.scm_models_data.utils import Season
from projects.altitude_spatial_model.altitudes_fit.altitudes_studies import AltitudesStudies
from projects.altitude_spatial_model.altitudes_fit.one_fold_analysis.altitudes_studies_visualizer_for_non_stationary_models import \
AltitudesStudiesVisualizerForNonStationaryModels
def plot_time_series(studies, massif_names=None):
studies.plot_maxima_time_series(massif_names=massif_names)
def plot_moments(studies, massif_names=None):
for std in [True, False][:]:
for change in [True, False, None]:
studies.plot_mean_maxima_against_altitude(massif_names=massif_names, std=std, change=change)
def plot_altitudinal_fit(studies, massif_names=None):
# model_classes = ALTITUDINAL_GEV_MODELS_LOCATION_ONLY_SCALE_ALTITUDES
# model_classes = ALTITUDINAL_GEV_MODELS_LOCATION_QUADRATIC_MINIMUM
model_classes = ALTITUDINAL_GEV_MODELS_LOCATION
# model_classes = ALTITUDINAL_GEV_MODELS_LOCATION_CUBIC_MINIMUM
# model_classes = ALTITUDINAL_GEV_MODELS_QUADRATIC
visualizer = AltitudesStudiesVisualizerForNonStationaryModels(studies=studies,
model_classes=model_classes,
massif_names=massif_names,
show=False,
temporal_covariate_for_fit=None)
# Plot the results for the model that minimizes the individual aic
plot_individual_aic(visualizer)
# Plot the results for the model that minimizes the total aic
# plot_total_aic(model_classes, visualizer)
def main():
altitudes = [900, 1200, 1500, 1800, 2100, 2400, 2700, 3000][4:6]
# todo: l ecart pour les saisons de l automne ou de sprint
# vient probablement de certains zéros pas pris en compte pour le fit,
# mais pris en compte pour le calcul de mon aic
# altitudes = [300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000][:]
# altitudes = [900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600, 3900][:]
# altitudes = [300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000][:]
# altitudes = [600, 900, 1200, 1500, 1800, 2100][:]
altitudes = [300, 600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600, 3900, 4200, 4500, 4800][:]
# altitudes = [1500, 1800][:]
study_classes = [SafranSnowfall1Day, SafranSnowfall3Days, SafranSnowfall5Days, SafranSnowfall7Days][:2]
study_classes = [SafranPrecipitation1Day, SafranPrecipitation3Days, SafranPrecipitation5Days,
SafranPrecipitation7Days][:]
study_classes = [SafranSnowfall1Day, SafranSnowfall3Days, SafranPrecipitation1Day
, SafranPrecipitation3Days][:1]
# seasons = [Season.automn, Season.winter, Season.spring][::-1]
seasons = [Season.winter]
# seasons = [Season.winter_extended]
massif_names = None
# massif_names = ['Aravis']
# massif_names = ['Chartreuse', 'Belledonne']
for season in seasons:
for study_class in study_classes:
studies = AltitudesStudies(study_class, altitudes, season=season)
print('inner loop', season, study_class)
# plot_time_series(studies, massif_names)
# plot_moments(studies, massif_names)
plot_altitudinal_fit(studies, massif_names)
if __name__ == '__main__':
main()