[contrasting] add code to retrieve gcm_rcm_couples. start code to compare bias...

[contrasting] add code to retrieve gcm_rcm_couples. start code to compare bias on the quantile period (between projecitons, and ADAMONT 2020)

extreme_data/meteo_france_data/adamont_data/get_list_gcm_rcm_couples_adamont_v2.py

+
+links = """
+CLMcom-CCLM4-8-17_CNRM-CERFACS-CNRM-CM5_HISTORICAL/
+CLMcom-CCLM4-8-17_CNRM-CERFACS-CNRM-CM5_RCP45/
+CLMcom-CCLM4-8-17_CNRM-CERFACS-CNRM-CM5_RCP85/
+CLMcom-CCLM4-8-17_ICHEC-EC-EARTH_HISTORICAL/
+CLMcom-CCLM4-8-17_ICHEC-EC-EARTH_RCP45/
+CLMcom-CCLM4-8-17_ICHEC-EC-EARTH_RCP85/
+CLMcom-CCLM4-8-17_MOHC-HadGEM2-ES_HISTORICAL/
+CLMcom-CCLM4-8-17_MOHC-HadGEM2-ES_RCP45/
+CLMcom-CCLM4-8-17_MOHC-HadGEM2-ES_RCP85/
+CLMcom-CCLM4-8-17_MPI-M-MPI-ESM-LR_HISTORICAL/
+CLMcom-CCLM4-8-17_MPI-M-MPI-ESM-LR_RCP26/
+CLMcom-CCLM4-8-17_MPI-M-MPI-ESM-LR_RCP45/
+CLMcom-CCLM4-8-17_MPI-M-MPI-ESM-LR_RCP85/
+CNRM-ALADIN53_CNRM-CERFACS-CNRM-CM5_HISTORICAL/
+CNRM-ALADIN53_CNRM-CERFACS-CNRM-CM5_RCP45/
+CNRM-ALADIN53_CNRM-CERFACS-CNRM-CM5_RCP85/
+CNRM-ALADIN62_ECMWF-ERAINT_HISTORICAL/
+CNRM-ALADIN63_CNRM-CERFACS-CNRM-CM5_HISTORICAL/
+CNRM-ALADIN63_CNRM-CERFACS-CNRM-CM5_RCP26/
+CNRM-ALADIN63_CNRM-CERFACS-CNRM-CM5_RCP45/
+CNRM-ALADIN63_CNRM-CERFACS-CNRM-CM5_RCP85/
+DMI-HIRHAM5_NCC-NorESM1-M_HISTORICAL/
+DMI-HIRHAM5_NCC-NorESM1-M_RCP45/
+DMI-HIRHAM5_NCC-NorESM1-M_RCP85/
+GERICS-REMO2015_NCC-NorESM1-M_HISTORICAL/
+GERICS-REMO2015_NCC-NorESM1-M_RCP26/
+GERICS-REMO2015_NCC-NorESM1-M_RCP85/
+ICTP-RegCM4-6_MOHC-HadGEM2-ES_HISTORICAL/
+ICTP-RegCM4-6_MOHC-HadGEM2-ES_RCP26/
+ICTP-RegCM4-6_MOHC-HadGEM2-ES_RCP85/
+IPSL-INERIS-WRF331F_IPSL-IPSL-CM5A-MR_HISTORICAL/
+IPSL-INERIS-WRF331F_IPSL-IPSL-CM5A-MR_RCP45/
+IPSL-INERIS-WRF331F_IPSL-IPSL-CM5A-MR_RCP85/
+IPSL-WRF381P_IPSL-IPSL-CM5A-MR_HISTORICAL/
+IPSL-WRF381P_IPSL-IPSL-CM5A-MR_RCP45/
+IPSL-WRF381P_IPSL-IPSL-CM5A-MR_RCP85/
+KNMI-RACMO22E_CNRM-CERFACS-CNRM-CM5_HISTORICAL/
+KNMI-RACMO22E_CNRM-CERFACS-CNRM-CM5_RCP26/
+KNMI-RACMO22E_CNRM-CERFACS-CNRM-CM5_RCP45/
+KNMI-RACMO22E_CNRM-CERFACS-CNRM-CM5_RCP85/
+KNMI-RACMO22E_ICHEC-EC-EARTH_HISTORICAL/
+KNMI-RACMO22E_ICHEC-EC-EARTH_RCP26/
+KNMI-RACMO22E_ICHEC-EC-EARTH_RCP45/
+KNMI-RACMO22E_ICHEC-EC-EARTH_RCP85/
+KNMI-RACMO22E_MOHC-HadGEM2-ES_HISTORICAL/
+KNMI-RACMO22E_MOHC-HadGEM2-ES_RCP26/
+KNMI-RACMO22E_MOHC-HadGEM2-ES_RCP45/
+KNMI-RACMO22E_MOHC-HadGEM2-ES_RCP85/
+MPI-CSC-REMO2009_MPI-M-MPI-ESM-LR_HISTORICAL/
+MPI-CSC-REMO2009_MPI-M-MPI-ESM-LR_RCP26/
+MPI-CSC-REMO2009_MPI-M-MPI-ESM-LR_RCP45/
+MPI-CSC-REMO2009_MPI-M-MPI-ESM-LR_RCP85/
+SAFRAN_2019/
+SAFRAN_2020/
+SMHI-RCA4_CNRM-CERFACS-CNRM-CM5_HISTORICAL/
+SMHI-RCA4_CNRM-CERFACS-CNRM-CM5_RCP45/
+SMHI-RCA4_CNRM-CERFACS-CNRM-CM5_RCP85/
+SMHI-RCA4_ICHEC-EC-EARTH_HISTORICAL/
+SMHI-RCA4_ICHEC-EC-EARTH_RCP26/
+SMHI-RCA4_ICHEC-EC-EARTH_RCP45/
+SMHI-RCA4_ICHEC-EC-EARTH_RCP85/
+SMHI-RCA4_IPSL-IPSL-CM5A-MR_HISTORICAL/
+SMHI-RCA4_IPSL-IPSL-CM5A-MR_RCP45/
+SMHI-RCA4_IPSL-IPSL-CM5A-MR_RCP85/
+SMHI-RCA4_MOHC-HadGEM2-ES_HISTORICAL/
+SMHI-RCA4_MOHC-HadGEM2-ES_RCP45/
+SMHI-RCA4_MOHC-HadGEM2-ES_RCP85/
+SMHI-RCA4_MPI-M-MPI-ESM-LR_HISTORICAL/
+SMHI-RCA4_MPI-M-MPI-ESM-LR_RCP45/
+SMHI-RCA4_MPI-M-MPI-ESM-LR_RCP85/"""
+
+s = set()
+for l in links.split('\n'):
+    print(l)
+    if '_' in l and 'SAFRAN' not in l:
+        gcm, rcm, _ = l.split('_')
+        s.add((gcm, rcm))
+print(len(s))
+for c in s:
+    print(c)
+
+"""
+('SMHI-RCA4', 'ICHEC-EC-EARTH')
+('CLMcom-CCLM4-8-17', 'CNRM-CERFACS-CNRM-CM5')
+('SMHI-RCA4', 'MOHC-HadGEM2-ES')
+('GERICS-REMO2015', 'NCC-NorESM1-M')
+('CLMcom-CCLM4-8-17', 'MPI-M-MPI-ESM-LR')
+('KNMI-RACMO22E', 'CNRM-CERFACS-CNRM-CM5')
+('IPSL-WRF381P', 'IPSL-IPSL-CM5A-MR')
+('MPI-CSC-REMO2009', 'MPI-M-MPI-ESM-LR')
+('CNRM-ALADIN62', 'ECMWF-ERAINT')
+('CLMcom-CCLM4-8-17', 'ICHEC-EC-EARTH')
+('SMHI-RCA4', 'CNRM-CERFACS-CNRM-CM5')
+('CNRM-ALADIN63', 'CNRM-CERFACS-CNRM-CM5')
+('CLMcom-CCLM4-8-17', 'MOHC-HadGEM2-ES')
+('CNRM-ALADIN53', 'CNRM-CERFACS-CNRM-CM5')
+('KNMI-RACMO22E', 'ICHEC-EC-EARTH')
+('SMHI-RCA4', 'MPI-M-MPI-ESM-LR')
+('SMHI-RCA4', 'IPSL-IPSL-CM5A-MR')
+('IPSL-INERIS-WRF331F', 'IPSL-IPSL-CM5A-MR')
+('KNMI-RACMO22E', 'MOHC-HadGEM2-ES')
+('DMI-HIRHAM5', 'NCC-NorESM1-M')
+('ICTP-RegCM4-6', 'MOHC-HadGEM2-ES')
+
+"""
+
+def get_year_min_and_year_max_used_to_compute_quantile(rcm):
+    if rcm == 'MOHC-HadGEM2-ES':
+        reanalysis_years = (1988, 2011)
+        model_year = (1982, 2005)
+    else:
+        reanalysis_years = (1981, 2011)
+        model_year = (1975, 2005)
+    return reanalysis_years, model_year
+

projects/projected_snowfall/comparison_with_scm/main_comparison_on_quantile_period.py

+import numpy as np
+import matplotlib
+
+from extreme_data.meteo_france_data.adamont_data.adamont.adamont_snowfall import AdamontSnowfall
+from extreme_data.meteo_france_data.adamont_data.adamont_scenario import AdamontScenario, gcm_rcm_couple_to_color, \
+    gcm_rcm_couple_to_str
+from extreme_data.meteo_france_data.scm_models_data.safran.safran_max_snowf import SafranSnowfall2020
+from extreme_data.meteo_france_data.adamont_data.get_list_gcm_rcm_couples_adamont_v2 import get_year_min_and_year_max_used_to_compute_quantile
+
+matplotlib.use('Agg')
+
+import matplotlib.pyplot as plt
+from extreme_data.meteo_france_data.scm_models_data.visualization.main_study_visualizer import \
+    STUDY_CLASS_TO_ABBREVIATION
+from projects.altitude_spatial_model.altitudes_fit.altitudes_studies import AltitudesStudies
+
+
+def compute_bias_and_display_it(ax,
+                                altitude_studies_reanalysis: AltitudesStudies,
+                                adamont_altitude_studies: AltitudesStudies,
+                                gcm_rcm_couple
+                                ):
+    bias_in_the_mean_maxima = []
+    altitudes = []
+    for altitude, study_reanalysis in altitude_studies_reanalysis.altitude_to_study.items():
+        altitudes.append(altitude)
+        adamont_study = adamont_altitude_studies.altitude_to_study[altitude]
+        mean_maxima_adamont = adamont_study.mean_annual_maxima
+        mean_maxima_reanalysis = study_reanalysis.mean_annual_maxima
+        bias = mean_maxima_adamont - mean_maxima_reanalysis
+        bias_in_the_mean_maxima.append(bias)
+
+    color = gcm_rcm_couple_to_color[gcm_rcm_couple]
+    label = gcm_rcm_couple_to_str(gcm_rcm_couple)
+    ax.plot(bias_in_the_mean_maxima, altitudes, label=label, color=color)
+
+    return np.array(bias_in_the_mean_maxima)
+
+
+def main_comparaison_plot():
+    altitudes = [600, 900, 1200, 1500, 1800, 2100, 2400, 2700, 3000, 3300, 3600]
+    ax = plt.gca()
+    gcm_rcm_couples = []
+
+    bias_in_the_mean = []
+    for gcm_rcm_couple in gcm_rcm_couples:
+        gcm, rcm = gcm_rcm_couple
+        years_reanalysis, years_model = get_year_min_and_year_max_used_to_compute_quantile(rcm)
+        reanalysis_altitude_studies = AltitudesStudies(study_class=SafranSnowfall2020,
+                                                       altitudes=altitudes,
+                                                       year_min=years_reanalysis[0],
+                                                       year_max=years_reanalysis[1])
+        adamont_altitude_studies = AltitudesStudies(study_class=AdamontSnowfall,
+                                                    altitudes=altitudes,
+                                                    year_min=years_model[0],
+                                                    year_max=years_model[1],
+                                                    scenario=AdamontScenario.histo,
+                                                    gcm_rcm_couple=gcm_rcm_couple)
+        bias_in_the_mean.extend(compute_bias_and_display_it(ax, reanalysis_altitude_studies,
+                                                            adamont_altitude_studies, gcm_rcm_couple))
+
+    bias_in_the_mean = np.array(bias_in_the_mean)
+    min_bias, median_bias, max_bias = [f(bias_in_the_mean, axis=0) for f in [np.min, np.median, np.max]]
+
+    # Plot the range for the bias, and the median
+    ax.yaxis.set_ticks(altitudes)
+    color = 'k'
+    ax.plot(median_bias, altitudes, label='Median bias', color=color)
+    ax.fill_betweenx(altitudes, min_bias, max_bias, label='Range for the bias', alpha=0.2, color=color)
+    ax.vlines(0, ymin=altitudes[0], ymax=altitudes[-1], color='k')
+    study_str = STUDY_CLASS_TO_ABBREVIATION[type(reanalysis_altitude_studies.study)]
+    plot_name = 'Bias for {}\n' \
+                '(on the period used for the quantile correction)'.format(study_str)
+    ax.set_ylim(top=altitudes[-1] + 500)
+    ax.legend()
+    reanalysis_altitude_studies.show_or_save_to_file(plot_name=plot_name)
+    plt.close()
+
+
+if __name__ == '__main__':
+    main_comparaison_plot()