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| import pandas as pd | |
| import pandas as pd | |
| import numpy as np | |
| from utils.summary import get_summary | |
| # Générer des dates sur 5 ans (historique) + 5 ans (prévision) | |
| dates_past = pd.date_range(start="2023-01-01", periods=36, freq='ME') # 3 ans d'historique | |
| dates_future = pd.date_range(start="2023-01-01", periods=60, freq='ME') # 5 ans de prévisions | |
| # Température: Tendance à la hausse selon le scénario | |
| def generate_temperature_trend(scenario): | |
| base_temp = 10 + 10 * np.sin(np.linspace(0, 2 * np.pi, len(dates_past) + len(dates_future))) | |
| if scenario == "optimiste": | |
| trend = base_temp + np.linspace(0, 1, len(base_temp)) # Faible réchauffement | |
| elif scenario == "modéré": | |
| trend = base_temp + np.linspace(0, 2, len(base_temp)) # Réchauffement moyen | |
| else: # pessimiste | |
| trend = base_temp + np.linspace(0, 3, len(base_temp)) # Fort réchauffement | |
| return trend | |
| # Précipitations: Variation selon le scénario | |
| def generate_precipitation_trend(scenario): | |
| base_rain = 50 + 20 * np.cos(np.linspace(0, 2 * np.pi, len(dates_past) + len(dates_future))) | |
| if scenario == "optimiste": | |
| trend = base_rain - np.linspace(0, 5, len(base_rain)) # Légère baisse | |
| elif scenario == "modéré": | |
| trend = base_rain - np.linspace(0, 10, len(base_rain)) # Baisse moyenne | |
| else: # pessimiste | |
| trend = base_rain - np.linspace(0, 15, len(base_rain)) # Forte baisse | |
| return trend | |
| # Irradiance: Augmentation progressive | |
| def generate_irradiance_trend(scenario): | |
| base_irradiance = 200 + 50 * np.sin(np.linspace(0, 2 * np.pi, len(dates_past) + len(dates_future))) | |
| if scenario == "optimiste": | |
| trend = base_irradiance + np.linspace(0, 5, len(base_irradiance)) # Faible augmentation | |
| elif scenario == "modéré": | |
| trend = base_irradiance + np.linspace(0, 10, len(base_irradiance)) # Augmentation modérée | |
| else: # pessimiste | |
| trend = base_irradiance + np.linspace(0, 20, len(base_irradiance)) # Forte augmentation | |
| return trend | |
| # Choix du scénario | |
| scenario = "modéré" # Changer entre "optimiste", "modéré" et "pessimiste" | |
| # Créer les DataFrames | |
| temperature_df = pd.DataFrame({"Date": dates_past.tolist() + dates_future.tolist(), | |
| "Température (°C)": generate_temperature_trend(scenario)}) | |
| rain_df = pd.DataFrame({"Date": dates_past.tolist() + dates_future.tolist(), | |
| "Précipitations (mm)": generate_precipitation_trend(scenario)}) | |
| irradiation_df = pd.DataFrame({"Date": dates_past.tolist() + dates_future.tolist(), | |
| "Irradiance (W/m²)": generate_irradiance_trend(scenario)}) | |
| # Afficher un extrait | |
| print("Température (extrait) :") | |
| print(temperature_df.head(3)) | |
| print("\nPrécipitations (extrait) :") | |
| print(rain_df.head(3)) | |
| print("\nIrradiance (extrait) :") | |
| print(irradiation_df.head(3)) | |
| summary = get_summary(scenario, temperature_df, rain_df, irradiation_df) | |
| print(summary) | |