add function to create bar plot for yield

compute_yield.py

@@ -125,6 +125,48 @@ def get_annual_yield(monthly_forecast: pd.DataFrame) -> pd.Series:
     return yield_forecast
 
 
+def plot_yield(
+        latitude: float,
+        longitude: float,
+        culture: str = "Colza d'hiver",
+        region: str = "Bourgogne-Franche-Comté",
+        scenario: str = "pessimist",
+        shading_coef: float = 0.,
+) -> plt.Figure:
+    monthly_forecast = compute_yield_forecast(
+        latitude=latitude,
+        longitude=longitude,
+        culture=culture,
+        scenario=scenario,
+        shading_coef=0.,
+    )
+
+    monthly_forecast_with_shading = compute_yield_forecast(
+        latitude=latitude,
+        longitude=longitude,
+        culture=culture,
+        scenario=scenario,
+        shading_coef=shading_coef,
+    )
+
+    yield_forecast = get_annual_yield(monthly_forecast)
+    yield_forecast_with_shading = get_annual_yield(monthly_forecast_with_shading)
+
+    n_years = 10
+    years = 2025 + np.arange(len(yield_forecast_with_shading))
+    aggregated_forecasts = yield_forecast.rolling(n_years).sum()[years % n_years == 0]
+    aggregated_forecasts_with_shading = yield_forecast_with_shading.rolling(n_years).sum()[years % n_years == 0]
+
+    width = 3  # the width of the bars
+    fig, ax = plt.subplots(layout='constrained')
+    aggregated_years = years[years % n_years == 0]
+    _ = ax.bar(aggregated_years, aggregated_forecasts, width, label="No shading")
+    _ = ax.bar(aggregated_years + width, aggregated_forecasts_with_shading, width, label="20% shading")
+    ax.legend()
+    ax.set_ylim(150)
+
+    return fig
+
 if __name__ == '__main__':
     culture = "Colza d'hiver"
     scenario = "pessimist"