final dashboard commit

PlantDashboard/main_dashboard.py

@@ -415,6 +415,7 @@ class PlantGrowthDashboard:
             params['ambient_mode'] = self.ambient_mode.get()
                 
             current_mode = self.ambient_mode.get()
+            happy_data = 0
             if current_mode == "open":
                 happy_data = self.happyMeteo.openMeteoCall(days_difference)
                 
@@ -432,6 +433,9 @@ class PlantGrowthDashboard:
                 'end_date': self.calendar.get_date().isoformat()
             }
             
+            if current_mode == "open":
+                submission_data['meteoForecast'] = happy_data
+            
             #Remove plant_info_text
             self.plant_info_text.delete(1.0, tk.END)
             

PlantDashboard/plant_meteo.py

@@ -31,53 +31,50 @@ class HappyMeteo:
             print(f"Error getting location: {e}")
             return None, None
         
-    def openMeteoCall(self, timeLapse):
-        lat, lon = self.get_current_location()
-        
-        # Make sure all required weather variables are listed here
-        # The order of variables in hourly or daily is important to assign them correctly below
-        url = "https://api.open-meteo.com/v1/forecast"
-        params = {
-            "latitude": lat,
-            "longitude": lon,
-            "daily": ["weather_code", "temperature_2m_mean", "rain_sum", "showers_sum", "precipitation_sum", "daylight_duration", "relative_humidity_2m_mean"],
-            "timezone": "auto",
-            "forecast_days": timeLapse
+def openMeteoCall(self, timeLapse):
+    lat, lon = self.get_current_location()
+    
+    # Make sure all required weather variables are listed here
+    # The order of variables in hourly or daily is important to assign them correctly below
+    url = "https://api.open-meteo.com/v1/forecast"
+    params = {
+        "latitude": lat,
+        "longitude": lon,
+        "daily": ["weather_code", "temperature_2m_mean", "rain_sum", "showers_sum", "precipitation_sum", "daylight_duration", "relative_humidity_2m_mean"],
+        "timezone": "auto",
+        "forecast_days": timeLapse
+    }
+    responses = self.openmeteo.weather_api(url, params=params)
+
+    # Process first location. Add a for-loop for multiple locations or weather models
+    response = responses[0]
+    
+    # Process daily data. The order of variables needs to be the same as requested.
+    daily = response.Daily()
+    daily_weather_code = daily.Variables(0).ValuesAsNumpy()
+    daily_temperature_2m_mean = daily.Variables(1).ValuesAsNumpy()
+    daily_rain_sum = daily.Variables(2).ValuesAsNumpy()
+    daily_showers_sum = daily.Variables(3).ValuesAsNumpy()
+    daily_precipitation_sum = daily.Variables(4).ValuesAsNumpy()
+    daily_daylight_duration = daily.Variables(5).ValuesAsNumpy()
+    daily_relative_humidity_2m_mean = daily.Variables(6).ValuesAsNumpy()
+
+    # Return comprehensive data structure
+    return {
+        "daily_data": {
+            "weather_code": daily_weather_code.tolist(),
+            "temperature_2m_mean": daily_temperature_2m_mean.tolist(),
+            "rain_sum": daily_rain_sum.tolist(),
+            "showers_sum": daily_showers_sum.tolist(),
+            "precipitation_sum": daily_precipitation_sum.tolist(),
+            "daylight_duration": daily_daylight_duration.tolist(),
+            "relative_humidity_2m_mean": daily_relative_humidity_2m_mean.tolist()
+        },
+        "summary": {
+            "avg_temperature": float(daily_temperature_2m_mean.mean()),
+            "total_precipitation": float(daily_precipitation_sum.sum()),
+            "avg_humidity": float(daily_relative_humidity_2m_mean.mean()),
+            "total_daylight_hours": float(daily_daylight_duration.sum() / 3600)  # Convert seconds to hours
         }
-        responses = self.openmeteo.weather_api(url, params=params)
-
-        # Process first location. Add a for-loop for multiple locations or weather models
-        response = responses[0]
-        print(f"Coordinates: {response.Latitude()}°N {response.Longitude()}°E")
-        print(f"Elevation: {response.Elevation()} m asl")
-        print(f"Timezone: {response.Timezone()}{response.TimezoneAbbreviation()}")
-        print(f"Timezone difference to GMT+0: {response.UtcOffsetSeconds()}s")
-
-        # Process daily data. The order of variables needs to be the same as requested.
-        daily = response.Daily()
-        daily_weather_code = daily.Variables(0).ValuesAsNumpy()
-        daily_temperature_2m_mean = daily.Variables(1).ValuesAsNumpy()
-        daily_rain_sum = daily.Variables(2).ValuesAsNumpy()
-        daily_showers_sum = daily.Variables(3).ValuesAsNumpy()
-        daily_precipitation_sum = daily.Variables(4).ValuesAsNumpy()
-        daily_daylight_duration = daily.Variables(5).ValuesAsNumpy()
-        daily_relative_humidity_2m_mean = daily.Variables(6).ValuesAsNumpy()
-
-        daily_data = {"date": pd.date_range(
-            start = pd.to_datetime(daily.Time(), unit = "s", utc = True),
-            end = pd.to_datetime(daily.TimeEnd(), unit = "s", utc = True),
-            freq = pd.Timedelta(seconds = daily.Interval()),
-            inclusive = "left"
-        )}
-
-        daily_data["weather_code"] = daily_weather_code
-        daily_data["temperature_2m_mean"] = daily_temperature_2m_mean
-        daily_data["rain_sum"] = daily_rain_sum
-        daily_data["showers_sum"] = daily_showers_sum
-        daily_data["precipitation_sum"] = daily_precipitation_sum
-        daily_data["daylight_duration"] = daily_daylight_duration
-        daily_data["relative_humidity_2m_mean"] = daily_relative_humidity_2m_mean
-
-        daily_dataframe = pd.DataFrame(data = daily_data)
-        print("\nDaily data\n", daily_dataframe)
+    }