added stuff

data_processing/get_station_coverage.py

@@ -55,7 +55,7 @@ if __name__ == '__main__':
     radius_meters = 400  # 400 meters
 
     # Get small areas
-    covered_areas = get_station_coverage(get_smallAreas("given_data/smasvaedi_2021.json"), station_coords, radius_meters)
+    covered_areas = get_station_coverage(get_smallAreas(), station_coords, radius_meters)
 
     # Print results
     for area in covered_areas:

data_processing/point_scoring.py

@@ -47,6 +47,8 @@ def score_current(station_coord, df_features, cov_smsv, w_density, w_income, w_a
     # 1. Get small area ids in range
     # 2. 
     # Score = [for all areas in range((density) * coverage percentage)]
+
+    # TODO: take into account fjoldi starfandi, if there are more people who work than live => many people need to get there, also works the other way around.
     final_score = 0
     for smsv in cov_smsv:
         
@@ -64,7 +66,7 @@ def score_current(station_coord, df_features, cov_smsv, w_density, w_income, w_a
         income_score = get_income_score(smsv_info["income_distribution_per_year"]) * w_income
 
         density_score = smsv_info["density"].iloc[0] * w_density
-        final_score += (age_score + income_score + density_score) * smsv["coverage_percentage"]
+        final_score += (age_score + income_score + density_score) * smsv["coverage_percentage"] # TODO: Area of the cricle * percent covered / total area of the small area
     return final_score
 
 def get_age_score(smsv_age_dict):

given_data/borgarlina_ggplot.py

@@ -53,3 +53,4 @@ for _, row in filtered_smallarea.iterrows():
 
 ax.set_title("Filtered Small Areas with IDs Written Inside")
 plt.show()
+

given_data/test.py

@@ -0,0 +1,55 @@
+import geopandas as gpd
+import pandas as pd
+import matplotlib.pyplot as plt
+from shapely.geometry import Point
+
+# Load data (assuming file paths are correct)
+lina1 = gpd.read_file("given_data/cityline_geojson/cityline_2025.geojson")
+pop = pd.read_csv("given_data/ibuafjoldi.csv")
+smallarea = gpd.read_file("given_data/smasvaedi_2021.json")
+dwellings = pd.read_csv("given_data/ibudir.csv")
+
+# Reproject to EPSG:3057 (projected CRS for Iceland, distances in meters)
+lina1 = lina1.to_crs(epsg=3057)
+smallarea = smallarea.to_crs(epsg=3057)
+
+# Add 400m radius circle using projected coordinates
+# Define station coordinates (in EPSG:3057)
+station_x = 356250.0
+station_y = 408250.0
+
+# Create a Shapely Point for the station
+station_point = Point(station_x, station_y)
+
+# Create a 400-meter buffer around the station
+buffered_circle = station_point.buffer(400)  # 400 meters in projected CRS
+
+# Convert the circle into a GeoDataFrame for plotting
+circle_gdf = gpd.GeoDataFrame(geometry=[buffered_circle], crs="EPSG:3057")
+
+# Data processing
+pop['smasvaedi'] = pop['smasvaedi'].astype(str).str.zfill(4)
+pop2024 = pop[(pop['ar'] == 2024) & (pop['aldursflokkur'] == "10-14 ára") & (pop['kyn'] == 1)]
+pop2024_smallarea = pd.merge(smallarea, pop2024, left_on='smsv', right_on='smasvaedi', how='left')
+
+# Filter for nuts3 == "001"
+filtered_smallarea = pop2024_smallarea[pop2024_smallarea['nuts3'] == "001"]
+
+# Plot the filtered small areas and write the IDs
+fig, ax = plt.subplots(1, 1, figsize=(10, 10))  # Adjust figsize as needed
+filtered_smallarea.plot(ax=ax, facecolor='none', edgecolor='blue')  # Plot small areas with blue borders
+lina1.plot(ax=ax, facecolor='none', edgecolor='black')  # Plot cityline data
+circle_gdf.plot(ax=ax, facecolor='none', edgecolor='red', linewidth=2)  # Add the circle in red
+# Set x and y axis limits to zoom into the area
+ax.set_xlim(355500, 357000)  # Adjust to your desired x-axis range
+ax.set_ylim(407500, 409000)  # Adjust to your desired y-axis range
+
+# Add IDs as text labels
+for _, row in filtered_smallarea.iterrows():
+    # Get the centroid of each small area
+    centroid = row.geometry.centroid
+    # Place the ID as text at the centroid
+    ax.text(centroid.x, centroid.y, str(row['smsv']), fontsize=8, color='darkred', ha='center')
+
+ax.set_title("Filtered Small Areas with IDs Written Inside")
+plt.show()