Create utils.py

utils.py

@@ -0,0 +1,89 @@
+import requests
+import json
+
+import pandas as pd
+
+import gmplot
+import matplotlib.pyplot as plt
+from matplotlib.colors import LinearSegmentedColormap
+
+import os
+from dotenv import load_dotenv
+
+# Load the .env file
+load_dotenv()
+
+
+lta_data_mall_token = os.getenv('LTA_DATAMALL_API_KEY')
+
+headers = {
+  'AccountKey': lta_data_mall_token
+}
+
+payload = {}
+
+
+def get_lta_data(url_dict, headers=headers, payload=payload):
+
+    for key, url in url_dict.items():
+
+        response = requests.request("GET", url, headers=headers, data=payload)
+
+        json_data = response.text
+
+        data_dict = json.loads(json_data)
+
+        if key == "Incidents":
+            incidents_df = pd.DataFrame(data_dict['value'])
+        elif key == "SpeedBands":
+            speedbands_df = pd.DataFrame(data_dict['value'])
+    
+    return incidents_df, speedbands_df
+
+def zip_columns(row):
+    '''
+        Function to zip values from four columns
+    '''
+    return list(zip([row['StartLat'], row['StartLon']], [row['EndLat'], row['EndLon']]))
+
+
+# Define color mapping function
+def get_color_from_value(value):
+    '''
+        This function allows you to change the colors of the plotted points on Google Map.
+
+        For example, you could use a gradient scale based on value ranges
+        Return the color based on your logic
+    '''
+    # Example: Mapping values from 0 to 100 to a gradient scale from red to green
+    min_value = 0
+    max_value = 1
+
+    # Can be used with color gradient
+    normalized_value = (value - min_value) / (max_value - min_value)  # Normalize value between 0 and 1
+
+    if normalized_value  <= 0.5:
+        return '#ffff00'  # Yellow color for values less than or equal to 0
+    elif normalized_value  >= 0.5:
+        return '#ff0000'  # Red color for values greater than or equal to 1
+    else:
+        return '#0000ff'  # Blue color for other values
+
+
+def plot_polygon_with_speed(polygons, speeds, gmap, map='map.html'):
+
+    # Define a custom color map from red to blue
+    colors = [(1, 0, 0), (0, 0, 1)]  # Red to Blue
+    cmap = LinearSegmentedColormap.from_list("CustomMap", colors, N=8)
+
+    # Plot polygons with corresponding colors based on speed
+    for polygon, speed in zip(polygons, speeds):
+        color = cmap(speed / 8)  # Map speed to color gradient
+        # Convert latitudes and longitudes to floats
+        lats = [float(polygon[0][0]), float(polygon[0][1])]
+        lngs = [float(polygon[1][0]), float(polygon[1][1])]
+
+        gmap.polygon(lats, lngs, color='#%02x%02x%02x' % (int(color[0]*255), int(color[1]*255), int(color[2]*255)), edge_width=2)
+
+    # Draw the map
+    gmap.draw(map)