🐜🍤 ↝ [SSG-100 SSP-51]: Code for pulling anom (PH)/sector# assets

archive/snippets/planets/creation/createCurvesAndUpload.py

@@ -18,7 +18,7 @@ def upload_to_supabase(filepath, bucket_name, folder_name, file_name):
 # Process each anomaly
 for anomaly in anomalies_list.data:
     anomaly_id = anomaly['id']
-    config = anomaly['configuration']
+    config = anomaly['configuration'] 
     tic_id = config['ticId']
 
     # Define TIC and other parameters from the configuration

content/anomalies/periodCurves.py

@@ -0,0 +1,64 @@
+import os
+import lightkurve as lk
+import matplotlib.pyplot as plt
+import random
+
+def generate_random_color():
+    """Generate a random color in RGB format."""
+    return [random.random(), random.random(), random.random()]
+
+def plot_individual_sectors_with_time_binning(tic_id, bin_time_minutes=15):
+    """
+    Downloads all available light curves for the TIC ID, bins them based on a time interval, 
+    and plots both the unbinned and binned light curves for each sector, using a random color for each plot.
+    
+    Parameters:
+    - tic_id: The TIC ID to query.
+    - bin_time_minutes: Time interval for binning, in minutes (default: 15 minutes).
+    """
+    # Convert binning time to days (Lightkurve uses days as the time unit)
+    bin_time_days = bin_time_minutes / 24 / 60
+
+    # Search for light curves
+    search_result = lk.search_lightcurve(f"TIC {tic_id}", author="SPOC")
+    if len(search_result) == 0:
+        print(f"No light curves found for TIC {tic_id}.")
+        return
+
+    # Create a folder for the TIC ID if it doesn't exist
+    if not os.path.exists(str(tic_id)):
+        os.makedirs(str(tic_id))
+
+    # Iterate over each sector and plot individually, then save to the folder
+    for i, lc_file in enumerate(search_result, start=1):
+        # Download the light curve and remove outliers
+        lc = lc_file.download()
+        lc = lc.remove_outliers(sigma=5)
+
+        # Bin the light curve based on the specified time interval
+        lc_binned = lc.bin(bin_time_days)
+
+        # Generate a random color for the plot
+        random_color = generate_random_color()
+
+        # Plot the unbinned and binned light curves
+        plt.figure(figsize=(10, 5))
+        lc_binned.plot(marker='o', linewidth=0, color=random_color, alpha=0.8, markersize=5, label='Binned')
+
+        # Add plot labels and legend
+        plt.title(f"Light Curve for TIC {tic_id} (Sector {lc.sector})\nBinned Interval: {bin_time_minutes} minutes")
+        plt.xlabel("Time [BTJD days]")
+        plt.ylabel("Normalized Flux")
+        plt.legend()
+
+        # Save the plot with the correct file name inside the corresponding folder
+        plt.savefig(f"{tic_id}/Sector{i}.png", format='png')
+        plt.close()  # Close the plot to avoid display
+
+# Function to process a list of TIC IDs
+def process_tic_ids(tic_ids, bin_time_minutes=15):
+    for tic_id in tic_ids:
+        plot_individual_sectors_with_time_binning(tic_id, bin_time_minutes)
+
+tic_ids = ["50365310", "65212867", "88863718", "106997505", "124709665", "156115721", "169904935", "238597883", "277039287", "57299130", "21720215", "263723967", "284300833", "269343479", "345724317", "210904767", "329981856", "201175570",]  # List of TIC IDs
+process_tic_ids(tic_ids, bin_time_minutes=15)